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Scoping study Assessing the value of freshwater quality at a global scale

Authors:
  • De Waterwerkers
De Waterwerkers
De Waterwerkers
Scoping study
Assessing the value of freshwater quality at a global scale
Client: PBL
November 30, 2021
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Scoping study assessing the value of freshwater quality at a global scale 1
In the abundance of water, the fool is thirsty – Bob Marley (1976)
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale
Colophon
Title Scoping study assessing the value of freshwater quality at a global scale
Version Final, November 30, 2021 (v.2)
Executed by De Waterwerkers
Authors Jarl Kind (De Waterwerkers), Sjoerd Schenau (CBS) & Marcel Bakker (RHDHV), with
contributions from Lex Bouwman & Arthur Beusen (PBL)
Client PBL Netherlands Environmental Assessment Agency
Cover photo Mambalam Canal, Chennai, India. Photo by Jarl Kind.
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Scoping study assessing the value of freshwater quality at a global scale 1
Contents
Summary ................................................................................................................................................. 4
1. Introduction ..................................................................................................................................... 5
1.1. Context/background................................................................................................................ 5
1.2. Objectives ................................................................................................................................ 6
1.3. Starting points ......................................................................................................................... 6
1.4. Report structure ...................................................................................................................... 7
2. CWON and scoping study on the valuation of freshwater quantities ............................................. 8
3. Methodology and conceptual framework ..................................................................................... 12
3.1. Conceptual framework .......................................................................................................... 12
3.2. Monetary valuation of effects or impacts ............................................................................. 13
3.2.1. Market based valuation (direct, priced effects) ............................................................ 14
3.2.2. Indirect, priced effects................................................................................................... 15
3.2.3. Non-market valuation methods .................................................................................... 15
3.2.4. Asset valuation .............................................................................................................. 16
4. Impacts due to changes in water quality ....................................................................................... 18
4.1. Introduction ........................................................................................................................... 18
4.2. Impacts on human health...................................................................................................... 19
4.2.1. Description .................................................................................................................... 19
4.2.2. Quantification ................................................................................................................ 20
4.2.3. Valuation ....................................................................................................................... 21
4.2.4. Models and data ............................................................................................................ 22
4.2.5. Link to freshwater quality parameters .......................................................................... 23
4.2.6. Activities for the roadmap ............................................................................................. 23
4.3. Impacts on the cost of drinking water treatment ................................................................. 24
4.3.1. Description .................................................................................................................... 24
4.3.2. Quantification ................................................................................................................ 24
4.3.3. Valuation ....................................................................................................................... 24
4.3.4. Models and data ............................................................................................................ 25
4.3.5. Link to freshwater quality parameters .......................................................................... 26
4.3.6. Activities for the roadmap ............................................................................................. 26
4.4. Impacts on Industries ............................................................................................................ 26
4.4.1. Description .................................................................................................................... 26
4.4.2. Quantification ................................................................................................................ 26
4.4.3. Valuation ....................................................................................................................... 26
4.4.4. Models and data ............................................................................................................ 27
4.4.5. Link to freshwater quality parameters .......................................................................... 27
4.4.6. Activities for the roadmap ............................................................................................. 27
4.5. Impacts on Mining ................................................................................................................. 27
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4.5.1. Description .................................................................................................................... 27
4.5.2. Quantification ................................................................................................................ 27
4.5.3. Valuation ....................................................................................................................... 27
4.5.4. Models and data ............................................................................................................ 27
4.5.5. Link to freshwater quality parameters .......................................................................... 27
4.5.6. Activities for the roadmap ............................................................................................. 28
4.6. Impacts on irrigated agriculture ............................................................................................ 28
4.6.1. Description .................................................................................................................... 28
4.6.2. Quantification ................................................................................................................ 28
4.6.3. Valuation ....................................................................................................................... 29
4.6.4. Models and data ............................................................................................................ 29
4.6.5. Link to freshwater quality parameters .......................................................................... 30
4.6.6. Activities for the roadmap ............................................................................................. 31
4.7. Impacts on livestock .............................................................................................................. 31
4.7.1. Description .................................................................................................................... 31
4.7.2. Quantification ................................................................................................................ 32
4.7.3. Valuation ....................................................................................................................... 33
4.7.4. Models and data ............................................................................................................ 33
4.7.5. Link to freshwater quality parameters .......................................................................... 34
4.7.6. Activities for the roadmap ............................................................................................. 35
4.8. Impacts on hydropower ........................................................................................................ 35
4.8.1. Description .................................................................................................................... 35
4.8.2. Quantification ................................................................................................................ 35
4.8.3. Valuation ....................................................................................................................... 35
4.8.4. Models and data ............................................................................................................ 35
4.8.5. Link to freshwater quality parameters .......................................................................... 36
4.8.6. Activities for the roadmap ............................................................................................. 36
4.9. Impacts on inland fish catch .................................................................................................. 36
4.9.1. Description .................................................................................................................... 36
4.9.2. Quantification ................................................................................................................ 37
4.9.3. Valuation ....................................................................................................................... 37
4.9.4. Models and data ............................................................................................................ 37
4.9.5. Link to freshwater quality parameters .......................................................................... 38
4.9.6. Activities for the roadmap ............................................................................................. 38
4.10. Impacts on recreation & tourism ...................................................................................... 38
4.10.1. Description .................................................................................................................... 38
4.10.2. Quantification ................................................................................................................ 38
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4.10.3. Valuation ....................................................................................................................... 39
4.10.4. Models and data ............................................................................................................ 39
4.10.5. Link to freshwater quality parameters .......................................................................... 40
4.10.6. Activities for the roadmap ............................................................................................. 40
5. Global Water Quality Modelling .................................................................................................... 41
5.1. Introduction ........................................................................................................................... 41
5.2. Modelling pollutants in surface water .................................................................................. 42
5.3. Towards integrated modelling of water quality .................................................................... 44
5.4. SEEA and Global Water Models ............................................................................................ 44
5.5. Activities for the roadmap ..................................................................................................... 46
6. Towards the assessment of global costs and health benefits of increased coverage of WWTPs . 47
6.1. Introduction ........................................................................................................................... 47
6.2. Estimating the costs of improving water quality through the treatment of wastewater ..... 47
6.2.1. Approach ....................................................................................................................... 47
6.2.2. Costs of wastewater treatment plants per country ...................................................... 48
6.2.3. Pipelines ........................................................................................................................ 50
6.2.4. Estimated total unit costs of WWTPs and pipelines ..................................................... 50
6.2.5. Current asset value and future investment costs ......................................................... 51
6.3. Quantification and monetization of health impacts ............................................................. 52
6.4. Cost of WWTPs confronted with monetized health benefits ............................................... 52
6.5. Activities for the roadmap ..................................................................................................... 53
7. Roadmap ........................................................................................................................................ 54
7.1. Prioritization .......................................................................................................................... 57
References ............................................................................................................................................. 59
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Summary
This report presents a scoping study on how to provide monetary values for freshwater quality
improvements at a global scale, values which can be linked to the global water quality models which
are used by PBL and other organisations, and which can be used to derive (changes) in the asset
values of freshwater resources. The study distinguishes between the impacts of water quality on
human health, drinking water treatment, industries, mining, irrigated agriculture, livestock,
hydropower, inland fisheries, and recreation & tourism. The report contains the following core
elements: (i) an outline of a methodology/framework on how to assess and value the impacts of
global water quality improvements; (ii) the identification of data and models which are needed to
apply this methodology/framework; and (iii) an assessment of what is missing and what follow-up
actions are needed to fill data and model gaps, in order to quantify and value the impact, and to
implement the methodology.
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1. Introduction
This section describes the context, background, objectives and limitations of the current study.
1.1. Context/background
General
Freshwater is crucial for human sustenance, nature, and most economic activities. The majority of
human settlements is located near a freshwater resource, which has proven to be a source for
collaboration and development. At the same time, water shortages and disputes have led to many
conflicts, and still do. Growing populations, economic development and global warming put
freshwater resources under increasing pressures, leading to water scarcity, water pollution and
deterioration of the hydrological catchment. This calls for an increasing effort in sustainable water
resources management and development, with a focus on both the quantitative and qualitative
aspects of freshwater. Estimates of the monetary and non-monetary values of freshwater quantities
and qualities can make significant contributions to this effort. Where earlier work specifically
focussed on valuing the quantitative aspects of freshwater resources (Kind et al., 2020), the focus of
this scoping study is on valuing water resources based on quantity and quality. 1
Valuing freshwater resources in monetary terms, however, is challenging, both at local, national and
global scales, as shown amongst others in our earlier report on valuing water for the World Bank
report Changing Wealth of Nation (Kind et al., 2020; see also Chapter 2). The present study builds on
this earlier report and aims to make a next step in developing a method for valuing water based on
quantity and quality, and hopes to contribute to other projects and processes like the PBL Future
Water Challenges project, the Dutch international Valuing Water Initiative and the UN Sustainable
Development Goals, see Textbox 1-1.
1 We greatly acknowledge the useful comments on an earlier draft of this manuscript received from Bert Hof,
Sonja Kruitwagen, Willem Ligtvoet, Paul Lucas, Michael Vardon, Lotte de Vos and Detlef van Vuuren.
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Textbox 1-1: Related projects and processes
Future Water Challenges
On the request of three Dutch Ministries —the Ministry of Infrastructure and Water Management, the Ministry of Foreign
Affairs, and the Ministry of Economic Affairs and Climate Policy—PBL works on the Future Water Challenges project – a
project which provides a global overview of development scenarios and pathways forward, within the context of the water-
related challenges up to 2050 (https://themasites.pbl.nl/future-water-challenges/). With respect to freshwater quality, the
report contains maps and tables with indicate the current state and selected impacts in quantitative terms. Implementation
of the activities proposed in this report can be used to complement and enrich the quantitative analyses for the next
versions of the FWC reports.
Valuing Water Initiative
The Valuing Water Initiative (VWI) was officially launched at the World Economic Forum in January 2019 by Prime Minister
Mark Rutte. This initiative uses practical case studies to showcase the five United Nations Valuing Water Principles2 in order
to bring systemic change in the way water is valued in policy, practice, finance and behaviour, and to inspire others to do
the same. The VWI conceptual framework is based on an approach which recognizes the multiple (social, environmental
and economic) values of water, which can not all be expressed as a single unit in order to commensurate. The report that
lies before you, has a focus on these economic values of (fresh-)water.
UN Sustainable Development Goals
The study links to the UN Sustainable Development Goals (SDGs), by providing a methodological contribution to the
assessment of the benefits of safe and clean water on the global scale (SDG6.3: by 2030, improve water quality by reducing
pollution, eliminating dumping and minimizing release of hazardous chemicals and materials, halving the proportion of
untreated wastewater and substantially increasing recycling and safe reuse globally).
1.2. Objectives
In light of the above, the objectives of this study are:
1. to present a methodology how to quantify and value in monetary terms the impacts of
(changes in) water quality, and
2. to identify gaps in data and global water quality models by assessing what is available and
what is needed to implement this methodology.
The study thus serves as an extension of the already developed roadmap for CWON which was
focussed on providing values for freshwater quantities.
1.3. Starting points
The following starting points for this study are important as guidance:
the aims of this study is to propose valuation concepts which can be universally applied, and
to identify data, databases and models which have near global coverage;
2 The five principles are (1) recognize and embrace water’s multiple values to different groups and interests in
all decisions affecting water; (2) reconcile values and build trust – conduct all processes to reconcile values in
ways that are equitable, transparent and inclusive; (3) protect the sources, including watersheds, rivers,
aquifers, associated ecosystems, and used water flows for current and future generations; (4) educate to
empower – promote education and awareness among all stakeholders about the intrinsic value of water and its
essential role in all aspects of life; and (5) invest and innovate – ensure adequate investment in institutions,
infrastructure, information and innovation to realize the many benefits derived from water and reduce risks.
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the study is focussed on the impacts associated with changes in water quality which can
reasonably be estimated and which can be monetized on the basis of generally accepted
economic principles. Methodologies for impacts which can not be quantified or valued in
monetary terms, are outside the scope of this study; and
this study is biased towards methodologies for the valuation of impacts which can be linked
to the water quality models currently running at PBL.
The first two points are in principal similar to the already developed roadmap for the valuation of
freshwater quantities as developed as input for CWON.
1.4. Report structure
This scoping study report contains three core elements:
(i) an outline of a methodology/framework on how to assess and value global water quality
improvements;
(ii) the identification of data and models which are needed to apply this
methodology/framework; and
(iii) an assessment of what is missing and what follow-up actions are needed to fill data and
model gaps, in order to implement the methodology (the roadmap).
Additionally, this report also provides:
(iv) indicative cost data of WWTPs to improve water quality; and
(v) an indicative assessment approach on the costs and health benefits of increasing global
waste water treatment.
Chapter 2 provides a brief summary of the earlies scoping study on valuing fresh water quantities.
Chapter 3 describes the methodology and conceptual framework. Chapter 4 focusses on the
quantification and valuation of impacts. Chapter 5 discusses the global water quality modelling and
the links to SEEA. Chapter 6 contains the indicative assessment approach and Chapter 7 the
roadmap. Appendix A (available as separate pdf-document) gives a detailed methodology for the cost
calculation of drinking water treatment plants (DWTPs) and wastewater treatment plants (WWTPs)
at the global level.
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2. CWON and scoping study on the valuation of freshwater
quantities
This chapter provides a brief overview of the approach adopted in the preceding scoping study on
valuing freshwater quantities on which the current study builds, and some of the preliminary
outcomes of that study.
CWON provides information on the wealth of nations and its development over time, where wealth
includes the asset values of produced, human and natural capital. In order to be included in CWON,
the asset data should (World Bank, 2018a; 2021):
allow for trend analysis, hereto data should cover multiple decades (1990 - 2019), or should
provide sufficient input to interpolate missing years;
be available for at least 100 countries; and
provide a consistent and heterogeneous assessment ensuring inter- comparability between
countries.
The approach to value assets in CWON is based on, and harmonised with, the key concepts of the
System of National Accounts (SNA) and the System of Environmental Economic Accounting (SEEA);
see Textbox 2-1. In CWON, the basic idea is that since much of produced capital is widely marketed,
the market price is a reasonable reflection of the asset value. Other assets - including many natural
resources (e.g. fossil fuel reserves) – may not be traded in markets, but the contributions that these
assets provide to economic activities – e.g. the extracted fossil fuels – do have a market price and the
implicit rent attributable to the asset can be reasonably derived from this price and the costs to
extract the fuels. The value of such asset can then be calculated as the discounted stream of
expected net earnings (i.e. the resource rents) generated over the asset’s lifetime.
In some situations, however, resource rents may turn out to be negative. When rents are negative,
the corresponding value of the asset turns out to be zero. Also in the case of water, resource rents
may turn out to be negative because in many countries, the provision of water is subsidised and
regulated by governments. The tariffs charged to users, if any, often do not cover the full costs of
supply. In such cases, CWON (and SEEA) allows for alternative approaches for asset valuation that
correct for these ‘market failures’ and yield more sensible results. An overview of the most common
non-market valuation approaches is presented in section 3.2.3.
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Textbox 2-1: Valuation of water in SEEA
SEEA describes how environmental assets (natural capital) provide all kind of benefits to our economy and society, as is illustrated in
the figure 1 below.
Figure 1: Schematic overview of contributions made by water to the economy and society
In the SEEA, environmental assets are considered from two perspectives. In the SEEA Central Framework, the focus is on individual
components of the environment that provide materials and space to all economic activities. In the case of water, this would be water
resources like surface water, groundwater or soil water. The focus is on material benefits from the direct use of environmental assets
as natural inputs for the economy by enterprises and households. SEEA Ecosystem Accounting encompasses the same environmental
assets, but focuses on the interactions between individual environmental assets within ecosystems, and on the broad set of material
and non-material benefits that accrue to the economy and other human activity from flows of ecosystem services. Accordingly, for
water we may look at freshwater ecosystems (rivers, lakes, wetlands etc.) and determine the contributions or ecosystem services
provided by these ecosystems. Table 1 below provides an overview of the different contributions that water may provide, the
associated benefits and the users of these benefits. A distinction is made between ecosystem services, i.e. the contributions of
ecosystems to benefits used in economic and other human activity, abiotic flows, i.e. are contributions to benefits from the
environment that are not underpinned by, or reliant on, ecological characteristics and processes, and spatial functions, i.e. the benefits
that arise from the provision of space. These different contributions provided by water may be described in physical terms (for
example how much water is extracted) but also in monetary terms. SEEA provides detailed guidelines on how and with which
methodologies these contributions may be valued in a way that is fully consistent with values as reported in the SNA. In turn, the
discounted value of future returns approach, commonly referred to as the net present value (NPV) approach, is used to calculate the
value of the asset.
Table 1: Contributions from water/ freshwater ecosystems to benefits for the economy and society
These different contributions provided by water may be described in physical terms (for example how much water is extracted) but
also in monetary terms. SEEA provides detailed guidelines on how and with which methodologies these contributions may be valued in
a way that is fully consistent with values as reported in the SNA. Those methodologies are summarized in section 3.2.3.
Benefits Users
Affected by
water q uality?
Ecosystem services
Domestic use: Water supply uti lities,
households,
Industrial use : bussine sses
Agriculture (i rrigation)
Agriculture (l ivestock)
Inland fi sheries Harvested aquatic products
Fishing i ndustry, including direct
househol d consumption; recreation al
fishing
Yes
Receation Physical and mental health; enjo yment Households yes
Nursery populati on and
habitat maintenance
Continuing sup ply of ecosystem services
All ecosy stems, ultimately all sectors
of society
yes
Ecosystem and species
appreciation
Wellbe ing of people deri ved from the existence
and preservation of the environme nt for current
and future generatio ns, irrespective of any
direct or indirect use
Households yes
Abiotic flows
Hydropower Electricity generated Energy sector yes
Cooling Cooling for ind ustrial processes Manufactering / energy sector yes
Spatial functions
Navigation Space for transport over water Transport sector no
Waste accumulation Space for the accumulation of waste House holds, bussinesse s, government no
Enviro nmental cont ributions
yes
Water supply: water
purifi cation + water flow
regulation
Consumptive use by the economy and socie ty,
reduced concentrations of wate r pollutants
providing i mproved health outcomes and/or
reduced water treatment costs
Water:
surface
water p lus
acquifers,
freshwater
ecosystems
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To estimate the asset value of freshwater resources, the 2020 scoping study distinguished between
consumptive and non-consumptive water uses. Consumptive water uses include domestic, industrial,
livestock and irrigation water use,3 while non-consumptive water uses include recreation and
tourism, hydropower, cooling, waste accumulation, inland fisheries, navigation, aquatic biodiversity,
and spiritual and cultural water use.
