Systemic Management of Water Resources with Environmental and Climate Change Considerations

River basin management is very varied and challenging due to the competition in water consumption in different parts. Therefore, modeling water resources and uses is complicated, time-consuming, and essential in catchments with a complex hydro system. In the present study, modeling was performed for the southeastern part of the Aras River catchment area located in Iran. In this area, there is intense competition for water due to the implementation of policies to increase the cultivation area and the need to provide environmental water rights, which causes a lack of water supply for some sectors. In this study, water supply and demand in five sub-basins of Aras River were investigated using the WEAP MABIA model. Four separate scenarios, including a reference scenario (S1), the reference scenario with a priority of meeting environmental demands (S2), and climate scenarios (S3, S4) under general circulation models (GCMs) based on the IPCC Sixth Assessment Report (AR6) were produced for the near (2021–2040), middle (2041–2060), and far (2061–2080) future periods. Scenarios S3 and S4 considered the policy of increasing efficiency and the cultivated area to evaluate the response of sub-basins to changes in demand. The simulation results of scenario S1 show that the current water resources provide the existing requirements in wet years but are insufficient in dry years and years of increasing the cultivated area. Water shortage will also rise due to the policy of increasing the cultivated area and the impact of climate change, especially in scenarios S3 and S4. The results also indicated that the rate of lack of environmental water rights and the deficit of three aquifers in the study area will increase significantly in scenarios S3 and S4 in comparison with scenarios S1 and S2, which requires the adoption of appropriate management policies to achieve sustainable water resources for all subsections.


