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INCORPORATING AQUIFER MODELING INTO A MULTI-PERIOD NETWORK FLOW PROGRAMMING OPTIMIZATION MODEL FOR WATER RESOURCES MANAGEMENT

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Abstract

Aquifers provide a very important source of water in river basins under great surface water stress, and conjunctive use represents sometimes the only way of supplying all the different demands within the basin in drought periods. On the other hand, optimization models help decision makers to depict the operations which should be done in a water resources system in order to maximize the benefits and minimize the costs while keeping a certain supply level and complying with some other constrains. Therefore, including aquifers modeling, and all their surrounding aspects, in a river basin optimization model does not only increase the representation of the model itself but also offers the possibility of studying the optimal pumping rules in a similar way as other operation rules are dealt with via the pumping control parameters. This article presents the development and integration of a groundwater module in an already existing water resources optimization model based in network flow programming. Network flow programming is an efficient form of linear programming, hence incorporating aquifer modeling that is a highly non-linear process supposes a big challenge. Moreover, in order to consider aquifers in a river basin model always implies considering as well some other non-linear related aspects such as seepage from reservoirs, river bed and irrigation schemes, additional pumping and pumping from demands, natural and artificial recharge, and water exchanges between river and aquifer, all aspects that must be incorporated to the network flow in form of new arcs and nodes and be dealt with in the optimization process. All these non-linearities have been approximated through iterations which have shown to be sufficient to yield proficient results in the example cases carried out during the development process. As an addition, different aquifer models have been considered so future modelers can choose among them one that better fits their needs.
INCORPORATING AQUIFER MODELING INTO A MULTI-
PERIOD NETWORK FLOW PROGRAMMING OPTIMIZATION
MODEL FOR WATER RESOURCES MANAGEMENT
HARO D., SOLERA A., PAREDES J., ANDREU J.
Institute of Water and Environmental Engineering, Technical University of Valencia,
Camino de Vera s/n, 46071, Valencia, Spain
Aquifers provide a very important source of water in river basins under great surface water
stress, and conjunctive use represents sometimes the only way of supplying all the different
demands within the basin in drought periods. On the other hand, optimization models help
decision makers to depict the operations which should be done in a water resources system
in order to maximize the benefits and minimize the costs while keeping a certain supply
level and complying with some other constrains. Therefore, including aquifers modeling,
and all their surrounding aspects, in a river basin optimization model does not only increase
the representation of the model itself but also offers the possibility of studying the optimal
pumping rules in a similar way as other operation rules are dealt with via the pumping
control parameters. This article presents the development and integration of a groundwater
module in an already existing water resources optimization model based in network flow
programming. Network flow programming is an efficient form of linear programming,
hence incorporating aquifer modeling that is a highly non-linear process supposes a big
challenge. Moreover, in order to consider aquifers in a river basin model always implies
considering as well some other non-linear related aspects such as seepage from reservoirs,
river bed and irrigation schemes, additional pumping and pumping from demands, natural
and artificial recharge, and water exchanges between river and aquifer, all aspects that must
be incorporated to the network flow in form of new arcs and nodes and be dealt with in the
optimization process. All these non-linearities have been approximated through iterations
which have shown to be sufficient to yield proficient results in the example cases carried
out during the development process. As an addition, different aquifer models have been
considered so future modelers can choose among them one that better fits their needs.
1. INTRODUCTION
Management of natural resources, one of which is water, is a very important activity in the
actual world. Availability and quality of water determine, among other important aspects of
quality of life and economy, public health levels and agricultural, industrial and energy
production. Inside management, planning is one of the most critical tasks.
Hydrological planning is a legal requirement established with the general objectives of
achieving the good status and adequate protection of water masses inside a river basin,
fulfillment of water demands and equilibrium and harmonization of regional and sectorial
development. These objectives must be achieved increasing water availability, protecting
its quality, and economizing its use, rationalizing it in harmony with environment and other
natural resources.
For these objectives attainment, hydrological planning will employ sustainability
criteria in the use of water through integrated management and protection to the long term
of resources, preventing water state deterioration, improvement of aquatic ecosystems and
reduction of pollution. Likewise, hydrological planning should contribute mitigating the
effects of floods and droughts.