Table 2-1 presents the average global gross and net physical water demand for consumptive users, as
calculated by the global hydrological model PCR-GLOBWB (Sutanudjaja et al., 2018) over the period
2000-2014. Here, domestic water demand covers all domestic water uses. Irrigation water demand
only covers the water that is supplied to alleviate deficits in soil moisture availability for non-paddy
crops, or to maintain ponded conditions for wet rice; the supplied irrigation water supplements the
crop water requirement that cannot be replenished by rain. Livestock water demand is the amount
of water required for consumption by animals. Gross demand is the demand for water withdrawn
from the water system, of which part is returned as a return flow. The net demand is the difference
between these two. For domestic water demand, the return flow consists of waste water. For
industrial water demand, a considerable part of the return flow is cooling water. In PCR-GLOBWB, a
distinction between gross and net demand is not made for livestock and irrigation.4
Table 2-1: Global gross and net water demand for different water users (average over the
period 2000-2014) (source: Kind et al., 2020)
Use Gross demand Net demand Total abstracted
Net demand
satisfied
(water use)
km3/year % km3/year % km3/year %
Domestic 368 8 221 6
Industrial 816* 17 258 6
Irrigation 3476 74 3476 88
Livestock 16 0.3 16 0.4
Total 4676 100 3971 100 3385 85
* excluding hydropower
The 2020 scoping study also provided a indicative estimate of the global value of freshwater
resources, see Table 2-2. The replacement cost method was used to value freshwater usage for
domestic, industrial and livestock water use, as has been done earlier in the context of SEEAs in
several other countries. The replacement cost is the cost of the next best source - for freshwater the
cost of desalinating and transporting seawater was assumed. The study used the difference between
the cost of water supply systems based on the desalination of seawater and those based on
freshwater to value domestic, industrial and livestock water use. This cost difference differs per
3 Note that water use for mining was not included. PCR-GLOBWB also does not include mining.
4 For livestock, the water demand is for drinking (no return flow). Surplus irrigation water infiltrates into the
ground and contributes to the local water system. Within PCR-GLOBWB this is not quantified as a separate flux
and hence gross and net demand are equal.
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country, region and location, but is likely to be in the range of US$ 0.5 to US$ 2.5 per m3 (Kind et al.,
2020). The other water uses were valued on the basis of resource rent, replacement cost or
opportunity cost. On the basis of the existing water use and uniform and constant global unit values,
Table 2-2 presents a global estimate of the monetary asset value of freshwater, calculated over a
period of 100 years and using a discount rate of 4% per year (as in CWON 2018). This exercise
revealed a total value in the range of US$ 19 to US$ 35 trillion for the uses of domestic (highest),
irrigation, navigation, industrial, hydropower and livestock (lowest). This value is roughly comparable
to the year 2014 values for Forests and Protected Areas (US$ 18 trillion), Agricultural Land (US$ 40
trillion) or Fossil Fuels (US$ 39 trillion), as reported in CWON 2018.
Table 2-2: Indicative Global Asset Value of Freshwater Resources (source: Kind et al., 2020)
User Quantity per
year5
Method Unit value or
range
Contribution to Global
Asset Value of Water
(US$ Trillion)
Remark
Domestic 312.8 km3
water
Replacement cost
(Cost of desalinization)
US$ 0.5 – 1.5
per m3
3.9 – 11.7
Industrial 219.3 km3
water
Replacement cost
(Cost of desalinization)
US$ 0.5 – 1.5
per m3
2.7 – 8.2 Net demand only (no
cooling etc.)
Livestock 13.6 km3 water Replacement cost
(Cost of desalinization)
US$ 0.5 – 1.5
per m3
0.2 – 0.5 For drinking purposes
only
Irrigation 2955 km3
water
Resource rent 5.3 20% of asset value of
Agricultural Land in
CWON 2018
Opportunity cost 0.1 US$/m3 7.4
Hydropower 4.1 million
GWh electricity
Replacement cost 0.02
US$/kWh
0.9
Resource rent 1.2
Inland fishery 11 million ton
fish
Resource rent p.m. Below US$ 2.5 trillion (on
basis of the GVA
indicated by FAO 2018)
Navigation 4.5 trillion tkm
cargo
Replacement cost 0.05€/tkm 6.0 2016, OECD countries
only
Total 19 – 35
Not assessed: recreation & tourism (overlapping values in CWON with forests and protected areas); aquatic biodiversity and
spiritual and cultural values.
p.m.: pro memoria (not valued in Kind et al., 2020)
The result of the analysis presented in Table 2-2 is preliminary. Implementation of the activities and
calculations proposed in the roadmap for CWON has not yet been carried out.
5 For water: 85% of gross demand (see Table 2-1).
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3. Methodology and conceptual framework
This chapter provides a description of the methodology and conceptual framework which is used to
identify and quantify impacts – the so called DPSIR framework. Next, the different steps and options
for valuing the impacts are discussed, and linkages to the valuation of water as done in CWON and
SEEA are provided.
3.1. Conceptual framework
A commonly used framework to describe the interactions between humans and the environment is
the so called DPSIR framework. The frameworks is shown on the left side of Figure 3-1. In the context
of describing the causes and impacts of (changes in) freshwater quality, the
1. Driving forces include human activities (such as agriculture, sanitation and industrial
production) which emit substances to water, but also the consequences of climate change
(like global warming, changing rainfall patterns and sea level rise) and soil subsidence which
ultimately have an impact on freshwater quality;
2. Pressures are for example emissions of different organic and inorganic substances to water,
water extractions, the discharge of water with high temperatures, and saltwater intrusion;
3. State describes amongst others the concentrations of these substances in the water, the
chemical and biological processes which are happening in the water, water temperature, and
the turbidity of the water;
4. Impacts refer (in this study) to the consequences which are of importance for the well-being
of humans, and include the direct and indirect effects on human systems, such as health,
productivity, agriculture, livestock, fisheries, recreation & tourism, biodiversity, and others;
and
5. Responses are the actions which can be taken to reduce or mitigate those adverse impacts.
These actions can either be directed to the driving forces, pressures, state or impact.
Until now, most global water quality assessments, scenarios and models have been focussing on the
driving forces, pressures, state, as well as on the response options. Quantification and valuation of
the (global) impacts of (changes in) water quality is challenging and has received less attention; this is
the focus of this study, which focusses on the relationship between state and impact (right side of
Figure 3-1). In this study, we consider quantification and valuation of impacts as two distinct
activities.
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Figure 3-1: Conceptual framework used in the scoping study. The DPSIR framework is indicated in
green colour. The study has a focus on the relationship between State and Impact.
Quantification and Valuation of Impacts are two distinct activities.
Quantification of impacts means that the impacts of a specific water quality state are expressed in a
physical unit. For example, in the case of human health, the number of deaths which can be
attributed to a specific water quality state (like the presence of pathogens), or in the case of
agriculture, the tonnes of crop yield lost due to a specific water quality state (like the level of
salinity). Quantification of impacts involves:
a) assessing the exposure (of humans, animals, crops, …) to the freshwater of a specific quality
(or state);
b) assessing the vulnerability (also called susceptibility or elasticity) (of humans, animals, crops,
…) of being exposed to freshwater of a specific quality; and
c) calculating the impact in physical terms.
In the context of this study, valuation means assigning monetary values to these physical impacts, as
far as reasonably possible.
3.2. Monetary valuation of effects or impacts
The proposed monetary valuation of the impacts (or effects) 6 in this study, is based on the principles
of social welfare economics. According to these principles, social welfare is a function of the well-
being of all individuals. Individual well-being depends on, among others, consumption, leisure,
health, social contacts and personal development.
6 In this section, we use the terms impacts and effects interchangeably, although they may have different
meanings. See https://pediaa.com/difference-between-impact-and-effect/
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For the monetary valuation of the economic effects, four different types of effect are distinguished,
along two different lines. First is the distinction between priced and non-priced effects. Priced effects
are the effects on the production of goods and services which are traded on markets and for which
market prices exist. Non-priced effects are the effects for which no direct market price exists. The
second distinction is between direct and indirect effects. Direct effects are the effects on a business
or person which are a direct consequence of, for example, the contact with polluted water. The
indirect effects are the result of the direct effects, for example the effects on suppliers or clients of a
business exposed to polluted water. Table 3-1 gives examples of the different types of effects.
Table 3-1: Typology of effects, with examples
Effect Priced Non-priced
Direct Output
Gross value added
Transportation costs
Household expenditures
Reduced travel time
Health effects
Indirect Effects on other businesses Effects on relatives from diseased persons
Congestion
Note: the effects mentioned in this table as an example of the type of effect, can also be classified differently, depending on
the project and on the context.
Different valuation methods are available for those different types of effects, see Table 3-2.
Table 3-2: Typical valuation methods for different types of effects
Effects Priced Non-priced
Direct Market based valuation (with corrections) Non-market valuation methods
Indirect Input/output models
GCE models
Non-market valuation methods
3.2.1. Market based valuation (direct, priced effects)
The valuation of direct priced effects can be based on the prices of goods and services (used as inputs
or outputs) observed in markets. For example, the effect of increased salinity of irrigation water for
the agriculture sector can be based on the market value of the reduced physical crop yield.
It should be noted that market based valuation is most appropriate in the absence of (important)
“market failures”. In this case, goods and services are freely traded in markets, and the prices of
goods and services as observed in markets may be used as good representations of their economic
values (which is, in welfare economics, the amount of money people are willing-to-pay or willing-to-
accept to exchange the (last unit of the) good or service). However, in many situations, market
failures do exist. Examples of market failures in the water domain are imperfect competition (e.g.,
monopolistic water supply), public goods (e.g., flood protection and water resource management),
externalities (e.g., “free” water pollution), the under-provision of merit goods (e.g., drinking water
and sanitation facilities), or environmental concerns (e.g., depletion of aquifers). In those cases,
governments often regulate markets, and provide subsidies or impose taxes on production or
consumption. In the case of water, one of the important consequences is that the tariffs (prices)
charged for agricultural and domestic water use are often subsidized and do not cover the cost of
supply. Such low water prices lead to excessive water demand, and the marginal benefit of using (the
last unit of water) is subsequently lower than the marginal cost of supplying it. In this case, raising
the tariff will decrease water use and will increase marginal water values.
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Scoping study assessing the value of freshwater quality at a global scale 15
Corrections for market failure are not (yet) part of the proposed valuation methodology. This is
complex and the required information (which incudes information on tariffs vs. costs, and price
elasticities of water supply and demand) is not available at the global level. A reflection on the values
of freshwater quality which takes into account the possible distortions caused by market failure on
the calculated values, and possibly a scenario in which (some of) the distortions are terminated, may
however be desired in future.
3.2.2. Indirect, priced effects
Typical approaches to estimate and value indirect priced effects are input-output models and
computable general equilibrium (CGE) models (e.g., Fadali et al., 2012). In the context of this study, it
is considered too complex to use such models and hence these are not included.
3.2.3. Non-market valuation methods
A variety of methods have been developed to monetary value goods, services or assets for which no
proper market price exists. For overviews, see for example Brouwer et al. (2009) and UNSD et al.,
2021). The most prevalent methods are summarized below. Which method is the most appropriate,
depends on the required value concept, the water use under consideration, as well as the availability
of data. Chapter 4 will discuss or propose some of these methods within a specific context.
Replacement cost method. This method values goods or services on the basis of its (least cost)
alternative. For example, for valuing the consumption of water from a freshwater resource, the
replacement cost would consider the cost of the alternatives desalinization of seawater, rainwater
harvesting or wastewater reuse. The validity of the replacement cost method depends upon three
conditions being maintained: (i) the substitute can provide exactly the same function as the service
being substituted for; (ii) the substitute used is the least-cost alternative; and (iii) there is a
willingness to pay for the substitute if the good or service were to be no longer supplied.
Avoided damage costs. The avoided damage costs method estimates the value of services based on
the costs of the damages that would occur due to the loss of these services. Similar to replacement
costs, the focus will generally be on services that are lost if the ecosystem or underlying asset were
not present or was in sufficiently poor condition such that the services were not available. For
example, the value of the provision of clean drinking water to households may be related to avoided
health costs.
Hedonic pricing method. This method attributes the value of an asset to its different characteristics.
For example, on the basis of the price differential between irrigated and rainfed cropland, the value
of irrigation water can be isolated.
Opportunity cost. These are equal to the benefits forgone by not allocating an additional unit of
water to its most economically productive use at a specific location in a river basin at a specific
moment in time.
Contingent valuation method. Contingent valuation is based on welfare economic theory which uses
willingness-to-pay (WTP) or willingness-to-accept (WTA) methods as a basis for valuation. WTP
indicates the well-being individuals derive from a good or service and can be estimated on the basis
of surveys. WTP can be used to estimate marginal values of incremental freshwater supply, but it
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Scoping study assessing the value of freshwater quality at a global scale 16
cannot be used to provide a total value of water for human consumption, simply because the value
of the first litres of water per day for drinking, cooking and hygiene is infinitely high.
Travel cost method. The travel cost method is used to estimate economic use values associated with
ecosystems or sites that are used for recreation. The method can be used to estimate the economic
benefits or costs resulting from (a) changes in access costs for a recreational site (b) elimination of an
existing recreational site (c) addition of a new recreational site or (d) changes in environmental
quality at a recreational site. The basic premise of the travel cost method is that the time and travel
cost expenses that people incur to visit a site represent the “price” of access to the site. Thus,
peoples’ willingness to pay to visit the site can be estimated based on the number of trips that they
make at different travel costs. This is analogous to estimating peoples’ willingness to pay for a
marketed good based on the quantity demanded at different prices
(https://www.ecosystemvaluation.org/travel_costs.htm).
Benefit transfer. The benefit transfer method is used to estimate economic values for ecosystem
services by transferring available information from studies already completed in another location
and/or context. For example, values for recreational fishing in a particular state may be estimated by
applying measures of recreational fishing values from a study conducted in another state
(https://www.ecosystemvaluation.org/benefit_transfer.htm).
3.2.4. Asset valuation
A common way to quantify and value effects or impacts is to express them in annual terms. For
example, the annual demand for water, the annual water treatment cost, or the annual number of
people which die because of diarrhoea. Physical and monetary values expressed in this way are
called “flows”. Expressing the monetary impacts in terms of flows allows for comparison and
aggregation of impacts.
Another option is to express and summarize the impacts in terms of changes in the values of capital
stocks. This is asset valuation. In CWON, the default approach to asset valuation is based on the
concept that the value of an asset is equal to the discounted stream of expected net earnings
(resource rents) generated over its lifetime. Asset value 𝑉 is calculated as the discounted sum of
annual rents, 𝑅, over the lifetime, 𝑇, with a real discount rate, 𝑟, of 4% per year. For resources that
are managed sustainably, CWON assumes a time horizon 𝑇 of 100 years.7 In case we do not assume
any growth in rents, then:
𝑉 =

() [Eq. 1]
𝑅 is calculated simply as the price, 𝑝, times quantity, 𝑞, minus the related costs for extraction,
purification, distribution, etc., 𝑐:
𝑅=(𝑝 × 𝑞) 𝑐) [Eq. 2]
7 In the case of renewable resources, the time horizon can be less when extraction exceeds natural
regeneration and hence sustainability is at stake. See Kind et al., 2020.
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Scoping study assessing the value of freshwater quality at a global scale 17
This is similar to the market valuation discussed in section 3.2.1. Also here, it shows that the value of
a freshwater resource is not only determined by its quantity 𝑞, but also by its quality. Water quality
has an impact on the costs to purify and re-use water (variable 𝑐 in Eq. 2).
Again, the rents can turn out to be zero when the tariff does not cover the full costs of supply, in
which case alternative methods are needed to derive values for freshwater and freshwater quality
improvements which have been discussed in section 3.2.3 above. Assessing the impact of (changes in
the ) freshwater quality on the values of water assets in the context of CWON thus requires that the
impacts are quantified and valued according to the principles described in this chapter. Additionally,
asset valuation also captures
- the potential growth in rents; and
- the sustainable use and remaining life time of the asset.
It is important to note that in case of more than one natural asset, like water and land used for
agriculture, or water and forests providing recreation ecosystem services, the derivation of the
resource rent and hence asset value for the single natural asset (e.g., water, land or forest) may not
be straightforward. This requires that the rent is attributed to two (or more) individual natural capital
assets for which no (proper) market prices exists. It is also important to note that the health impacts
discussed in this study are in the context of natural capital accounting (like CWON ) not reflected in
the asset value of water, but in the asset value of human capital instead.
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Scoping study assessing the value of freshwater quality at a global scale 18
4. Impacts due to changes in water quality
In this chapter, some of the most important impacts associated with changes in freshwater quality
are described. The chapter discusses those impacts and identifies global data sources and models
which can be used to quantify and value the impacts. Actions for a roadmap are identified; these
actions form the basis for an overall roadmap in chapter 7.
4.1. Introduction
There is no universal definition of “Water quality”. Water quality is a complex concept with different
dimensions and multiple parameters or indicators which can be used to ‘measure’ it. Near-global
coverage of monitoring data for specific water quality parameters is scant or absent. When water
quality is not well known, the possibilities to quantify and value impacts associated with water
quality changes are limited, and any estimate and compilation of such impacts will be uncertain and
incomplete.
Figure 4-1 provides an overview of the driving forces, pressures, states and impacts in the context of
freshwater quality, roughly based on the literature consulted for this scoping study. There are many
relationships between those D’s-P’s-S’s and I’s, which are not exclusive. For example, health impacts
may be the results of different water quality problems (states), for example pathogens, arsenic or
harmful algal blossom. A water quality state, such as the presence of harmful algal blossom, may be
the result of different pressures (e.g., nutrients and high temperature). And different pressures (e.g.,
nutrients) may be the result of different driving forces (e.g., agriculture and sewage).
Figure 4-1: Illustration of Driving Forces, Pressures, State and Impact in the context of freshwater
quality
The following subsections describe for a number of these impacts the relationship between the
impact and freshwater quality (state). Existing databases and models to quantify and value those
impacts are identified, and gaps in knowledge and data formulated. The following impacts are
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Scoping study assessing the value of freshwater quality at a global scale 19
included: human health impacts, impacts on drinking water costs, impacts on industries, impacts on
mining, impacts on irrigated agriculture, impacts on livestock, impacts on hydropower, impacts on
inland fisheries, and impacts on recreation and tourism.
