Introduction

Due to the severe shortage of water and increasing demand in the world, the role of managing supply and demand has become vital [3, 7]. Vaghefi et al. [46] and Kuhn et al. [26] have pointed out that Iran is a country in arid and semi-arid part of the world and due to population growth, urbanization and development of agricultural and industrial sectors demand for water has been increasing. Continued rise in demand will increase the gap between supply and demand in the future. Thiam et al. [43] and Green et al. [17] have pointed out that due to human interaction with nature and the involvement of numerous space-time variables, it is almost impossible to reach a solution in most cases consistent with the basic principle in the management of water resources [12, 15]. Therefore, it is necessary to choose an appropriate solution for each location according to the particular circumstances and this solution should also be corrected and optimized over time. In proper water management, it is necessary to first understand the natural behavior of the hydrologic system for the management of hydrological events [17, 25]. In the past decades, with the growth of software capabilities, computer models have been developed, which in turn have been instrumental in optimizing and simulating water resources with different components [38]. Using these models, water can be allocated at the catchment level between urban, agricultural, industrial, and environmental protection areas, creating the least problems in the present and future. Such models, which are known as Integrated Water Resources Management Models (IWRMs), take into account various hydrological events and integrate them with technical, economic, environmental, and social issues for water resources management at the catchment area [4, 14, 46]. In recent years, the use of computer models for the management of water resources has become common, for example WEAP, RIBASIM, MIKEBASI, WBALMO, and MODSIM are noted as examples of their application [4, 11, 15, 22]. Among the existing models, the WEAP model has been popular, due to its ability to combine important processes affecting the natural and human systems of water resources management in the river basin [39]. WEAP considers all water sources in a basin for sustainable development. Adebola et al. [1] mentioned that for accomplishing water level reduction in the Aprasing River Basin, water use in the USA used the Mod flow groundwater model and evaluated the effect of water allocation using the WEAP model. The WEAP was used in the Olifants basin by Thiam et al. [43] for analysis, modeling, and scenario planning for water allocation. By applying management practices, 10, 20, and 30% reduction in water consumption were sought to compensate for lack of funding. Dubinsky and Karunanithi [14] in the Sacramento catchment adaptation project, which includes adaptation to environmental, climate, food, and natural changes, WEAP was used for development and assessment of adaptation strategies. The purpose of this study is to coordinate management practices with changes occurring in the catchment area, such as land use changes, to maximize the use of water resources.

Kuhn et al. [26] used WEAP to find the causes and types of future problems in the Nivashha Lake Basin in Kenya. Results indicated that the main problem was related to the agricultural sector, so that in some areas water allocation was much higher than the irrigation requirement, while in other areas the total needs were not provided. In order to improve the water allocation within the Dongh River basin in Vietnam, water allocation was examined using WEAP, from a comprehensive viewpoint, including economic efficiency [35]. The framework of this model is based on the type of water use (agriculture, industry, hydroelectricity, domestic, and environmental uses), the location of areas where water was usable, and the rules for prioritizing water in the basin. Under this framework, policies that can influence the prioritization and use of water included the basin and macroeconomic policies. Water quality management indexes were evaluated upstream of the Lithianian basin in Lebanon using WEAP and GIS models [43]. In order to allocate water, WEAP was used as a planning tool to minimize water conflict in Sacramento [14].

Tizro et al. [45] used WEAP in the Hamedan watersheds and the results showed that by changing cropping patterns or reducing the land area of agriculture, groundwater balance could be achieved.

In order to cope with water crisis and supplying water needs in arid lands, considering the needs of agriculture, drinking, and industry by simulation based on optimization using the WEAP and LINGO software in two current situations and the implementation of the plan with the average percentage of 6% annual deficit for different scenarios provided an acceptable water utilization plan [48]. Using monthly modeling of water resources using the WEAP model, the effect of water transfer between the Karoon basins was examined [9]. Results showed that the output of the Beheshtakad and Koohrang Rivers in the future, assuming that the development plans for water resources defined in the exploitation stage, will decrease by 27%, compared with the conditions for the development of the basin, up to 27%.

Dehghan et al. [12] used WEAP for planning the allocation of water resources for the purpose of transferring water at the Gorganroud area.

Tizro et al. [45] applied the WEAP model to analyze improvement in irrigation efficiency in the Hamedan basin. Also, Kishiwa et al. [23] used the WEAP model in the assessment of impacts of climate change on surface water for the present time for the Pangani River Basin in Tanzania.