The development of models which help reaching a higher comprehension of a water
resources system and its operation is a common practice in the planning process which
serves of great help for the achievement of the objectives previously stated while
respecting the imposed criteria. Moreover, system modeling provides a way, perhaps the
main one, to predict the future behavior of the system or its possible modifications
(Loucks[1]). Water resources systems modeling implies the development of a mathematical
or computational framework for describing a particular system and its operation to study,
identify and evaluate all the possible solutions to the existing problems in that very system.
When facing a hydrological planning problem, the most usual is having one or more
objectives to accomplish under various efficiency measures, or manners of evaluating the
achievement of the objectives. Normally, there will be a limited amount of resource and a
series of water uses which will compete for it, besides all the different restrictions both
physical and environmental. Under this perspective, a water manager will want to know
what will be the optimal flow distribution throughout the system so the benefits for water
use are maximized while costs are minimized, and all the demands are properly supplied.
This problem is usually called “water allocation problem”, and the path to follow will
involve defining several alternatives and the form of evaluating each of them to finally
decide which one of them will be the chosen one. At this point is where an optimization
model comes to play to solve the problem.
An optimization model obtains the optimal values of the control variables defined for a
certain system (a water resources system in this case), which usually are the circulating
flows in it. To do this, the optimization model will obtain the best value (maximum or
minimum) of a function which components represent both the control variables and the
different weight parameters for them, while respecting a series of restrictions limiting the
values selection of the control variables. However, as the mathematical optimization
process is usually quite complex, optimization models have had a tendency to make
important simplifications of the systems studied, what have made them less detailed than
the more extended simulation models and therefore less utilized by water managers
(Labadie [2]). On the other hand, continuous advances in computing techniques and
computing speeds have made that complex mathematical processes, even though are still
laborious, can be solved in less and less time. This makes possible to include more
complexities in previous simplistic optimization models so they reach a higher degree of
representation, what in the end will make their results closer to real systems.
This paper shows how aquifers, a high complexity element inside many water
resources systems, have been introduced in the optimization process of a prescriptive
model running under network flow programming.
2. GROUNDWATER IN WATER RESOURCES OPTIMIZATION MODELS
Global groundwater volume stored beneath the Earth’s surface represents 96 percent of the
Earth’s unfrozen freshwater (Shiklomanov [3]). Groundwater provides useful functions and
services to humans and the environment. It feeds springs and streams, supports wetlands,
maintains land surface stability in areas of unstable ground, and acts as an overall critical
water resource serving our water needs.
IGRAC (International Groundwater Resources Assessment Centre) estimates that
about 60 percent of withdrawn groundwater is used to support agriculture in arid and semi-
arid climates [4]. Morris et al. [5] report that groundwater systems globally provide 25 to
40 percent of the world’s drinking water. Today, half the world’s megacities and hundreds
of other major cities on all continents rely upon or make significant use of groundwater.
Small towns and rural communities particularly rely on it for domestic supplies. Even
where groundwater provides lower percentages of total water used, it still can serve local
areas with relatively low-cost good-quality water where no other accessible supply exists.
Finally, groundwater can bridge water supply gaps during long dry seasons and during
droughts.
Therefore, aquifers suppose a very important element in water resources planning and
management of many river basins. Thanks to aquifers it is possible to supply, or give
additional supply, of numerous demands, being agricultural demands the most favored,
especially in surface water scarcity periods during which thanks to groundwater pumping
many crops can be saved. However, indiscriminate pumping may result in aquifer
overexploitation, what would later create several problems for future pumping supply, in
rivers connected to the aquifer, and even in zones far from them. Because these reasons,
including aquifers in the optimization process should be mandatory when the groundwater
utilization in the studied water resources system has certain significance. Doing this would
be beneficial allowing, for example, operation rules for pumping from demands or
reservoir operation curves taking into account the possibility of additional pumping.