Introduction
Water is considered a vital natural resource in human socioeconomic development and ecosystem life. Population growth, economic development, and climate change have increased pressure on water resources. Water treatment and transfer are complex and costly, and it is impossible to replace water (Oki and Kanae 2006;Vörösmarty et al. 2010). Therefore, efficient management of water resources is essential due to the differences between various water consumption sectors (such as domestic, industry, and agriculture). Balancing water supply and demand is challenging in many parts of the world, especially in critical conditions when the water supply is lower than demand (Bejranonda et al. 2013). Population growth, rapid urbanization, and economic development exacerbate environmental tensions and increase water demand and shortage problems. Consequently, agricultural water resources, food security, and successful and sustainable regional development in many areas are directly affected by water shortage (Fan et al. 2015;Singh and Panda 2012;Yu and Qingshan 2014;Zhang et al. 2008). Water shortage is a critical issue that substantially impacts the whole global system, especially the world water supply systems (Hoekstra 2016;Li et al. 2017). Water shortage has increased widely in today's world (Hong et al. 2016) due to issues such as climate change (Al-Kalbani et al. 2014;DeNicola et al. 2015;Poff et al. 2016), rising water demand (Eliasson 2015; Khan et al. 2017), shifting consumption patterns (Khan et al. 2017), making supply and demand a major challenge of the century to protect humans and the environment (Poff et al. 2016).
Due to the complex nature of water issues, different consumptions, and limited water resources, it is necessary to utilize new methods that integrate technical, economic, environmental, social, and logical perspectives into an interconnected format. Modeling water resources and consumption is complicated, time-consuming, and essential on the basin scale, especially for basins with complex hydro systems (Dukhovny and Tuchin 2005).
Simulation models focusing on water supply issues are not always satisfactory. Recently, an integrated or combined approach has been created for water resources planning and development that, in addition to managing water supply and demand issues, pays attention to environmental sustainability. Water Evaluation and Planning (WEAP) is software for integrated water resources planning, developed by the Stockholm Environment Institute (SEI). An integrated approach to simulating water resources systems through policy is a principal feature of WEAP. This tool has been used as a support system to better water resources management in basins of the world (Al-Omari et al. 2009;Ali et al. 2014;Demertzi et al. 2014;Hamlat et al. 2013;Hoff et al. 2011;Lévite et al. 2003;Shumet and Mengistu 2016;Swiech et al. 2012).
Mohie El Din and Moussa (2016) studied water resources management in Egypt using WEAP. Adgolign et al. (2016) used the WEAP model to investigate the allocation of surface water resources in the Didessa river basin located in western Ethiopia. Using WEAP, Myat and Aye (2017) examined water allocation plans for the Mandalay area in Myanmar. Gao et al. (2017) focused on the Strategic Environmental Assessment (SEA) for Chinas arid/semiarid areas by the use of WEAP. Zohrabi et al. (2017) employed the WEAP model to simulate the evaluation of the improving surface irrigation efficiency impacts on water resources system indicators, including the reliability and vulnerability of water resources. Using the WEAP model, Winter et al. (2017) simulated water supply limitations in the agricultural irrigation sector in the Yolo area of California. Khalil et al. (2018) studied predicted changes in water status in the Mae Klong Basin, Thailand with the WEAP model. Faiz et al. (2018) applied WEAP to investigate flow changes and drought severity in the Songhua River Basin, in northeastern China. Olabanji et al. (2020) evaluated the climate change impact on water availability in the Olifants catchment (South Africa) with potential adaptation strategies using WEAP. Mirzaei and Zibaei (2021) used the WEAP model examined the management of water conflict between agriculture and wetland under the influence of climate change using economic-hydrological-behavioral modeling in the Halil River basin of Kerman province, Iran. Using WEAP, Kalbali et al. (2021) researched adaptation approaches to the impacts of climate change in northern Iran using a Hydrogy-Economics model. Dau et al. (2021) conducted a study on the effect of future changes in water availability due to climate change projections for the Huong Basin, Vietnam using the WEAP model. Lotfirad et al. (2022) evaluated the effect of the uncertainty of CMIP6 models under climate change scenarios SSP on extreme flows of the Caspian Hyrcanian forest watersheds using the BMA method.
Although there are various management solutions in a system to achieve the goals of water supply (Garrote et al. (2016), integrated water resources planning is superior due to considering all components and factors affecting the system (Garrote et al. 2016;Hong et al. 2016;Khan et al. 2017) and has higher potential in regions with water shortages (Garrote et al. 2016).
As with other countries, Iran suffers from a water shortage crisis in most of the provinces. Therefore, increasing irrigation efficiency (productivity) in agriculture is one of the best practical strategies. Surface irrigation networks are widely used in agriculture and food supply in Iran and play an essential role in the water resources of the country. Although surface irrigation is applied in a wide range, other studies indicate that the efficiency of these irrigation networks is less than usual (Navidi Nassaj 2016). Aras sub-basins in northwestern Iran, with abundant water resources, are one of the most crucial river areas and an important agricultural area. Still, low efficiency (about 60%) is reported in these sub-basins.
In the present study, basin modeling was performed using the WEAP MABIA model with several scenarios of increasing the cultivated area, improving irrigation efficiency, and providing environmental water rights, by considering the impact of climate change. The investigation aims to examine the predicted changes in water supply and demand concerning access to surface water and groundwater resources for more appropriate water management.
Numerous studies worldwide have been conducted on integrated monitoring, modeling, and decision-making to evaluate reliability and vulnerability indicators in basins (Al-Kalbani et al. 2014;Dessu et al. 2014;Gao et al. 2017). However, the main advantage of this study is the use of general circulation models (GCMs) based on the IPCC Sixth Assessment Report (AR6) to study climate change and allocate environmental water rights to the river.

Study Area
The Aras River basin is a transboundary located in regions of Iran, Turkey, Azerbaijan, and Armenia. The total area of the Aras Basin is about 110,000 km2, and this study was conducted on the southeast part of this basin (18,183 km2)  Moghan, which include Ardabil, Sarein, Namin, Nir, Meshgin Shahr, Garmi, Parsabad, and Bileh Savar cities (Fig. 1). Traditional irrigation patterns, such as flood and furrow methods, are mostly adopted in the study area because of their low costs while they are relatively inefficient. Therefore, the irrigation water use efficiency is 65% in sub-basins Olya Ghareh Su, Sofla Ghareh Su, and Ahar Chay sub-basins, whereas it is 55% in Darreh-Rud, and Moghan sub-basins. The land use and the NDVI map are shown in Fig. 2.