It should be noted that quantification and valuation of those impacts are characterized by a high
degree of uncertainty. How uncertainty is best taken into account in an impact assessment, is
dependent of the specific context and purpose of the assessment and is not further discussed in this
chapter.
4.2. Impacts on human health
4.2.1. Description
Human health is directly and indirectly related to the quality of freshwater and the management of
the water resource. Water is used by households for different purposes such as drinking, cooking,
washing, bathing, cleaning, swimming and (vegetable) gardening. Health problems arise when the
water is unsafe for these purposes. This may be the case due for example the presence of pathogens,
or contaminants such as nitrate, lead or arsenic. Health is also related to the management and
maintenance of fresh waterbodies, which can provide habitats for vector related diseases. An
example are plastics in waterbodies that provide habitats for malaria mosquitoes (WWQA, 2020).
Table 4-1 lists the so-called health outcomes which, according to the literature, can at least partly be
attributed to unsafe water, sanitation and hygiene (WASH) behaviour. For health outcomes indicated
in bold, the attribution to WASH is described and quantified in Prüss-Ustün et al. (2019). For the
other health outcomes, only an indicative attribution to WASH and other (non-WASH) environmental
factors is available, see WHO (2018: Table A2.2).
Table 4-1: Adverse health outcomes that are at least partly attributable to inadequate water,
sanitation and hygiene behaviours (Table copied from Prüss-Ustün et al., 2019).
Health impacts can be acute or chronic and include mortality, disease, disability and stunting. Those
health impacts also cause secondary (non-health) impacts, such as medical cost incurred to treat the
water related health impacts, losses in productivity and/or wage earnings, and losses in education.
Some of those losses are indirect and often long term results of the water related health impacts,
esp. when young children are affected. See for examples and case studies of direct and indirect
immediate and long-term health impacts the report Quality Unknown (World Bank, 2019a).
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Scoping study assessing the value of freshwater quality at a global scale 20
4.2.2. Quantification
Health
The most commonly used health metric to compare and quantify different health impacts, as well as
to quantify the global burden of disease (GBD), is the disability adjusted life years (DALYs). DALYs
combine mortality and disability and are equal to the sum of years of life lost (YLL) and the years
lived with disability (YLD).
At the global level, the most important water related disease is diarrhoea. This disease is primarily
present in developing countries, where many people are still lacking access to safe drinking water
and sanitation facilities. Other major water related diseases are malaria and malnutrition. For the
quantification of the GBD and the WASH attributable part of the GBD, there are two major data
sources: IHME (http://www.healthdata.org/) and WHO (https://www.who.int/data/gho). Although
these organisations use different methodologies and data sources to quantify the GBD, the order of
magnitude of the WASH related health outcomes does not differ.
According to Prüss-Ustün et al. (2019), who uses WHO data, the total number of diarrhoeal deaths in
2016 was 1.4 million. Of those, 485,000 deaths were attributable to inadequate water, 432,000 to
inadequate sanitation and 165,000 to inadequate hygiene behaviours. Of these numbers, in total,
829,000 diarrhoeal deaths (60% of total diarrhoeal deaths) could have been prevented through
improved drinking water and sanitation services, and handwashing with soap. Table 4-2 provides a
summary of the WASH-attributable (and preventable) disease burden for 2016, in terms of both
deaths and DALYs.
Table 4-2: WASH-attributable (and preventable) disease burden for 2016 (Table based on Prüss-
Ustün et al., 2019)
Disease
Deaths
DALYs
Schistosomiasis
10,405
1,095,658
Diarrhoea
828,651
49,773,959
Acute respiratory infections*
370,370
17,308,136
Protein
-
energy malnutrition
28,194
2,995,329
Malaria
354,924
29,707,805
Soil
-
transmitted helminth
Infections
6,248
3,430,614
Trachoma
<10
244,471
*Acute respiratory infections are mainly linked to hygiene behaviour; see Table 4-1.
Exposure and vulnerability data
In general, data linking human health impacts directly to specific water quality parameters is scarce
and lacking at the large spatial scale, making quantification of the impacts on the basis of water
quality parameters difficult (WWQA, 2020). Attribution of a death or disease to a specific
cause/contaminant is problematic, due to the lack of exposure and vulnerability data. The existing
risk models which are used for the attribution of the disease burden to specific causes, are based on
censuses and health surveys, which link the health impacts to exposure factors such as the type of
water supply and sanitation facilities used. These risk models also provide the basis for estimating
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Scoping study assessing the value of freshwater quality at a global scale 21
the health benefits of WASH interventions, see as an example Table 4-3. It is important to note that
water quality parameters (i.e., state) are not used in those types of risk models to estimate impact.
Table 4-3: Relative risk reductions in health impacts for WASH interventions (copied from
Hutton 2015)
In terms of our DPSIR model presented in Figure 3-1, this means that a linkage between State and
Impact is unknown. Rather, the estimated reductions in health outcomes are based on what is known
about the effects of the Response options (i.e., the uptake of interventions to improve water supply,
sanitation and health behaviour).
Medical costs, loss in productivity and loss in education
In ‘Benefits and Costs of the Water and Sanitation Targets for the Post-2015 Development Agenda’,
World Bank economist Guy Hutton presents global estimates of the benefits of improving WASH
coverage worldwide (Hutton, 2015). Those benefits include reduced mortality, increased productivity
and reduced health care costs. 8
4.2.3. Valuation
Health
Valuing health impacts in monetary terms is not uncontroversial. Three approaches are most
common (European Commission, n.d.; WHO, 2011):
1. Value of Statistical Life (VOSL) and Value of Statistical Life Year (VOLY) approaches, which
are based on stated preferences by individuals for a lower risk of mortality (VOSL) or an
increase of one year life expectancy (VOLY). VOSL and VOLY do not include values for the
quality of life;
2. Cost of Illness method, which considers only the medical expenses related to the incidence
of an illness; and
8 According to Hutton, at the global level, reduced access time represents the largest benefit of improved
WASH interventions (about 70%; Figures 1 and 2 in Hutton, 2015). Those benefits are not related to improved
freshwater quality. The other 30% of the benefits is roughly equally distributed over reduced mortality,
increased productivity and reduced health care costs (Figures 1 and 2 in Hutton, 2015). Also note that some of
the assumptions underlying the calculations by Hutton are not without concerns (see Whittington, 2018).
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Scoping study assessing the value of freshwater quality at a global scale 22
3. Human Capital Method, which captures the loss of future earnings in case of disability or
premature death.
Those methods partly overlap and cannot be used simultaneously, and choosing a method and value
is not without controverse. A standard value for the DALY, which is based on the human capital
approach, implies that the monetary value of a DALY is equal to 1 × GDP per capita (WHO, 2011). This
is roughly in line with the results of Daroudi et al. (2021), who show that actual medical cost per
DALY adverted ranges from 0.34 times GDP per capita for countries with a low human development
index (HDI), to 1.46 times GDP per capita for countries with a very high HDI.
Another option is to use the VOSL and VOLY, which also differ per country. For an indicative value, an
estimate of the VOSL of 120 × GDP per capita can be used (Miller, 2000).
Medical costs
Hutton (2015) provides assumptions and values to estimate these costs; those are not repeated here.
4.2.4. Models and data
The following model and/or data sources have been identified which are helpful for the
quantification and valuation of the health impacts.
Table 4-4: Global models and data – health
Name Organisation/Author Description URL
Global health
observatory (GHO)
WHO Contains global health data including
WASH
https://www.who.int/data/gho
Prüss-Ustün et al., 2019 Appendix A - Supplementary data
presents per country the
WASH-attributable (and preventable)
disease burden for 2016 (as presented
in Table 4.2 above).
https://www.sciencedirect.com
/science/article/pii/S143846391
8310484?via%3Dihub#appsec1
Demographic and
Health Surveys(DHS)
USAID Presents global and national survey data
on WASH, health and diseases, including
data on for example measures taken by
households and medical treatments.
https://www.statcompiler.com/
en/
UNICEF Data UNICEF Contains datasets on for example on
diarrhoea and WASH.
https://data.unicef.org/resourc
es/resource-type/datasets/#
Multiple Indicator
Cluster Surveys (MICS)
UNICEF Contains country surveys of key
indicators on the well-being of children
and women.
https://mics.unicef.org/
JMP global database on
WASH
WHO and UNICEF Includes nearly 5,000 national datasets
enabling the production of estimates for
over 200 countries, areas, and
territories. National, regional and global
estimates can be explored online or
downloaded for further analysis.
https://washdata.org/
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Scoping study assessing the value of freshwater quality at a global scale 23
Name Organisation/Author Description URL
Global Health Data
Exchange (GHDx)
and
GBD Compare
Institute for Health Metrics
and Evaluation
(IHME)
These databases contain global health
data as well as the results of risk
models.
http://ghdx.healthdata.org/gbd
-results-tool
and
https://vizhub.healthdata.org/g
bd-compare/
Onehealth Tool WHO Model to support national strategic
health planning in low- and middle-
income countries. The tool facilitates an
assessment of resource needs
associated with key strategic activities
and their associated costs, with a focus
on integrated planning and
strengthening health systems.
This model can be used to estimate the
medical treatment costs in different
countries.
https://www.who.int/tools/one
health
https://avenirhealth.org/softwa
re-onehealth.php.
https://avenirhealth.org/Downl
oad/Spectrum/Manuals/Treatm
ent%20Assumptions%202016%
201%2010.pdf
4.2.5. Link to freshwater quality parameters
As has been explained in section 4.2.2, it is currently not possible to quantitatively link health impacts
to specific freshwater quality parameters (WWQA, 2021). Obvious candidates for which such linkage
would be desirable, are the parameters mentioned in the different drinking water standards. Those
drinking water standards differ per country. The WHO guidelines for drinking water quality (WHO,
2017) discuss a large number of water quality parameters which relate to human health.
4.2.6. Activities for the roadmap
We propose the following activities for the roadmap:
Develop and test a methodology to assess the global exposure of the world population to the
most important contaminants in water, combining country data, micro-studies and
modelling. Apart from concentrations, exposure data should likely also consider frequency
and duration.
Collect and review case-studies on the relationships between contaminants and human
health. Prioritise what contaminants should be taken into account. Set up a database,
develop functions which consider concentrations, frequency and duration.
Conduct additional efforts to attribute other health outcomes to unsafe WASH and/or
contaminants.
Develop an integrated model to estimate health impacts as function of exposure, dose and
vulnerability.
Develop a – as widely supported as possible – monetary valuation concept for the different
health impacts associated with water quality.
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Scoping study assessing the value of freshwater quality at a global scale 24
4.3. Impacts on the cost of drinking water treatment
4.3.1. Description
When the pollution of the surface water (the influent) increases, more water treatment processes
may be needed to purify the water sufficiently to meet the drinking water standards of a specific
country, and hence the cost of drinking water supply increases. An overview of the different
technical options for treating water quality problems can be found in Brikké and Bredero (2003, par.
6.1) or online at https://www.nesc.wvu.edu/drinking-water/resources-for-operators/water-
treatment and https://wateroperatorhq.com/water-treatment-process/.
4.3.2. Quantification
Domestic water use is estimated at some 312.8 km3 per year (Table 2-2). Only part of this volume is
actually treated and delivered by water supply utilities. Data collected by the Joint Monitoring
Programme (JMP) of the WHO/UNICEF shows that the global population with piped water supply in
2020 amounts to just over 60% (www.washdata.org).
4.3.3. Valuation
The impact of changes in the quality of freshwater as influent for drinking water production can be
valued on the basis of the additional treatment cost. The additional treatment depends on the
contaminants which need to be removed from the water.
The number of scientific articles on the cost of municipal water supply as function of raw surface
water quality is rather limited. Sediment, measured as turbidity, is the most often used primary
indicator of water quality in such articles, as this often accounts for the largest percentage of
suspended solids, and chemical contaminants attach to it (Dearmont et al., 1998). In a case study for
Texas, Dearmont et al. conclude that a 1% increase in turbidity increases the chemical costs by
0.25%. In Texas, the presence of raw water contamination for selected utilities leads to an additional
cost for water treatment of about US$ 0.025 per m3 (1998 prices).9
The additional treatment cost can also be determined on the basis of the extra treatment steps
needed to purify the water, which depend on the influent. For the Netherlands, such calculations can
be made with the Cost Calculator Drinking Water (see https://kostenstandaard.nl/), for some
examples, see Table 4-5 . Appendix A discusses how such cost estimates can be translated to other
countries, with different labour, material and other costs.
9 US$95 per 3785 m3 (Dearmont et al., 1998).
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Scoping study assessing the value of freshwater quality at a global scale 25
Table 4-5: Examples of unit treatment cost on the basis of different qualities of the influent
Level of
treatment
Description Treatment
cost (US$/m3,
year 2020
price level)*
Basic treatment A basic treatment consists of the following steps:
intake pump station
pre settlement
cascade
chemical dosing and coagulation
lamella or tube settlers
rapid sand filtration
chlorine dosing
clear water tank
high pressure pump station
0.43
Normal water
treatment
When the quality of the freshwater source is less than average (like most surface
water sources in the Netherlands), additional treatment steps may be needed like
micro sieve at the intake and active coal after rapid sand filtration.
0.52
Intensive water
treatment
When the quality of the freshwater source further deteriorates, an intake settling
lake may be necessary including advanced oxidation processes to kill all the
bacteria, viruses and chemical residues in the water.
0.90
Very intensive
water treatment
When the quality of the freshwater source further deteriorates, a different kind
of treatment process may be needed, for example membrane technology to
sufficiently kill all the bacteria, viruses and chemical residues in the water source.
1.30
*: see Appendix A-1. Indicated unit costs are for a treatment plant with a capacity of 1000 m3 per hour. Exchange rate of €
1= US$ 1.13 has been used.
4.3.4. Models and data
The following model and/or data sources have been identified which are helpful for the
quantification and valuation of the impacts on the cost of drinking water treatment.
Table 4-6: Global models and data – cost of drinking water treatment
Name Organisation/Author Description URL
Joint Monitoring
Programme (JMP)
WHO and UNICEF JMP estimates are calculated from data
produced by national authorities. The
JMP database includes over 5,000
national data sources with information
on WASH in households including
nationally representative household
surveys, censuses and administrative
reports.
https://washdata.org/data
Kostenstandaard
drinkwater
RHDHV In collaboration with Dutch water
companies, RHDHV developed the Cost
Standard for drinking water. The costs
are broken down per treatment step.
@In Appendix A, a methodology has
been proposed to adjust the water
treatment cost calculated for the
Netherlands to other
countries/contexts.
https://kostenstandaard.nl/
(paid subscription)
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4.3.5. Link to freshwater quality parameters
There are many parameters which are relevant for drinking water quality; these however differ per
country. The WHO has also issued guidelines (WHO, 2017a).
The main drinking water treatment indicator is the removal of pathogenic bacteria, viruses and
protozoa. The necessary log reduction values can be used as an indicator (WHO 2017b).
Other parameters which may be important for drinking water include electrical conductivity,
hardness, pH, chloride. See for example
https://www.lenntech.com/applications/process/process.htm
4.3.6. Activities for the roadmap
We propose the following activities for the roadmap:
Break down the total drinking water use in drinking water use with different types of raw
water sources: groundwater, surface water, brackish or seawater;
Define the main types of drinking water treatment processes used by countries depending on
the water source and the development of a specific country;
Develop a coherent set of water quality criteria which may be assumed for those main types
of drinking water treatment;
Calculate the unit costs of water treatment for each country, based on the different water
qualities parameters of the influent, and construct a cost function.
4.4. Impacts on Industries
4.4.1. Description
Global industrial water use is estimated at some 694 km2 per year, of which 220 km2 per year is for
processing and 474 km2 per year for cooling.10 For both cooling and processing, water quality can be
important. A lower quality of surface water or ground water can lead to higher purification costs,
depending on the industries’ water quality criteria. Those criteria depend on the processes and the
products water is used for.
4.4.2. Quantification
The different quality requirement of industrial water at the global level are not known. This makes it
hard to quantify and value impacts.
4.4.3. Valuation
Once the quality requirements of industrial water are known, the ‘kostenstandaard’ for domestic
water treatment can also be used to value the impacts of changes in water qualities for industries in
terms of changes in the treatment cost.
10 85% of the figures in Table 2-1.
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Scoping study assessing the value of freshwater quality at a global scale 27
4.4.4. Models and data
Global data and models on the water quality requirements for different industries are not available.
4.4.5. Link to freshwater quality parameters
Parameters which may be important for industries include suspended solids, electrical conductivity,
hardness, pH, chloride, bacteria, and others. See for example
https://www.lenntech.com/applications/process/process.htm and
https://www.lenntech.com/applications/process/cooling/cooling-water-quality.htm
4.4.6. Activities for the roadmap
The following activities are proposed for the roadmap:
Break down the total industrial water use to the water use for different main types of industries,
based on for example SEEA statistics and-coefficients, and water footprint (or similar) statistics
(see https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/).
Develop a coherent set of water quality criteria which may be assumed for those main types
industries;
For the development of cost functions, see the section on the roadmap activities for the cost of
drinking water treatment (section 4.3.6 above).
4.5. Impacts on Mining
4.5.1. Description
Mining was not included in the previous study for CWON, and the global quantities of water used in
mining activities are currently unknown. The demands for water within a mining operation will vary
from system to system and may include water for cooling, dust control, flotation operations, human
consumption and steam production (https://blog.burnsmcd.com/water-for-mining-whats-needed-
and-whats-available). Like water for industries, water quality is important for some of those uses for
mining.
4.5.2. Quantification
The water usage of mines is not known, nor a breakdown of this water usage for the different uses.
This makes it hard to quantify and value impacts.
4.5.3. Valuation
Once the quality requirements of mining water are known, the ‘kostenstandaard’ for domestic water
can also be uses to value the impacts on mining in terms of changes in the treatment cost.
4.5.4. Models and data
Not available.
4.5.5. Link to freshwater quality parameters
See industries and domestic water supply.
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Scoping study assessing the value of freshwater quality at a global scale 28
4.5.6. Activities for the roadmap
The following activities are proposed for the roadmap:
To get better insights in the relationship between mining and freshwater demand (and
pollution), several mining data (e.g., Maus et al., 2020; Werner et al., 2020; Liang et al., 2021)
may be used in combination with overlays of water.