At present, there are few models of general use including the possibility of introducing
aquifers as a specific element when developing a water resources scheme for study. These
models are mainly for simulation (SIMGES [6], Modsim [7], or WEAP [8]), which solve
an optimization problem for each time step in the simulation to obtain the flows through
the system. However, any pure optimization model has been found that allows introducing
aquifers as a separate element and they are usually dealt with by tricks in the system
description using, for example, reservoir elements, what will not show the usual complex
behavior of aquifers, although it could be a first approach. Therefore, it has been found
interesting to develop a model where this inconvenience is solved and aquifers, and their
related features inside the water system, are considered as a specific separate element. To
do this, an existing optimization model has been used as a base so focus was exclusively
upon the aquifer development. In the following sections describe the optimization model
used and how an aquifer module has been developed for it together with an example of
how it works.
3. OPTIGES, A NETWORK FLOW PROGRAMMING MODEL FOR
WATER RESOURCES SCHEMES OPTIMIZATION
OPTIGES (Andreu [9]) is a program of general use that allows optimizing a scheme of
water resources. It is integrated in the DSS AQUATOOL (Andreu et al. [10]).
For its use, the user must previously make a simplified scheme of the water resources
system with the elements considered by the model which are, namely, channels (natural
and artificial), nodes (forks, junctions or reservoirs), hydrological inflows and demands
(zones where water is used). The user supplies the program with the configuration data of
the scheme together with the physical data of the elements (for example maximum
capacities of channels, or maximum volume stored in reservoirs), the demands data as well
as the data used for fixing priorities between scheme elements and for defining guarantee
criteria of demands satisfaction and environmental requirements.
The program works with monthly values and allows optimization periods of at least
one year, with a number of periods also fixed by the user. The model results include the
values of the stored volumes in reservoirs, circulating flows and supply deficits for each
month, as well as a final summary of the whole optimization horizon including average,
monthly and yearly values of all variables.
To solve the optimization problem, OPTIGES converts the user scheme with all the
introduced data into a minimum cost network flow problem which is afterwards solved
with either the Out-of-Kilter algorithm (Ahuja [11]) or the RELAX-IV algorithm
(Bersetkas [12]), depending on the choice of the user and being the first one used mainly
for schemes created in the initial versions of the program and the second for the later
versions.
OPTIGES is also capable to deal with evaporation from reservoirs and water returns
from demands. These two aspects represent non-linearities which are a priori impossible to
solve directly with network flow programming, since it is a form of linear programming.
What it is done instead is solving iteratively the minimum cost network flow problem,
changing the characteristics of the arcs in the network associated to each of the non-linear
elements, after each iteration, until convergence is reached. The iteration routine calculates
the evaporation or return flows associated to the solution obtained with the network flow
algorithm and compares these values with the ones obtained in the corresponding arcs of
the network; if there is a difference between them, the routine modifies the flow limits of
the arcs and runs again the algorithm. This is done until the difference between the
calculated values and the ones obtained from the algorithm is minimal, or the maximum
number of iterations is reached.
4. AQUIFER MODULE DEVELOPMENT
When considering aquifers in a water resources system, not only their storage capacity
must be taken into account but also all the possible relations they may have with the
surface system. This means that infiltration from reservoirs and from river bed must be
considered, also pumping from demands or for other uses as well as artificial recharges and
last but not least the connection between river and aquifer which sometimes exists.
Therefore, the inclusion of an aquifer will require several actions that will affect the
optimization model at different levels:
- Water resources system schematization
- Network flow definition
- Iterative process of new non-linear elements (infiltration from reservoirs, looses
from rivers and demands…)
- Aquifer simulation
- Reading of results
Both, the water resources system schematization and the network flow definition are
intimately related. Together with the element “Aquifer” were also included new options for
existing elements of the OPTIGES model both as new scheme elements and extra options
for existing ones. The new possibilities added to OPTIGES are:
- Aquifer elements
- Channel elements, or river reaches, with looses by infiltration
- Channel elements, or river reaches, hydraulically connected to the aquifer
- Additional pumping elements
- Artificial recharge elements
- Infiltration from reservoirs
- Pumping supply to consumptive demands
- Infiltration looses from consumptive demands
Each of these new features will require, when defined by the user, the creation of extra
arcs in the network flow, what will noticeable enlarge it adding an extra complexity to the
resolution process.
