A surface water management model for the Integrated Southern Ghor Project, Jordan
Identifieur interne : 001415 ( Istex/Corpus ); précédent : 001414; suivant : 001416A surface water management model for the Integrated Southern Ghor Project, Jordan
Auteurs : Malek Abu Rumman ; Mohammad Hiyassat ; Bashar Alsmadi ; Ahmad Jamrah ; Maha AlqamSource :
- Construction Innovation [ 1471-4175 ] ; 2009-07-10.
Abstract
Purpose The purpose of this paper is to assess the longterm ability of the Integrated Southern Ghor Project ISGP to meet the required water demands, assess the resulting energy requirements, pumping costs, water transfers, benefits of the current system with respect to predevelopment conditions and effect of projected water demands increase on the resulting water deficits. Designmethodologyapproach A surface water resources management model is developed using dynamic programming. The model inputs are the hydrological inflows from the different wadis in the project area, reservoirs characteristics and evaporation rates, system water demands. The model outputs are water deficits at the different demand areas, reservoirs storage and release sequences, water transfers and energy requirements and the associated costs. The average annual values of different performance criteria with the annual frequency curves are used to evaluate the implications of different water scenarios on the ISGP. Findings The results show the efficiency of the ISGP model in reducing the water deficits in the demand areas as compared to predevelopment conditions. Increased demand scenario showed the importance of finding new water projects to supplement the Southern Ghor Area in the future in order to meet the increasing water demands. The proposed water transfer will reduce the resulting deficits at the agricultural areas without the expenses of increasing the water deficits at other demand areas. The application of this model is expected to enhance decision making regarding water policies in Jordan. Originalityvalue This paper provides critical quantitative information to decision makers in Jordan about the potential of the different storage facilities and proposed transfers in meeting the required water demands in the Southern Ghor Project and assesses the required energy for that. This can help decision makers to have a holistic view about the expected water deficits in the area and therefore assist them in determining the areas impacted most and what alternative solution to use. The paper also shows the importance of using optimal controlmanagement models to support water resources decision making in Jordan.
Url:
DOI: 10.1108/14714170910973510
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<front><div type="abstract">Purpose The purpose of this paper is to assess the longterm ability of the Integrated Southern Ghor Project ISGP to meet the required water demands, assess the resulting energy requirements, pumping costs, water transfers, benefits of the current system with respect to predevelopment conditions and effect of projected water demands increase on the resulting water deficits. Designmethodologyapproach A surface water resources management model is developed using dynamic programming. The model inputs are the hydrological inflows from the different wadis in the project area, reservoirs characteristics and evaporation rates, system water demands. The model outputs are water deficits at the different demand areas, reservoirs storage and release sequences, water transfers and energy requirements and the associated costs. The average annual values of different performance criteria with the annual frequency curves are used to evaluate the implications of different water scenarios on the ISGP. Findings The results show the efficiency of the ISGP model in reducing the water deficits in the demand areas as compared to predevelopment conditions. Increased demand scenario showed the importance of finding new water projects to supplement the Southern Ghor Area in the future in order to meet the increasing water demands. The proposed water transfer will reduce the resulting deficits at the agricultural areas without the expenses of increasing the water deficits at other demand areas. The application of this model is expected to enhance decision making regarding water policies in Jordan. Originalityvalue This paper provides critical quantitative information to decision makers in Jordan about the potential of the different storage facilities and proposed transfers in meeting the required water demands in the Southern Ghor Project and assesses the required energy for that. This can help decision makers to have a holistic view about the expected water deficits in the area and therefore assist them in determining the areas impacted most and what alternative solution to use. The paper also shows the importance of using optimal controlmanagement models to support water resources decision making in Jordan.</div>
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<p>The purpose of this paper is to assess the long‐term ability of the Integrated Southern Ghor Project (ISGP) to meet the required water demands, assess the resulting energy requirements, pumping costs, water transfers, benefits of the current system with respect to predevelopment conditions and effect of projected water demands increase on the resulting water deficits.</p>
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<p>A surface water resources management model is developed using dynamic programming. The model inputs are the hydrological inflows from the different wadis in the project area, reservoirs characteristics and evaporation rates, system water demands. The model outputs are water deficits at the different demand areas, reservoirs storage and release sequences, water transfers and energy requirements and the associated costs. The average annual values of different performance criteria with the annual frequency curves are used to evaluate the implications of different water scenarios on the ISGP.</p>
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<sec><title content-type="abstract-heading">Findings</title>
<x> – </x>
<p>The results show the efficiency of the ISGP model in reducing the water deficits in the demand areas as compared to predevelopment conditions. Increased demand scenario showed the importance of finding new water projects to supplement the Southern Ghor Area in the future in order to meet the increasing water demands. The proposed water transfer will reduce the resulting deficits at the agricultural areas without the expenses of increasing the water deficits at other demand areas. The application of this model is expected to enhance decision making regarding water policies in Jordan.</p>
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<x> – </x>
<p>This paper provides critical quantitative information to decision makers in Jordan about the potential of the different storage facilities and proposed transfers in meeting the required water demands in the Southern Ghor Project and assesses the required energy for that. This can help decision makers to have a holistic view about the expected water deficits in the area and therefore assist them in determining the areas impacted most and what alternative solution to use. The paper also shows the importance of using optimal control/management models to support water resources decision making in Jordan.</p>
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<body><sec><title>Introduction</title>
<p>The design and operation of surface water systems are typical watershed management problems. The main components of surface water systems include the reservoirs (dams) and their structures as well as pipelines, channels and hydropower/pumping units.</p>
<p>Water resources management requires a comprehensive and integrated viewpoint to the decision‐making problem. Many challenging issues face researchers in this area such as: the stochastic nature of future inflows and system parameters (like in groundwater aquifer parameters), the nonlinearities in the system dynamics and other uncertainties in water systems, the large number of decision/state variables involved, and the need to meet multiple benefits (domestic/irrigation water demands, hydropower, pumping and aquifer heads, flood control, environmental standards, etc.). Furthermore, in large water resources systems when managing more than one watershed political conflicts rise between authorities, political entities and even between countries when there are different interests.</p>