Use SEEAs of countries for information on water usage of mines and mining products to
estimate emission coefficients.
Develop a coherent set of water quality criteria which may be assumed for the different
types of mining activities.
4.6. Impacts on irrigated agriculture
4.6.1. Description
Irrigation is the largest water user, with an estimated average global use of 2955 km3 per year (see
Table 2-2). About 20% of the earth’ agricultural land is irrigated (255 thousand km2), while the
contribution of irrigated agricultural land to global food production is estimated at some 40%.
The most important link between freshwater quality (State) and irrigated agricultural production
(Impact) is the level of salinization (e.g., Mateo-Sagasta & Burke, 2010). Higher levels of salinity lead
to reduced crop yields, or render freshwater unsuitable for irrigation purposes.
Other linkages between freshwater quality and irrigated agricultural production include toxicity
(especially chloride, sodium and boron ; see FAO, 1985: chapter 4), the uptake by crops of
contaminants from irrigation water that are dangerous for humans (e.g., Stasinos & Zabetakis, 2013),
and suspended sediment in water which reduces the storage volume and lifetime of reservoirs and
hence reduces irrigation water availability. These other linkages have not been included in this
scoping study.
4.6.2. Quantification
In order to quantify the physical impact (of different levels) of salinity on crop production, the
following information is required:
the types of crop grown on irrigated areas;
the amount of irrigation water applied;
the salinity of irrigation water;
crop yields; and
the response curve relating crop yields to salinity.
The extent to which those are available, is discussed in section 4.6.4.
A recent study which has provided a (first) estimate of the global average loss (i.e., impact) due to
saline irrigation water, is the World Bank study “Salt of the Earth, Quantifying the Impact of Water
Salinity on Global Agricultural Productivity” (Russ et al., 2020; also published in World Bank, 2019a).
This study employs advanced machine learning techniques to estimate concentrations and hotspots
of electrical conductivity (i.e., salinity). Amongst others, GEMSTAT data (see chapter 5) has been used
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Scoping study assessing the value of freshwater quality at a global scale 29
as input. This study has estimated global average annual losses over the period 2001-2013 due to
saline water of in total 124 trillion kilocalorie equivalents. On the basis of 2,000 calories/person/day,
these calories cover the food budgets of 170 million people annually. In the report by Russ et al., this
loss in calories has not been translated into a monetary amount.11
4.6.3. Valuation
There are two candidate methods to value changes in the salinity of irrigation water in economic
terms.
A first method is to look at agricultural land prices and to investigate how these are related to salinity
(i.e., hedonic pricing). An advantage of this method is that the derived values do not only reflect the
differences in yields of a specific crop due to saline water, but also the options farmers have to
change (adapt) their agricultural practices, for example by choosing more salt tolerant crops. For a
discussion and examples of this method, see Koundouri & Pashardes (2001) and Lee (2020).
However, because detailed, georeferenced information on (urban and rural) land prices is not
available in a global database (Coomes et al., 2018), and because in many countries, land markets are
not free but regulated (and hence land prices may not reflect economic land values), this method
does not qualify for a global application.
The second method is based on the valuation of modelled yield losses (as described in section 4.6.2).
The valuation can be based on the loss in revenues in case the agricultural costs do not change. See
for an example D’Odorico et al., 2020. In case irrigation is no longer economically feasible, the losses
should also be adjusted for the savings in the cost of irrigation, which is then no longer practised.
This method is likely to overestimate the damage caused by salinization, as it does not take the
ability of farmers to adapt into account, unless a model is developed and employed which optimizes
farmers’ crop choices based on amongst others the level of salinity. To our knowledge, such a model
does not exist at the global level.
4.6.4. Models and data
Table 4-7 lists models and data which can be used to quantify and value the impacts for irrigated
agriculture.
Table 4-7: Global models and data – irrigated agriculture
Name Organisation/Author Description URL
FAOSTAT FAO Provides food and agriculture data for
over 245 countries from 1961 to the
most recent year available. Data
includes yields and prices of agricultural
outputs and inputs.
https://www.fao.org/faostat/e
n/#data
11 To give an idea: the energy value of cereals is about 4,000 calories/kg. Hence, for 2,000 calories a person
needs 0.5 kg of cereals per day. At a world price of US$0.20/kg, the loss would be 170 million x 0.5 x US$0.20 x
365 / 1000 = US$6.2 billion per year. Depending on demand and supply, in local markets, higher prices may
apply and the monetary loss would be valued subsequently higher.
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Scoping study assessing the value of freshwater quality at a global scale 30
Name Organisation/Author Description URL
Global Map of Irrigation
Areas (GMIA)
FAO Map showing the area (2005) equipped
for irrigation and area actually used for
irrigation (in % of cell).
Water sources include groundwater,
surface water and non-conventional
water sources
Raster with a spatial resolution of 5 arc-
minutes (cells of about 10 x 10 km at the
equator).
http://www.fao.org/land-
water/land/land-
governance/land-resources-
planning-
toolbox/category/details/es/c/1
029519/
https://www.researchgate.net/
publication/264556183_Update
_of_the_digital_global_map_of
_irrigation_areas_to_version_5
Land Cover Map 2020 Climate Change Initiative Landuse map. Contains detailed data on
irrigation
http://maps.elie.ucl.ac.be/CCI/v
iewer/index.php
MODIS Primary
Production
NASA Net primary production (NPP) from
cropland on the basis of satellite data
can be used to estimate detailed
agricultural crop production (as has
been proposed in Russ et al. (2020))
https://modis.gsfc.nasa.gov/dat
a/dataprod/mod17.php
Response curves for
salinity
Tanji & Kielen (2002) / FAO This book provides in Annex 1 detailed
response curves for salinity for different
crops.
http://www.fao.org/3/ap103e/
ap103e.pdf.
Global Agro-Ecological
Zones (GAEZ)
FAO GAEZ is a model which can be used to
calculate global attainable yields and
actual yields. In this model, salinity is an
input which constrains crop production.
http://www.fao.org/documents
/card/en/c/cb4744en
Lund-Potsdam-Jena
managed Land (LPJmL)
PIK & PBL Global crop-hydrology mode, which is
able to calculate global irrigation
demand based on gridded global crop
allocation (13 crops rainfed, 13 crops
irrigated).
https://www.pik-
potsdam.de/en/institute/depar
tments/activities/biosphere-
water-modelling/lpjml/versions
4.6.5. Link to freshwater quality parameters
Table 4-8 provides the most relevant water quality parameters for irrigation water according to the
FAO (1985). Next to salinity, the most relevant parameters are sodium, chloride, boron, nitrogen,
bicarbonate and pH.
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Scoping study assessing the value of freshwater quality at a global scale 31
Table 4-8: Guidelines for interpretations of water quality for irrigation (copied from FAO, 1985)
4.6.6. Activities for the roadmap
We propose the following activities for the roadmap
Development of an agricultural (meta?) model to estimate the global impacts of salt in
irrigation water. All building blocks are available.
Determine which other pollutants in water are the most relevant for agriculture and it these
can be integrated in future versions of the model.
4.7. Impacts on livestock
4.7.1. Description
The global use of freshwater by livestock for drinking is relatively small, estimated at 13.6 km3 per
year (Table 2-2). Data on the different sources of livestock drinking water (i.e. surface water,
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Scoping study assessing the value of freshwater quality at a global scale 32
groundwater, municipal water supply, desalinated water) is missing at the global scale, making it
difficult to link livestock drinking water to the quality of those fresh water resources.
The quality of drinking water is important for livestock and influences animal welfare, health,
mortality, reproduction and livestock products.
4.7.2. Quantification
The quantification and valuation of the impacts of water quality on livestock should at least
distinguish between:
livestock health – diseases;
livestock health – poisoning; and
livestock products.
Diseases
The ‘World Livestock Disease Atlas’ (World Bank, 2011) provides a quantitative analysis of global
animal health data for the period 2006-2009. The disease burden (in terms of LSUs12 lost) is
quantified per type of disease and per country. The analysis is based on amongst other data from the
OIE World Animal Health Information System (OIE-WAHIS) published by the World Organisation for
Animal Health (OIE). On average, 762,212 LSUs were lost during this period. The top 10 diseases,
which make up some 80% of total LSUs lost, are listed in Table 4-9 below.
Table 4-9: Top 10 livestock diseases (copied from World Bank, 2011)
12 LSU = livestock unit and is used for the aggregation of different types of livestock animals. In the EU, the
reference unit used for the calculation of 1 livestock unit is the grazing equivalent of one adult dairy cow
producing 3,000 kg of milk annually. LSU coefficients for other animals can be found at
https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Livestock_unit_(LSU). Note that in
the World Bank (2011) report, somewhat other coefficients have been used.
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Scoping study assessing the value of freshwater quality at a global scale 33
A quick-and-dirty internet search on those top-ten diseases in combination with “water” or “water
quality” reveals that although some of those diseases can be spread via surface water, water and
water quality itself are not risk factors. Hence, the attribution of animal health to surface water
quality – comparable to the attribution of human health to WASH deficiencies – is not likely to
conclude that surface water quality is a relevant factor for the spreading of the above diseases. A
sound scientific review of the literature on livestock and animal health may be needed to confirm this
premature conclusion, including for the diseases not listed in this top-10. In the context of this
scoping study, the impact of the current water quality on livestock diseases remains however
unspecified.
Poisoning
Harmful algal bloom, salt, nitrate, arsenic, lead and other substances may lead to the poisoning of
livestock and to acute or chronic health impacts. However, we have identified no data or global
database which can be helpful to quantify those impacts (i.e., data on exposure, dose &
vulnerability).
Livestock products
The most often mentioned water quality parameter with respect to livestock products is salt. For
example, Solomon et al. (1995) and Abdelsattar et al. (2020) indicate that water salinity can
negatively affect milk production. Another important issue is the bioaccumulation of toxins which
makes livestock products harmful for humans (e.g., Giri et al., 2020). Also here, data on exposure,
dose & vulnerability are lacking.
4.7.3. Valuation
Three methods are likely candidates to estimate values of different water qualities for livestock
drinking:
1. the price of pasture land as a function of water quality (hedonic pricing). As is the case for
agricultural land (see section 4.6.3), we consider this method not feasible at the global scale;
2. by valuing the different impacts on livestock which can be attributed to insufficient water
quality (e.g., the impacts due to diseases and poisoning, and the impacts on livestock
products);
3. in CWON, the value of freshwater for livestock drinking was based on the replacement cost,
i.e. the difference between the cost of piped water supply and the cost of desalinating salt
water. This implicitly assumes that all livestock water is sourced from a piped water supply.
When the quality of freshwater deteriorates, the treatment and purification cost of piped
fresh water supply will increase and hence the difference in cost between piped water supply
and desalination salt water – and hence the value of freshwater – will reduce.
Although the first method does not seem to be feasible, also the second and third method are
difficult to implement due to a general lack of data.
4.7.4. Models and data
Table 4-10 provides an overview of models and data which can be used to quantify and value the
impacts on livestock.
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Scoping study assessing the value of freshwater quality at a global scale 34
Table 4-10: Global models and data – livestock
Name Organisation/Author Description URL
Gridded Livestock of the
World (GLW)
FAO / Gilbert et al. (2018) GLW 3 provides global population
densities of cattle, buffaloes, horses,
sheep, goats, pigs, chickens and ducks in
each land pixel at a spatial resolution of
0.083333 decimal degrees
(approximately 10 km at the equator).
https://www.fao.org/livestock-
systems/global-
distributions/en/
OIE World Animal
Health Information
System (OIE-WAHIS)
World Organisation for
Animal Health (OIE)
OIE collects data originating from
national veterinary authorities which
are then twice verified before
dissemination. However, the data is not
complete since underreporting is known
to happen, the extent of which is
unknown. Still, OIE animal health data is
considered the best reference currently
available( source:
https://www.tafsforum.org/livestock-
disease-atlas.html).
https://wahis.oie.int/#/home.
FAOSTAT FAO Provides food and agriculture data for
over 245 countries from 1961 to the
most recent year available. Data
includes animals, production and prices.
https://www.fao.org/faostat/e
n/#data
Global Livestock
Production and Health
Atlas (GLIPHA)
FAO Currently offline. Expected to become
online again.
The atlas contains the following data:
Biophysical, Livestock population and
production, Socio-economic, Animal
health and Trade.
http://kids.fao.org/glipha/
https://ledsgp.org/resource/glo
bal-livestock-production-and-
health-atlas-glipha/
Global Burden of Animal
Diseases (GBADs)
Institute of Infection and
Global Health, University of
Liverpool
Under development. This vision for 2030
states amongst others “Metrics used to
describe and compare burden of animal
disease as it changes over time, by
region and production system and the
impact on individuals with different
gender and socioeconomic status
https://animalhealthmetrics.or
g/
4.7.5. Link to freshwater quality parameters
Several freshwater quality parameters (describing state) are important to assess the suitability of
water and potential impacts on livestock, those include (e.g., Pfost et al., 2001; Valente-Campos et
al., 2014; FAO, 1985; Government of Western Australia, 2021):
salinity;
nitrates;
bacteria;
organic materials;
suspended solids;
blue-green algae;
magnesium; and
heavy metals, chemicals and other toxic substances including arsenic.
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Scoping study assessing the value of freshwater quality at a global scale 35
4.7.6. Activities for the roadmap
We propose the following activities for the roadmap:
Construct a global database on livestock drinking water sources, based on existing SEEAs,
expert judgement, livestock census and surveys.
Detailed literature review of veterinary studies, livestock surveys, livestock census on the
relationship between livestock and water.
Development of a livestock model to estimate the global impacts of water quality on
livestock health and products.
4.8. Impacts on hydropower
4.8.1. Description
Hydropower is an indirect user of water. Much of the water used for hydropower is first stored in a
reservoir. The sediment which flows along with relatively fast-moving rivers, is deposited in this
reservoir. Reservoirs slowly fill up with sediment and mud, eventually making them unusable for
their intended purposes. Increased sediment loads in rivers shortens the lifespan and storage
capacity of dams and reservoirs.
4.8.2. Quantification
Quantifying the impact of sediment on hydropower requires that the impact of sedimentation on the
potential for hydropower generation needs to be assessed over the entire lifetime of the
hydropower dam. The current estimate is that 0.5 – 1% of reservoir capacity is lost each year due to
sedimentation (Schellenberg et al., 2017). Quantification of alternative sediment loads needs:
the deployment of global sediment model (e.g., Beusen et al., 2005) to calculate sediment
trapping in reservoirs; and
the application of a global model to estimate the future hydropower generation potential as
a function reservoir capacity and sediment load. Those models can be based on approaches
described in Hoes et al. (2017) and Zhou et al.( 2015).
4.8.3. Valuation
In Kind et al. (2020), the value of water used for hydropower generation was based on the
replacement cost of hydropower with the least cost alternative renewable energy resource. At the
global level, a cost difference of US$ 0.02 per kWh was assumed between hydropower and the least
cost renewable alternative for hydropower, while the average remaining life time of the hydropower
dams was assumed to be 15 years (i.e. 50% of 30 years). IRENAs cost metric methodology (IRENA
2021: Annex 1) can be used to calculate the global hydropower quantities and unit cost on the basis
of different power generation potentials and life times of the systems that belong to different
sedimentation rates, and hence new unit costs of hydropower can be calculated.
4.8.4. Models and data
Table 4-11 lists the available global models and data which are useful to quantify and value the
impacts of different water qualities on hydropower.
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Scoping study assessing the value of freshwater quality at a global scale 36
Table 4-11: Global models and data – hydropower
Name
Organisation/Author
Description
URL
IRENASTAT
International Renewable
Energy Agency (IRENA)
Contains at the level of countries data
on public investments, installed capacity
and electricity generation for different
forms of renewable energy
http://pxweb.irena.org/pxweb/
en/IRENASTAT
IRENA Renewable Cost
Database
IRENA
Contains around 18,000 utility
-
scale
renewable power generation projects
and 11,000 power purchase agreements
and tender results that provide new
insights into trends in the costs and
performance of renewables
(https://www.irena.org/costs)
Database not available online.
GlObal
36
odelling
36
ced
Database of Dams
(GOODD)
Mulligan
et al
.
(2000)
C
omprehensive
global georeferenced
database on dams containing more than
38,000 dams as well as their associated
catchments.
https://www.nature.com/articl
es/s41597-020-0362-5
World Register of Dams
(WRD)
International Commission
on Large Dams (ICOLD)
The World Register of Dams is a
database including more than 58,000
dams.
https://www.icold
-
cigb.org/GB/world_register/dat
a_search.asp (requires a paid
subscription to access)
Global sediment model
Different options exist
, e.g.
Beusen et al., 2005
https://doi.org/10.1029/2005G
B002453
Global model to
estimate hydropower
potential as function of
reservoir capacity
Different options exist
e.g.
Hoes et al. (2017) and Zhou
et al.( 2015).
https://doi.org/10.1371/journal
.pone.0171844
https://doi.org/10.1039/c5ee00
888c
4.8.5. Link to freshwater quality parameters
For hydropower, suspended sediment is the most relevant water quality parameter.
4.8.6. Activities for the roadmap
We propose the following activity for the roadmap:
Develop a costing model on the basis of IRENAs costing methodology which calculates the
unit cost of hydropower electricity with reservoir capacity as input.
4.9. Impacts on inland fish catch
4.9.1. Description
Inland fish catch is an important source of protein for many local populations. According to FAO
(2018), inland fishery catch in 2015 was 11 million tons, representing 12 percent of total global
capture fishery production. Seventeen countries produce 80 percent of this catch. The global gross
value added (GVA) of inland fishing is estimated by FAO at some US$100 billion annually.
Inland fisheries are under threat due to several water quality issues. However, not only the health of
the fish population itself is of concern, but also the bioaccumulation of toxins in fisheries products
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Scoping study assessing the value of freshwater quality at a global scale 37
and hence the potential negative impacts on human health. This section is limited to the impacts on
the fish population or catch.
4.9.2. Quantification
Quantification needs:
an estimate of the current fish population and/or catch (exposure);
relevant water quality parameters (dose); and
a relationship between fish population (/catch) and water quality (vulnerability).
For quantification of catch, FAO FishStatJ is a useful starting point. However, the reported figures in
FishStaJ are likely to be underestimates, mainly because of household consumption which does not
enter the formal statistics. See also Fluet-Chouinard et al. (2018) and FAO (2018).