Several of the newly added features correspond to aspects absolutely non-linear. Thus,
as it is already done in OPTIGES with the non-linear aspects considered (evaporation and
returns); an iterative solution process will be followed to deal with the new non-linear
processes. All the non-linearities include require that the flow circulating through a certain
arc is related in some way to the flow circulating through a different arc. For example, in
the case of filtration looses from reservoirs, the circulating flow through the arc connecting
the reservoir and the aquifer in one month will be related to the flow representing the stored
volume following the infiltration law:F = a + bV c, where F represents the infiltration
looses flow, V is the volume stored in the reservoir and a, b and c are three coefficients
which must have been defined by the user previously. The same procedure is followed for
infiltration looses in channels. The infiltration looses from consumptive demands depend
from the usage and return factors associated to the demands, which must be defined by the
user as well. Finally, the hydraulic connection between the aquifer and the river reaches
with had been included in the scheme will depend on the volume balance of the aquifer
with its inputs and outputs, as well as the aquifer type considered
All the non-linear flows and affections to the aquifer are calculated first and a call is
made to a routine (ACUIFERO); where the aquifer balance is calculated and the flows
circulating between aquifer and hydraulically connected river reaches is obtained. The
ACUIFERO routine simulates the aquifer behavior for the whole optimization period and
checks for impossible water withdrawals from river reaches as well as pumping control
parameters. The aquifer simulation yields as a result the connection flow between aquifer
and river which is the last non-linearity to be calculated. As explained before, the iteration
routine checks for convergence in all the affected arcs of the network and reassigns their
limits if necessary, triggering a new run of the resolution algorithm.
The previously commented pumping control parameters are rules for groundwater
extraction through wells that are defined by the user and depend of the aquifer status (either
the volume stored in the aquifer or the volume circulated between river and aquifer). When
the value of any of the two aquifer parameters is below certain threshold, the pumping
controlled by that parameter will stop until the value is above the defined threshold.
After convergence has been reached for all the non-linearities, the program will extract
the results for the complete optimization period and will write average, monthly and annual
summaries, as well as create a results file for graphical output.
5. APPLICATION IN THE OPTIMIZATION OF A SIMPLE WATER
RESOURCES SYSTEM
To show how the developed module works a simple water resources system scheme was
created. The system has a single reservoir which has looses by infiltration, a urban demand
which returns part of the supplied water to the river, a rural demand that can extract
groundwater for complementing the surface water supply (only half of the total demand is
possible to supply from pumping), a unicellular aquifer hydraulically connected to two
river reaches and receiving precipitation recharge. The urban demand has priority of supply
respect the rural demand.
With the same hydrological inflows for a 60 year period, the scheme was run with the
SIMGES [6] simulation model and with the OPTIGES optimization model with the
groundwater module included.
The results obtained show how the optimization model allows more pumping for the
rural demand since it considers the whole 720 month period while the simulation model
only uses the groundwater supply as a complement in months when surface supply is not
enough, and allows maintaining a higher storage volume in the reservoir instead of
emptying it. Of course, all this means that the deficits in both the urban and the rural
demands are reduced. However, the higher exploitation of the aquifer yields, of course, a
diminishment in the groundwater storage during the driest periods. Anyway, aquifer
overexploitation problems may be avoided by using a pumping control parameter which
will prevent water to be extracted from the aquifer if its levels decrease below the value of
the parameter.
6. CONCLUSIONS AND FURTHER WORK
Optimization is an important task in water resources planning and management. Thus, it is
important that the optimization models, even though they are primarily used for
alternatives filtering, show a good degree of detail. This should help to make better
decisions on the actions to be studied more in deep. Moreover, water resources systems are
becoming more and more complex, and water managers require giving more precise
answers to the principal stakeholders’ necessities. Therefore, improving the representation
of the optimization models being used is a need to be fulfilled in the short term.
An aquifer module has been developed for an existing optimization model working
under network flow programming. The aquifer consideration in the network flow has been
made through iterations so the non-linear behavior of the new element and all the new
features related to it, which have also been implemented, can be dealt with. The results for
simple cases show that the module works fine as the model improves the water availability
in the system, reducing the water deficits while saves water for future needs. At the same
time, the model makes an efficient use of the aquifer and only extracts water when it is
necessary.