<p>The problem of managing water resources systems is an optimal control problem, different optimization methods are used in water resources management problems. Water resources management models combine optimization algorithms and water resources systems dynamical models (mainly surface water and groundwater, dynamical models but could also include treatment plants effluent models). Based on certain management policies that the decision makers opt to adopt factors such as environmental standards, economical targets, water deficits, social constraints and others are embedded in the management models. The following review covers the different water resources management models that are found in the literature by different seminal authors.</p>
<p><xref ref-type="bibr" rid="b23">Reichard (1995)</xref>
used a nonlinear solver using modular in‐core nonlinear optimization system – MINOS (<xref ref-type="bibr" rid="b22">Murtagh and Saunders, 1987</xref>
) to solve the conjunctive use management problem (surface water and groundwater resources), and applied it to the Santa Clara‐Calleguas Basin in California, different environmental and economical constraints were used in the model related to the river flows and water demands. <xref ref-type="bibr" rid="b9">Georgakakos and Marks (1987)</xref>
represented the surface water system dynamics in a state space form and developed a stochastic optimization method called the extended linear quadratic Gaussian (ELQG) method based on gradient search algorithms that can be used for medium to large reservoir systems, the stochastic nature of the inflows was also addressed in later studies (<xref ref-type="bibr" rid="b10">Georgakakos, 1989</xref>
; <xref ref-type="bibr" rid="b11">Georgakakos <italic>et al.</italic>
, 1997</xref>
). Simulation techniques also were used in the management of reservoir systems, the main shortcoming is that it requires prior specification of the system operating policy. As a result, the only way to locate an optimal policy is through trial and error simulation runs. Researchers also applied optimization within simulation models (<xref ref-type="bibr" rid="b14">Herrling and Heckele, 1986</xref>
; <xref ref-type="bibr" rid="b15">Johnson <italic>et al.</italic>
, 1991</xref>
; <xref ref-type="bibr" rid="b26">Tejada‐Guibert <italic>et al.</italic>
, 1993</xref>
; <xref ref-type="bibr" rid="b1">Ahlfeld, 1994</xref>
), used a linear optimization procedure to solve a deterministic groundwater management problem. <xref ref-type="bibr" rid="b16">Jones <italic>et al.</italic>
(1987)</xref>
used a differential dynamic programming (DP) to solve a deterministic and nonlinear groundwater management problem. <xref ref-type="bibr" rid="b13">Gorelick and Voss (1984)</xref>
combined a solute‐transport simulation model (SUTRA), with a nonlinear optimization solver (MINOS) to produce a methodology for aquifer rehabilitation. <xref ref-type="bibr" rid="b12">Georgakakos and Vlatsa (1991)</xref>
used a gradient search method (ELQG) to solve a stochastic groundwater management problem.</p>
<p>The main drawback of some of the algorithms reported above is that they do not guarantee convergence to globally optimal solutions as proposed by <xref ref-type="bibr" rid="b28">Wagner and Gorelick (1987)</xref>
and <xref ref-type="bibr" rid="b13">Gorelick and Voss (1984)</xref>
. Linear programming (LP) had been used widely in management problems. While efficient, this optimization method has certain disadvantages: first, the objective function and the constraints have to be linear. In water resources management problems, however, nonlinearities are embedded in the problem formulation. Therefore, the use of LP limits the management problem formulation. Second, according to <xref ref-type="bibr" rid="b2">Ahlfeld and Mulligan (2000)</xref>
, in large regional systems with many constraints, the LP can be computationally challenging due to the calculation of the inverse basis matrix.</p>
<p>The optimization method used in this work to solve the water resources management problem is DP (<xref ref-type="bibr" rid="b3">Bellman and Dreyfus, 1962</xref>
; <xref ref-type="bibr" rid="b18">Loucks <italic>et al.</italic>
, 1981</xref>
; <xref ref-type="bibr" rid="b25">Stedinger <italic>et al.</italic>
, 1984</xref>
; <xref ref-type="bibr" rid="b24">ReVelle, 1999</xref>
). When the dimensionality of the system is not high, DP is considered a very efficient method in formulating, solving and finding the optimal solution. This method is used for dynamical systems where the state vector – here represented by reservoir storages or elevations – change during the period of optimization (with respect to time). The optimal solution for the system is obtained by finding the control vector – reservoir releases – that minimize/maximize a certain individual or combined goals (irrigation deficits, reservoir storages or stages, power generation, environmental standards, etc.) that the decision makers like to accomplish. So, like an example minimizing the system monthly water deficits while meeting the environmental standards related to reservoir storages, downstream minimum flows, or groundwater aquifer heads.</p>
<p>From a holistic perspective and for readers who are not familiar with the area of water resources management, there are other subjects/topics that are also related to this area. Like an example water resources management includes – among others – subjects as irrigation scheduling and management, hydropower generation, geographic information system (GIS) mapping and the effects of climate change. Few references that provides examples on these additional topics follow.</p>
<p><xref ref-type="bibr" rid="b19">Maddock (1973)</xref>
formulated a stochastic management problem for an irrigated farm subject to variations in economic factors such as pumping costs and crop prices, and to uncertainty to groundwater parameters. <xref ref-type="bibr" rid="b4">Brumbelow and Georgakakos (2007b)</xref>
developed a new algorithm based upon differential crop yield response to irrigation that used crop models to determine planning‐level irrigation schedules and crop water production functions. <xref ref-type="bibr" rid="b5">Brumbelow and Georgakakos (2007a)</xref>
also looked at the effect of climate variability on the changes on the agricultural water resources planning for lake Victoria Basin in East Africa. <xref ref-type="bibr" rid="b17">Khan <italic>et al.</italic>
(2008)</xref>
applied a combined approach of water accounting using remote sensing and GIS coupled with groundwater modeling to evaluate water saving options by tracking non‐beneficial evaporation in the Liuyuankou irrigation system of China. <xref ref-type="bibr" rid="b11">Georgakakos <italic>et al.</italic>
(1997)</xref>
applied a new multilevel control model to derive estimates of the reservoir hydropower with or without dependable capacity commitments. The model is able to optimize individual turbine operation as well as overall system operation on an hourly and daily basis. <xref ref-type="bibr" rid="b20">Markoff and Cullen (2008)</xref>
presented an assessment of uncertainty in future Pacific Northwest (PNW) hydropower generation potential based on a comprehensive set of climate models and greenhouse gas emissions pathways. The authors found that the prognosis for PNW hydropower supply under climate change is worse than anticipated.</p>
</sec>
<sec><title>Methodology</title>
<p>A surface water resources management model was developed for Jordan Integrated Southern Ghor Project (ISGP). The management model included all the different storage elements, conveyors, wadi flows and water transfers for the ISGP. The methodology of developing this model included the following steps (which will be explained in more details in the following sections). Therefore, the following sections will follow the same order as shown in the steps below but with more analysis:<list list-type="order"><list-item><label>1. </label>
<p>Acquire hydrological data inputs and system characteristics for the different elements of the ISGP: wadi inflows, reservoir evaporation, reservoirs characteristics, etc.</p>
</list-item>
<list-item><label>2. </label>
<p>Identifying the main water resources issues to be addressed by the management model in order to provide answers for the decision makers.</p>
</list-item>
<list-item><label>3. </label>
<p>Formulation of the management problem to include the: reservoirs and transfer points dynamics, system constrains and the system targets and objectives.</p>
</list-item>
<list-item><label>4. </label>
<p>Solution of the formulated management problem using a management algorithm.</p>
</list-item>
<list-item><label>5. </label>
<p>Conducting assessment scenarios for the ISGP that look at the impact of the different management options and analyzing the results of that.</p>
</list-item>
</list>
</p>
</sec>
<sec><title>Background and description of water resources system</title>
<p>Water resources planning and management is a top national priority and necessity in Jordan. There are several compelling reasons for this as evidenced by the following facts:<list list-type="bullet"><list-item><label>• </label>