Water Supply Sources
This study uses surface water (flowing water in rivers and water stored behind dams) and groundwater as water supply sources. Hydrometric stations, river flow rates, dam specifications, and groundwater resources information were obtained from the Iran Water Resources Management.
Surface water resources, including main rivers and hydrometric stations, are shown in Fig. 2, and the location and characteristics of dams are shown in Table 1 and Fig. 3.
Groundwater resources are in the form of three major aquifers of Ardabil, Meshgin Shahr, and Ahar-Varzegan, located in Ardabil, Sarein, Namin, Nir, Meshgin Shahr, and Ahar (Table 2). Due to the low altitude, there is no aquifer in the cities of Germi, Bileh Savar, and Parsabad.

Water Demand
The domestic, industrial, agricultural, and environmental sectors were considered water demands in the study area. These sectors' surface and groundwater consumption information was obtained from the Iran Water Resources Management (Table 3).

Meteorological Parameters
In the present study, minimum and maximum temperature, precipitation, and sunshine hours over 32 years are the required meteorological data, which were obtained from the Iran Meteorological Organization. The average values of these data are shown in Fig. 4.

LARS-WG Model
LARS-WG is a well-known model that can generate stochastic weather data (precipitation, maximum/minimum temperature, and solar radiation) in daily time series at a single site for use under both current and future climate conditions. (Semenov and Stratonovitch 2010). This model uses quasi-empirical distributions many times. The high accuracy of this model in generating climatic data, such as temperature and precipitation, has been documented in California (Zubaidi et al. 2019) and 30 weather stations located in different climate zones of Iran (Bayatvarkeshi et al. 2020).  LARS-WG 6.0 is implemented for downscaling GCMs by the IPCC Fifth Assessment Report (AR5) scenarios (Semenov and Stratonovitch 2015). According to the model's practical guideline, it can also be utilized for modeling using the outputs of GCMs (Goodarzi et al. 2015;Hashemi Monfared et al. 2017;Semenov et al. 2002).

WEAP Model Schematic in the Study Area
The WEAP model schematic in the study area is shown in Fig. 5. In the WEAP model, water supply from the surface, underground, and dam resources to demand sites is based on specified priorities depending on different policies as follows. 1) Providing domestic water as the priority, 2) providing the minimum required environmental flow of the river, and 3) allocating water to the agricultural sector.

Water Evaluation and Planning (WEAP) Software
WEAP software is a tool for integrated water resources planning. Because WEAP is an integrated model, it considers ecosystem preservation in addition to water supply and demand. WEAP is a semi-theoretical model that needs calibration (Abrishamchi et al. 2007) and is used to study and test alternative water development and management strategies (WEAP 2005). The model simulates the river system with the basic principles of water accounting based on a user-defined time step and computes the mass water balance for each node and link in the system for the simulation period (Yilmaz and Harmancioglu 2010). Simulation allows the prediction and evaluation of "what if" scenarios and water policies, such as water conservation programs, demand projections, hydrologic changes, new infrastructure, and changes in allocations or operations (Mutiga et al. 2010). Thus, WEAP software is a simulation-optimization tool for allocating water resources to supply the maximum demand. This software considers the priority of needs and prefers to provide them from different sources according to the constraints defined for resources and consumption. Finally, the rules of water reservoir utilization are defined by this algorithm.

Rainfall-Runoff Models in WEAP
To simulate some basin processes, such as evapotranspiration, runoff, infiltration, and irrigation in the WEAP model, five methods can be selected as follows: WEAP-MABIA is a complete software package for modeling crop water requirements and the different water balance components. It is used by scientists, engineers, and resource and asset managers to simulate evapotranspiration, runoff, infiltration, and percolation processes resulting from natural rainfall, irrigation scheduling, crop growth and efficiency, and the performance of engineered systems that manage water resources.
WEAP-MABIA is used to develop link-node and spatially distributed models for analyzing and simulating agricultural water demands and modeling flow and recharge in natural systems, including rivers and lakes, with groundwater interaction.