The relation between fish health and fresh water quality is pluriform and depends on species and
locations. As an example, Hashim and Ismail (2015) find a (weak) correlation between the Water
Quality Index (as defined by the Malaysian Department of Environment) and fish biomass. Wątor and
Robert (2021) propose the development of novel Fish Water Pollution Indexes which are tailored to
the requirements of specific fish species.
4.9.3. Valuation
Prices of fish can be obtained from FAO 2018 and FishStatJ. In the valuation of yield increments, the
marginal costs should also be considered to derive increments of gross values added or resource
rents. See for an estimation of those costs, FAO (2018), which adopt value added ratios (VARs) of
between 0.6 tot 1.21 of gross revenues for different countries and continents (FAO 2018: Table 5-5).
4.9.4. Models and data
Table 4-12 lists the available global models and data which are useful to quantify and value the
impacts of different water qualities on hydropower.
Table 4-12: Global models and data – fisheries
Name
Organisation/Author
Description
URL
Review of the State of
the World Fishery
Resources: Inland
Fisheries
FAO 2018
Report gives a.o.
Regional and Country Detail on Inland
Capture Fisheries and Freshwater
Aquaculture Production (Annex 5-1)
Average Prices (Table 5-4)
Global Sample of Freshwater Fish prices
(Annex 5-3)
https://www.fao.org/3/ca0388
en/CA0388EN.pdf
FishStatJ
FAO
Global database on production, trade
and consumption of fish.
https://www.fao.org/fishery/st
atistics/software/fishstatj/en
Gridded Map of
Estimated Riverine Fish
Catch
McIntyre
et al.
,
2016
Gridded global map of estimated
riverine fish catches at 6-arcmin (
10-
km) resolution. Catch is modelled based
on discharge and constrained using
national statistics.
https://doi.org/10.1073/pnas.1
521540113
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Scoping study assessing the value of freshwater quality at a global scale 38
4.9.5. Link to freshwater quality parameters
FAO (1973) mentions finely divided solids, pH, temperature, ammonia, monohydic phenols, dissolved
oxygen, chlorine, zinc, copper and cadmium. Water quality parameters that are commonly
monitored in the aquaculture industry include temperature, dissolved oxygen, pH, alkalinity,
hardness, ammonia, and nitrites. Depending on the culture system, carbon dioxide, chlorides, and
salinity may also be monitored (https://freshwater-aquaculture.extension.org/water-quality-in-
aquaculture/).
4.9.6. Activities for the roadmap
We propose the following roadmap activities:
Literature survey on the relation between fish population and water quality.
Develop a global model to estimate fish catch as function of water quality.
4.10. Impacts on recreation & tourism
4.10.1. Description
Freshwater bodies provide a range of benefits or ecosystem services linked to recreation & tourism.
Examples of such services include boating, swimming or recreational fishing.
Visitors to a specific water location or site often have a range of motives for their visit, which are not
only linked to the services provided by the waterbodies, but also linked to the other amenities of the
location/site, wider region or area. Examples are the services enjoyed by visitors and which are
provided by forests and protected nature areas in the vicinity of the water bodies, services like
hunting, bird watching or hiking. Because such ecosystem services provided by forests and protected
areas were already included in the natural capital accounts of CWON, and to prevent overlapping
values, in Kind et al. (2020) it was advised not to separately value the recreational benefits due to
ecosystem services provided by freshwater bodies.
This section, however, addresses those impacts. In principle, those impacts are not limited to the
impacts on tourism and recreational activities in or nearby freshwater bodies, but also cover coastal
tourist sites which may be impacted due to pollution originating from rivers (note that the largest
part of pollution in the oceans originates from land and is transported by rivers).
4.10.2. Quantification
The available global data on tourists and visitors in general is limited. The World Tourism
Organization of the United Nations (UNWTO) – the agency responsible for the promotion of
responsible, sustainable and universally accessible tourism – collects and collates data on domestic
and international travel (inbound and outbound, expenditures), but does not record on the
underlying travel purposes or motives (as recommended in e.g. UN (2008)). This means that an
estimate of the volume of trips related to holidays, leisure and recreation is unknown at the global
level and hence also a part of that can not be attributed to the presence of water related amenities
or activities.
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Scoping study assessing the value of freshwater quality at a global scale 39
A possible alternative route to gain some insight in the relationships between recreation and tourism
and freshwater availability and quality is proposed under the roadmap.
4.10.3. Valuation
In theory, there are several options to quantify (and value) the recreational ecosystem services
provided by freshwater bodies:
a. through the development of a benefit transfer function (see section 3.2.3). Benefit transfer
has been used in CWON 2018 for non-wood forest ecosystem services (Siikamäki, 2015). To
value changes in freshwater quality, a benefit transfer function needs to be developed which
includes a parameter for freshwater quality. Examples of approaches applying benefit
transfer to value water quality improvements can be found in Alvarez (2014), Brander &
Wagtendonk (2010) and Hampson et al. (2017). Note that most of the benefit-transfer
studies are based on willingness-to-pay (WTP) estimates derived through contingent
valuation methods (CVM). Those WTPs do not distinguish between use and non-use values of
freshwater, but provide estimates for total economic value and use composite water quality
indexes or water quality ladders which are communicable with the general public. The
application of a benefit-transfer function for recreation and tourism alone, needs to filter out
the relevant use values only.
b. though the application of a travel-cost method. This requires the estimation of all travel
related expenditures attributable to water recreation and tourism (volumes of travel,
expenditures), and estimating an elasticity relating water quality to travel volumes and
expenditures; and
c. through the GVA or resource rent method. This requires estimating the GVA for the entire
recreation & tourism industry; the attribution of the GVA to water (in case of resource rent);
and estimating the elasticity.
4.10.4. Models and data
Table 4-13 lists the limited available global data on recreation and tourism.
Table 4-13: Global models and data – tourism
Name Organisation/Author Description URL
World Development
Indicators
World Bank Global data on the level of
countries on inbound and outbound
tourists and on tourism
expenditures.
http://wdi.worldbank.org/ta
ble/6.14
Tourism Statistics UNWTO As above, but also includes data on
tourism industries, employment
and complementary indicators.
https://www.e-
unwto.org/toc/unwtotfb/cu
rrent
https://www.unwto.org/
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Scoping study assessing the value of freshwater quality at a global scale 40
4.10.5. Link to freshwater quality parameters
There are several links to water quality ranging from recreational use to ecological value. The WHO
(2021) swimming water guidelines mentions different parameters, including faecal pollution, harmful
algal blooms and chemicals.
In studies using public surveys, alternative ways to describe water quality may be more appropriate.
E.g., Hime et al. (2009) compose a transferable water quality ladder for conveying use and ecological
information within public surveys. Also well known is the Resources for the Future (RFF) water
quality ladder, indicating surface water as (a) having no uses, (b) okay for boating, (c) okay for fishing,
(d) safe for swimming and (e) safe to drink (See Cameron et al., 1981: Appendix 1).
4.10.6. Activities for the roadmap
Roadmap activities for recreation and tourism include:
Estimate the global volume (no. of visits) of water related recreation and tourism. This
activity involves collating and combining data from different sources, including national
statistical offices, census and survey data, as well as mining big data from sources like google
(https://destinationinsights.withgoogle.com/intl/en_ALL/), Flickr (http://mmcommons.org/)
(http://projects.dfki.uni-kl.de/yfcc100m/), artificial intelligence from booking.com
(www.booking.ai), Twitter and other sources, and possibly the deployment of machine
learning;
Construct and apply a global water quality index or ladder for water related recreation &
tourism ;
estimate the elasticity between water quality and recreational water demand. See for
example Keeler et al., (2015), who estimate such elasticity on the basis of Flickr photo’s; and
estimate the GVA and resource rent for recreation and tourism.
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Scoping study assessing the value of freshwater quality at a global scale 41
5. Global Water Quality Modelling
This chapter provides a brief overview of the current status of global water quality modelling for
different water quality parameters. Those global models link the driving forces to pressures, and
pressures to state. The linkage between state and impact has been explored in the previous chapter.
The chapter also discusses the prospect of using SEEA to improve water quality modelling and the
prospect of using global water models to fill preliminary version of SEEAs for those countries where
monitoring data is scarce or lacking.
5.1. Introduction
Increasing pollution of inland waters in low-income countries caused by rapid economic growth and
urbanization, and persistent chronic pollution in high-income, industrialized, countries poses a risk to
human health, ecosystem health and biodiversity, and food security. Recently, the World Water
Quality Alliance presented a first global assessment of water quality (WWQA, 2021). This inventory
provides an overview of the current knowledge of the status of global water quality and its impacts,
the hotspot regions in the world, and the major causes and socio-economic drivers.
The scope of the WWQA is the SDG 6, in particular target 6.3 (see chapter 1). The WWQA will not
only assess the current situation, but also explore how target 6.3 can be achieved by scenario
analysis and other approaches.
While a definition of water quality is lacking, WWQA initially focused on a series of water quality
indicators, including physical ones (water temperature), biological (biological oxygen demand, BOD),
presence of pathogens (cryptosporidium), loads of nutrient (N, P, Si), chemical pollutants (arsenic,
various chemicals, insecticides, pesticides and herbicides), pharmaceutical products, plastics and
salinity. This wide spectrum of water quality indicators has been addressed by a variety of models
with different scales (Europe, Africa, world), resolutions and approaches, see Table 5-1.
It is clear that many pollutants have not been addressed at all, including a long list of pathogens,
chemicals and plastics. This is due to the inherent difficulty of describing the emissions or loading and
instream processes, which could then be used to assess the relationships between the pollutants
considered (i.e., pressures), state and impacts on human health, agriculture and biodiversity.
Table 5-1: General group of water quality (WQ) indicators, and specific indicators, and
approaches used in WWQA
General group Specific WQ indicator Model approach in WWQA
Physical Water temperature WaterGap-WorldQual
QUAL
Biological Biological Oxygen Demand WaterGap-WorldQual
QUAL
Pathogens Bacteria Escherichia Coli
Campylobacter Jejuni
Giardia Lamblia
Salmonella
Legionella Pneumophila
Viruses Hepatitis A
Protozoa Cryptosproidium Hofstra et al. (2013) simplified
in the MARINA model
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General group Specific WQ indicator Model approach in WWQA
Nutrients Total nutrient load in
freshwater and export to
coastal waters
TN, TP IMAGE-GNM
Dissolved nutrient load in
freshwater and coastal waters
DIN, DON, DIP, DOP MARINA, only export to
coastal waters
Particulate nutrients PC, PN, PP Not in WWQA
Silica in freshwaters and coastal
waters
DSi Global NEWS, export to
coastal waters
Chemical
pollutants
Natural chemicals Arsenic Global AsGW
Agro-chemicals Insecticides, fungicides,
herbicides
WFLOW-DWAC, but not
specific
Heavy metals
Other (emerging) chemicals WFLOW-DWAC, but not
specific
Pharmaceutical products Long list of products Triclosan export to coastal
waters by MARINA
Carbamazepine and
ciprofloxacin with GNM
Plastics Microplastics Undefined microplastics
export to coastal waters,
MARINA
Macroplastics
Salinity Sodium chloride mainly WaterGap-WorldQual
QUAL
5.2. Modelling pollutants in surface water
Different stages of model development can be distinguished. Early models lack approaches or
detailed information on the emissions of a nutrient, chemical or other pollutant, and on the
processing in surface water bodies. These models use specific drivers as proxies for the emissions -
such as fertilizer use - to describe the nitrate loss from the whole agricultural system. The lumped
data at the scale of river basins is regressed against observed nitrate export to mimic instream
processing. An example of a black-box model of this type is the model presented by Caraco and Cole
(Caraco and Cole, 1998). This approach was refined later by adding more distant drivers of emissions
and providing a simple approach to estimate in-stream retention, as described in Seitzinger et al.
(2005), the first version of the Global NEWS models covering all forms of carbon and nutrient export
to the global coastal ocean, and MARINA model which uses Global-NEWS equations for dissolved N
and P (Strokal et al., 2016).
The above simple approaches help to identify hot-sport regions of coastal nutrient loading, but are
not appropriate for assessing freshwater quality, since emissions and retention were simulated using
lumped regressions.
To address inland freshwater quality, spatially explicit approaches have been developed that describe
the loading (emissions) and processing at every location within a river basin. In their review, Borah
and Bera (2003) compared a range of continuous and event-based models for watershed-scale
hydrology and pollution. A common aspect of these models (with examples in Table 5-2) is that they
all require large amounts of data that may be difficult to collect in all countries. To avoid this data
problem, some models allow the user to run the model at different levels of water quality
complexity.
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Data availability is a key problem in developing the river biogeochemistry models. Except for a
limited number of intensively studied systems, data on the input of pollutants and transfer to the
adjacent or downstream compartments in a river basin are scarce. This means that often the
sediment and pollutant concentrations at one particular place in the system may be known, for
example in the stream, and that the processing and retention in those landscape elements delivering
to the stream are either poorly known or not known at all. The problem of missing information is not
easily solved and will require targeted and appropriately-scaled data collection efforts.
Table 5-2 Examples of models for watershed-scale distributed simulation of nutrient transport
in river basins.
Model Temporal
scale
Description Reference
AnnAGNPS Day or less Annualized Agricultural nonpoint-source pollution
model, annualized version of AGNPS for continuous
simulation of hydrology, erosion, transport of
nutrients, sediment and pesticides
Young et al. (1995);
Bingner and Theurer
(2013)
ANSWERS-
continuous
Day or less Areal Nonpoint Source Watershed Environment
Response Simulation, expanded with elements from
other models (GLEAMS, EPIC) for nutrient transport
and inputs
Bouraoui et al. (2002)
Hydrological
Simulation
Progr–m -
Fortran
Hour Continuous watershed simulation of water quantity
and quality at any point in a watershed developed for
US-Environmental Protection Agency (EPA).
USEPA (2011); Skahill
(2004)
SWAT Day Soil Water Assessment Tool to predict the impact of
management on water, sediment and agricultural
chemical losses in large ungauged river basins
Arnold and Fohrer
(2005)
MIKE-SHE Variable,
depending on
numerical
stability
Comprehensive, distributed, physically based model to
simulate water, sediment and water quality
parameters in 2-dimensional overland grids, one-
dimensional channels, and 1-dimensional unsaturated
and 3-dimensional saturated flow layers, with both
continuous and single event simulation capabilities
Refsgaard and Storm
(1995)
Riverstrahler Reach, decade Riverstrahler allows for analyzing, apart from other
disturbances, the impact of changing nutrient load and
changing nutrient ratios, and potential saturation of
retention processes such as denitrification and P
retention by sediment. While in-stream processes are
modelled with a mechanistic model, the delivery
processes are described with coefficients, lumping
soils, aquifers and riparian zones
Garnier et al. (1995);
Billen et al. (2000)
INCA Day Integrated flow and nitrogen model for multiple source
assessment in catchments
Wade et al. (2002);
Whitehead et al.
(1998a,b)
IBIS-HYDRA Variable, 1 day
to 1 year
Land surface and terrestrial ecosystem model model
IBIS with hydrology model HYDRA, used f43odellinging
dissolved inorganic nitrogen fluxes and removal
Donner et al. (2002)
and Donner et al.
(2004)
IMAGE-DGNM Variable, 1
month to 1
year
Starting from global land-nutrient budgets, estimates
of wastewater N and P flows, deposition, weathering
and other natural nutrient inputs, DGNM simulates the
transport within the soil, groundwater, riparian zone to
surface water, and in-stream biogeochemistry using a
mechanistic approach; DGNM has also been employed
to simulate the fate of farmaceutical products in inland
waters.
Beusen et al. (2016)
and Beusen (2015);
farmaceutical products
in Oldenkamp et al.
(2019)
Extended from Borah and Bera (2003)
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5.3. Towards integrated modelling of water quality
Many of the models listed in Table 5-2 describe in-stream processes, including the water-sediment
exchanges of chemical substances. With these features, the models listed can also be used to
describe the processing of other chemicals, once the correct data for specific model parameters have
been obtained. A common aspect is that all these models need information on the loading of the
chemicals considered. A good example of a model that was developed for one group of compounds
(nutrients) and was applied to simulate the processing and fate of two pharmaceutical products, is
IMAGE-GNM (Oldenkamp et al., 2019). In order to achieve internal consistency in approaches, these
authors used emission inventories of the two chemicals, and the hydrology and in-stream processing
of the integrated model framework of IMAGE-GNM.
The first step for integrated water quality modelling is thus to integrate data from the emissions
inventory for the pollutants considered, and to include these emissions in the general modelling of
the human system, for example by considering the relationships between emissions and economic
parameters, health services information, regulations for specific chemicals (e.g. agro-chemicals) or
existing policies for these chemicals. An example of an approach to estimate emissions was recently
described for Europe for a series of chemical pollutants (van Gils, 2020).
The second step is to describe the behaviour of these chemicals in the water column. This could be
done by grouping chemicals on the basis of their general characteristics of recalcitrance against
biological decomposition, or absorption/desorption behaviour in the water column and sediment as
a function of the concentration in the water column and historical accumulation in the sediment.
5.4. SEEA and Global Water Models
SEEA is an integrated statistical framework, which can be used to organise environmental-economic
information including water data. In this paragraph we describe (a) in what accounts of SEEA water
quality data can be found and if these data can be used as an input for water quality modelling, and
(b) to what extent data generated by water quality modelling can be used to populate or fill data
gaps of certain SEEA accounts. In SEEA, water is addressed in five different accounts: the water flow
accounts, the water emission accounts, the water asset accounts, the ecosystem condition accounts
and the ecosystem service accounts.
a) Water flow accounts
Water flow accounts describe, in physical units, the flows of water, encompassing (a) the initial
abstraction of water resources from the environment into the economy, (b) the water flows within
the economy in the form of supply and use by industries and households, and (c) finally, flows of
water back to the environment. The focus of SEEA is on the inland water system, with provisions for
the inclusion of sea or ocean water abstracted for production or consumption. Water flow accounts
describe all relevant water flows between the economy and the environment in quantitative terms,
disregarding any difference in water quality.
b) Water emission accounts
The water emissions accounts present information on the activities responsible for the emissions and
releases to water, the types and amounts of substances, as well as the destination of the emissions.