<p>The per capita water supply is currently 150 cubic meters per year, which is much below the 1,000 cubic meters per year considered to be the threshold of water scarcity (<xref ref-type="bibr" rid="b8">Food and Agricultural Organization of the United Nations, 1993</xref>
).</p>
</list-item>
<list-item><label>• </label>
<p>Water supply is seriously deficient relative to the rapidly rising demand, in spite of significant infrastructure investments in the water sector (<xref ref-type="bibr" rid="b7">El‐Naser, 1997</xref>
). Presently, the deficit is covered by over‐exploiting groundwater aquifers at rates far beyond their sustainable range (146‐235 per cent; <xref ref-type="bibr" rid="b7">El‐Naser, 1997</xref>
). The over‐exploitation of surface and groundwater has caused a historically unprecedented decline of the Dead Sea level (over 21 meters since 1930).</p>
</list-item>
<list-item><label>• </label>
<p>The population of Jordan, presently about 5 million, is growing at a high rate of 2.5 percent annually, intensifying the stress on the country's water resources and placing serious limitations on her economic growth.</p>
</list-item>
<list-item><label>• </label>
<p>Jordan's primary surface water resources are shared with neighboring countries, including the Yarmouk River (on the Syrian border) and the Jordan River (on the border with Israel).</p>
</list-item>
</list>
The purpose of this paper is to describe a water resources assessment model conducted for Jordan Southern Ghor Project. The management model is part of a decision support system (DSS) to quantify the tradeoffs associated with various management options that could potentially interest the decision makers and planners. For those readers who are not familiar with the concept of a DSS in water resources, the DSS at its general form would include the following components as shown in <xref ref-type="fig" rid="F_3330090305012">Figure 1</xref>
: surface water and groundwater models to compute the system responses based on different inputs (inflows, recharges, boundary conditions, etc.), an optimization algorithm to find the optimal water policy based on the system constraints, dynamics and objective function, and forecast models to forecast the unknown components (future river inflows, future aquifer recharge and boundary conditions, etc.). Furthermore, energy demands/generation is also important to decision makers, therefore assessment of energy demands (pumping) or generation (hydropower) should be part of a DSS. Typically, the DSS is connected to a database where data can be retrieved and updated. For complex DSS, it is convenient to have an interface so as the DSS becomes more user friendly for users of different backgrounds. For the purpose of this work and at this stage, only the surface water components are included. Since the developed model is not an operational model no forecast components are included. Future extension on this management model will include the developments of groundwater and forecast models components.</p>
<p>Trade‐offs essentially circumscribe the ability of the water resources system to meet the demands placed on it and can help identify the most promising strategies. This is the notion of a system that supports decisions, not one that actually makes them. However, at the operational level, once a particular option is selected, the DSS can be used to determine the appropriate operational strategy that implements it. Furthermore, as conditions change, decisions can be re‐evaluated and revised as often as appropriate. Though the DSS version used for this assessment does not yet include operational components, it can further be expanded to support such decisions. To this end, future necessary enhancements are discussed in the last section.</p>
<p>The Jordanian ISGP (<xref ref-type="fig" rid="F_3330090305013">Figure 2</xref>
) lies within the Wala, Mujib and Dead Sea basins (<xref ref-type="bibr" rid="b27">United States Geological Survey, 1998</xref>
). The project includes the following elements: Mujib Dam, Wala Dam, Tannur Dam, Wadi Mujib, Wadi Wala, Wadi Tannur and the Northern springs of Wadi Zarqa Main and Wadi Abu Khusheiba.</p>
<p>The project also includes small collection tanks; water from the dams is pumped to the tanks before it is being released back from them to meet the different water demands. These collection tanks are the Mazra'a, the New Zara and the Suweimah water tanks. The water demands from the system are agricultural, municipal and industrial demands. The agricultural water demands are in Ghor Feifa and Khanzeira, and in Ghor Mazra'a. Municipal water demands are in Amman (withdrawn from Suweimah Water Tank), and industrial water demands are for the Arab Potash Company (APC) near Ghor Mazra'a. The flow at the Mujib Diversion Weir consists of the releases from the Mujib Dam, Wala Dam and baseflow estimated annually to be about 20 million cubic meters (MCM).</p>
<p>A short description of these elements follows. Data for the modeling of these elements were kindly provided by the Ministry of Water and Irrigation (MWI) in Jordan.</p>
<sec><title>Hydrologic inputs</title>
<p>Hydrologic data include the stream flow data for the following: monthly flows for Wadi Wala, Wadi Mujib and Wadi Tannur for the period of January 1977‐December 1999. Hydrological data inputs are provided by the MWI in Jordan, unfortunately data beyond 1999 had many missing months and due to the type of analysis conducted the period beyond 1999 was not included in the developed model. Incomplete hydrological data records can be a main issue in Jordan. It could be due to many reasons: flow gages failure, sabotage, or being lost during major floods. Also during the periods of reservoir construction measurements reading may not be taken as frequent. Therefore, unfortunately data acquisition is beyond the control of the authors.</p>
<p>It is important to note that missing data can have a downside but does not invalidate the purpose of the developed model. Like an example, the developed model can also be used at the operational level in conjunction with the appropriate hydrological forecast models, where daily, weekly, or monthly time steps are used and the management horizon is yearly (a short management horizon).</p>
<p>The monthly flows of the Northern Springs at Wadi Zarqa Main and Wadi Abu Khusheiba is estimated based on annual value of 23 MCM per year (almost 1.9 MCM per month) as provided by the MWI, Jordan. The baseflow at the confluence of Wadi Mujib and Wadi Wala was estimated to be 20 MCM per year. In addition to streamflow data, hydrologic data includes evaporation and rain measurements. <xref ref-type="fig" rid="F_3330090305014">Figure 3</xref>
shows the monthly streamflows of Wadi Mujib, Wadi Wala and Wadi Tannur. The figure shows few flooding events (1979, 1980, 1992, etc) the major flooding event was basically in 1992. The figure also shows that during the dry season (April‐September), the flows through these wadis are very small compared to the wet season. This affects the storage cycles for the reservoir facilities constructed as they are filled up during the wet season to meat the water demands for the rest of the year and even the subsequent years if there is a drought condition.</p>
</sec>
<sec><title>Modeled elements</title>
<p><xref ref-type="fig" rid="F_3330090305015">Figure 4</xref>
shows a schematic with the system elements modeled: the figure shows the different components of the Southern Ghor Project water resources system: the storage facilities, conveyors, weirs and water demands. More discussion on these components follows.</p>
<p>The main characteristics of the Mujib, Wala and Tannur reservoirs are shown in <xref ref-type="fig" rid="F_3330090305020">Table I</xref>
followed by more details of each one of them.</p>
</sec>
<sec><title>Conveyors and the associated weirs and collection projects</title>
<p><xref ref-type="fig" rid="F_3330090305021">Table II</xref>
lists the conveyors, weirs and collection projects to carry out the released (from dams) and discharged (from baseflow and springs) water to the areas of demand, these elements are also shown in <xref ref-type="fig" rid="F_3330090305015">Figure 4</xref>
.</p>
</sec>
<sec><title>System demands and energy requirements</title>
<p>The system water demands are as follows:<list list-type="bullet"><list-item><label>• </label>
<p>About 53 MCM per year of potable water is supposed to be transferred to Amman from Suweimah collection tank (30 MCM per year from the Mujib and Wala dams through Mujib Weir and 23 MCM per year from the Zarqa Maein and Abu Khashaba springs).</p>
</list-item>
<list-item><label>• </label>
<p>Almost 12 MCM per year for agricultural and industrial purposes in the Ghor Mazra'a area and the APC taken from the Mujib and Wala dams through Mujib Diversion Weir and the Southern Conveyor.</p>