WEAP Model Calibration and Validation
To evaluate the calibration results in this study, the percent bias (PBIAS), Nash-Sutcliffe efficiency (NSE), and coefficient of determination (R2) are the statistical parameters that are expressed by Eqs. 1-3 (Moriasi et al. 2007): where Q obs , Q sim , N, and O obs are respectively the values of observed and simulated data, the total number of observations, and the average of the observed data.
PBIAS ± 25% for river flow, NSE > 0.50 , the value of R 2 is equal to 0-1, and 1 shows full coordination between the observed and simulated values. It can be claimed that the performance of the model is generally satisfactory based on the conditions mentioned above (Moriasi et al. 2007).
The general structure, including input data to WEAP MABIA and LARS-WG models and the outputs required to simulate the study area, are shown in Fig. 6.

Results
Model calibration means changing the parameters until the simulated results are close to the observed data. In this study, data from 2006 to 2016 are available for the WEAP model. The calibration and validation were performed from 2006 to 2012 and 2013 to 2016, respectively. The model was calibrated at the Boran region hydrometric station according to the topology situation of the study basin and the path of rivers. The calibration and validation results for 2006 to 2016 (Fig. 7) indicate that the simulated results reasonably correspond to the observed data in a desirable range. (1)

Environmental Demand
In the comprehensive water plan reports of Iran, the environmental demand is considered by determining environmental water rights, which mainly use ecological methods. However, the compatibility of these methods with the climatic conditions and environmental  situations of aquatic ecosystems in the country is controversial. The environmental flow of the rivers of the Aras catchment was calculated by the Tennant method, which determines the river's environmental flow as a percentage of the annual natural flow at a site. Data for different fish habitat aspects were collected by Tennant to provide a method based on the available information that required only the average annual flow (AAF) in the river (Tharme 2003). The results of Tennant's research in 58 cross-sections in 11 rivers in the western United States are summarized in Table 4. According to the Tennant method, the values of environmental demands used in the Aras and Darreh-Rud River study area are shown in Table 5 and Fig. 8. Table 4 and Fig. 8 show the environmental demand for Aras and Darreh-Rud rivers based on the Tenant method. Due to the conditions of the basin, the percentages of the environmental need supply for the Darreh-Rud and Aras rivers are considered in fair and very good conditions, respectively. As a result, the highest allocations of the Darreh-Rud and Aras rivers belong to April and May, and the lowest values are related to August and October, respectively.

Scenarios
The development of scenarios inherited from the reference or zero scenario is the main advantage of the WEAP model. These scenarios are possible future conditions to show the impact of supply and demand conditions changes and can answer the question, "what if." Four scenarios were developed in the present study to consider various factors and policies that affect the availability of water resources in the study basin in future years.

Reference Scenario (S1)
In all scenarios, the "base year" is regarded as the start year of the simulation in the WEAP model, which is the initial definition of the basic water system. In the model, 2006 was considered the base year. To assess the water situation in the study area based on current hydrological, social, and technological trends, the reference scenario was also named the "Usual Method" after the base year.
The reference or zero scenario is developed based on current policies in the management of water resources of the basin so that no managing plan is considered for the supply  and demand of various sectors, and the current situation allocates the aquifer extraction and the amount of environmental water rights.
In the current situation, domestic demand is the priority. After that, all available water is consumed in the agricultural sector due to the suitable climatic conditions. The excess demand of this sector flows to the rivers of this sub-basin; thus, the environmental water right is not provided continuously.
The S1 results during the period 2006-2016 show that the demand of the domestic sector for all sub-basins is fully met in this period.
The highest and lowest total demands in the study area (a total of five sub-basins) were 1952.1 and 1214.9 million m3 in 2014 and 2010, respectively. The highest and the lowest water demands in the agricultural sector belong to the Moghan and Olya Ghareh Su sub-basins, and the Darreh-Rud sub-basins, respectively (Fig. 9a, b). The highest unpredicted demands were 104.4, 223.4, and 294.4 million m3 in 2008, 2006, and 2014, respectively, which were mostly observed in Sofla Ghareh Su and Olya Ghareh Su sub-basins (Fig. 9c, d). The agricultural sector's demands supplied in the years mentioned above were 93.6, 88.4, and 83.3%. The demand required by this sector was almost entirely met in the other years. Reduction of annual precipitation (dry years) and an increase in the cultivated area can be the reasons for the unmet demand of the agricultural sector in the above years, which indicates water shortage in the agricultural sector in some years.
The unmet values of environmental demands and the levels of aquifers are shown in Fig. 9e, f. The results indicate that this demand is not fully met in 2008 and 2014, with negative levels of aquifers in the study basin. Aquifer deficit also increases in years with decreased precipitation and the increased cultivated area leading to more use of groundwater resources.

