Introduction

Many researchers around the world have applied WEAP to simulate how water is distributed, e.g., Fatemi et al. (2013), Adgolign et al. (2016), and Winter et al. (2017). Alfarra (2004) for the Naivasha River Basin and Ouled Zaoui et al. (2010) for the Souk-AHRAS Basin of Algeria, using WEAP, concluded that the main problem in the agriculture sector was improper management rather than water scarcity. Over-allocation of demand in some areas prevented meeting the demand in other areas. Alfarra et al. (2012) examined the effects of rapid population growth and agricultural development using WEAP and defined five scenarios. The results showed that while the agricultural sector maintained its output, the continuation of the current consumption trend would lead to a widening gap between future supply and demand for water in Amman.

Mehta et al. (2013) defined three scenarios and compared in a basin of California with WEAP to provide a solution to the effects of climate change. The maximum water saving is achieved by combining the change in the pattern of efficient cultivation with the development of irrigation technology. Esteve et al. (2015) applied the hydro-economic model of the Middle-Guadiana Basin, Spain, to estimate the potential impacts of climate change on irrigated agricultural areas. The results show that climate change drastically increases water demand. Farajzadeh et al. (2014) applied WEAP to evaluate the effect of climate change on the water supply system of Karkheh watershed. The results showed that water reuse was the most effective solution to adapt to climate change. However, changing the cultivation pattern is more feasible, because it is less expensive. Salehpour (2016) determined the best exploitation scenarios with WEAP for the Hablehroud Basin. The results showed that climate change will result in water shortage crisis, especially in hot months of the year.

Kermanshahi et al. (2013) applied WEAP to investigate the status of irrigation demands in the Neyshabur plain. The reference scenario was compared to scenarios with changes in cultivation pattern, reduction of irrigated land area, and combined scenario of these two factors. The results showed that the annual mean deficit fraction decreased by 13, 8, and 18%, respectively. Aghaie et al. (2013) evaluated demand and supply using WEAP for Mashhad plain watershed. The results showed that the application of hybrid scenarios in water use management was more effective than the single-objective scenarios. Mehri et al. (2015) used WEAP for Gorganrood River to determine operation patterns. The results showed that some of the demand was not supplied and to improve the current situation, prioritization of demand allocation should be considered. Amini et al. (2017) used WEAP to assess the management applied in the Gamasiab watershed and to investigate the impact of upstream dams on the Bistoun dam performance. The definition of different management scenarios was done according to the current conditions and landscape of the basin development, and their results showed the full coverage of the demands under current conditions and water scarcity if other dams were constructed in the basin.

In a study in the Aral Sea Basin, which has problems similar to the Sefidroud irrigation and drainage network, using a hydro-economic model, Bekchanov et al. (2015) managed to improve water efficiency, reduce transmission losses, and distribute the grid, and increase crop yields at a constant level under cultivation. Effective support from government and organizations has also been cited as an incentive to improve the network status and agricultural channels and markets in resolving problems.

The quality and quantity of Sefidroud River water as the main water supplier for Sefidroud irrigation and drainage network have decreased by approximately 50% (Javadzadeh et al. 2017). Therefore, optimum allocation of water is essential in order to maintain sustainability of rice production in the region. One of the suitable tools for water allocation in irrigation and drainage network is WEAP model to study different feasible management scenarios.

Water resources management is one of the main possible solutions to the problems of quantity reduction and decline in water quality. The complex nature of water issues requires new approaches to integrating technical, economic, environmental, social, and rational perspectives into one integrated framework in order to fully manage water resources. The WEAP model was selected for use in this study because of its comprehensive integration into water management and allocation systems and the combination of physical, hydrological, and management processes to gain a close understanding of the present and future conditions of the Sefidroud irrigation and drainage network and the status of paddy fields, downstream environment, and the Caspian Sea inlet. In this regard, different management scenarios were defined and considered with regard to the probability of their occurrence in the near future.