</list-item>
<list-item><label>• </label>
<p>About 8 MCM per year for agricultural uses in the Ghor Feifa and Khanzeira area provided by the Tannur Dam and Mujib and Wala dams through the proposed conveyor to Tannur Dam.</p>
</list-item>
</list>
The allocation of water at the Mujib Weir to the Northern and Southern conveyors is based on the ratio of the demands at these conveyors (just north and south to the Weir) which are 30 and 12 MCM per year, respectively, (<xref ref-type="fig" rid="F_3330090305015">Figure 4</xref>
).</p>
<p>There are also energy requirements due to pumping the water from the Wala and Mujib Dams to the collection tanks at the New Zara Tank (North) and the Mazra'a Tank (South). The pumping stations are located at the Mujib Diversion Weir. The head differences (with respect to the Mujib Diversion Weir) at the New Zara Tank and the Mazra'a Tank are 136 and 109 meters, respectively, (<xref ref-type="bibr" rid="b6">Dar Al‐Handasah Shair and Partners, 2005</xref>
).</p>
</sec>
</sec>
<sec><title>Water resources issues addressed</title>
<p>Unfortunately, water resources planning in Jordan lacks the use of management models to build its policies on. Usually, management policies are applied individually without collectively considering all the other water system components in the management process and without taking long‐term planning into consideration. Like an example groundwater aquifers and reservoirs are not managed conjunctively, therefore the main aquifers – like in the Amman – Zarqa and Yarmouk basins – are being exploited over their sustainable ranges. Furthermore, individual analysis based on reservoir simulation is applied to the main reservoirs along the Jordan Valley to King Talal Dam, Arab Dam, Ziglab Dam, etc. Such analysis lacks the coordinated management and long‐term assessment using optimization‐based models in order to better estimate their ability to meet the system water demands with respect to long‐term dry and wet climatic cycles. This can cause the use of inappropriate policies in the management of the water resources system.</p>
<p>The use of management models will lead to the appropriate coordination between the different system components in order to meet the different water demands without depleting one of them with respect to the others. Also, inflow forecast models can be combined with optimal control models to produce operational models on a daily or weekly basis. Inflow uncertainty can be characterized and the management models can operate within certain reliability levels based on the level of risk that the decision makers are willing to take.</p>
<p>The management model developed in this paper gives an example of collective and long‐term planning in order to lay out the water policies and assessments. Using this management model, the ISGP can be effectively assessed and the system efficiency can be evaluated using the statistics of the optimal decisions.</p>
<p>The specific issues addressed in this study are:<list list-type="order"><list-item><label>1. </label>
<p>The evaluation of the system ability to meet the water demands for the three demand locations: Amman at Suweimah, Ghor Mazra'a and the APC and Ghor Feifa and Khanzeira area. The long‐term ability of the ISGP in meeting the different water demands can be assessed against the seasonality of the existing surface water system (Wadi Mujib, Wadi Wala and Wadi Tannur). It is not sufficient to consider just the seasonal averaged quantities of water inflows and precipitation and make decisions based on them. Efficient management has to consider the combined effect of dry and wet periods on the intermediate and long‐terms in order to obtain an accurate assessment of the system water deficits. The management model used the monthly flows (1977‐1999) to optimally find the monthly water allocation between the different demand sectors. The statistical averages of the resulting long‐term deficits were used to assess the long‐term system efficiency in meeting the water demands. Frequency analysis was also used to examine the annual water deficits at the different demand areas and estimate the probability of occurrence of the years with high‐water deficits.</p>
</list-item>
<list-item><label>2. </label>
<p>The evaluation of the energy requirements (due to pumping) and the associated costs. As discussed later, there will be energy requirements mainly due to pumping the released water from the reservoirs to the transfer tanks. The developed management model will quantify such required energy in order to estimate the long‐term operational costs for the ISGP. Hence, based on the optimal water allocation the energy requirements for pumping are estimated, this can be beneficial to the decision makers in order to evaluate the running cost for the ISGP.</p>
</list-item>
<list-item><label>3. </label>
<p>The developed management model can assess the effect of the reservoir system on the Dead Sea (environmental issues). This can be done through estimating the amounts of water inflows from the wadis (Mujib, Wala and Zara‐Main springs) that will not now replenish the Dead Sea; the building of the reservoir system will cause the water in the above mentioned wadis to be controlled by the reservoirs and therefore not reaching the Dead Sea. As it is known, the Dead Sea is being depleted significantly on a yearly basis as the losses due to evaporation are much more than the water inflows from the side wadis to the Dead Sea. The Depletion of the Dead Sea can cause groundwater quality and quantity problems in the adjacent aquifers to the Dead Sea. Furthermore, the Dead Sea is an important tourism area for all the surrounding riparian countries, thus it should be in favor of these countries to environmentally protect it. More discussion on this is provided in the assessment and future work sections (fifth and sixth sections, respectively).</p>
</list-item>
</list>
The first two points are addressed in section five in the assessments within the framework of the considered scenarios.</p>
<p>Tourism is another major sector that will also benefit from the ISGP. The proposed tourism projects (hotels, resorts, parks, treatment spas, etc.) on the Dead Sea are estimated to cost more than JD700 million. Such development will require considerable supply of water that will be provided mainly from the ISGP through the Northern Conveyor. Therefore, it is important on the long run to assess the ability of this project to meet the water demands for such development on the Dead Sea. Using the developed management model, the ISGP can be assessed to quantify its ability in meeting the required water demands.</p>
</sec>
<sec><title>Model formulation, inputs and outputs</title>
<sec><title>Mathematical formulation of the management problem</title>
<p>The water resources management problem for the ISGP can be mathematically stated as follows: <xref ref-type="fig" rid="F_3330090305001">Equation 1</xref>
Subject to: system dynamics: state equations (<xref ref-type="bibr" rid="b29">Yao and Georgakakos, 2001</xref>
): <xref ref-type="fig" rid="F_3330090305002">Equation 2</xref>
<xref ref-type="fig" rid="F_3330090305003">Equation 3</xref>
<xref ref-type="fig" rid="F_3330090305004">Equation 4</xref>
System constraints: <xref ref-type="fig" rid="F_3330090305005">Equation 5</xref>
<xref ref-type="fig" rid="F_3330090305006">Equation 6</xref>
<xref ref-type="fig" rid="F_3330090305007">Equation 7</xref>
<xref ref-type="fig" rid="F_3330090305008">Equation 8</xref>
<xref ref-type="fig" rid="F_3330090305009">Equation 9</xref>
<xref ref-type="fig" rid="F_3330090305010">Equation 10</xref>
where <italic>g</italic>
<sub>1</sub>
‐<italic>g</italic>
<sub>20</sub>
in equation (1) are penalty terms that are associated with weighing factors based on the water policies that are most important for the decision makers. More specifically:<list list-type="bullet"><list-item><label>• </label>
<p><italic>g</italic>
<sub>1</sub>
, <italic>g</italic>
<sub>2</sub>
and <italic>g</italic>
<sub>3</sub>
: nonlinear, non‐quadratic penalty terms (barrier functions) to penalize storage state variables for Mujib, Wala and Tannur dams, respectively, if their storages are less than the minimum storages or higher than the maximum storages.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>4</sub>
, <italic>g</italic>
<sub>5</sub>
and <italic>g</italic>
<sub>6</sub>
: quadratic terms for reservoirs releases for Mujib, Wala and Tannur dams, respectively, to meet various release targets. For example, if Mujib Dam is to follow a certain target sequence, then <italic>g</italic>
<sub>4</sub>
(<italic>u</italic>
<sub>Mujib</sub>
(<italic>k</italic>
))=(<italic>u</italic>
<sub>Mujib</sub>
(<italic>k</italic>
)−<italic>u</italic>
<sub>Mujib_Target</sub>
(<italic>k</italic>
))<sup>2</sup>
where <italic>u</italic>
<sub>Mujib_Target</sub>
(<italic>k</italic>