In order to analyze ecological water demands in the Mara River Basin in Kenya, Metobwa et al. [31] used the WEAP model.

In addition, Slaughter and Mantel [40] and Tian et al. [44] used the WEAP model to analyze groundwater quality.

Considering water crisis and the importance of planning and managing water resources in the country in light of the lack of planning for water allocation in the future, introducing new models of climate change and socioeconomic conditions for water resource management tries to create a better understanding of water resources management by using the integrated water resources model and its integration with the variable-prediction model as well as socioeconomic parameters (such as population increase and agricultural productivity changes, etc.). Decision-making, consistent with the current and future corrective plans, can help with better water resource management. In this study, WEAP was used for planning and managing water resources. The basis of this software is the calculation of water balance, in which both water resources management and environmental management are considered. The WEAP management structure, using the scenarios in which it is written, illustrates the status of the future of water, which can include climate change impact, land use management, demand, setting, and planning for different sectors, including agriculture, industry, drinking, and environment in the Zayandeh Rud area.

Materials and Methods

Overview of Methodology

In WEAP, the regular scenario modeling effort contains three steps: (1) a Current Accounts year is selected to serve as the base year of the model, (2) a Reference scenario is established from the Current Accounts to simulate likely evolution of the system without intervention, and (3) “what-if” scenarios created to alter the “Reference Scenario” and evaluate the effects of changes in climate change/policies and/or technologies. The data used in modeling for current accounts is ranged for the period of 1973–2005. For allocation of available resources, a number of option tested by developing several scenarios and future water demands are projected. The WEAP software was used to evaluate the future water demands and future water resource management in the Zayandeh Rud River basin.

WEAP applications generally contain the following steps:

  • Problem definition including time frame, spatial boundary, system components, and configuration

  • Establishing the “current accounts,” which provides a snapshot of actual water demand, resources, and supplies for the system

  • Building scenarios based on different sets of future trends based on policies, technological development, and other factors that affect demand, supply, and hydrology

  • Evaluating the scenarios with regard to criteria such as adequacy of water resources, costs, benefits, and environmental impacts

The scenarios can address a broad range of “what if” questions, such as: What if population growth and climate change? What if irrigation techniques and crop patterns are altered? What if various demand management strategies are implemented?

WEAP model has two primary functions.

  • Simulation of natural hydrological processes (e.g., evapotranspiration, runoff, and infiltration) to enable assessment of the availability of water within a catchment

  • Simulation of anthropogenic activities superimposed on the natural system to influence water resources and their allocation (i.e., consumptive and non-consumptive water demands) to enable evaluation of the impact of human water use

Using Multi-Index Decision for water resource management, various challenges which occur in river basins in present and future time periods can be controlled. Therefore, after obtaining vulnerability factors for current conditions in the river basin, with using the multi-decision-making model for water management, multiviews of the future conditions with full ranges of uncertainties can be managed better. Also, it can help for future decision makers because probability of the future problems can be characterized and alternative strategies can be built [13, 22].

In this study, at first, the integrated water resource management model (WEAP) is used for present conditions (including the parameter of climate, hydrology, water demands, and policy situation) to show the current water management in the basin. Then, predicted data, including the parameter of climate change (e.g., precipitation, temperature, humidity, and evapotranspiration), water demands, policy factors (e.g., priority of water user and rules for water reuse), and social factors (e.g., population growth rates) for the future time period, were inserted into the WEAP model to display the possible future water management in the basin. If the value of water availability cannot cover the water demands for the future time period, then alternative strategies for adaptation water management are built as adaptation scenarios. The following sections explain the overview of the basin, structure of the WEAP model, data used for the integrated water resource management model (WEAP) for current and future time periods, and the possible adaptation scenarios for making better strategies and proper water management in the basin.

Figure 1 also shows the applied processes in integrated water resource management (WEAP) with using multi-index decision.