However, the module behavior can still be improved. It has been observed that the
model withdraws water from the aquifer in the very months that it is needed. Although this
is a logical behavior, it is also interesting the possibility of pumping water before it is
needed, so the water stored in the reservoir is saved and, at the same time, during dry
periods, when the aquifer recharge is lower, the pressures on it are minor, since the water
supplied can come from the superficial storage.
Another aspect to be improved is the behavior of the pumping control parameters. At
present, this feature works either allowing groundwater pumping at whole capacity or
stopping it completely when the threshold is surpassed. A more optimal solution could be
obtained if the pumping capacity could be reduced gradually until the parameter was just at
its threshold.
These two improvements are being dealt with at the moment and new advances are
being done so a proper version of the optimization model is available in the coming time.
7. REFERENCES
[1] Loucks D., “Water Resource System Models: Their Role in Planning”, Journal of
Water Resources Planning and Management, Vol. 118, No. 3, (1992), pp 214-223
[2] Labadie J., “Optimal Operation of Multireservoir Systems: State-of-the-Art Review”,
Journal of Water Resources Planning and Management, Vol. 130, No. 2, (2004), pp 93-
111
[3] Shiklomanov I.A. and Rodda J.C., “World Water Resources at the Beginning of the 21st
Century”, Cambridge, UK, Cambridge University Press, (2003)
[4] IGRAC, “Global Groundwater Information System Database”
(igrac.nitg.tno.nl/ggis_map/start.html lvJan12)
[5] Morris B.L., Lawrence A.R., Chilton P.J., Adams B., Calow R.C. and Klinck B.A.,
“Groundwater and its Susceptibility to Degradation. A Global Assessment of the Problem
and Options for Management”. Early Warning and Assessment Report Series, RS. 03-3,
UN, (2003)
[6] Andreu J., Solera A., Capilla J. and Ferrer J., “Modelo Simges para Simulación de
Cuencas. Manual de Usuario v3.00”, Valencia, Spain, Universidad Politécnica de Valencia
(2007)
[7] Labadie, J. and R. Larson, “MODSIM: River basin management decision support
system, User Manual”, Department of Civil Engineering, Ft. Collins, CO, Colorado State
University, (2007)
[8] Yates D., Sieber J., Purkey D. and Hubert-Lee A.,WEAP21 A Demand-, Priority-,
and Preference-Driven Water Planning Model. Part 1: Model Characteristics”. Water
International, Vol. 30, No. 4, (2005), pp 487-500
[9] Andreu J. “Modelo OPTIGES de Optimización de la Gestión de Esquemas de Recursos
Hídricos. Manual del Usuario v2.00”, Valencia, Spain, Universidad Politécnica de
Valencia, (1992)
[10] Andreu J., Capilla J. and Sanchís E., “AQUATOOL: a generalized decisión support
system for water resources planning and operational management”. Journal of Hydrology,
Vol. 177, (1996), pp 269-291
[11] Ahuja R., Magnanti T. and Orlin J., Network Flows: theory, algorithms and
applications”, New York, Prentice Hall, (1993)
[12] Bersetkas D. and Tseng P., “RELAX-IV: A Faster Version of the RELAX code for
Solving Minimum Cost Flow Problems”, Completion Report for NSF Grant CCR-
9103804, Dept. of Electrical Engineering and Computer Science, Massachusetts Institute of
Technology, Cambridge, USA, (1994)
... OPTIGES is also capable to deal with evaporation from reservoirs and water returns from demands. Additionally, it is also capable of considering, to a certain extent, the relation between the surface system and groundwater [16]. The user can make use of several aquifer models and connecting them to the surface system via infiltration losses from conductions and reservoirs, hydraulic connected river stretches, pumping from demands and artificial groundwater recharges. ...
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Groundwater and its Susceptibility to Degradation. A Global Assessment of the Problem and Options for Management
  • B L Morris
  • A R Lawrence
  • P J Chilton
  • B Adams
  • R C Calow
  • B A Klinck
Morris B.L., Lawrence A.R., Chilton P.J., Adams B., Calow R.C. and Klinck B.A., "Groundwater and its Susceptibility to Degradation. A Global Assessment of the Problem and Options for Management". Early Warning and Assessment Report Series, RS. 03-3, UN, (2003)