) is the target values for the Mujib Dam release for month (<italic>k</italic>
), and (<italic>u</italic>
<sub>Mujib</sub>
(<italic>k</italic>
)) is the release in Mujib Dam for the same month.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>7</sub>
, <italic>g</italic>
<sub>8</sub>
, and <italic>g</italic>
<sub>9</sub>
: quadratic terms to meet the different water demands at Suweimah, Mazra'a‐APC and Feifa‐Khanzeira areas, respectively.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>10</sub>
, <italic>g</italic>
<sub>11</sub>
, and <italic>g</italic>
<sub>12</sub>
: quadratic terms to coordinate reservoirs storages for Mujib and Wala dams, Mujib and Tannur dams and Wala and Tannur dams, respectively. For example, to coordinate storages between Mujib and Wala dams: <xref ref-type="fig" rid="F_3330090305011">Equation 11</xref>
where (<italic>S</italic>
<sub>Mujib</sub>
(<italic>k</italic>
)) is the storage in Mujib Dam at month (<italic>k</italic>
), (<italic>S</italic>
<sub>Mujib–min</sub>
) is the minimum storage capacity for Mujib Dam, and (<italic>S</italic>
<sub>Mujib–max</sub>
) is the maximum storage capacity for Mujib Dam. Similar explanations follow for the Wala Dam terms.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>13</sub>
and <italic>g</italic>
<sub>14</sub>
: quadratic terms to represent the energy requirements for pumping at the New Zara and Mazra'a tanks, respectively.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>15</sub>
, <italic>g</italic>
<sub>16</sub>
and <italic>g</italic>
<sub>17</sub>
: quadratic terms for reservoirs storages at Mujib, Wala and Tannur dams, respectively, to follow various storage targets. For example, if Mujib Dam storage is to follow a certain target sequence, then <italic>g</italic>
<sub>15</sub>
(<italic>S</italic>
<sub>Mujib</sub>
(<italic>k</italic>
))=(<italic>S</italic>
<sub>Mujib</sub>
(<italic>k</italic>
)−<italic>S</italic>
<sub>Mujib_Target</sub>
(<italic>k</italic>
))<sup>2</sup>
where <italic>S</italic>
<sub>Mujib_Target</sub>
(<italic>k</italic>
) is the target values for the Mujib Dam storage at month (<italic>k</italic>
) and <italic>S</italic>
<sub>Mujib</sub>
(<italic>k</italic>
) is the storage in Mujib Dam for the same month.</p>
</list-item>
<list-item><label>• </label>
<p><italic>g</italic>
<sub>18</sub>
, <italic>g</italic>
<sub>19</sub>
and <italic>g</italic>
<sub>20</sub>
: quadratic terms for reservoirs storages at Mujib, Wala and Tannur dams, respectively, to follow various storage targets at the end of management horizon (time step <italic>N</italic>
).</p>
</list-item>
<list-item><label>• </label>
<p><italic>S</italic>
(<italic>k</italic>
+1)<sub>Mujib</sub>
: the storage at the Mujib Dam at the beginning of time step (<italic>k</italic>
+1).</p>
</list-item>
<list-item><label>• </label>
<p><italic>u</italic>
(<italic>k</italic>
)<sub>Mujib</sub>
: the release from the Mujib Dam during time step (<italic>k</italic>
).</p>
</list-item>
<list-item><label>• </label>
<p><italic>e</italic>
(<italic>k</italic>
)<sub>Mujib</sub>
: the evaporation from the Mujib Dam during time step (<italic>k</italic>
) function of the storage.</p>
</list-item>
<list-item><label>• </label>
<p><italic>w</italic>
(<italic>k</italic>
)<sub>wadi‐Mujib</sub>
: the inflow to Mujib Dam during time step (<italic>k</italic>
).</p>
</list-item>
<list-item><label>• </label>
<p><italic>α</italic>
, <italic>β</italic>
, <italic>γ</italic>
, <italic>ϵ</italic>
, <italic>θ</italic>
, <italic>χ</italic>
and <italic>μ</italic>
: constant weights to provide priorities to the different terms in the objective function.</p>
</list-item>
<list-item><label>• </label>
<p><italic>σ</italic>
: a constant which is based on the ratio between the demands directly north to the Mujib Diversion Weir to those south of the weir.</p>
</list-item>
</list>
All other remaining terms are defined based on the above terms.</p>
<p>The above formulation is a nonlinear dynamical optimization problem that has the following components, the system:<list list-type="bullet"><list-item><label>• </label>
<p>objective function with different terms that include the control and state variables as in equation (1);</p>
</list-item>
<list-item><label>• </label>
<p>state variables dynamical equations (equations (2)‐(4)); and</p>
</list-item>
<list-item><label>• </label>
<p>constraints (control and state variables constraints) (equations (5)‐(10)).</p>
</list-item>
</list>
The management problem is solved using typical DP approach through discretization of the storage and release variables (<xref ref-type="bibr" rid="b3">Bellman and Dreyfus, 1962</xref>
). The reason for using DP is due to the low dimensionality of the surface water system in this study; the number of state variables are only three (reservoir storages of Mujib, Wala and Tannur dams). Furthermore, DP is also suitable for nonlinear systems (in the objective function, system dynamics, or system constraints).</p>
</sec>
<sec><title>Model inputs and outputs</title>
<p><xref ref-type="fig" rid="F_3330090305022">Table III</xref>
shows model input and out puts for the assessment period January 1977‐December 1999. Model inputs were provided by the MWI in Jordan.</p>
<p>Frequency curves indicate the magnitude of the annual deficits and can be used as a criterion to compare the system performance for different management scenarios.</p>
</sec>
</sec>
<sec><title>Assessments</title>
<sec><title>Scenario definition</title>
<p>The ISGP DSS model was used herein to assess four scenarios, each of which has one or two runs. The first scenario represents the baseline case scenario against which the remaining three scenarios were compared with. The baseline scenario includes all system components that would potentially be part of any other scenario. Therefore, for any proposed scenario any changes were simply modification to the components in the baseline scenario. The second scenario represented the predevelopment conditions where Wadi Mujib, Wadi Wala and Wadi Tannur dams are not operating. The remaining scenarios considered the effect of demand increases and the water transfer to Tannur Dam. <xref ref-type="fig" rid="F_3330090305023">Table IV</xref>
summarizes the main components of each scenario a detailed description follows.</p>
</sec>
<sec><title>Baseline case</title>
<p>This scenario included all the system elements, and therefore assesses the ability of the system in meeting the different demands. It has the following main characteristics:<list list-type="bullet"><list-item><label>• </label>
<p>Wadi Mujib, Wadi Wala and Wadi Tannur dams are operating;</p>
</list-item>
<list-item><label>• </label>
<p>water demands are similar to existing demands; and</p>
</list-item>
<list-item><label>• </label>
<p>water transfer from Ghor Mazra'a area to Tannur Dam to assist in meeting the water demands of Ghor Feifa and Khanzeira.</p>
</list-item>
</list>
</p>
</sec>
<sec><title>Predevelopment conditions</title>
<p>This scenario assumed that there is no development at the Southern Ghor Area, specifically, that the Mujib, Wala and Tannur dams, and the conveyors did not exist. Therefore, this scenario assessed the benefits of the constructed/proposed storage and conveyor facilities in reducing the water deficits. It has the following main characteristics:<list list-type="bullet"><list-item><label>• </label>
<p>Wadi Mujib, Wadi Wala and Wadi Tannur dams are not operating;</p>
</list-item>
<list-item><label>• </label>
<p>water demands are similar to existing demands; and</p>
</list-item>
<list-item><label>• </label>
<p>no water transfer from Ghor Mazra'a area to Tannur Dam.</p>
</list-item>
</list>
</p>
</sec>
<sec><title>No water transfer to Tannur Dam case</title>
<p>This scenario assessed the benefits of the proposed water transfer to Tannur Dam on the system. It has the following main characteristics:<list list-type="bullet"><list-item><label>• </label>
<p>Wadi Mujib, Wadi Wala and Wadi Tannur dams are operating;</p>
</list-item>
<list-item><label>• </label>
<p>water demands are similar to existing demands; and</p>
</list-item>
<list-item><label>• </label>
<p>no water transfer from Ghor Mazra'a area to Tannur Dam.</p>
</list-item>
</list>
</p>
</sec>
<sec><title>Increased demands case</title>
<p>This scenario assessed the effect of increased future demands on the system water deficits. It has the following main characteristics:<list list-type="bullet"><list-item><label>• </label>
<p>Wadi Mujib, Wadi Wala and Wadi Tannur dams are operating;</p>
</list-item>
<list-item><label>• </label>
<p>water demands increase by 25 and 50 per cent as compared to existing demands; and</p>
</list-item>
<list-item><label>• </label>
<p>Water transfer from Ghor Mazra'a area to Tannur Dam.</p>
</list-item>
</list>
</p>
</sec>
</sec>
<sec><title>Scenario assessments</title>