Fig. 1
figure 1

Applied processes in integrated water resource management (WEAP) with using multi-index decision

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Basin Studied

The study basin is one of the main basin districts of the desert, with an area of 41,548 km2, between 32° 10′ to 33° 40′ northern latitude and 50° 30′ to 53° 23′ eastern longitude. The geographical area is limited from the north of Salt Lake to the west of the Gulf of Oman and the Oman Sea and from the east of the Kavir-siyahkooh mountain range to the south of the Kavirirsirjan subzone. Among its important rivers, the Zayandeh Rud has a length of 405 km, Khoshkehrood River has a length of 165 km, Izodkhad has a length of 125 km, Segonbad has a length of 85 km, Kahrooye has a length of 60 km long, Dharar has a length of 52 km, Esfarian has a length 50 km, Tighezard has a length of 50 km, and Joshaghan has a length of 40 km. The catchment area covers parts of the provinces of Isfahan, Chaharmahal and Bakhtiari, Fars, and Yazd, with Isfahan Province having more than 83% and Yazd having less than 3.5%, the largest and the lowest shares, respectively. Figure 2 shows the scope of the study.

Fig. 2
figure 2

The area studied in the Zayandeh Rud Basin [19]

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Natural flows of the Zayandeh Rud River increase with the diversion of water from the deviant tunnels of the first and second Koohrang, which originates from the Koohrang River in Chaharmahal and Bakhtiari provinces. Because the average rainfall in the basin is less than 150 mm per year, the Zayandeh Rud Dam storage in Chadegan is provided by spring and winter runoff and released as a stream set in the river. The upstream parts of the basin cover less than 10% of the entire basin, which is mostly mountainous. The central and lower parts of the basin consist of sedimentary plains, with the most consuming agriculture (89%). Also, a large number of overflows and detours have been constructed along the river, thus water is drained for urban and industrial areas. The Zayandeh Rud basin ends in a natural swamp and gullous salts.

The components of this study include water resources and consumption points. Water resources in this area include surface water, groundwater, and reuse. The Zayandeh Rud, Khoshkehrood, Izadkhast, Segonbad, Garghooye, Dharar, Asfarian, Tighezard, and Joshaghan rivers provide the surface waters of the study area.

To analyze the demand for water in the basin, the needs are divided into three sectors: agriculture, industry, and domestic (drinking) in 17 sub-basins (as shown in the prefix 42 in Fig. 3). Figure 3 shows the position of these areas. Each of the consumption points is fed from three river water sources and wells. The purpose of allocation of water is to supply water needed in different sectors and to review their improvement for the future.

Fig. 3
figure 3

Configuration of resources and water consumption in the Zayandeh Rud area (modified and updated from chapter seven of MYCE [32] about water consumption and water needs of urban and rural communities)

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WEAP Model

WEAP, developed in 1988 by Ruskin and subsequently revised under his supervision, is a computerized tool for integrated water resources planning. This was developed with the intention of engaging water projects in the context of issues related to the management of consumption, water quality, and conservation in water resource planning. It provides a comprehensive framework for policy analysis [25].

The main advantage of WEAP is the integrated approach for simulating and optimizing water resources systems and orienting them in line with policies [6]. It considers needs (water patterns, equipment returns, reuse, costs, and allocations) in line with resources (surface flows, groundwater, reservoirs, and water transitions) and using linear optimization for the best solution [23].

WEAP can be used in urban and agricultural systems, independent basins, or complex river systems [49]. It can cover a wide range of issues such as needs analysis, water protection, rights and allocation privileges, simulation of surface and underground waters, reservoir operation, hydroelectric power generation, pollution control, environmental requirements, vulnerability assessment, and cost benefit analysis [24, 37].

WEAP Approach

Working with WEAP involves several steps. In the definition of the study, the time frame, spatial boundaries, system components, and problem settings are specified. The existing conditions, which can be used as a step for calibration of the model in terms of development, show a general picture of real water needs, pollution loads, sources, and supply of the system. Under existing conditions, key assumptions are defined for the expression of policies, costs, and factors that affect the need, pollution, water supply, and hydrology. Scenarios are first created according to existing conditions, then they can be used to examine the impact of different assumptions or policies on future access and use of water in the future [19].