Materials and methods

Description of the study area

Guilan province is one of the northern provinces of Iran with an area of 14,044 km2 (Fig. 1). It is located on the west coast of the Caspian Sea from − 26 to 100 m above the sea level. The Mediterranean climate and average rainfall of about 1200 mm annually make it one of the rainiest provinces of Iran, which unfortunately near 70% of the rainfall occurs in the non-cultivated season. A summary of the meteorological data of Guilan province (Rasht meteorological station) from 1985 to 2010 and the base year of this study (2013) is given in Table 1.

Fig. 1
figure 1

Left: map of Iran and the location of Guilan province, and map of Guilan province and Sefidroud irrigation and drainage and its canals

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Table 1 Meteorological data of Guilan province, Rasht
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Guilan province is located in the Sefidroud River basin, Iran. Sefidroud reservoir dam, a vital vein in the Guilan province’s agricultural economy, has been built on the Sefidroud River. The main purpose of the Sefidroud dam is to regulate the inflows to the Sefidroud irrigation and drainage network for irrigation of about 189,832 ha of paddy fields in Guilan plain. Guilan’s economy is based mainly on agriculture, especially rice production. More than 70% of Guilan paddy fields are within the Sefidroud irrigation and drainage network. More than 350,000 households equal to 50% of Guilan households work on the paddy fields. The water that is stored behind the Sefidroud dam is provided for paddy fields through the Sefidroud irrigation and drainage network. The role of water in rice cultivation is not simply limited to supplying the water requirement of the plant, but also to the control of weeds.

Water supply resources of the study area

The water resources in the study area for paddy fields are divided into several categories: groundwater, local rivers, rainfall during crop season, Sefidroud irrigation and drainage network, and reusing drain water. Sefidroud irrigation and drainage channels are the most important sources of water that supply a considerable portion of the region’s water demand. The lands covered by the Sefidroud irrigation and drainage network are divided into three irrigation areas including the central plain (G units) with 78,503 ha, the Foumanat area (F units) with 56,775 ha, and the eastern area (D units) with 54,555 ha (Fig. 1).

Using the WEAP model

Model description

The software was developed in 1990 by the U.S. Center of the Stockholm Environment Institute (www.weap21.org, 2019). This model is based on the basic equations of the water balance and can be applied to urban system, agricultural, and independent basins, or complex boundary river systems.

WEAP calibration and validation

The discharge data at the Roudbar hydrometric station and the volume of the Sefidroud Dam reservoir over the period 1992–2012 were used to calibrate and validate the model. The model has a sub-model called PEST for auto-calibration, which was used in this study. The 15 years of data were used for calibration and the remaining 6 years for validation. The results show that the model has successfully passed the calibration and validation stage and NRMSE < 10 indicates excellent model simulation satisfaction according to Bannayan and Hoogenboom (2009) classification. Therefore, this model was used to simulate the 2013 as base year and study different climate change scenarios in the period of 2013–2040.

Steps to apply the WEAP model

To apply WEAP software, the following steps are considered: first, determining the study area in the software; second, specifying the time horizon for the model and base year, being 2040 and 2013, respectively; third, water demand, resources, and supply; fourth, scenarios design; and finally, scenarios evaluation of the water supply sufficiency.

The main path of the Sefidroud River, Sefidroud, Tarik, and Sangar dams, irrigation and drainage network in the area, the return channels for each demand site, and all the effects of the basin are schematically identified. The schematic diagram of the model is shown in Fig. 2. The names of the components used in the model schematic are given in Table 2.

Fig. 2
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Introducing the study area in WEAP model

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Table 2 Introduction of component names in WEAP model schematic
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In the WEAP model, input data are divided into two series of demand nodes and water supply sources. The demand nodes in this study include agricultural and environmental need nodes and, also, for each of these demand nodes, the monthly requirement of each development unit is calculated. The total efficiency, water reuse, losses, and the minimum environmental requirement for downstream of these nodes were added to the model. The volume of Sefidroud, Tarik, and Sangar dams in 2013 from Guilan Regional Water Authority reports as storage capacity, monthly river discharge, and design of right and left canals of Sangar and Fouman tunnels were inputs of network water supply sources. Further, the amounts of extraction from groundwater and reservoirs were added to the data section (Guilan Regional Water Authority 2014). Then, the required data for the base year and the following years were inserted into the model, and the scenarios were then compiled and analyzed.