<p>The ISGP water resources system has multiple objectives. For this reason, several quantities were used to evaluate each scenario. Specifically, the following performance criteria were used in this assessment:<list list-type="bullet"><list-item><label>• </label>
<p>water deficits at the Amman‐Suweimah node;</p>
</list-item>
<list-item><label>• </label>
<p>irrigation and industrial deficits at the APC and Ghor Mazra'a area;</p>
</list-item>
<list-item><label>• </label>
<p>irrigation deficits at Ghor Feifa and Khanzeira area;</p>
</list-item>
<list-item><label>• </label>
<p>total deficits (agricultural, municipal and industrial);</p>
</list-item>
<list-item><label>• </label>
<p>water transfer to Tannur Dam; and</p>
</list-item>
<list-item><label>• </label>
<p>energy requirements for pumping.</p>
</list-item>
</list>
In order to compare between different scenarios, average annual values were computed for the previous mentioned assessment criteria over the 23 years of management horizon. <xref ref-type="fig" rid="F_3330090305024">Table V</xref>
shows the average annual values of the assessment criteria for the four scenarios (the total deficits is not shown due to lack of space, but intuitively the total deficits is the sum of the individual deficits), the percentage quantities in the table represent percent change from the baseline run. This table will be discussed with more details when discussing each scenario individually.</p>
<p>It is important to note that the deficits estimated herein are the difference of the actual demand and the water that can be provided mainly by the surface water resources system. In reality, groundwater is used on a lager scale to supplement the surface water supply and meet the demand. However, pumping is costly and some of the groundwater aquifers are not replenishable. Thus, by minimizing deficits one also minimizes the use of groundwater resources.</p>
<p><xref ref-type="fig" rid="F_3330090305016">Figure 5</xref>
shows a graphical comparison between all scenarios for the different criteria used in the comparisons.</p>
<sec><title>Baseline case results</title>
<p>Detailed results from the baseline run include the following outputs for the assessment period January 1977‐December 1999:<list list-type="bullet"><list-item><label>• </label>
<p>Storage and release sequences of Wadi Mujib, Wadi Wala and Wadi Tannur dams.</p>
</list-item>
<list-item><label>• </label>
<p>Monthly water deficits sequences at Suweimah (Amman), Mazra'a and APC and Ghor Feifa and Khanzeira.</p>
</list-item>
<list-item><label>• </label>
<p>Monthly energy requirements for pumping at the New Zara and Mazra'a tanks and the associated total pumping cost.</p>
</list-item>
<list-item><label>• </label>
<p>Annual deficits frequency curves in Suweimah (Amman), Mazra'a and APC and Ghor Feifa and Khanzeira. Also, annual frequency curve for water transfer to Tannur Dam.</p>
</list-item>
</list>
It is shown from <xref ref-type="fig" rid="F_3330090305024">Table V</xref>
and <xref ref-type="fig" rid="F_3330090305016">Figure 5</xref>
that on the average there are deficits in all demand areas; the largest deficit was in the Suweimah demand node with average annual deficit of 4.25 MCM per year. The average annual deficits in the APC‐Mazra'a and Feifa‐Khanzeira demand areas were 0.51 and 0.96 MCM per year, respectively. The baseline scenario showed that the Tannur Dam would benefit from water transfer through the proposed conveyor. <xref ref-type="fig" rid="F_3330090305024">Table V</xref>
and <xref ref-type="fig" rid="F_3330090305016">Figure 5</xref>
shows that the average annual water to be transferred for the Tannur Dam through the conveyor was around 5 MCM per year. As for the energy requirements, the baseline case showed that average annual energy required for pumping is 34.3 and 17.6 × 10<sup>6</sup>
million Joules per year at the New Zara and the Mazra'a tanks, respectively. Hence, based on the tariffs shown in the world web site for the Jordanian National Electric Power Company, the average annual cost of pumping was about JD578000 (equivalent to about US$770,000). This underpins the considerable operational costs to the ISGP associated with pumping.</p>
<p>More quantitative discussion on the baseline run will be carried on later as the results from the three scenarios are discussed and compared with the baseline run. <xref ref-type="fig" rid="F_3330090305017">Figure 6</xref>
shows the important point of coordinated management for all the system components as they try to meet the different water demands. More specifically, the graphs of the storage and release sequences for the reservoirs depict similar fluctuations during wet and dry periods. During wet periods, the reservoirs release enough water to meet the system water demands, storing any additional flooding water. If the reservoirs reach their maximum storage capacities then any extra flooding water is released through their spillways. During dry periods, the stored water from floods will be used to meet the water demands. Hence, reservoir releases are coordinated to meet the system water demands jointly and not on the expense of depleting one with respect to the others.</p>
<p><xref ref-type="fig" rid="F_3330090305018">Figure 7</xref>
shows that the annual deficits in the Suweimah demand node are larger than the average annual deficits at the remaining two demand areas almost 70 per cent of the time. However, in the remaining 30 per cent of the time annual deficits at all demand areas are equivalent and equal to zero.</p>
<p>Also, Tannur Dam transfer annual frequency curve shows that almost 80 per cent of the time the annual transfer is not less than 3.4 MCM per year which is a good indication of the validity of this transfer in reducing the deficits for the Feifa and Khanzera demand areas.</p>
</sec>
<sec><title>Predevelopment conditions results</title>
<p>The purpose of this scenario is to evaluate the benefits of adding Wadi Mujib, Wadi Wala and Wadi Tannur dams to the system before any storage or conveying facilities were constructed:<list list-type="bullet"><list-item><label>• </label>
<p>Average annual municipal water deficits – over 23 years – at Suweimah have increased by 169 per cent as compared to the baseline case. The average annual industrial and irrigation water deficits at APC and Mazra'a increased by 335 per cent as compared to the baseline case. Finally, the average annual irrigation water deficits at Feifa and Khanzeira increased by 601 per cent as compared to the baseline case.</p>
</list-item>
</list>
The results of this scenario showed the importance of adding Wadi Mujib, Wadi Wala and Wadi Tannur dams to the Jordanian water system. The resulting deficits have been reduced significantly.</p>
</sec>
<sec><title>No transfer to Tannur Dam results</title>
<p>The purpose of this scenario is to evaluate the benefit of adding a water transfer to the Tannur Dam from the Mazra'a area as an extension to the Southern Conveyor. The water of this transfer has to be provided from Wadi Mujib and Wadi Wala dams:<list list-type="bullet"><list-item><label>• </label>
<p>The impact on water deficits was almost only at Feifa and Khanzeira irrigation areas, the average annual water deficits have increased by 259 per cent as compared to the baseline case.</p>
</list-item>
<list-item><label>• </label>
<p>There was almost no effect on the energy requirements for pumping at the New Zara and Mazra'a tanks.</p>
</list-item>
</list>
This scenario showed the importance of the water transfer to the Tannur Dam in terms of reducing the water deficits at Feifa and Khanzeira irrigation areas without affecting the deficits at Suweimah and Mazra'a‐APC. Furthermore, the increase in the energy requirements for pumping was not significant at all indicating more credit to the construction of this transfer.</p>
</sec>
<sec><title>Increased demands results</title>
<p>The purpose of this scenario is to evaluate the effect of increasing the water demands on the system. It is very likely that within few years the municipal, industrial and irrigational water demands will increase causing the pressure on the Southern Ghor Project to increase. The results of this scenario show:<list list-type="bullet"><list-item><label>• </label>
<p>Average annual municipal water deficits at Suweimah have increased by 150 and 311 per cent for the 25 and 50 per cent of demand increase, respectively, as compared to the baseline case. The average annual industrial and irrigation water deficits at APC and Mazra'a increased by 301 and 694 per cent for the 25 and 50 per cent, respectively, as compared to the baseline case. Finally, the average annual irrigation water deficits at Feifa and Khanzeira increased by 150 and 356 per cent for the 25 and 50 per cent, respectively, as compared to the baseline case.</p>
</list-item>
<list-item><label>• </label>