Modeling Structure

The WEAP software is based on the calculation of water balance and focuses on water resources and environmental considerations simultaneously. Equation (1) is used to calculate the total system requirement [23]:

$$ AD=\sum \left( TAL\times WUR\right) $$
(1)

where AD is the annual water requirement and TAL is the total activity level that can be abandoned for residential or agricultural areas depending on the point of need. In Eq. 2, R is the runoff, PAE is the precipitation for evapotranspiration, ETP is the potential evapotranspiration, P is the precipitation and PE is the effective precipitation, IF is irrigation, and S is the volume of storage (all components in millimeters) [18, 29, 41]:

$$ {\displaystyle \begin{array}{c}R=\mathit{\operatorname{MAX}}\left(0, PAE- ETP\right)+\left(P\times \left(1- PE\right)\right)\\ {}+\left(\left(1= IF\right)\times S\right)\end{array}} $$
(2)

T calculate the amount of groundwater fed by runoff, Eq. 3 is used to calculate the surface water of Eq. 4:

$$ RTG=\sum \left(R\times RTG F\right) $$
(3)
$$ RTS=\sum \left(R\times \left(1- RTGF\right)\right) $$
(4)

where RTG shows groundwater feed (cubic meter), RTGF shows the groundwater feed rate, and RTS shows feeds from surface water (cubic meters).

The flow of water at the bottom of the stream is used in the model using Eq. 5:

$$ DO= UI+ SI+ GFTR- RFTR-E $$
(5)

In Eq. 5, DO is the water flow downstream, UI is the water flow upstream, SI is the surface water flow, GFTR is the groundwater, and E is the evaporation (all components in cubic meters per second).

Figure 4 shows the volume of available water supply in the dam. This volume is calculated by Relation (6), which shows the storage of reservoir dam:

Fig. 4
figure 4

Volume available for storage of the Zayandeh Rud Dam [19]

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$$ SA=S+\left( BC\times BS\right) $$
(6)

where SA is the available storage volume (cubic meter), S is the storage volume (cubic meter), BC is the buffer factor, and BS is the buffer volume (cubic meter).

Time Period

For modeling using WEAP, 1 year should be considered as the base year. The base year means the first year that there is an adequate level of information and statistics on the status of the study area. The base year of this study was considered to be 1972. The base year was selected with regard to the completeness of the available information. The historical study period was considered to be 46 years by 2018 and modeling was continued with the simulation of climate change with the CM1P5 model and the simulation of pure irrigation demand and socioeconomic assumptions (such as population growth) until 2100.

Required Data

The input data of the model included census statistics, which was extracted from the report of a consulting company (cited from the website of the Statistics Center of Iran) [16]. The per capita consumption of water was estimated at 73 m3 per person over a year [19].

The level of cropping and water requirement in each region were extracted from the report. The average of 34 years of discharge of each river basin as well as the amount of harvesting from wells were also obtained and entered into the model [16].

The evaporation rate was calculated from the level of the dam, and the surface of the basin was calculated using the Penman Monteith method. Climate change forecasting data and future weather forecasting were obtained from the Climate Explorer online data and the statistical down scaling method was used (the details of future climate change models and scenarios are shown in [19]). For this work, the climate data sets were obtained from the Koninklijk Nederlands Meteorologisch Instituut (KNMI) which cooperated with observer station data to project the historical and future climate models for Iran and the study area. The observational surface temperature (°C) and monthly precipitation (mm/day) data cover the time period from 1971 to 2005 in a monthly time step. Raw projection data are retrieved from the Coupled Model Intercomparision Project phase 5(http://climexp.knmi.nl/help.cgi?id) multi-model dataset for the period of 1971 to 2100. CMIP5 includes the climatic variables such as temperature, precipitation, relative humidity, and wind speed projections under four emission scenarios (RCP) for 2006–2100. However, the severest scenario (RCP 8.5) is used. To obtain the simulation of climate variables for the meteorological stations, the latitude and longitude of the stations were selected. This gave the simulation points which are the nearest points to the given observation points.

Then, future meteorological data was included in the CROPWAT model and the net irrigation requirement was calculated. The projected future water per capita consumption in urban and industrial areas was assumed with a population growth rate of 2.5% and then all re-information was included in WEAP to simulate runoff for future years.

Scenarios

In WEAP, modeling scenarios typically consist of three steps. First, 1 year is selected for the current conditions as the base year of the model. The current conditions or existing system conditions without applying future plans and policies as reference scenarios. A reference scenario is extracted from the existing conditions to compare the evolutionary probabilistic simulation of the system without change and with change [19].

For the reference scenario in this study, climatic conditions, runoff, and water demand are projected according to the current situation and the upcoming trend (climate modeling and impact for water demand). The purpose of this scenario is to approach the present and future realities (without modifying or modifying).