Environmental Scenario (S2)
The levels of ecological water rights for the Darreh-Rud and Aras rivers are fair and very good, respectively (Table 5).
In this scenario, the cultivated area and the population are according to S1. The priorities are respectively meeting the domestic demands, environmental water rights, and the agricultural sector. There is no management plan in agricultural policies (such as increasing efficiency), and the extraction level from aquifers and surface water is in line with the current situation. The environmental scenario results during the period 2006-2016 show that the demand of the domestic sector is totally met for all sub-basins in this period. The amounts of demand and unpredicted demand in the agricultural sector are also shown in Fig. 9.
As with S1, the highest and lowest total demands in the study area (a total of five subbasins) were 1952.1 and 1214.9 million m3 in 2014 and 2010, respectively, in this scenario due to the lack of necessary policy in the agricultural sector (Fig. 10a, b).
During this period, the environmental water rights of the Aras and Darreh-Rud rivers were entirely fulfilled, but the non-supply rate for the Aras River was less than 2% only in 2014 (Fig. 10f). Compared to the current situation, the aquifer deficit increased by 10, 10, 24, and 6 million m3 in 2008, 2009, 2014, and 2016 (Fig. 10e). The reason for this growth in the deficit can be as attributed to meeting part of the demand for the agricultural sector Demand and unmet of water demand in agriculture, aquifer balance, and unmet of environmental water rights from groundwater resources. Because fulfilling the environmental demands of the river is a priority, it was not possible to fully use surface water resources.