Water emissions accounts cover (a) substances added to wastewater and collected in the sewerage
system; (b) substances added to wastewater and discharged directly to water bodies; and (c)
substances from non-point sources, for example, emissions and releases from urban run-off and
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Scoping study assessing the value of freshwater quality at a global scale 45
emissions from agriculture. The water emissions accounts thus describe the flows of pollutants to
water, but not the resulting concentration of pollutants in water bodies.
c) Water asset accounts
The asset accounts for water present information on the stock of water at the beginning and end of
an accounting period, whether it is in artificial reservoirs, lakes or rivers, or stored as groundwater or
soil water. The accounts then record the flows of water as it is abstracted, consumed, added to
through precipitation, or changed through flows to and from other countries and returns to the sea.
A distinction is made by type of water resource, i.e. surface water, groundwater and soilwater. These
accounts can be compiled in physical and monetary terms. Like the water flow accounts, in principle
no distinction is made with regard to water quality.
d) Ecosystem condition accounts
A key feature of SEEA ecosystem accounting is its organization of biophysical information on the
condition of different ecosystems and ecosystem types. Ecosystem condition accounts provide a
structured approach to recording and aggregating data describing the characteristics of ecosystems
and how they have changed. Condition is assessed with respect to an ecosystem’s composition,
structure and function which, in turn, underpin the ecosystem integrity of the ecosystem, and
support its capacity to supply ecosystem services on an ongoing basis. Water quality - the chemical,
physical, and biological characteristics of water based on the standards of its usage - is addressed in
these ecosystem condition accounts. Information from the condition account can be used to assess
the change in water quality for different ecosystem types (i.e. rivers, lakes, aquifers, wetlands) over
time.
e) Ecosystem service accounts
The ecosystem service accounts describe the supply and use of all relevant ecosystem services for a
specific country or region. In the SEEA ecosystem accounting framework, ecosystem services serve as
the connecting concept between ecosystem assets and the production and consumption activity of
businesses, households and governments. These accounts can be expressed both in physical and
monetary units. With regard to water and water quality, the water purification service is in particular
relevant. Water purification services are the ecosystem contributions to the restoration and
maintenance of the chemical condition of surface water and groundwater bodies through the
breakdown or removal of nutrients and other pollutants by ecosystem components that mitigate the
harmful effects of the pollutants on human use or health. Other ecosystem services which are linked
and or relevant to water quality, include recreation, inland fisheries (see also Textbox 2-1).
Coupling of SEEA with Water Quality models
The SEEA accounts are based on statistics and observations on a country level. At the moment (2020)
the water accounts data are available for 30 countries, of which 11 developed and 19 developing
countries (UNSD, 2020). Global water quality models need a consistent set of input data for all
countries (> 200) in the world. From this standpoint, the integration of SEEA data in global water
quality model inputs looks at this moment preliminary. However, on the basis of SEEA, certain
coefficients – such as the water emissions per unit of product - may be derived which can be used to
improve global water quality models. Furthermore, SEEA water emission accounts can be used as an
intermediary framework between data from emission inventories and the water quality models, in
particular to allocate data to the different economic activities. Especially in the case of industries, this
may be a valuable route to explore, as industry data are currently often missing in global water
quality models.
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Another question is if global model results can be used as additional data sources for SEEAs for
countries where monitoring data is lacking. In particular, the SEEA EA condition account is in need for
water quality variables and indicators, as these are important parameters to describe and evaluate
the quality of ecosystems. Most of the global water quality models are calculating on different spatial
resolution, ranging from 1 km2 up to 2500 km2 or sub-basin or basin scale. But the calculation
resolution is not the spatial resolution that the results are presented. Mostly the models aggregate
the results to a coarse resolution or to regions. The models also present results on individual large
countries like China, US, India and Brazil. To answer the question, a first activity would be a
comparison between SEEA data and model results for large countries, such as Canada, Mexico or
Brazil. A key issue to be investigated is whether the spatial resolution and the underlying data quality
is sufficient to be used to populate SEEA accounts.
5.5. Activities for the roadmap
For the roadmap, we propose the following activities:
Use SEEA to estimate coefficients (water emissions per unit product) to improve global water
quality models.
Compare results of selected water quality models and SEEAs for larger countries to
determine the accurateness of the global models. This as a possible first step to populate
SEEA accounts with the results of these models, for countries where other data is not
available.
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6. Towards the assessment of global costs and health benefits of
increased coverage of WWTPs
This chapter presents the results of the first steps taken in the context of this project for a global
exploration of the costs and health benefits of improving water quality through the expansion of
WWTPs. The chapter serves as an illustration, the presented WWTP scenario is not meant to serve as
a realistic scenario for the near future and results should be interpreted with caution. The last section
also presents our actions for the road map which are based on lessons learned from this exercise.
6.1. Introduction
Treating wastewater can be a valuable approach for increasing the overall water quality, and
therewith for providing benefits to societies. Examples of these benefits are a reduction of health
impacts, increased agricultural production and benefits for various industries. The evaluation of
increasing coverage of WWTPs involves the evaluation of costs and benefits, which include – but are
not limited to – the health benefits associated with improved sanitation. This chapter only has a
focus on these costs and the associated health benefits.
6.2. Estimating the costs of improving water quality through the treatment of wastewater
6.2.1. Approach
Estimating global wastewater treatment costs is challenging. To estimate the costs of expanding
communal wastewater treatment (WWT) in countries around the world, numerous sources of
information are needed, which are often lacking, incomplete, not always reliable, or difficult to
collect and compare. Instead of collating data from different sources, countries and organisations,
this section discusses an alternative approach based on Dutch cost data.
In the Netherlands, complete and reliable data on the cost of wastewater treatment is available from
different (semi-) government organizations, like Rioned, STOWA, Unie van Waterschappen, as well as
from the cost databases of engineering firms. In this section, we illustrate how this data can be used
to estimate the WWT costs in other countries on the basis of different global parameters. The
method for the “translation” of Dutch cost to the cost of a particular country x is based on the
approach developed by Pieters (2020), which is included as Appendix A-3.
To estimate the costs and benefits of increasing WWTP coverage, an important requirement is that
the total flow of the produced, collected and treated communal wastewater in a country is also
known. This depends amongst others on the number of household connections. For data, the
databases of PCRGLOB-WB (connection rates) and Aquastat (capacities) can be used. On basis of this
data and the translated unit cost, the cost of expanding the coverage in a country can be estimated.
WWTPs around cities are generally larger due to the large number of inhabitants connected to it. In
rural areas, WWTPs are much smaller. In this analysis, we assume for rural areas an average
treatment plant capacity of 50,000 population equivalent (PE). For WWTPs in highly dense urban
areas, we assume a capacity of 250,000 PE. The size of the WWTP influences the overall costs, since
treatment with large capacities provides economies of scale.
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6.2.2. Costs of wastewater treatment plants per country
Dutch cost for different WWTPs
The initial calculations of the different WWTPs costs assume that those are to be built in the
Netherlands. These costs are computed with a calculation sheet for process performance and costs.
In this sheet, prepared by Wim Wiegant (RHDHV), both investment (CAPEX) and operational (OPEX)
costs are calculated. This costing approach has been validated with publicly available data, like those
of the Union of Water Boards (Unie van Waterschappen, 2018). In Table 6-1, the results of the cost
calculations are shown for “Dutch” WWTPs. The table distinguishes between four different types of
wastewater treatment (primary, secondary, tertiary, quaternary) and three different sizes (small –
5000 PE; med – 50,000 PE and large – 250,000 PE).
Table 6-1: Dutch” costs of different sizes and types of WWTPs (year 2020 prices)
Size Size
PE 5,000 50,000 250,000 5,000 50,000 250,000
Average cap. m3/h 31 313 1563 31 313 1563
Primary treatment Up to secondary treatment
Investment 000 USD 2,813 9,455 36,162 9,801 24,865 95,333
Capital costs 000 USD/yr 200 647 2,435 777 1,831 6,618
Operational costs 000 USD/yr 174 1,224 5,642 278 1,085 3,838
Total annual cost 000 USD/yr 374 1,871 8,078 1,054 2,916 10,456
Annual cost per PE USD/yr 75 37 32 211 58 42
Up to tertiary treatment Up to quaternary treatment
Investment 000 USD 10,491 33,086 139,978 11,950 38,382 155,423
Capital costs 000 USD/yr 821 2,351 9,429 923 2,698 10,397
Operational costs 000 USD/yr 284 1,148 4,510 319 1,344 5,336
Total annual cost 000 USD/yr 1,105 3,499 13,939 1,242 4,042 15,733
Annual cost per PE USD/yr 221 70 56 248 81 63
The total annual cost consists of several components and includes depreciating (based on 40 years)
and interest costs (2% per year). The depreciation and interest costs make up ±58% of the total
annual cost in the Netherlands. Other annual operational cost components are the costs for sludge
removal (15%), personnel costs for operating and maintaining the installation (22%) and expenses for
energy and chemicals (5%) (Wiegant, 2021).
Translating WWTPs costs to other countries
The costs for WTTPs for country X can be estimated by comparing the Netherlands and country X on
several aspects using globally available parameters. The parameters used are the GDP per capita,
Construction Productivity Ratio (CPR), Human Capital Index (HCI) and Income class, see Table 6-2.
These parameters shape the costs in terms of labour, materials and procurement costs. For an
extensive discussion, see Pieters 2020.
The Construction Productivity Ratio is an index for the labour productivity in construction per
country. Economists refer to labour productivity as the rate at which goods and services are
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produced (Mckinsey Global Institute, 2017). The Human Capital Index measures which countries are
best in mobilizing the economic and professional potential of its citizens.
Table 6-2: Elaboration of global parameters, their goal and source
Global parameter Goal Source
GDP per capita Proportional conversion of labour
costs between NL and country X.
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD
Country Production
Rate
Proportional conversion of labour
costs between NL and country X,
taking into account the efficiency
of labour production.
Mckinsey Global Institute. (2017). Reinventing
construction: a route to higher productivity (Executive
summary). Houston: McKinsey&Company.
Human Capital
Index
Determining the demanded
quality of a treatment installation,
rated A to F.
Human Capital Index | DataBank (worldbank.org)
Pieters, S. (2020). International Cost Calculator Drinking
Water - BH2061-RHD-ZZ-XX-RP-Z-0001
Determining procurement
percentage of materials bought in
Western countries or China/ India
(depending on quality demand).
Pieters, S. (2020). International Cost Calculator Drinking
Water - BH2061-RHD-ZZ-XX-RP-Z-0001
Income Class Determining economisation of an
automated installation (depending
on labour cost). Low labour cost
indicate a choice for labour
intensive operation, with less
automation. This lowers the
investment cost.
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD
Pieters, S. (2020). International Cost Calculator Drinking
Water - BH2061-RHD-ZZ-XX-RP-Z-0001
Table 6-3 presents an example of parameter values for a small set of countries.
Table 6-3: Example of global available parameters required to “translate” costs from NL to
country X
Country name ISO Code Aggrigate Income Group
GDP/cap
HCI Quality inst. CPR
(based on HCI)
Netherlands NLD Europe & Central Asia High income 52,842$ 0.80 A 42
Australia AUS East Asia & Pacific High income 51,214$ 0.80 A 28.5
France FRA Europe & Central Asia High income 39,079$ 0.76 A 31.5
Germany DEU Europe & Central Asia High income 46,466$ 0.79 A 28.5
Greece GRC Europe & Central Asia High income 16,571$ 0.68 B 20.5
Portugal PRT Europe & Central Asia High income 21,197$ 0.78 A
United States USA North America High income 62,358$ 0.76 A 31
Canada CAN North America High income 43,518$ 0.80 A 36
Colombia COL Latin America & Caribbean Upper middle income 5,195$ 0.59 C 4
Peru PER Latin America & Caribbean Upper middle income 6,426$ 0.59 C
Brazil BRA Latin America & Caribbean Upper middle income 6,855$ 0.56 C 4
Oman OMN Middle East & North Africa High income 22,565$ 0.62 C
Libya LBY Middle East & North Africa Upper middle income 3,407$ 0.60 C
Qatar QAT Middle East & North Africa High income 57,124$ 0.61 C
China CHN East Asia & Pacific Upper middle income 10,675$ 0.67 B 2.5
Indonesia IDN East Asia & Pacific Lower middle income 4,044$ 0.53 D 2
Malaysia MYS East Asia & Pacific Upper middle income 10,219$ 0.62 C 2.5
Singapore SGP East Asia & Pacific High income 59,448$ 0.88 A
South Africa ZAF Sub-Saharan Africa Upper middle income 5,510$ 0.41 E 5
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6.2.3. Pipelines
Dutch costs levels of pipelines
Collecting pipelines can be divided into two types: municipal sewerage and pressure pipes to
WWTPs. For municipal sewage in the Dutch situation, the total asset value is estimated at US$ 99
billion and the operational costs (including depreciation and interest cost) are about US$ 1.8 billion
per annum, or US$ 102 per capita per year (https://www.riool.info/geld-voor-watertaken).
The costs for pressure pipelines to WWTPs are derived from the total costs of the Dutch WWTPs (323
plants) and pressure pipelines (7800 km, excluded municipal sewerage). This totals to US$ 1.2 billion
per year, which equals to ± US$ 68,- per capita per year. It is known that 80% of these costs are
accounted for WWTPs (Stokkum et al., 2008), which indicates that the remaining 20% are costs for
pressure pipelines towards the WWTPs (± US$ 14 per capita per year).
Translating costs of pipelines to other countries
Pipeline networks are civil constructions. The Dutch cost level is compared with other countries by
one parameter for civil construction works (Turner and Townsend, 2019).
Pumping stations are considered as a part of the pipeline costs. Its costs are incorporated as a share
of the overall costs. For the Dutch situation, a specific percentage is applied. Depending on the
hilliness of country X, the portion of the pump station costs may differ as height differences need to
be dealt with.
6.2.4. Estimated total unit costs of WWTPs and pipelines
To calculate the average cost per country, the distribution of inhabitants over rural and urban needs
to be known. This data is available in PCRGLOBE-WB. It is assumed that urban residents are
connected to a large WWTP of 250,000 PE and rural residents are connected to an WWTP of 50,000
PE.
The Human Capital Index in a country is used as an indication of the quality level of the WWT
process. The following assumptions have been applied: HCI < 0.6 then a secondary treatment is
applied. Above a HCI of 0.6, a tertiary WWT is applied and above a HCI of 0.8 also a proportionate
part of the WWTPs is quaternary.
The sum of the costs for WTTPs and pipelines for the different sizes and qualities provides an overall
country-specific estimate of total costs per capita and m3. Table 6-4 provides these values for some
selected countries.
Table 6-4: Cost for wastewater collection and treatment (in US$, year 2020 price level)
Country
Per capita per year Per m3
WWTP Pipelines Total WWTP Pipelines Total
Netherlands 82 111 192 0.79 1.17 1.96
Australia 31 186 217 0.41 2.84 3.25
France 27 198 224 0.47 3.45 3.92
Germany 36 198 234 0.57 3.53 4.10
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Country
Per capita per year Per m3
WWTP Pipelines Total WWTP Pipelines Total
Greece 19 73 93 0.35 1.52 1.87
Portugal 37 94 131 1.18 1.62 2.80
United States 66 105 171 0.38 0.65 1.03
Canada 83 105 188 0.47 0.64 1.11
Colombia 3 74 78 0.92 1.54 2.46
Peru 4 81 85 0.32 3.21 3.53
Brazil 12 70 82 0.26 1.50 1.76
Oman 7 105 111 0.12 2.19 2.31
Libya 3 63 65 0.32 2.05 2.37
Qatar 39 96 135 0.33 0.94 1.28
China 22 86 108 0.36 2.57 2.92
Indonesia 2 76 79 0.26 5.00 5.26
Malaysia 61 85 147 0.30 0.46 0.76
Singapore 39 98 137 0.38 1.26 1.64
South Africa 18 77 95 0.27 1.18 1.44
6.2.5. Current asset value and future investment costs
Most countries do not reach a connection rate of 100%. The cost to reach 100% can be calculated by
computing the infrastructure cost of 1% connection rate and by multiplying this by the percentage of
missing connections . This provides the costs of achieving a connection rate of 100%. Table 6-5
presents insights in the required future investments in several countries to reach 100% WWTP
coverage.
Table 6-5: Current asset value and future investment costs to reach 100% connection rate
Country Connection
rate
Asset value existing assets Investments to reach 100% connection rate
In US$ billion, 2020 prices
WWTP Pipelines Total WWTP Pipelines Total
Netherlands 99.3% 36 99 136 0 1 1
Australia 91.4% 26 126 153 2 12 14
France 83.6% 34 305 339 7 60 66
Germany 96.4% 50 439 489 2 16 18
Greece 88.7% 5 41 46 1 5 6
Portugal 79.7% 7 45 52 2 11 13
United States 77.9% 448 1,456 1,904 127 412 539
Canada 87.1% 71 180 251 11 27 37
Colombia 79.9% 3 176 179 1 44 45
Peru 69.0% 2 100 102 1 45 46
Brazil 61.1% 34 507 542 22 323 344
Oman 48.9% 0 10 10 0 10 11
Libya 61.3% 0 16 17 0 10 11
Qatar 86.0% 2 12 14 0 2 2
China 58.1% 406 3,803 4,209 293 2,746 3,040
Indonesia 12.5% 2 143 145 13 996 1,009
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Scoping study assessing the value of freshwater quality at a global scale 52
Country Connection
rate
Asset value existing assets Investments to reach 100% connection rate
In US$ billion, 2020 prices
WWTP Pipelines Total WWTP Pipelines Total
Malaysia 38.9% 18 57 75 29 90 119
Singapore 100.0% 6 31 36 - - -
South Africa 58.2% 14 136 149 10 98 107
As the table shows, reaching a connection rate of 100% is very costly. For example, the estimated
investment cost is some US$ 3 trillion for China only, whereas China’s GDP is about US$ 15 trillion per
year. Hence, increasing the connection rate of WWTPS may not be the best solution to improve
water quality and health. Lower cost options like pit latrines have to be included in a future analysis
of costs and benefits of sanitation.
6.3. Quantification and monetization of health impacts
For the quantification and monetization of the health impacts, the number of DALYs which can be
attributed to unsafe WASH behaviour from Prüss-Ustün et al., (2019) can be used (excluding those
attributed to malaria). In total, this amounts to some 70 million DALYs per year, of which the largest
part in Sub-Saharan Africa and South Asia, see Table 6-6. In this Table, the DALYs have been valued
per country at 1 x GDP per capita (taken from World Development Indicators, World Bank (2018)).