<p>The average annual water transfer to the Tannur Dam was reduced by 16 and 27 per cent for the 25 and 50 per cent of demand increase, respectively, as compared to the baseline case.</p>
</list-item>
<list-item><label>• </label>
<p>The average annual energy requirements for the pumping at the New Zara Tank increased by 4 and 7 per cent for the 25 and 50 per cent of demand increase, respectively, as compared to the baseline case.</p>
</list-item>
<list-item><label>• </label>
<p>The average annual energy requirements for the pumping at the Mazra'a Tank increased by 4 and 6 per cent for the 25 and 50 per cent of demand increase, respectively, as compared to the baseline case.</p>
</list-item>
<list-item><label>• </label>
<p>The average annual total pumping cost for the 25 and 50 per cent of demand increases are about $803,000 and 823,000, respectively, (about 4 and 7 per cent increase with respect to baseline case).</p>
</list-item>
</list>
The results of this scenario showed that by increasing the water demands the resulting deficits were affected significantly more than any other criterion. For example, when the demands where increased by 25 and 50 per cent, the resulting deficits increased by more than 150 per cent and up to 694 per cent at some areas. The average annual water transfer to the Tannur Dam was reduced as expected since Wadi Mujib and Wadi Wala had to supply more water at the demand areas in Suweimah and Ghor Mazra'a‐APC.</p>
</sec>
<sec><title>Energy requirements</title>
<p>In the following scenarios: baseline case, no transfer to Tannur Dam, and the increased demands, the changes in the energy requirements were small, maximum of about 4‐6 per cent for the increased demand scenarios (<xref ref-type="fig" rid="F_3330090305016">Figure 5</xref>
). This is because the required energy for pumping is function of the water released by the reservoirs to meet the different demands. However, as the system suffers from deficits in all the scenarios considered, this puts the reservoirs under pressure to release water at their maximum capacity to meet the different demands. Therefore, with such small variability in the reservoirs releases – and hence small variability in water pumped to the collection tanks (New Zara and Mazra'a tanks) – the resulting pumping energy requirements were also similar.</p>
</sec>
<sec><title>Environmental effects on the Dead Sea</title>
<p>Comprehensive environmental assessment of the effects on the Dead Sea from the ISGP is out of the scope of this paper. However, from a water resources perspective the average annual volume of water that will be tapped by the ISGP – and therefore will not reach the Dead Sea – can be estimated. The average annual water tapped is equivalent to the average annual water supplied to Ghor Mazra'a area and the APC, and to Amman (Suweimah). Ghor Feifa and Khanzeira demand areas were excluded as they are mainly supplied by Tannur Dam south of the Dead Sea. Using the baseline case, this amount equals on the average to about 60 MCM per year.</p>
<p>It is true that the Dead Sea is replenished through major flooding events as shown in the <xref ref-type="fig" rid="F_3330090305019">Figure 8</xref>
from the baseline case showing the releases of the reservoirs (February 1992, March 1988, February 1985, etc.). However, these flooding events are not frequents enough to overcome the losses due to the high rates of evaporation.</p>
<p>The depletion of the Dead Sea will adversely affect the adjacent groundwater aquifers. As the head differences between the Dead Sea and these aquifers increase the aquifer heads will continue to deplete due to the increased leakage towards the Dead Sea.</p>
</sec>
</sec>
<sec><title>Conclusion and recommendations</title>
<p>Many water projects are being planned and constructed in Jordan to meet the continuously growing water demands. There is a need to use decision‐support models for water resources management in the country. The currently used management tools are based on fragmented analysis to individual water resources system components, this can lead to misleading planning and on the intermediate/long run to considerable decision problems.</p>
<p>This paper described a monthly model for water resources management in the Southern Ghor Project and its use for the assessment of various development options. The methodology approach of the management model in principle incorporated the hydrological inputs and system characteristics of the ISGP, the dynamics of the storage facilities and water transfers, and optimization algorithms to find the optimal system performance for the management horizon. The optimization algorithm used is DP, and the management horizon is 23 years on a monthly basis (1977‐1999).</p>
<p>Results from the management model showed that the baseline case – which included all the system elements – reduced the water deficits significantly as compared to the predevelopment conditions. This was due to storing the floods during wet periods to be used in a coordinated management among the three storage facilities. The model showed that the deficits range from 169 to 600 per cent.</p>
<p>The transfer to the Tannur Dam reduced the resulting deficits in the Feifa and Khanzeira agricultural areas without affecting the energy requirements for pumping and more importantly without affecting the water deficits in Ghor Mazra'a and APC or in the Suweimah demand node.</p>
<p>Increased demand scenario showed the importance of finding new water projects to supplement the Southern Ghor Area in the future in order to meet the increasing water demands. The new projects may be related to local groundwater resources in the area or any water transfer from any regional projects like the Disi Conveyor (<xref ref-type="bibr" rid="b21">MWI, 2000</xref>
) or the Red Sea – Dead Sea Canal Project (MWI web page: <ext-link ext-link-type="uri" xlink:href="http://www.mwi.gov.jo/home/homepage.aspx">www.mwi.gov.jo/home/homepage.aspx</ext-link>
). Also another option would be industrial and wastewater reuse projects, like an example for water used in the APC, this water can be treated and then used again for agricultural and industrial purposes.</p>
<sec><title>Model limitations</title>
<p>The developed model cannot be used for operational purposes as it is an assessment model. Operational models are short‐term management models (daily or weekly) that are associated with hydrological forecast component. Forecast models require lots of information in order to produce predictions for future inflows. In an operational model inflow forecast realizations are generated, then based on the statistical inferences of the inflow realizations the optimal reservoir releases and hence storage trajectories are found for the management period. The reservoir storages are then updated based on the actual inflows that materialized and the previous steps of inflow forecasting and reservoir releases are repeated again for the next management horizon (open‐loop feedback management procedure).</p>
<p>This management model is a first step towards the development of a more comprehensive DSS. Future work can be extended in several ways:<list list-type="bullet"><list-item><label>• </label>
<p><italic>Updating the management model.</italic>
The developed model can be updated with respect to the period beyond 1999 as soon as data gaps are provided by the MWI in Jordan. Interpolation and estimation techniques can be used to estimate the missing data gaps. However, caution is advised in order to make sure that the estimated values make sense with respect to the other observed data and are within the range of confidence required.</p>
</list-item>
<list-item><label>• </label>
<p><italic>Watershed modeling.</italic>
The model used a deterministic description of the system inflows over the assessment horizon. This assumption is acceptable for the purposes of this assessment. However, use of the model in an operational setting requires the quantification of hydrologic uncertainty and the use of forecasting models. More specifically, a hydrologic model to forecast the inflows for Wadi Mujib, Wadi Wala and Wadi Tannur can be developed and included in the DSS if the model to be used for operational purposes.</p>
</list-item>
<list-item><label>• </label>
<p><italic>Dead Sea depletion.</italic>
Originally, Wadi Mujib, Wadi Wala and the Zara‐Main springs used to replenish the Dead Sea especially during flood periods. However, due to the new storage and conveyor facilities this replenishment is reduced significantly. The developed management model can assess the effect of the storage facilities on the Dead Sea, any future management schemes should take this into consideration. Like an example, the model could include a penalty term to allow for minimum flows to the Dead Sea based on certain environmental standards related specifically to the Dead Sea. Although these minimum flows would increase the water deficits but it would help in the replenishment of the Dead Sea.</p>