Water supply priority in WEAP

In the preparation of the WEAP model, each defined need point takes priority in water supply with respect to the performance of WEAP, and the dam reservoir has the lowest priority, meaning that the dam reservoir does not dewater until the lowland needs are met; or, more precisely, the model first deals with the downstream needs and, then, the surplus water is stored in the dam reservoir.

Environmental demand

According to the spatial scale study, available data, estimation time step, and technical and financial capacities, different methods are used to determine environmental requirements. One of these methods is the hydrological method of Tenant (Montana) applied in this study. According to available data on discharge flow during the non-growing months of the Sefidroud dam, the environmental requirement at the bottom of the study area is 5 m3/s, which is included in the software.

Scenario definition

This study evaluated agricultural consumption using the WEAP simulation model. Guilan Regional Water Authority information was used to determine the amount of water delivered in recent years to calculate the volume of water in subsequent years and to produce different scenarios. This information is given in Table 3 (Guilan Regional Water Authority 2014). In the reference scenario, monthly river flow data for the base year (2013) were taken from the Roudbar station based on data from the Guilan Regional Water Authority. The demand for water in the agricultural sector is assumed to be constant according to the current situation.

Table 3 Sefidroud River discharge at Roudbar station in different months of the year (m3/s)
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Scenarios are a set of different assumptions about future conditions in terms of policies, costs, and components that affect demand, resources, and hydrology that are ultimately analyzed based on a set of criteria. These scenarios illustrate how the system will engage in the future over time and will be recognized in the economic, social, or specific context of policymaking. All scenarios are derived from 1 year of the base. The scenarios considered in this study are given as follows:

The scenarios of 5% and 10% increases in the total efficiency of network include S1 and S2, respectively. In this scenario, the questions is: how are the improvement of the network status and the implementation of the land leveling and renovation plan in the network linked to the amount of consumption and the percentage of supply? In this scenario, the overall network efficiency is assumed to be increasing by 5% and 10%, respectively, compared to the reference scenario.

Scenarios of 5% and 10% increases in the drain water reuse include S3 and S4, respectively. Due to the flood irrigation in paddy fields, there is always water ponding sized between 3 and 5 cm above the soil surface. Some of this water, which is runoff, is drained. If this reuse is 5% or 10% higher than the reference scenario mode, what changes should be made to the supply?

Scenario exploring the impacts of climate change on the rice water requirement (S5)

According to the results found by Hadinia et al. (2017), rice water demand under climate change conditions in Guilan province changes over time. The results of the study showed a growing trend in future periods for the rice-growing season, mean temperature, Tmin, Tmax, and ETo. According to the A1B scenario, the highest increase in water demand would be 571.9 m3. Due to a decrease in water resources behind the Sefidroud dam in recent years, it is necessary to adjust water demand based on water resources of Guilan province’s inner basins. For this purpose, considering the maximum anticipated water requirement of rice during the mentioned periods, this study applied the WEAP software to determine the allocation and supply requirements of the network.

The scenarios of the dam release reduction in the crop season’s months by 10% and 20% compared to the base year are S6 and S7, respectively. In these scenarios, the dam release rates were reduced by 10% and 20% during the rice cultivation period to reflect the change in the area’s supply requirements.

These above scenarios are defined to evaluate the impact of all scenarios on all points of need. The purpose of these scenarios is to examine and apply these measures simultaneously. The scenarios description and their combinations are presented in Table 4.

Table 4 Combined scenarios of Sefidroud irrigation and drainage network management
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Determination of the superior scenarios

Evaluation indicators including social, economic, and environmental indices were used to determine the best exploitation scenarios. In this study, environmental reliability index (RE (env)) and percentage of environmental requirement coverage were considered as the environmental indices. In order to analyze and evaluate each scenario and select the best scenario, the indicators of demand percentage, reliability index, index of water deficit (IWD), and the coefficient of variation of supply-to-demand ratio at demand points (CV) were used for each scenario.