The monetized health impacts amount to a total of US$ 172 billion per year. On average, at the
global level, the average amount (“value”) per DALY is US$ 2326, , with the highest values in North
America, and the lowest values in Sub-Saharan Africa.
Table 6-6: Quantified and monetized potential health benefits due to improved WASH
interventions (excluding Malaria)
Region mln DALYs US$/DALY
(avg.)
US$ bln per year
Sub-Saharan Africa 42.9 1,415 60.7
Middle East & North Africa 1.5 3,216 4.9
Europe & Central Asia 0.8 15,623 12.6
East Asia & Pacific 5.1 6,473 33.2
South Asia 21.8 1,840 40.1
North America 0.1 61,831 8.7
Latin America & Caribbean 1.9 6,578 12.2
Total 74.2 2,326 172.5
At a discount rate of 4% per year (used in CWON 2018), the present value of these health benefits
amount to some US$ 4.3 trillion. Note that in case of wealth accounting, this benefit should be
reflected in the value of human capital.
6.4. Cost of WWTPs confronted with monetized health benefits
On the basis of the above approach, per country, a rough confrontation of the costs and benefits of
improving the WWTP connection rate is possible. If we assume:
annual cost of WWTPs equal to 10% of investment (see Table 6-1); and
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Scoping study assessing the value of freshwater quality at a global scale 53
a reduction of 40% of the WASH related DALYs can be achieved (on the basis of Prüss-Ustün
et al., (2019),
then the annual health benefits / annual cost of WWTP (i.e., the health-benefit/cost ratio) for the
countries listed in Table 6-4 ranges between 0.02 (for China) and 1.38 (for the Netherlands), with an
average of 0.15. It is important to note that total benefits of improved WASH interventions may be
substantially higher than the health benefits only - up to 10 times or more; see the earlier discussion
in footnote 8 op page 21.
6.5. Activities for the roadmap
We propose the following activities for the roadmap:
Complete a global dataset with parameters needed to calculate the capacity and type of
treatment processes used for wastewater treatment facilities;
Complete the dataset with parameters needed to translate the investment costs for all
countries;
Develop a coherent set of water quality criteria which may be assumed for those main types
of wastewater treatment. Depending on regulation, certain types of WWT processes are
needed which influences the costs of the WWTPs;
Determine a realistic pace of investment in relation to SDG’s also with other investments
(e.g., pit-latrines); and
Define the parameters that significantly influence the investment cost for pipeline
construction, and retrieve this information. Examples are the type of land, presence of hills,
soil type (e.g., rocky or clay), existing infrastructure and amount of inhabitant/km2.
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Scoping study assessing the value of freshwater quality at a global scale 54
7. Roadmap
In this chapter, a roadmap is developed for quantifying and valuing for different water use(r)s (some
of ) the impacts of changes in freshwater quality at the global scale. For each of the water uses, a
description is included of what is needed, what is available, and what can be done to fill data and
modelling gaps. An illustration of an approach how to prioritize the roadmap actions is also included;
however due to the unavoidable highly subjective character of the prioritization approach,
prioritization of actions remains ultimately the responsibility of the client (i.e., PBL).
In order to quantify and value the impacts of changing water qualities, the following type of data is
required:
exposure – the extent to which a water use is potentially affected by changes in the water
quality
dose – representing the water quality parameter (such as concentration of contaminants,
temperature, turbidity) affecting the water users; or state;
vulnerability – describing the relationship(s) between dose and impact (also called
susceptibility, elasticity);
impact – the impact in physical terms of changes in water quality; and
valuation – the monetary value of the impacts.
The availability of this data has been discussed in chapters 4 and 5. Table 7-1 summarizes this
availability and proposes 33 roadmap activities to complement the data and models.
Table 7-1: Roadmap with activities for quantifying and valuing the impacts of freshwater quality
improvements
Item Description Availability of global
data or models
Activity for roadmap
A. Human health
Exposure # of persons exposed to specific
contaminants in water which
negatively influence health
Global exposure data
not available
Activity 1. Develop and test a methodology to assess
the global exposure of the world population to the
most important contaminants in water, combining
country data, micro-studies and modelling. Apart
from concentrations, exposure data should likely also
consider frequency and duration.
Dose Concentrations of contaminants in
water
Only available for a
few contaminants
(GEMstat, water
quality models)
Vulnerability Effects of contaminants on human
health (Mortality, DALYs, …)
Not available at global
level
Activity 2. Collect and review case-studies on the
relationships between contaminants and human
health. Prioritise what contaminants should be taken
into account. Set up database, develop functions
which consider concentrations, frequency and
duration.
Impact # of DALYs lost
Mortality
Medical cost
Available for limited
number of health
outcomes.
Note that the health
impacts are based on
indirect evidence
(attribution). They are
not the result of an
Activity 3. Conduct additional efforts to attribute
other health outcomes to unsafe WASH and/or
contaminants.
Activity 4. Develop an integrated model to estimate
health impacts as function of exposure, dose and
vulnerability.
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Scoping study assessing the value of freshwater quality at a global scale 55
Item Description Availability of global
data or models
Activity for roadmap
analysis integrating
exposure, dose and
vulnerability (as
above).
Valuation Monetary valuation (e.g., $ per
DALY)
Available Activity 5. Develop a – as widely supported as
possible – monetary valuation concept for the
different health impacts associated with water
quality.
B. Drinking water cost
Exposure m3 of drinking water
use/production from different raw
water sources
Not available (only
total)
Activity 6.
Break down the total drinking water use in
drinking water use with different types of raw water
sources: groundwater, surface water, brackish or
seawater.
Dose Concentrations of pollutants in
different raw water sources
Only available for a
few parameters
Vulnerability Cost of drinking water treatment as
function of raw water quality
Methodology available Activity 7.
Define the main types of drinking water
treatment processes used by countries depending the
water source and development of a specific country.
Activity 8.
Develop a coherent set of water quality
criteria which may be assumed for those main types
of drinking water treatment
Impact Methodology available Activity 9. Calculate the unit costs of water treatment
for each country, based on the different water
qualities parameters of the influent, and construct a
cost function.
Valuation
C. Industries
Exposure m3 of water demand of industries
with specific water quality
requirements
Not available Activity 10.
Break down the total industrial water use
to the water use for different main types of industries,
based on for example SEEA statistics and-coefficients,
and water footprint (or similar) statistics (see
https://waterfootprint.org/en/resources/waterstat/pr
oduct-water-footprint-statistics/).
Dose Water quality parameters most
significant for specific types of
industries
Not available Activity 11. Develop a coherent set of water quality
criteria which may be assumed for those main types
industries
Vulnerability Cost of industrial in-situ water
treatment as function of water
quality
Methodology available
(See B. Drinkwater
water cost)
Impact Cost of in-situ water treatment Methodology available
(See B. Drinkwater
water cost)
Valuation
D. Mining
Exposure m3 of water demand of mining with
specific water quality requirements
Not available Activity 12. To get better insights in the relationship
between mining and freshwater demand (and
pollution), several mining data (e.g., Maus et al.,
2020; Werner et al., 2020; Liang et al., 2021) may be
used in combination with overlays of water.
Activity 13. Use SEEAs of countries for information on
water usage of mines (and mining products to
estimate emission coefficients).
Dose Water quality parameters most
significant for specific type of
activities in mines
Not available Activity 14. Develop a coherent set of water quality
criteria which may be assumed for the different types
of mining activities.
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Scoping study assessing the value of freshwater quality at a global scale 56
Item Description Availability of global
data or models
Activity for roadmap
Vulnerability Cost of in-situ water treatment for
mines as function of water quality
Methodology available
(See B. Drinkwater
water cost)
Impact Cost of in-situ water treatment Methodology available
(See B. Drinkwater
water cost)
Valuation
E. Irrigated agriculture
Exposure ha of different types of irrigated
crops
Available Activity 15. Development of an agricultural (meta?)
model to estimate the global impacts of salt in
irrigation water. All building blocks are available.
Dose - m3 of irrigation water applied
- salinity of irrigation water
Available Activity 16. Determine which other pollutants in
water are the most relevant for agriculture and it
these can be integrated in future versions of the
model.
Vulnerability crop yield as function of salinity Available
Impact kg/ha Available
Valuation $/kg Available
F. Livestock
Exposure number of livestock which uses
different sources of water sources
for drinking
Global database not
available.
Activity 17. Construct a global database on livestock
drinking water sources, based on existing SEEAs,
expert judgement, livestock census and surveys.
Dose - m3 of water from different
sources
- water quality parameters most
relevant for livestock drinking
Global data available
for a limited number
of parameters (e.g.,
salt)
Vulnerability Livestock health as function of
water quality
Global data not
available
Activity 18. Detailed literature review of veterinary
studies, livestock surveys, livestock census on the
relationship between livestock and water.
Livestock products as function of
water quality
Global data not
available
Impact Livestock health (LSUs lost) Activity 19. Development of a livestock model to
estimate the global impacts of water quality on
livestock health and products.
Livestock products
Drinking water cost for livestock
see B.
Valuation $ Available
G. Hydropower
Exposure Hydropower generation potential Global data available
Dose Suspended sediment Model available
Vulnerability Relation between suspended
sediment, hydropower generation
and unit cost of hydropower
electricity
Model not available Activity 20. Develop a costing model on the basis of
IRENAs costing methodology which calculates the unit
cost of hydropower electricity with reservoir capacity
as input.
Impact Changes in cost of hydropower
Valuation Available
H. Inland fisheries
Exposure Inland fish catch Available
Dose Water quality parameters most
significant for fish population
Global data partly
available
Vulnerability Fish catch (fish population,
sustainable yield) as function of
water quality parameter
Global data not
available
Activity 21. Literature survey on the relation between
fish population and water quality
Impact Kg of fish Activity 22. Develop a global model to estimate fish
catch as function of water quality
Valuation $/kg Available
I. Recreation & tourism
Exposure National and international water
related visits
Global data not
available
Activity 23. Estimate the global volume (no. of visit) of
water related recreation and tourism
Dose Water quality parameters relevant
for tourism
Global data not
available
Activity 24. Construct and apply a global water quality
index or ladder for water related recreation & tourism
Vulnerability No of visits from water related
recreation & tourism as function of
water quality
Not available Activity 25. Estimate tourism elasticity on basis of
community science and big data
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Scoping study assessing the value of freshwater quality at a global scale 57
Item Description Availability of global
data or models
Activity for roadmap
Impact No of visits from water related
recreation & tourism
Activity 26. Estimate GVA and resource rent for
recreation and tourism
Valuation GVA or resource rent per visit Globally not available
J. Other road map activities
J1. SEEA &
Water
quality
modelling
Activity 27. Use SEEA to estimate coefficients (water
emissions per unit product) to improve global water
quality models.
Activity 28. Compare results of selected water quality
models and SEEAs for larger countries to determine
the accurateness of the global models. This as a
possible first step to populate SEEA accounts with the
results of these models, for countries where other
data is not available.
J2. Cost of
WWTP
Activity 29. Complete a global dataset with
parameters needed to calculate the capacity and type
of treatment processes used for wastewater
treatment facilities.
Activity 30. Complete the dataset with parameters
needed to translate the investment costs for all
countries;
Activity 31. Develop a coherent set of water quality
criteria which may be assumed for those main types
of wastewater treatment. Depending on regulation,
certain types of WWT processes are needed which
influences the costs of the WWTPs.
Activity 32. Determine a realistic pace of investment
in relation to SDG’s also with other investments (e.g.,
pit-latrines).
Activity 33. Define the parameters that significantly
influence the investment cost for pipeline
construction, and retrieve this information. Examples
are the type of land, presence of hills, soil type (e.g.,
rocky or clay), existing infrastructure and amount of
inhabitant/km2.
7.1. Prioritization
In this section, the activities of the roadmap are prioritized. This serves as an example, since
prioritization is (a) a highly subjective exercise, and (b) depends on expert opinion on criteria and
scoring used for such prioritization. The prioritization exercise thus serves as an example and should
ultimately be done with the client and possible stakeholders.
For the users/categories A – I, the prioritization is done at the level of all activities within this group.
After all, the execution of all the proposed activities in this group is needed in order to arrive at the
monetary values of the impacts. Table 7-2 explains the proposed criteria.
Table 7-2: Example of criteria used for the prioritization
Criteria
Explanation
I
.
Estimated
size of the
impac
t
The size of the impact relative to the ot
her impacts
II
.
Complexity
and
cost of roadmap
activit
ies
The
cost and complexity
of the activities
III
Expected reliability of the result
The expected quality of the impact assessment
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Scoping study assessing the value of freshwater quality at a global scale 58
Finally, Table 7-3 provides an example of the prioritized activities, with scores of 1-3 for each criteria
assigned on the basis of expert judgement, and equal weighting of the criteria.
Table 7-3: Example of the prioritized roadmap activities, per water user/category
Use/category
Score on criteria
(
expert judgement
)
Total score
(equal
weights on
criteria
applied)
Priority
(Rank)
(1=highest
priority)
I.
Estimated size
of the impact
II. Complexity
and cost of
roadmap
activities
III. Expected
reliability of the
result
1=low
2=medium
3 = high
1=high
2=medium
3 = low
1=
low
2=medium
3 = high
A
.
Human health
3
1
2
6
3
B
.
Drinking water cost
2
2
2
6
3
C. Industries
1
1
2
4
4
D. Mining
1
1
2
4
4
E. Irrigated agriculture
3
3
3
9
1
F. Livestock
1
2
1
4
4
G. Hydropower
1
3
3
7
2
H. Inland fisheries
2
2
2
6
3
I. Recreation & tourism
1
2
1
4
4
J. Other
roadmap
activities
2
7
.
Coefficients for sectors
on basis of SEEAs
1
3
3
7
2
2
8
. Comparison global
models with SEEAs
1
3
3
7
2
29
-
33
. Cost of WWTP
Scores n
ot assessed.
Those activities are of a different nature: the are not about estimating
and valuing impacts, but about costing the response options.
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Scoping study assessing the value of freshwater quality at a global scale 59
References
Abdelsattar, M.M., Ahmed M. A. Hussein, M.N. Abd El-Ati and A.M. Saleem (2020). Impacts of saline
water stress on livestock production: A review. SVU-International Journal of Agricultural
Sciences. 2. 1-12. http://dx.doi.org/10.21608/svuijas.2020.67635
Alvarez, Sergio (2014). Estimating the Benefits of Water Quality Improvements Using Meta-Analysis
and Benefits Transfer. https://ageconsearch.umn.edu/record/162534
Annette Prüss-Ustün, et al. (2020). Burden of disease from inadequate water, sanitation and hygiene
for selected adverse health outcomes: An updated analysis with a focus on low and middle-
income countries. International Journal of Hygiene and Environmental Health,
https://doi.org/10.1016/j.ijheh.2019.05.004
Arnold, J.G., Fohrer, N. (2005) SWAT2000: current capabilities and research opportunities in applied
watershed modelling. Hydrological Processes 19, 563-572.
Beusen, A. H. W., Dekkers, A. L. M., Bouwman, A. F., Ludwig, W., and Harrison, J. (2005), Estimation
of global river transport of sediments and associated particulate C, N, and P, Global
Biogeochem. Cycles, 19, GB4S05, https://doi.org/10.1029/2005GB002453
Beusen, A.H.W., Bouwman, A.F., Van Beek, L.P.H., Mogollón, J.M., Middelburg, J.J. (2016) Global
riverine N and P transport to ocean increased during the 20th century despite increased
retention along the aquatic continuum. Biogeosciences 13, 2441-2451,
https://doi.org/10.5194/bg-13-2441-2016.
Beusen, A.H.W., Van Beek, L.P.H., Bouwman, A.F., Mogollón, J.M., Middelburg, J.J. (2015) Coupling
global models for hydrology and nutrient loading to simulate nitrogen and phosphorus
retention in surface water. Description of IMAGE-GNM and analysis of performance.
Geoscientific Model Development 8, 4045–4067, doi:4010.5194/gmd-4048-4045-2015
(http://www.geosci-model-dev.net/4048/4045/2015/).
Billen, G., Garnier, J. (2000) Nitrogen transfers through the Seine drainage network: a budget based
on the application of the 'Riverstrahler' model. Hydrobiologia 410, 139-150.
Bingner, R.L., Theurer, F.D., (2013) AnnAGNPS Pollutant Loading Model
(http://www.ars.usda.gov/Research/docs.htm?docid=5222). Accessed 13 August 2013.
Borah, D.K., Bera, M. (2003) Watershed-scale hydrologic and nonpoint-source pollution models:
Review of mathematical bases. Transactions of the American Society of Agricultural
Engineers 46, 1553-1566.
Bouraoui, F., Braud, I., Dilaha, T.A., (2002) ANSWERS. A nonpoint-source pollution model for water,
sediment, and nutrient losses, in: Singh, V.P., Frevert, D.K. (Eds.), Mathematical models of
small watershed hydrology and applications. Water Resources Publications, Highlands Ranch,
Colorado, pp. 833-882.
Brander, L and Wagtendonk, A. (2010). GIS and meta-analysis based value maps of changes in water
quality, IVM, Amsterdam (offline only).
Brikké, François, Bredero, Maarten & Water Supply and Sanitation Collaborative Council. Operation
and Maintenance Network. (2003). Linking technology choice with operation and
maintenance in the context of community water supply and sanitation : a reference
document for planners and project staff / prepared by François Brikke and Maarten Bredero.
World Health Organization. https://apps.who.int/iris/handle/10665/42538
Brouwer, Roy, David Barton, Ian Bateman, Luke Brander, Stavros Georgiou, Julia Martín-Ortega, Stale
Navrud, Manuel Pulido-Velazquez, Marije Schaafsma, Alfred Wagtendonk (2009). Economic
Valuation of Environmental and Resource Costs and Benefits in the Water Framework
Directive: Technical Guidelines for Practitioners. AquaMoney.
https://iwlearn.net/resolveuid/8da1cc13-7005-4c8d-99c7-07c746c8fbfe
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale 60
Cameron, Robert Mitchell & Richard T. Carson (1981). AN EXPERIMENT IN DETERMINING
WILLINGNESS TO PAY FOR NATIONAL WATER QUALITY IMPROVEMENTS .
https://www.epa.gov/sites/default/files/2017-12/documents/ee-0011_1-5.pdf. Appendix 1
presents the RFF Water Quality Ladder.