Five Percent Efficiency Scenario Considering Agricultural Sector Development Plans and the Impacts of Climate Change (S3)
The assumptions of this scenario are as follows: 1. The cultivated area increased by 10% in the four sub-basins, Sofla Ghareh Su, Olya Ghareh Su, Ahar, and Darreh-Rud. The Moghan sub-basin increased by about 60% compared to the initial level in the agricultural development plans (Fig. 11a, b). 2. Water efficiency in the agricultural sector increased by 5% in all sub-basins compared to prior scenarios. 3. The priorities for meeting the demands were respectively the domestic sector, the environment, and finally the agricultural sector. 4. The amount of aquifers extraction was considered given the current situation. The impact of climate change was investigated based on the IPCC Sixth Assessment Report (AR6) using the MIROC6 under climate change scenarios SSP245 and SSP585. The precipitation results and maximum and minimum temperature changes are shown in Fig. 12a-f.
The climate change rate of precipitation, the minimum and maximum temperature in the near (2021-2040), middle (2041-2060), and far (2061-2080) future periods under two SSP245 and SSP585 scenarios compared to baseline data (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) are presented in Tables 6, 7 and 8. These results show that precipitation decreases in all sub-basins, except for an increase in the Sofla Ghareh Su sub-basin. The minimum temperature rose in all sub-basins. The maximum temperature increased in all sub-basins compared to the average of the baseline data. However, it decreased in the Sofla Ghareh Su sub-basin in the near and middle future periods.
In S3, the demand for domestic is wholly met in all future periods. The amount of required demand and non-supply of water demand in the agricultural sector, aquifer balance, and the amount of non-supply of environmental water rights were studied according to the above assumptions during the baseline and the far future periods.
According to the results for the amount of water demand from 2006 to 2080 (Fig. 13a-d), the water demand increased in the baseline period due to the increase in the cultivated area compared to S1. This demand will increase due to the predicted climate change and an uptrend in future periods. The highest and lowest total demands in the study area (a total of five sub-basins) in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) were 2282.7 and 2673.3 million m 3 in 2008 and 2014, respectively. The results showed that the lowest total demand was 1250.9 in 2006 (Fig. 13a, b). The values of this demand in the near (2021-2040), middle (2041-2060), and far (2061-2080) future periods are 2186.8, 2416.9, and 3006.8 in the SSP245 scenario, and 2295.3, 2470 in the SSP585 scenario, respectively. 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 2 0 1 0 2 0 1 1 2 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 2 0 1 6  The non-supply of water demand (Fig. 14a-d) indicates that the amount of no water supply in the agricultural sector rose in this scenario in the baseline period due to the increased cultivated area and water resource limitations. This amount has a more significant increase in SSP245 and SSP585 scenarios in all future periods, indicating the significant impacts of climate change on the amount of water available and plant water requirements. In general, there is a non-supply demand required by the agricultural sector in this scenario in most years in the baseline and the three future periods for both climate scenarios.
According to Fig. 15a, b, the non-supply rates of environmental water rights in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) were 11.7 and 33.9% in the Darreh-Rud River in 2009 and 2016 compared to 1.6 and 8.5% in the Aras River in 2008 and 2014. Likewise, the non-supply rates of environmental water rights in the SSP245 scenario in the Darreh-Rud River in the near (2021-2040), middle (2041-2060), and far (2061-2080) future periods were 33.4, 1, and 3.4%, respectively, and 8.5% in the Aras River in the near future period. The non-supply rates in the SSP585 scenario were 19.7% and 6% in Darreh-Rud and Aras rivers in the far and near future periods, respectively. In the other years, the environmental water rights will be fully supplied for both rivers.
Aquifer deficit has grown in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) in most years due to the priority of meeting environmental demands and increasing the cultivated area (although taking into account an increase of 5% efficiency in the irrigation system), and about 55% per year has been added compared to the reference scenario. As this trend has been observed in future periods for both climate scenarios, the percentage of this deficit is higher in the SSP585 scenario than in SSP245 (Fig. 16a, b).

Ten Percent Efficiency Scenario Considering Agricultural Sector Development Plans and the Impacts of Climate Change (S4)
In this scenario, water efficiency in the agriculture sector increased by 10 and 5% in all sub-basins compared to the reference, environmental, and S3 scenarios, respectively, and the other assumptions were the same as S3. In S4, the demand for domestic is wholly met in all future periods. The amount of required demand and non-supply of water demand in the agricultural sector, aquifer balance, and non-supply of environmental water rights were studied according to the above assumptions during the baseline and the far future period. The amount of required demand in the period 2006-2080 is shown in Fig. 17a-d. According to the illustrated results, the required demand by 2013 increased by 10% and in 2014, 2015, and 2016 by almost 27% in the baseline period due to the increase in the cultivated area compared to the reference scenario. Due to the predicted climate change, this demand will increase, with an uptrend in future periods. However, given that the efficiency has increased by 5% compared to S3, the total demand has decreased by approximately 7 to 10% in SSP245 and SSP585 scenarios for all years compared to S3. The highest and lowest total demands in the study area (a total of five sub-basins) in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) were 2108, 2173, and 2500 million m3 in 2008, 2016, and 2014, respectively. The results showed that the lowest total demand was 1205 in 2006. The amounts of this demand in the near (2021-2040), middle (2041)(2042)(2043)(2044)(2045)(2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054)(2055)(2056)(2057)(2058)(2059)(2060), and far (2061-2080) future periods were 1999, 2224.49, and 2723.3 in the SSP245 scenario, compared to 2140.3, 2179.5, and 2788.5 in the SSP585 scenario, respectively (Fig. 18a, c).
According to Fig. 19a-d, the non-supply of required water has significantly increased compared to the reference and environmental scenarios due to water resources limitations but the non-supply of demand of needed water has declined by almost 20-30% in the baseline and future periods compared to S3 due to increased efficiency. However, there is a non-supply demand required by the agricultural sector in this scenario in most years in the baseline and the three future periods for both climate scenarios.
According to Fig. 18a, b, the non-supply rate of environmental water rights in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) was fully met in the Darreh-Rud River, but it was fully completed at 1.6 and 6.5% in the Aras River in 2008 and 2014. Likewise, the non-supply rates of environmental water rights in the SSP245 scenario were 33.8 and 8.5% in Darreh-Rud and Aras rivers, respectively, in the near (2021-2040) future period. For the other future periods, environmental water rights will be fully provided in both rivers (Fig. 19a). In the SSP585 scenario, the non-supply rates are 12.8% and 5.9% in Darreh-Rud and Aras Rivers in the far and near future periods, respectively. In other years, the environmental water rights will be fully supplied for both rivers. Aquifer deficit has grown in the baseline period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) in most years due to the priority of meeting environmental demands and increasing the cultivated area (although taking into account a 10% increase of the efficiency in the irrigation system), and about 45% per year has been added compared to the reference scenario. Since this trend has been observed in future periods for both climate scenarios, the percentage of this deficit is higher in the SSP585 scenario than in SSP245 (Fig. 20a, b).