Corrective scenarios adapted to the effects of climate change and increased water demand are as follows:

Development Scenario for Water Entering the Zayandeh Rud River

This scenario is the reference scenario based on climatic conditions and water demand similar to the reference scenario, with the difference that the amount of water entering the Zayandrood dam has been increased by the construction of a new channel in the upstream.

Scenario to Reduce the Level of Cropping

This scenario is based on the reference scenario, taking into account climatic conditions and water demand similar to the reference scenario, with the difference that the crop area is reduced by 30% in all areas of agriculture.

Scenario Increasing Irrigation Efficiency

This scenario is based on a reference scenario considering climatic conditions and water demand similar to the reference scenario, with the difference that irrigation under pressure develops and improves irrigation efficiency by up to 80%, thus reducing irrigation water losses.

Scenario Changing Crop Pattern

This scenario is based on a reference scenario considering climatic conditions and water demand similar to the reference scenario, with the difference that instead of rice and potatoes that consume more water, wheat, and barley that consume less water are replaced.

Results

As it is mentioned before, this study is the first work which used the WEAP model as an integrated water resource management model to project future water resources and water demands under climate change and human impacts and also compared the results for the future time period with the present time period.

The situation of unmet demand under the current climate for each water sector and each sub-catchment for the present time period is estimated and showed in Figs. 5 and 6.

Fig. 5
figure 5

Unmet demands for each water sector for the present time in the basin

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Fig. 6
figure 6

Total unmet demands (%) in the sub-catchments for the present time

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The summary of the present situation of water resources, water demands, and reliability to water resources to deliver water from water supplies to water demand sections are shown in Table 1.

Table 1 Reservoir capacity of the Zayandeh Rud dam, unmet demands, and reliability of the system to meet the consumption needs in the present time
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For the future time period, if the reference scenario is assumed to be such that the prediction of the condition of the study basin with regard to the modeling of climatic conditions and the hypothesized population growth rate and the level of net irrigation requirement are done from 1971 until the end of study period 2100, the situation of future climate change is showed in Fig. 7. The mean monthly precipitation and temperature changes are indicated in Fig. 7. The figure shows that the temperature is predicted to rise under the RCP 8.5 scenario for all months. As explained before, the scenario of RCP 8.5 is selected in order to analyze the severest conditions of climate change. However the variability of the precipitation projection is significant. The climate model predicts increased monthly precipitation from July to September; while for other months, it predicts decreased precipitation.

Fig. 7
figure 7

Projected mean monthly precipitation and temperature averaged change for the four stations under RCP8.5 scenario by 2006–2100

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Also, the situation of water resources which is simulated by the WEAP model is shown in Figs. 8 and 9. In addition, Fig. 8 shows that in some years, there are dry and wet years according to decrease and increase of precipitation. Furthermore, in Fig. 9, there are some dry and wet years for groundwater, according to decrease and increase of precipitation..

Fig. 8
figure 8

Projected storage volume of the Zayandeh Rud dam for a future period, which is simulated by WEAP. The red circle shows the reduction of storage in dry years

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Fig. 9
figure 9

Groundwater storage for a future period (2006–2100), which is simulated by WEAP under the climate change and human water abstraction impacts. The red circle shows the reduction of storage in dry years

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Also, the average monthly rate of unmet need is presented with the consideration for deductions and reuse in Fig. 10. As can be seen, the unannounced water in agriculture is the highest due to the priority of three utilizations of water for agriculture and the need for over-farming in the basin.

Fig. 10
figure 10

Comparison of the unplanned amount of water without implementing corrective plans and implementing corrective plans for the years 2018 to 2100

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The estimated water levels peaked in the months of October, November, and October, which coincided with the time of preparation of the land with the highest water requirement.

Uncontrolled adaptation scenarios in the basin are unplanned, as shown in Fig. 9. As can be seen, the estimated uncultivated water in the agricultural sector is 3000 million m3 without implementing the plans, while implementing the consistent plans for this amount in the total amount is reduced to 1700 m3million m3 (Table 2).

Table 2 Average monthly (million cubic meters) rate of unmet need for the future time period (2006–2100)
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The Zayandeh Rud dam storage, as shown in Fig. 11, will increase by 2 to 3 times the implementation of consistent water management plans compared to the reference scenario (without implementing corrective actions).

