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Spatially explicit assessment of nutrient demands for promoting efficient
regional fertilizer-use management in Vietnam
Tien Minh Tran1,*; Thu Minh Tran1; Thu Nguyen Bich2; Quang Bao Le3
1 Soils and Fertilizers Research Institute, Dong Ngac, Tu Liem, Hanoi, Vietnam
2 Southern Soils and Fertilizers Research Centre, District 1, Ho Chi Minh City
3 Swiss Federal Institute of Technology Zurich (ETH Zurich), Institution for Environmental Decisions (IED), Natural and
Social Science Interface (NSSI), Universitaestrasse 22, CH-8092 Zurich, Switzerland
* Corresponding author, email address: tranminhtien74@yahoo.com
Abstract
To transition to efficient fertilizer use for promoting food production, a wide range of stakeholders need to know nutrient
demands for meeting crop yield potentials over an agricultural region. However, knowledge about spatial patterns of these
demands is often deficient in developing countries. This study (1) assesses the nutrient demands of potential crop productions
in two intensive agricultural regions in Vietnam (i.e., Dong Nai and Bac Ninh provinces), and (2) provides a public access to
the outputs. We calculated the demands of nitrogen (N), phosphorus (P) and potassium (K) required for reaching crop yield
potentials over the farmlands in the two provinces with taking soil nutrient balance into account. The balance accounting
considered natural nutrient supplies (e.g., from soils), and different natural nutrient losses (e.g., by volatilization, erosion,
leaching and runoff crops’ uptake with different fertilizer use efficiency). The results were spatially explicit, presented at the
map scale of 1:100,000, and managed by a web-based geographic information system (GIS). The web-based GIS allows lay
users to query the results at different levels of aggregation (i.e., farm, commune, district and province) in an responsive and
iterative manner.
Key words: nutrient supply and demand, web-based GIS, potential crop yield, soil nutrient balance
Introduction
Over the period 1965-1990, global cultivated area
increased only 9.4% while the global population increased
68.5%, thus the cultivated area per capital decreased by
35.1% [2]. In Vietnam, from 1930 to 2000 the farming
area per capital had been dramatically reduced from 2,548
m2 to 675 m2. To meet the increasing requirement of foods
and fuels while the national farm land is limited,
increasing crop yield is essential for national food
security. So far the increasing of crop yield in Vietnam has
mainly depended on mineral fertilizers. The use of mineral
fertilizers has rapidly increased: the fertilizer input per
areal unit in 2007 was 5.8 times the rate in 1985 [2; 3]. At
present, mineral fertilizers use in Vietnam is around 6-7
million tons per year and 50% of it is imported [5], being a
costly input factor for the country’s agricultural
production. Furthermore, fertilizer use efficiency is still
low, which is around 30-45% for nitrogen, 15-25% for
phosphorus and 40-50% for potassium [2].
There were many research results on soil
characteristics, fertilizer application and related spatial
data that are useful for guiding the improvement of
mineral fertilizer use efficiency. However, stakeholders’
access to the information is limited because it lacks viable
assessment frameworks and user-friendly operational
tools. Recently the availability spatial information system
technology, together with the availability of spatially
explicit agronomic data, offers new opportunities to fill
the gap [1; 4; 6]. In this paper, we introduce an approach
and a case study in Vietnam that applied IT techniques and
spatially explicit assessment to (1) assesses the nutrient
demands of potential crop productions in two intensive
agricultural regions in Vietnam (i.e., Dong Nai and Bac
Ninh provinces), and (2) provides a public access to the
outputs. The study is expected to provide a wide range of
stakeholders (e.g. farmers, producers and policy makers)
with necessary information of due fertilizer demand that
should be useful for optimizing their farming management
and policies.
Assessment of nutrient demands for potential crop
productions
Nutrient demand for obtaining potential crop production
is calculated by the difference between (1) nutrient release
from soil, fertilizer and (2) nutrient losses by runoff,
leaching and crops’ uptake. The Information sources and
calculation procedure are illustrated in Figure 1.
The calculation of nutrient demand for a given
farmland location is shown in Equation 1:
100
E ca S
use
M M M
MHS
Eq. 1
where:
Muse = nutrient demand (kg ha-1),
ME = nutrient losses by runoff and leaching (kg ha-1)
which is calculated by Universal Soil Loss Equation
(USLE),
Mca = nutrients uptake by crops (kg ha-1), data
collected from field experiments and literature review,
MS = nutrients for crops from soil (kg ha-1) that is
estimated from soil characteristics (soil bulk density, soil
depth, and available nutrients in soil) and crop’s nutrient
uptake ability, and
HS = mineral fertilizer use efficiency index (%) that is
estimated from field experiments and literature review.
We spatially calculated the nutrient demand (N, P and
K) per area unit for main crops, and then aggregate the
results for main crop groups (e.g. industrial, fruit and cash
crops) for each district/commune. The results are
illustrated in Figure 2.
Fig 1. Steps for determining crop-soil-specific nutrient demand
Fig 2. Nutrient demand by crop groups and districts
Mapping crop-soil-specific nutrient demands
Given the basic Equation (1) and available spatial data
geographic information system (GIS) technology was
applied to calculate and map the nutrient demand for crop
groups in every commune in the study province.
The maps were built based on site condition data (e.g.
soil data, present land use, rainfall, slope and altitude) and
crop data (e.g. crop type, crop area). The GIS synthesis
procedure is shown in Figure 3.
Web-based geographic information system (GIS)
Based on the above-mentioned calculation procedure
and the database of related variables, a web-based GIS
was developed for responsive assessment and visualization
of soil-crop-specific nutrient demand in the study
province.
We used ASP.NET technique and SQL server to
provide a public access to the outputs of the research. A
snapshot of the web-based GIS is shown in Figure 4.
Fig 3. Process of building nutrient maps
Fig 4. The map and data in the web
The web-based GIS includes (i) the home page, (ii) a
catalogue for information of soil, crops and administrative
units, (iii) input data for calculating nutrient demands (e.g.
climate, soil characteristics, total area in
communes/districts, cropping areas, mineral fertilizer use
efficiency index, and nutrient demands for crops), and (iv)
a software to calculate nutrient demands for farmers in
their field, nutrient demands in commune/district/province
or nutrient for each crop groups.
To run the calculation, the web-based GIS requires
some user-defined data/parameters such as that illustrated
in Figure 5.
Fig 5. Form for farmers input data in the web
Conclusion and recommendation
This study assesses the nutrient demands of potential
crop productions in two intensive agricultural regions in
Vietnam, and provides a public access to the outputs. We
calculated the demands of N, P and K required for
reaching crop yield potentials over the farmlands in the
two provinces with taking soil nutrient balance into
account. The balance accounting considered natural
nutrient supplies (e.g., from soils), and different natural
nutrient losses (e.g., by volatilization, erosion, leaching
and runoff crops’ uptake with different fertilizer use
efficiency).
The results were spatially explicit, presented at the
map scale of 1:100,000, and managed by a web-based
geographic information system (GIS). The web-based GIS
allows lay users to query the results at different levels of
aggregation (i.e., farm, commune, district and province) in
an responsive and iterative manner.
However, the presented web-based GIS model still
needs to be calibrated regarding its key parameters and
component, such as the soil erosion model used, crop
nutrient uptakes and mineral fertilizer use efficiently. This
requires the establishment of field experiments over the
soil-crop matrix found in the study area.
References
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Environmental Modeling & Software 20: 291-308.
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