Discussion
Due to the increased emission of greenhouse gases, climate change is to occur in Iran in the coming years. A key step to assess the effects of climate change on the life of human communities is to examine temperature and rainfall variations. These variations were determined by general circulation models (GCMs) based on the IPCC Sixth Assessment Report (AR6) using the MIROC6 in the present study. According to Tables 6, 7 and 8, the average minimum and maximum temperatures increased and rainfall decreased in general in all sub-basins, except SUB-BASIN2 minimum, but rainfall increased and maximum temperature decreased in SUB-BASIN2.
Sherafati et al. studied the effects of climate change in Moghan plain using the fifth report scenarios (RCP4.5-RCP8.5) and EC-EARTH, Hand GEM2-ES, MIROC5, and MPI-ESM models for three time periods 2021-2040, 2041-2060, and 2061-2080. The results of climate change of the MIROC5 model show an increase in maximum and minimum temperatures and a decrease in rainfall in the Moghan plain (Sharafati et al. 2022), which is consistent with the results of climate change of this study in the Moghan sub-basin using the MIROC6 model. Kalbaali et al. observed an increase in the temperature and a decrease in rainfall in northern Iran using scenario A2, which assumes rapid economic growth (Kalbali et al. 2021).
The results of climate change in this study are consistent with those of Sherafati et al. and Kalbaali et al. but our obtained results are more reliable because the Sixth Assessment Report was used in the present work.  In other studies, an increase in temperature and a decrease in rainfall were also observed in Iran (Mosavi et al. 2020;Zareian 2021).
Compared precipitation and temperature in GCM models in South Korea based on the scenarios of the fifth report (CMIP5) and the sixth report (CMIP6). According to their results, the mean of total precipitation and temperature changes showed a greater difference in the far future than the near future for RCPs and SSPs (Song et al. 2021), which is consistent with the results of the present study (Tables 6, 7 and  results of future precipitation and temperature changes are consistent with a previous study (Wang et al. 2020). In this study, the water evaluation and planning model (WEAP) was used to evaluate current water resources by considering four scenarios.
In the reference or zero scenario (S1), the current conditions of the basin were simulated in the baseline (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). The results showed that the demand for the agricultural sector was not been fully met in some years due to a lack of precipitation (droughts), declined river discharge, and increased cultivated area compared to previous years (such as 2008 and 2014). In some years, farmers in some sub-basins suffered from financial losses due to no water supply for up to 20%. In the current situation, the allocation of environmental water rights to rivers has been affected by the lack of reasonable management policies and has been unstable for some years. The simulation results show that, due to drought, reduced river flow, and the increasing cultivated area in some years, farmers have used more groundwater resources to supply the required water, resulting in a deficit in the aquifer level. The priority of meeting the environmental demands after the domestic needs in Scenario (S2) has supplied full environmental water rights for Darreh-Rud and Aras rivers in all years. The simulation results of this scenario show that prioritizing the supply of environmental demands over the agricultural sector has increased the non-supply of required water by the agricultural sector and the deficit of three aquifers. Thus, 60-70% of the water required for the agricultural sector has been provided in some years.
Scenarios (S3) and (S4) were analyzed according to the large number of the employed population in the agricultural sector of these sub-basins and the policy of increasing the cultivated area. In these scenarios, different irrigation efficiencies were simulated by considering the impacts of climate change predicted using the MIROC6 model in the baseline (2016-2016) and the future (2021-2080) periods, aiming to assess the feasibility study of development plans. In a study on the Denso River in Ghana, it was observed that the temperature would increase by 8.23% and the precipitation would decrease by 17%, resulting in a reduced will river flow by 58.3% in future climate change (Oti et al. 2020).
According to scenarios (S3) and (S4), it can be concluded that agricultural development plans have a greater impact on the deficit of water resources in the agricultural sector in the future than climate change. Thus, the implementation of management policies is essential to change irrigation systems and increase efficiency in the studied basins.
The results of comparing the supply of environmental demands in Scenarios (S3) and (S4) showed that the non-supply rate of environmental water rights for Aras and Darreh-Rud rivers was higher in Scenario (S3). Furthermore, the balance of the three aquifers shows that the deficit has increased in the above two scenarios.