Fig. 11
figure 11

Comparison of Zayandeh Rud reservoir capacity without implementing corrective plans and implementing corrective plans for the years 2018 to 2100

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Another factor that results from this study is the reliability of each point. As shown in Fig. 12 and Table 3, with the implementation of consistent management plans, the reliability level will increase by 10 to 15% for meeting the needs of different sectors.

Fig. 12
figure 12

Comparison of reliability (percent) to meet needs without implementing corrective plans and implementing corrective plans for the years 1395 to 1490

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Table 3 Reservoir capacity of the Zayandeh Rud dam, not needed, and reliability of the system to meet the consumption needs in the reference scenario, compared to the four scenarios for implementing consistent designs
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Table 3 summarizes the amount of water stored in the Zayandeh Rud dam, which is not needed and does not represent the reliability of the system to meet the consumption needs in the reference scenario (without implementing a consistent plan) compared to four scenarios for implementing consistent management planning plans.

Table 4 shows a comparison of system reliability to meet consumption in historical time (years 1972–2018) and reliability of the system to meet consumer needs in the future reference scenario (without implementing a consistent plan for 2019–2100) compared to four scenarios for implementation of plans that are consistent with management planning (for the years 2019–2100).

Table 4 Reliability of the system to meet the consumption needs in the baseline scenario (1972–2108), reference scenario without a consistent design and with the implementation of scenarios for the implementation of compatible designs (2019–2100)
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Discussion

Water Evaluation and Planning System

This study suggested a water management strategy in the Zayandeh Rud River basin based on the different socioeconomic, management, and climate change scenarios for the sustainable availability of future water resources in the basin. To develop a sustainable water supply–demand system, the first step was to understand the current water supply–demand system in the study area and to evaluate the future impacts of externally driven factors and the impact of climate change on the water resources of the basin. Then, based on the current supply–demand situation, the supply and demand side management scenarios were applied in the model in order to optimize the water management system to achieve better results (decrease the unmet water demands). In this study, the reference scenario was built for two situations: (1) reference scenario without adaptation strategies and (2) reference scenario with adaptation scenarios.

In previous studies, the last version of WEAP as a tool for analyzing water management strategy had several limitations, including an allocation scheme that treated rivers independently, gave priority to demands on upstream sites over downstream sites, and assured demand sites that preferred groundwater to surface water were last in line in getting surface water allocations [27, 28].

So in this study, WEAP 21 (new version) was selected because as an integrated model it can represent multidimensional processes related to drought as an extreme event of climate change, water resources, and water management. Also, with regards to the spatial scale of this study (basin scale), physical data availability, knowledge level, and time availability for this study, the WEAP 21is suitable to simulate water allocation. Furthermore, it operates in a simple manner. The goal was not to examine the hydrological process of the Zayandeh Rud basin accurately, but, to be capable of simulating the water resources and water demands of the basin with limited data and to use fewer parameters.

Unlike other water allocation models, such as the MODSIM model in the Awash river basin in Ethiopia [20], our results indicate WEAP can simulate human abstractions with some accuracy and could be applied as a planning or policy analysis tool.

There are some limitations in the application of the model:

  • Calibration of the rainfall-runoff component of WEAP was done manually as no optimization routine was contributed.

  • The WEAP model is time-consuming, since it has to be set up for each run.

  • An important development for the user would be the establishment of an optimisation model in WEAP, to give an output set of parameters that optimize one of the efficiency criteria.

Output of the Model

The WEAP system provides the planning tool for water resource management as it can analyze:

  • Impact of the drought and climate change

  • Impact of the hydrological structures on the river flows

  • Impact of the change in water demand over time

  • Impact of the allocation rules of upstream/downstream

  • Impact of the setting up of the ecological reserve

In previous works, the WEAP was used only for one specific aim. For example, a study [30] on a coastal region showed that with using WEAP modeling, water distribution between neighbor catchments which use water for the navigation purpose can be managed well. Another study [28] represented that the WEAP model can analyze and organize wastewater resources for a basin in China. However, in this study, the WEAP model was used for simulating future stream flow and also for analyzing a number of adaptation strategies to combat future water shortage.

The WEAP model used the data of climate models such as precipitaion, temperature, humidity, evapotranspiration, and so on. The climate scenario which is used in this study is RCP 8.5 in order to analyze the severest condition and impacts on water scarcity in the study area. The significant limitation of the data which was used in the WEAP model is that the available data was in a monthly scale. The precious of data analyzing in a monthly scale is acceptable, however, in a daily scale, the precious can increase..