Reliability index (RE)

This indicator is the ratio of the total number of months the system has been successful in water supply to the total number of months of operation (Eq. 1). In other words, this index analyzes the failure of the system.

$${\text{RE}} = \frac{{\sum\nolimits_{j = 1}^{M} {d}_{j} }}{T}$$
(1)

In this equation, RE denotes the reliability index, M is the total number of times the system has been successful in meeting the needs, dj is the system victory event, and T is the total number of times the system has run. To calculate the reliability index, the threshold for determining the failure of the system in the field of water supply is 70% for agricultural need nodes, 90% for drinking and industrial need nodes, and 100% for environmental requirement (ASCE 1998).

Percentage of supplying demand

Supply percentage means the percentage of total demand that is estimated by the system and calculated through Eq. 2.

$${\text{Percentage}}\,{\text{of}}\,{\text{supply}}\,{\text{demand}} = ({\text{The}}\,{\text{amount}}\,{\text{of}}\,{\text{demand}}\,{\text{fully}}\,{\text{met/total}}\,{\text{demand}}) \times 100$$
(2)

Index of water deficit

The indicator shows the annual water shortage for agricultural land on a million-cubic-meter basis, indicating dissatisfaction.

Coefficient of variation of supply-to-demand ratio at demand points (CV).

This indicator shows the coefficient of variation of supply-to-demand ratio at demand points.

Results and discussion

Results of resource and consumption water simulation with WEAP model for the Sefidroud irrigation and drainage network

The effect of different scenarios on the minimum environmental flow. In this study, because of the priority of allocating resources to environmental needs (demand) in downstream of the development units, environmental needs are fully met in all scenarios and all months of the year.

Percentage of supplying demand for triple irrigation units in the Sefidroud irrigation and drainage network in the defined scenarios

Most parts of the agricultural area reported here are under rice cultivation in all three areas (Foumanat, central, and eastern units), and the water requirement of other crops can be ignored. Annual water requirements of Foumanat, central, and eastern areas with the total efficiency of irrigation in the region according to the reports are approximately 289, 801, and 556 million cubic meters (MCM), respectively. According to the results of the reference scenario obtained from the WEAP model, in the rice crop season months (May, June, July, and early August), the irrigation water of rice in each of these areas was not fully met through the irrigation and drainage network of Sefidroud and water scarcity in July and August was more severe, where the pressure on water resources is higher and rainfall is lower. According to the supply needed in the Foumanat area, about 2.09% of the ponding reservoirs, 28.42% of the local rivers, and 16.19% of the groundwater are provided. In the central region, about 3.4% of the need is met by ponding reservoirs, 24.65% by the flow of local rivers, and 6.63% by groundwater. In addition, about 5.22% of the ponding reservoirs, 12.85% of the flow from the local rivers, and 17.23% of the groundwater are provided by the water requirement in the East region. Therefore, by increasing efficiency and promoting reuse of drainage water and so on, supply and demand can be balanced. Therefore, different scenarios are defined, the results of which are presented in Tables 5, 6, 7, 8, 9, 10 and 11.

Table 5 Demand amount (MCM) and supply percentage of agricultural demand in Foumanat (F), central (G), and eastern (D) regions in the reference and increased total network efficiency scenarios
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Table 6 Demand amount (MCM) and supply percentage of agricultural demand in Foumanat (F), central (G), and eastern (D) regions in the reference and increase in drain water reuse scenarios
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Table 7 Demand amount (MCM) and supply percentage of agricultural demand in Foumanat (F), central (G), and eastern (D) regions in the reference and exploring the impacts of climate change on the rice water requirement scenarios
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Table 8 Demand amount (MCM) and supply percentage of agricultural demand in Foumanat (F), central (G), and eastern (D) regions in the reference and reduction of dam release in crop month’s season scenarios
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Table 9 Demand amounts (MCM) and Foumanat region (F) agricultural demand percentage in combined scenarios
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Table 10 Demand amounts (MCM) and percentage of supply coefficient of demand in the central region (G) in combined scenarios
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Table 11 Demand amounts (MCM) and percentage of supply coefficient of demand in eastern region (D) in combined scenarios
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According to the results of Table 5 of the WEAP model for the Foumanat area, with the continuation of the present conditions (the reference scenario), the annual water requirement amount is 285.55 MCM. In the months of May, June, July, and August, the region’s water supply is not fully met. The amounts of supply needed (demand) by the network in these months are 89%, 88.17%, 79%, and 68.35% of total demand, respectively.