Caraco, N.F., Cole, J.J. (1998) Human impact on aquatic nitrogen loads: A regional scale study using
large river basins. Ambio
Coomes, Oliver T., Graham K MacDonald & Yann le Polain de Waroux (2018) Geospatial Land Price
Data: A Public Good for Global Change Science and Policy.
https://doi.org/10.1093/biosci/biy047
D’Odorico, Paolo, Davide Danilo Chiarelli, Lorenzo Rosa, Alfredo Bini, David Zilberman, Maria Cristina
Rulli (2020). The global value of water in agriculture. Proceedings of the National Academy of
Sciences Sep 2020, 117 (36) 21985-21993; DOI: 10.1073/pnas.2005835117.
https://www.pnas.org/content/117/36/21985
Daroudi, R., Akbari Sari, A., Nahvijou, A. et al. (2021), Cost per DALY averted in low, middle- and high-
income countries: evidence from the global burden of disease study to estimate the cost-
effectiveness thresholds. Cost Eff Resour Alloc 19, 7 (2021). https://doi.org/10.1186/s12962-
021-00260-0
Dearmont, David, Bruce A. McCarl andDeborah A. Tolman (1998), Costs of water treatment due to
diminished water quality: A case study in Texas. https://doi.org/10.1029/98WR00213
Donner, S.D., Coe, C.T., Lenters, J.D., Twine, T.E. (2002) Modeling the impact of hydrological changes
on nitrate transport in the Mississippi River Basin from 1955 to 1994. Global Biogeochemical
Cycles 16, 101029.
Donner, S.D., Kucharik, C.J., Oppenheimer, M. (2004) The influence of climate on in-stream removal
of nitrogen. Geophysical Research Letters 31, L20509 20501-20505, https//doi.org/
10.1029/2004gl020477.
European Commission (n.d.), Better regulation toolbox. https://ec.europa.eu/info/law/law-making-
process/planning-and-proposing-law/better-regulation-why-and-how/better-regulation-
guidelines-and-toolbox/better-regulation-toolbox_en
Fadali, E, K. Rollins and S. Stoddard (2012). Determining Water Values with Computable General
Equilibrium Models. Report submitted for presentation at “The Importance of Water to the
U.S. Economy: Technical Workshop, September 19, National Academy of Public
Administration, 900 7th Street NW, Suite 600, Washington D.C.
https://www.researchgate.net/publication/266024480_Determining_Water_Values_with_C
omputable_General_Equilibrium_Models
FAO (1973). Water Quality Criteria for Freshwater Fish. https://doi.org/10.1016/B978-0-408-10849-
2.50001-0
FAO (1985). Water quality for agriculture. FAO irrigation and drainage paper, 29 rev. 1.
https://www.fao.org/3/t0234e/T0234E00.htm#TOC
FAO (2018). Review of the State of the World Fishery Resources: Inland Fisheries.
https://www.fao.org/3/ca0388en/CA0388EN.pdf
Fischer, G., Nachtergaele, F.O., van Velthuizen, H.T., Chiozza, F., Franceschini, G., Henry, M.,
Muchoney, D. and Tramberend, S. (2021). Global Agro-Ecological Zones v4 – Model
documentation. Rome, FAO. https://doi.org/10.4060/cb4744en
Fluet-Chouinard, Etienne, Simon Funge-Smith, Peter B. McIntyre (2018). Global hidden harvest of
freshwater fish revealed by household surveys. Proceedings of the National Academy of
Sciences Jul 2018, 115 (29) 7623-7628. https://doi.org/10.1073/pnas.1721097115
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale 61
Garnier, J., Billen, G., Coste, M. (1995) Seasonal succession of diatoms and Chlorophyceae in the
drainage network of the Seine river: Observations and modeling. Limnology and
Oceanography 40, 750-765.
Gilbert, M., Nicolas, G., Cinardi, G. et al. (2018). Global distribution data for cattle, buffaloes, horses,
sheep, goats, pigs, chickens and ducks in 2010. Sci Data 5, 180227 (2018).
https://doi.org/10.1038/sdata.2018.227
Gilbert. M. et al. (2018). Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs,
chickens and ducks in 2010. https://doi.org/10.1038/sdata.2018.227
Gils, J.J.J. van (2020) Computational material flow analysis for thousands of chemicals of emerging
concern in European waters. Journal of Hazardous Materials 397.
Giri, A., Bharti, V.K., Kalia, S. et al. (2020). A review on water quality and dairy cattle health: a special
emphasis on high-altitude region. Appl Water Sci 10, 79. https://doi.org/10.1007/s13201-
020-1160-0
Government of Western Australia (2021). Water quality for livestock. https://agric.wa.gov.au/n/3989
Hampson, Danyel I., Silvia Ferrini, Dan Rigby, and Ian J. Bateman (2017). "River Water Quality: Who
Cares, How Much and Why?" Water 9, no. 8: 621. https://doi.org/10.3390/w9080621
Hashim, Rohasliney and Noor Fakira Ismail (2015), Fish Biomass in Relation to Water Quality Index as
an Indication of Fisheries Productivity of Four Selected Fish Species Along the Galas River,
Kelantan, Malaysia. Procedia Environmental Sciences Volume 30, 2015, Pages 38-43.
https://doi.org/10.1016/j.proenv.2015.10.007
Hime, Stephanie, Ian J. Bateman, Paulette Posen and Michael Hutchins (2009), A transferable water
quality ladder for conveying use and ecological information within public surveys.
https://www.econstor.eu/obitstream/10419/48821/1/601512707.pdf
Hoes OAC, Meijer LJJ, van der Ent RJ, van de Giesen NC (2017), Systematic highresolution assessment
of global hydropower potential. PLoS ONE 12(2.
https://doi.org/10.1371/journal.pone.0171844
Hofstra, N., Bouwman, A.F., Beusen, A.H.W., Medema, G.J. (2013) Exploring global Cryptosporidium
emissions to surface water. Science of The Total Environment 442, 10-19, https//doi.org/
http://dx.doi.org/10.1016/j.scitotenv.2012.10.013.
Hutton, Guy (2015). Benefits and Costs of the Water and Sanitation Targets for the Post-2015
Development Agenda.
https://www.copenhagenconsensus.com/sites/default/files/water_sanitation_assessment_-
_hutton.pdf
IRENA (2020). RENEWABLE POWER GENERATION COSTS IN 2019.
https://www.irena.org/publications/2020/Jun/Renewable-Power-Costs-in-2019
IRENA (2021), Renewable Power Generation Costs in 2020, International Renewable Energy Agency,
Abu Dhabi. https://www.irena.org/-
/media/Files/IRENA/Agency/Publication/2021/Jun/IRENA_Power_Generation_Costs_2020.p
df
Juha Siikamäki, Francisco J. Santiago-Ávila, and Peter Vail (2015).Global Assessment of Non-Wood
Forest Ecosystem Services: Spatially Explicit Meta-Analysis and Benefit Transfer to Improve
the World Bank's Forest Wealth Database.
https://www.wavespartnership.org/en/knowledge-center/global-assessment-non-wood-
forest-ecosystem-services-spatially-explicit-meta
Keeler, Bonnie L, Spencer A Wood, Stephen Polasky, Catherine Kling, Christopher T Filstrup, John A
Downing (2015), Recreational demand for clean water: evidence from geotagged
photographs by visitors to lakes. https://doi.org/10.1890/140124
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale 62
Koundouri, Phoebe and Panos Pashardes (2001). HEDONIC PRICE ANALYSIS AND SELECTIVITY BIAS:
WATER SALINITY AND DEMAND FOR LAND.
https://ucy.ac.cy/econ/documents/working_papers/0102.pdf
Lee, Juhee (2020). Essays on the economics of salinity in irrigated agriculture. Dissertation.
https://hdl.handle.net/2097/40344
Mateo-Sagasta, Javier & Burke, Jacob. (2010). Agriculture and water quality interactions: a global
overview. http://www.fao.org/3/bl092e/bl092e.pdf
McIntyre, Peter B. , Catherine A. Reidy Liermann, Carmen Revenga (2016), River fisheries, food
security, and biodiversity Proceedings of the National Academy of Sciences Nov 2016, 113
(45) 12880-12885; https://doi.org/10.1073/pnas.1521540113
McKee, Anna M. and Marcella A. Cruz (2021). Microbial and Viral Indicators of Pathogens and Human
Health Risks from Recreational Exposure to Waters Impaired by Fecal Contamination.
https://ascelibrary.org/doi/pdf/10.1061/JSWBAY.0000936.
Mckinsey Global Institute (2017). Reinventing construction: a route to higher productivity (Executive
summary). Houston: McKinsey&Company.
Miller, Ted R. (2000), Variations between Countries in Values of Statistical Life. Journal of Transport
Economics and Policy Vol. 34, No. 2 (May, 2000), pp. 169-188 (20 pages).
https://www.jstor.org/stable/20053838
Mulligan, M., van Soesbergen, A. & Sáenz, L. (2020) GOODD, a global dataset of more than 38,000
georeferenced dams. Sci Data 7, 31. https://doi.org/10.1038/s41597-020-0362-5\
NRA - National Rivers Authority (1990). THE EFFECTS OF WATER QUALITY ON FRESHWATER FISH
POPULATIONS- FINAL REPORT. https://core.ac.uk/download/pdf/11022774.pdf
Oldenkamp, R., Beusen, A.H.W., Huijbrechts, M.A.J. (2019) Aquatic risks from human
pharmaceuticals - Modelling temporal trends of carbamazepine and ciprofloxacin at the
global scale. Environmental Research Letters 14.
Pfost, Donald L. , Charles D. Fulhage and Stan Casteel (2001). Water Quality for Livestock Drinking,
https://extension.missouri.edu/media/wysiwyg/Extensiondata/Pub/pdf/envqual/eq0381.pdf
Pieters, S. (2020) International Cost Calculator Drinking Water (BH2061-RHD-ZZ-XX-RP-Z-0001),
RHDHV
Puijenbroek, P.J.T.M. van , A.H.W. Beusen and A.F. Bouwman (2019), Global nitrogen and
phosphorus in urban waste water based on the Shared Socio-economic pathways,Journal of
Environmental Management, Volume 231, 2019,
https://doi.org/10.1016/j.jenvman.2018.10.048.
Refsgaard, J.C., Storm, B., (1995) MIKE SHE, in: Singh, V.P. (Ed.), Computer models of watershed
hydrology. Water Resources Publications, Highlands Ranch, Littleton, Colorado, pp. pp. 809-
846.
Russ, Jason, Esha Zaveri, Richard Damania, Sébastien Desbureaux, Jorge Escurra and Aude-Sophie
Rodella (2020), Salt of the Earth. Quantifying the Impact of Water Salinity on Global
Agricultural Productivity. Policy Research Working Paper 9144, World Bank.
https://openknowledge.worldbank.org/handle/10986/33070
Schellenberg, Greg, C. Richard Donnelly, Charles Holder and Rajib Ahsan (2017), Dealing with
Sediment: Effects on Dams and Hydropower Generation.
https://www.hydroreview.com/world-regions/dealing-with-sediment-effects-on-dams-and-
hydropower-generation/#gref
Seitzinger, S.P., Harrison, J.A., Dumont, E., Beusen, A.H.W., Bouwman, A.F. (2005) Sources and
delivery of carbon, nitrogen, and phosphorus to the coastal zone: an overview of Global
NEWS models and their application. Global Biogeochemical Cycles 19, GB4S01,
https//doi.org/ 10.1029/2004GB002606.
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale 63
Skahill, B.E., (2004) Use of the Hydrological Simulation Program - FORTRAN (HSPF) Model for
Watershed Studies. System-wide Modeling, Assessment, Restoration and Technologies
(SMART) / U.S. Army Engineer Research and Development Center (ERDC), p. 26.
Smith, Allan H., Elena O. Lingas & Mahfuzar Rahman (2000), Contamination of drinking-water by
arsenic in Bangladesh: a public health emergency.
https://www.scielosp.org/pdf/bwho/2000.v78n9/1093-1103/en
Solomon,R. , J. Miron, D. Ben-Ghedalia and Z. Zomberg (1995). Performance of High Producing Dairy
Cows Offered Drinking Water of High and Low Salinity in the Arava Desert, Journal of Dairy
Science, Volume 78, Issue 3, 1995, https://doi.org/10.3168/jds.S0022-0302(95)76672-3.
Stasinos, Sotiris and Ioannis Zabetakis (2013). The uptake of nickel and chromium from irrigation
water by potatoes, carrots and onions. https://doi.org/10.1016/j.ecoenv.2013.01.023
Stokkom, Hein van, Jaap Petraeus, Jack Jonk en Freek Kramer (2008). Vergelijking kosten zuivering
communaal en industrieel afvalwater. H20. https://edepot.wur.nl/342365
Strokal, M., Bai, Z., Franssen, W. et al., (2020). Urbanization: an increasing source of multiple
pollutants to rivers in the 21st century. npj Urban Sustain 1, 24 (2021).
https://doi.org/10.1038/s42949-021-00026-w
Strokal, M., Kroeze, C., Wang, M., Bai, Z., Ma, L. (2016) The MARINA model (Model to Assess River
Inputs of Nutrients to seas): Model description and results for China. Science of The Total
Environment 562, 869-888, https//doi.org/ 10.1016/j.scitotenv.2016.04.071.
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J.,
de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S.,
Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P. (2008).
PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model
Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018
Turner and Townsend (2019), International construction market survey. http://www.infrastructure-
intelligence.com/sites/default/files/article_uploads/Turner%20Townsend%20International%
20Construction%20Market%20Survey%202019.pdf
Unie van Waterschappen (2018). Bedrijfsvergelijking zuiveringsbeheer 2018.
https://www.waterschapsspiegel.nl/wp-content/uploads/2019/09/Bedrijfsvergelijking-
Zuiveringsbeheer-2018.pdf
United Nations et al. (2021). System of Environmental-Economic Accounting— Ecosystem Accounting
(SEEA EA). White cover publication, pre-edited text subject to official editing. Available at:
https://seea.un.org/ecosystem-accounting
USEPA (2011) Hydrological Simulation Program - FORTRAN (HSPF).
http://www.epa.gov/ceampubl/swater/hspf/.
Valente-Campos, Simone , Elizabeth de Souza Nascimento and Gisela de Aragão Umbuzeiro (2014),
Water quality criteria for livestock watering – a comparison among different regulations,
https://doi.org/10.4025/actascianimsci.v36i1.21853
Wade, A.J., Durand, P., Beaujouan, V., Wessel, W.W., Raat, K.J., Whitehead, P.G., Butterfield, D.,
Rankinen, K., Lepisto, A. (2002) A nitrogen model for European catchments: INCA, new model
structure and equations. Hydrol. Earth Syst. Sci. 6, 559-582.
Wątor, Katarzyna and Robert Zdechlik (2021). Application of water quality indices to the assessment
of the effect of geothermal water discharge on river water quality – case study from the
Podhale region (Southern Poland),Ecological Indicators, Volume 121, 2021,
https://doi.org/10.1016/j.ecolind.2020.107098.
Whitehead, P.G., Wilson, E.J., Butterfield, D. (1998a). A semi-distributed Integrated Nitrogen model
for multiple source assessment in Catchments (INCA): Part I - Model structure and process
equations. Science of The Total Environment 210-211, 547-558.
De Waterwerkers
Scoping study assessing the value of freshwater quality at a global scale 64
Whitehead, P.G., Wilson, E.J., Butterfield, D., Seed, K. (1998b) A semi-distributed integrated flow and
nitrogen model for multiple source assessment in catchments (INCA): Part II - Application to
large river basins in south Wales and eastern England. Science of The Total Environment 210-
211, 559-583.
Whittington, D. (2018). Five Concerns about the Cost-benefit Calculations in the Assessment Paper.
In Benefits and Costs of the Water Sanitation and Hygiene Targets for the Post-2015
Development Agenda (pp. 3–9). Copenhagen Consensus Center.
http://www.jstor.org/stable/resrep16361.5
WHO (2011). Valuing water, valuing livelihoods. Guidance on social cost-benefit analysis of drinking-
water interventions, with special reference to small community water supplies.
https://www.who.int/publications/i/item/9789241564281
WHO (2017a). Guidelines for drinking water quality, 4th edition incorporating the 1st addendum.
https://apps.who.int/iris/rest/bitstreams/1080656/retrieve
WHO (2017b). Potable Reuse, guidance for producing safe drinking water.
https://www.who.int/publications/i/item/9789241512770
WHO (2018). Preventing disease through healthy environments: a global assessment of the burden
of disease from environmental risks.
https://www.who.int/publications/i/item/9789241565196
WHO (2021). Guidelines on recreational water quality. Volume 1: coastal and fresh waters.
https://apps.who.int/iris/rest/bitstreams/1356051/retrieve
Wiegant, W. (2021) Calculation tool wastewater processes and costs.
World Bank (2011). World Livestock Disease Atlas: A Quantitative Analysis of Global Animal Health
Data (2006-2009). http://hdl.handle.net/10986/27118
World Bank (2018a). The Changing Wealth of Nations 2018. Building a Sustainable Future.
https://openknowledge.worldbank.org/bitstream/handle/10986/29001/9781464810466.pdf
World Bank (2018b). Building the World Bank’s Wealth Accounts: Methods and Data.
https://development-data-hub-s3-public.s3.amazonaws.com/ddhfiles/94641/wealth-
methodology-january-30-2018_4_0.pdf
World Bank (2019a). Quality Unknown: The Invisible Water Crisis.
http://hdl.handle.net/10986/32245
World Bank (2019b). Quality Unknown: Technical Appendixes.
https://openknowledge.worldbank.org/bitstream/handle/10986/32245/211459App.pdf?seq
uence=5&isAllowed=y
World Bank (2021), The Changing Wealth of Nations 2021 : Managing Assets for the Future.
https://openknowledge.worldbank.org/handle/10986/36400
World Water Quality Alliance (2021). World Water Quality Assessment: First Global Display of a
Water Quality Baseline. A consortium effort by the World Water Quality Alliance - towards a
full global assessment. Information Document Annex for display at the 5th Session of the
United Nations Environment Assembly, Nairobi 2021.
Young, R.A., Onstad, C.A., Bosch, D.D., (1995) AGNPS: An agricultural nonpoint source model, in:
Singh, V.P. (Ed.), Computer models of watershed hydrology. Water Resources Publications.
Highlands Ranch, Colorado, USA, pp. 1001-1020.
Zhou, Yuyu et al., (2015), A Comprehensive View of Global Potential for Hydro-generated Electricity.
https://doi.org/10.1039/c5ee00888c
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