Also, in previous studies such as [5], the WEAP modeling suggested that only one water management option such as reducing the losses to domestic demand sites in urban areas, or the reduction in the per capita water requirement, or (mainly) the construction of a proposed dam, would help in retaining the water supply services in the future.

However, the WEAP model can evaluate the externally driving factors (population growth, social policies, and climate change) which puts immense pressure on the current water supply system and intensifies the water scarcity situation not only in a catchment but also downstream. The results of the study encourage water resources managers to adopt a management policy to resolve the water crisis or to render the unmet water demands in the Zayandeh Rud River basin. Based on the analysis of this study, it is necessary to identify an effective management strategy. For this purpose, a comparative analysis was designed to consider the possible options and to identify an effective policy for the maintenance of the water security in the basin.

Evaluating the Chadegan Reservoir storage in the Zayandeh Rud River basin indicates that the reservoir does not always receive adequate flows to supply full irrigation demands.

The analysis of the results shows that despite the shortages in the flows (occurring due to supply inadequacy and drought conditions), the water demand was increased.

Generally in the basin, because of high water demands for irrigation, the system operates in a failure risk range that was obtained by unmet demands. Also, the current irrigation infrastructure and irrigation techniques provide much more water losses, especially in the 4202, 4203, 4204, 4205, 4206, and 4207 sub-catchments (Fig. 6). The lack of implementation of rules or control methods for limiting water uptake in those areas increases the exposure of the water supplies. So, the value of “reliability of supply to deliver water to demand site” indicated the current situation of water management is not fair enough to cover water demands.

Most of the previous studies [8, 16] only focused on direct effects of climate change on water demands; however, they did not estimate adequately a range of social and policy impacts on the water demands. The methodology in this study has evaluated the social and policy impacts. The study confirms the previous study of [34] that the social and policy impacts are significant in water resource management in the developing the world.

As a consequence, WEAP can be used as a management tool. The results of this paper show that alternative management is needed to prevail over future drought impacts. The potential adaptation scenario as Altieri and Nicholls [2, 47] suggest will be:

  1. 1)

    Permanent reduction of agriculture water demands

  2. 2)

    Increase in water regulation capacity by construction of a new dam

  3. 3)

    Upgrade irrigation techniques and crop diversification

In this study, with making possible adaptation scenarios, the ability of the water resources to meet the demands is investigated during future dry years. Unlike a previous study by Paparrizos and Maris [33] which used a Mike basin model or the Basco-Carrera et al. [10] and Digna et al. [13] studies which used a Ribasim model in Egypt as an adaptation strategy in the Mun River Basin, Thailand, the WEAP software is strong in running models for different scenarios and for comparison of the scenarios.

All adaptation scenarios can prevent the Zayandeh Rud reservoir being significantly dry in drought periods. As in previous research on the Guadiana Basin in Spain [42], the adaptation plans (based on preserving environmental flows) can importantly reduce water demand. Especially if all adaptation scenarios combine, the storage of the Zayandeh Rud reservoir will increase significantly and unmet demand will decrease dramatically.

However, results from agricultural demands should be viewed with caution, as even with the adaptation scenarios, all irrigation requirements will not be completely fulfilled. Maybe as Playán et al. [36] mentioned in a previous research on a region in Canada, additional adaptation plans should be established to decrease more unmet demands. In this research, even with adaptation scenarios, irrigation demands suffer deficits in the range of 10–13% during dry years, but the unmet demands still decrease in comparison with having no adaptation scenario. With the adaptation scenarios, the reliability of the water resources will increase up to the year 2100. Table 4 and indicate the summary of future monthly average storage volume, unmet demands, and the reliability of the system to deliver water to demand sites with and without adaptation scenarios. As shown in the table, mix adaptation scenario represents the highest storage volume and the greatest reliability of the system with the lowest unmet demands. However, adaptation scenario 3 indicates the lowest storage volume and the lowest reliability of the system with the highest unmet demands.