Conclusion
The present study used the Water Evaluation and Planning (WEAP) model to evaluate the current water resources. Future water changes were predicted using the output of GCMs based on the IPCC Sixth Assessment Report (AR6) and with climate change scenarios SSP245 and SSP585 using the MIROCE6 model. The model was calibrated and validated to compare the simulation results with the observed data. The results showed that the model could simulate and analyze the basin well, and four scenarios were used for this purpose.
Due to the lack of water in the agricultural sector, the non-supply of environmental water rights in rivers, and the aquifer level deficits in the studied sub-basins, it is recommended to adopt appropriate management policies to increase irrigation efficiency, reduce the cultivated area, modify the cultivation pattern according to the regional needs, and integrated management of surface and underground water resources to achieve sustainability in these sub-basins. Moreover, appropriate management solutions are needed to observe the results regarding the amount of required water supply in the domestic, environmental, and agricultural sectors, and thus its impact on available water resources, which needs developing the right scenarios. For this purpose, three scenarios (S2), (S3), and (S4) (which cover the increasing cultivated area, efficiency, and the impact of predicted climate change) were presented in this study.
According to the results of the four scenarios, the following proposals are presented due to water shortage in the agricultural sector, no environmental water rights of rivers, and a deficit of aquifers in the studied basins. Adoption of appropriate management policies to increase irrigation efficiency, reduce the cultivated area, modify cultivation patterns to the demands of the region, and perform integrated management of surface and groundwater resources to achieve sustainability in these basins. Applying the WEAP model to the studied basins is also a helpful tool for decision-makers to effectively manage water resources in the basin.

Authors Contributions
Behnam Sadeghi has contributed to idea conceptualization of the study, data curation, software, methodology, design, analysis, and conclusion; reviewed the edited manuscript; writingoriginal draft. Mahmoud Ahmadpour Borazjani: supervision, idea conceptualization of the study, design and conclusion, reviewed the edited manuscript, and approved the final submission. Mostafa Mardani: literature search and methodology. Saman Ziaee: reviewed the edited manuscript. Hamid Mohammadi: design and conclusion, reviewed the edited manuscript.
Funding Authors would like to acknowledge the financial support for this study provided by the University of Zabol using Grant code IR-UOZ-GR-8086.

Data Availability
The data is accessible from the corresponding author (Mahmoud Ahmadpour Borazjani) upon request.

Declarations
Ethical Approval The study obtained ethical approval from University of Zabol, Faculty of Agriculture, Zabol, Iran.

Consent to Publish
Authors have provided consent to publish this work.

Competing Interests
The authors declare no competing interests.