</list-item>
<list-item><label>• </label>
<p><italic>Aquifer modeling.</italic>
Aquifers represent a vital asset for Jordan. Groundwater pumping is used extensively to supplement surface water supplies and mitigate shortages. However, excessive pumping has adverse consequences including saline water intrusion to aquifers. A comprehensive surface water‐groundwater management model would coordinate the operation and use of all major water aquifers and storage elements within the Southern Ghor Area and ultimately in Jordan.</p>
</list-item>
</list>
</p>
</sec>
</sec>
<sec><fig position="float" id="F_3330090305001"><caption><p>Equation 1</p>
</caption>
<graphic xlink:href="3330090305001.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305002"><caption><p>Equation 2</p>
</caption>
<graphic xlink:href="3330090305002.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305003"><caption><p>Equation 3</p>
</caption>
<graphic xlink:href="3330090305003.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305004"><caption><p>Equation 4</p>
</caption>
<graphic xlink:href="3330090305004.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305005"><caption><p>Equation 5</p>
</caption>
<graphic xlink:href="3330090305005.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305006"><caption><p>Equation 6</p>
</caption>
<graphic xlink:href="3330090305006.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305007"><caption><p>Equation 7</p>
</caption>
<graphic xlink:href="3330090305007.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305008"><caption><p>Equation 8</p>
</caption>
<graphic xlink:href="3330090305008.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305009"><caption><p>Equation 9</p>
</caption>
<graphic xlink:href="3330090305009.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305010"><caption><p>Equation 10</p>
</caption>
<graphic xlink:href="3330090305010.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305011"><caption><p>Equation 11</p>
</caption>
<graphic xlink:href="3330090305011.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305012"><label><bold>Figure 1<x> </x>
</bold>
</label>
<caption><p> Water resources DSS general components</p>
</caption>
<graphic xlink:href="3330090305012.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305013"><label><bold>Figure 2<x> </x>
</bold>
</label>
<caption><p> The ISGP site map</p>
</caption>
<graphic xlink:href="3330090305013.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305014"><label><bold>Figure 3<x> </x>
</bold>
</label>
<caption><p> Side wadis monthly inflows</p>
</caption>
<graphic xlink:href="3330090305014.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305015"><label><bold>Figure 4<x> </x>
</bold>
</label>
<caption><p> The ISGP system schematic</p>
</caption>
<graphic xlink:href="3330090305015.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305016"><label><bold>Figure 5<x> </x>
</bold>
</label>
<caption><p> Average annual criteria values for all scenarios</p>
</caption>
<graphic xlink:href="3330090305016.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305017"><label><bold>Figure 6<x> </x>
</bold>
</label>
<caption><p> Monthly storage sequences</p>
</caption>
<graphic xlink:href="3330090305017.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305018"><label><bold>Figure 7<x> </x>
</bold>
</label>
<caption><p> Annual frequency curves</p>
</caption>
<graphic xlink:href="3330090305018.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305019"><label><bold>Figure 8<x> </x>
</bold>
</label>
<caption><p> Monthly release sequences</p>
</caption>
<graphic xlink:href="3330090305019.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305020"><label><bold>Table I<x> </x>
</bold>
</label>
<caption><p> Reservoirs characteristics</p>
</caption>
<graphic xlink:href="3330090305020.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305021"><label><bold>Table II<x> </x>
</bold>
</label>
<caption><p> Conveyors characteristics</p>
</caption>
<graphic xlink:href="3330090305021.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305022"><label><bold>Table III<x> </x>
</bold>
</label>
<caption><p> Model inputs and outputs</p>
</caption>
<graphic xlink:href="3330090305022.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305023"><label><bold>Table IV<x> </x>
</bold>
</label>
<caption><p> Scenario definition</p>
</caption>
<graphic xlink:href="3330090305023.tif"></graphic>
</fig>
</sec>
<sec><fig position="float" id="F_3330090305024"><label><bold>Table V<x> </x>
</bold>
</label>
<caption><p> Average annual criteria quantities for all scenarios and their percentage change from baseline case</p>
</caption>
<graphic xlink:href="3330090305024.tif"></graphic>
</fig>
</sec>
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<app-group><app id="APP1"><title>Corresponding author</title>
<p>Malek Abu Rumman can be contacted at: malek_rumman@yahoo.com</p>
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<name type="personal"><namePart type="given">Bashar</namePart>
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<abstract>Purpose The purpose of this paper is to assess the longterm ability of the Integrated Southern Ghor Project ISGP to meet the required water demands, assess the resulting energy requirements, pumping costs, water transfers, benefits of the current system with respect to predevelopment conditions and effect of projected water demands increase on the resulting water deficits. Designmethodologyapproach A surface water resources management model is developed using dynamic programming. The model inputs are the hydrological inflows from the different wadis in the project area, reservoirs characteristics and evaporation rates, system water demands. The model outputs are water deficits at the different demand areas, reservoirs storage and release sequences, water transfers and energy requirements and the associated costs. The average annual values of different performance criteria with the annual frequency curves are used to evaluate the implications of different water scenarios on the ISGP. Findings The results show the efficiency of the ISGP model in reducing the water deficits in the demand areas as compared to predevelopment conditions. Increased demand scenario showed the importance of finding new water projects to supplement the Southern Ghor Area in the future in order to meet the increasing water demands. The proposed water transfer will reduce the resulting deficits at the agricultural areas without the expenses of increasing the water deficits at other demand areas. The application of this model is expected to enhance decision making regarding water policies in Jordan. Originalityvalue This paper provides critical quantitative information to decision makers in Jordan about the potential of the different storage facilities and proposed transfers in meeting the required water demands in the Southern Ghor Project and assesses the required energy for that. This can help decision makers to have a holistic view about the expected water deficits in the area and therefore assist them in determining the areas impacted most and what alternative solution to use. The paper also shows the importance of using optimal controlmanagement models to support water resources decision making in Jordan.</abstract>
<subject><genre>keywords</genre>
<topic>Water retention and flow works</topic>
<topic>Modelling</topic>
<topic>Reservoirs</topic>
<topic>Dams</topic>
<topic>Decision support systems</topic>
<topic>Jordan</topic>
</subject>
<relatedItem type="host"><titleInfo><title>Construction Innovation</title>
</titleInfo>
<genre type="journal">journal</genre>
<subject><genre>Emerald Subject Group</genre>
<topic authority="SubjectCodesPrimary" authorityURI="cat-PMBE">Property management & built environment</topic>
<topic authority="SubjectCodesSecondary" authorityURI="cat-BCN">Building & construction</topic>
</subject>
<identifier type="ISSN">1471-4175</identifier>
<identifier type="PublisherID">ci</identifier>
<identifier type="DOI">10.1108/ci</identifier>
<part><date>2009</date>
<detail type="volume"><caption>vol.</caption>
<number>9</number>
</detail>
<detail type="issue"><caption>no.</caption>
<number>3</number>
</detail>
<extent unit="pages"><start>298</start>
<end>322</end>
</extent>
</part>
</relatedItem>
<identifier type="istex">B2E94B04459BA04E0681053E7F0B8877A52BB08B</identifier>
<identifier type="DOI">10.1108/14714170910973510</identifier>
<identifier type="filenameID">3330090305</identifier>
<identifier type="original-pdf">3330090305.pdf</identifier>
<identifier type="href">14714170910973510.pdf</identifier>
<accessCondition type="use and reproduction" contentType="copyright">© Emerald Group Publishing Limited</accessCondition>
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