In agreement with the previous study [21], cooperation with the water management can provide awareness and a tool set for planning local integrated use policies to make changes in irrigation technology, crop areas, and crop patterns. When water resources are managed at the river basin level, there is an opportunity to reply straightforwardly to policy decisions. Creating the adaptation scenarios in this chapter is not enough. The government has a significant role in advancing flexibility in the water sector. The performance of the government in the agricultural sector needs to contain:

  1. 1)

    Granting farmers clear information about the projected changes and possible influences on their current situation

  2. 2)

    Providing farms with the tools to determine their future farming plans

  3. 3)

    Creating development and educational training about how to make these changes

  4. 4)

    Allowing new favorable circumstances to increase as a result of climate changes

Conclusion

The present study suggests that to provide an acceptable flow of input into the Zayandeh Rud basin and the supply of water, demand for water in the basin for the future years requires targeted forecasting with acceptable climate conditions and human impacts simultaneously. So the amount of runoff in the future years and estimating the level of supply needs, through integrated WEAP modeling for water management as well as the new CMIP5 climate change model and the establishment of various adaptive correction scenarios and comparing them with each other provide a secure ground for water resource management and planning, Zayandeh Rud basin water resources were evaluated considering climate change and effective socioeconomic changes. The CMIP5 climate change prediction model was used under the RCP 8.5 scenario (the most critical climatic condition) and the small-scale method for the basin was used. Also, future ruoff are simulated by the WEAP model and the results shows that in the same future years of decreasing precipitation, reducing of runoff can happen and so making adaptation scenarios is compulsory. All assumptions about population growth and demand, especially the water requirement of the majority of cultivated plants, entered the integrated water resource management of WEAP. The results from the water allocation simulation revealed that WEAP is an effective tool for the estimation of water resource development and management demand in the basin.

In this study, generic modeling software based on the network flow algorithms’ computer-based simulation model successfully evaluated the effective parameters in integrated water resource management (including parameter of climate change (e.g., precipitation, temperature, humidity, and evapotranspiration), water demands, policy factors (e.g., priority of water user and rules for water reuse), and social factors (e.g., population growth rates)).

After preparing the resource-water resource model for future status, then, by exploring the region’s conditions and needs and considering the views of managers and stakeholders and water resources officials, adaptive corrective scenarios were designed to reduce the effects of climate change and human impacts on water resources were designed and measured for future years. In analyzing scenarios, the amount of water scarcity (unmet needs) and the percentage of reliability of water resources were evaluated for water transfer to the required water sector so that using the obtained information, the correct diagnosis in decision-making and analysis can be made.

Results showed that water delivery to the drinking and industrial sectors was the first priority; therefore, in all adaptive scenarios, drinking water and industry were almost fully supplied and only water supply to irrigation networks should be managed.

Analysis of future irrigation water demand shows that there is an important increase of water requirement which make additional stress on the water supply system.

These increases should be considered in the development of water supply management systems to mitigate the impact on crop production.

The investigation of water demands’ variations is interesting since the potential to choose alternative crops applicable to the water availability in the system in the long term will be defined.

Therefore, four adaptation scenarios for helping better management of water resources are built. From four corrective correction scenarios, although the scenario of increasing the inputs through the channel and the new reservoir dam is the best result for increasing water supply and increasing the reliability of the system to meet the needs of the water, but due to the lack of water in the adjacent basin, it cannot be done by drying the adjacent basin to increase water supply in the basin. Therefore, the scenario of changing the cropping pattern is the best scenario for increasing water storage with high system reliability to meet the water needs in the region. This scenario, in addition to reducing the water needs of agriculture, reduces the length of preparation for cultivation and saves more water. Evaluation of the results of the scenario of increasing agricultural efficiency and reducing the area under cultivation in terms of increasing water supply and reliability of the system to meet the needs of water are in lower priority. At present, the way out of the impasse in water resources management in Iran is the use of system analysis tools and management decisions in the supply and demand segment for the future. Past research lacks the prediction and analysis of water resources and resources for the future [32]. Also, selecting the best option after identifying the scenarios is necessary after each simulation and in the present study, WEAP as a multi-index decision analysis model, can be a suitable tool for supporting and solving decision problems.

Given the current status of water resources and the future needs of planning, integrated planning is available to planners and the sample of this study can be made available to the rest of the watersheds.

Results suggest that, as pointed out [32], for determining the superior choice of multi-index decision analysis, other methods, such as TOPSIS, are proposed. It will design a matrix that is rooted in the various indices and its pillar is the scenario.

A closer look at adaptive corrective scenarios from a sociological point of view involves greater social interest for farmers and people in the region, as well as more job creation, while also helping to save more water resources.