By increasing the network efficiency by 5% (Scenario 1), compared to the reference scenario, not all needs of Foumanat area are met during the crop season, but supply coefficients increased by 9.17, 9.1, 13.38, and 8.34% in May, June, July, and August, respectively, which is facing a shortage of supply. The unmet water demand in these months decreased from 19.03, 20.48, 39.70, and 24.34 to 3.17, 4.72, 13.62, and 16.09 MCM, respectively. In total, the amount of unmet demand in the Foumanat area reduced from 103.55 to 37.6 MCM by increasing the efficiency of the Sefidroud irrigation and drainage network by 5%. If the network efficiency increased by 10% with land leveling and renovation compared to the reference scenario (Scenario 2), all the needs of Foumanat area would not be met by the Sefidroud irrigation and drainage network. However, supply coefficients in May, June, July, and August, which are facing shortages, increased by 9.19, 9.1, 18.8, and 29.83%, respectively. The unmet water demand in these months reduced by 15.89, 15.76, 34.32, and 22.94 MCM, respectively. The supply coefficient for other months in this scenario is 100%. Meanwhile, the unmet need reduced from 103.55 MCM in the reference scenario and from 37.6 MCM in Scenario (1) to 14.63 MCM in Scenario (2).

Table 5 shows the comparative results of the reference scenario and defined scenarios with respect to the increasing network efficiency in the central region. In the case of maintaining the present conditions (the reference scenario), the annual water requirement is 400.36 MCM annually and the water supply of the central region is not fully met in May, June, July, and August. The amount of supply needed by the network in these months is 99.12%, 97.38%, 97.30%, and 98.41% of the total demand, respectively.

In the central region, by increasing the network efficiency by 5% (Scenario 1), compared to the reference scenario, all the area needs would not be met during the crop season. However, the supply coefficient in April, exposed to a shortage of supply, increased by 0.38% and the unmet water demand in May decreased from 2.10 to 1.19 MCM. If the network efficiency increased by 10% compared to the reference scenario (Scenario 2), all the needs of the central area would not be met yet by the network; however, the supply coefficient in May, facing a shortage of supply, increased by 0.44% and the water requirement in this month dropped to 1.04 MCM. Meanwhile, the unmet need reduced from 17.26 MCM in the reference scenario and from 16.34 MCM in Scenario (1) to 16.21 MCM in Scenario (2).

The results of the WEAP model (Table 5) for the eastern region show that, with the current situation (the reference scenario), the annual water requirement is 278.22 MCM and the water requirement of the region is not fully met in June, July, and August. The amount of supply needed by the network in these months is 98.86%, 97.74%, and 99.52% of the total demand, respectively.

By increasing the network efficiency by 5% (Scenario 1) compared to the reference scenario, the supply coefficient did not change in the months facing supply shortages. If the efficiency of the network increased by leveling and renovating up to 10% compared to the reference scenario (Scenario 2), all needs would not be met by the network. According to the results of all three regions, the coefficient of supply needed to decrease as the rice reached the ripening stage. The main reason for these changes is the increase in water requirements of the plant and the climatic conditions of the region in summer.

According to the results of Table 6, Scenario 3, which projects a 5% increase in the drain water reuse scenario, compared to the reference scenario in May, June, July, and August, where Foumanat area is not fully met through the Sefidroud irrigation and drainage network, supply coefficients increased by 5.45, 5.46, 4.92, and 4.17%, respectively. With a 10% increase in the drain water reuse scenario (Scenario 4) compared to the reference scenario, the supply coefficient increased by 9.19, 9.1, 14.98, and 8.89% in the months when the total water requirement was not met. The volume of unsecured demand also reduced from 335.3 MCM in the reference scenario to 10.33 MCM in the reference Scenario 4.

Table 6 shows the results of Scenarios 3 and 4; the same scenarios project 5% and 10% increases in drain water reuse and reference scenario in the central region. In the months of May, June, July, and August, the need for the central region is not fully met through the Sefidroud irrigation and drainage network, with the percentage increasing by only 0.19% in May. In Scenario 4, compared to the reference scenario, the coefficient of supply increased by 0.4% only in May when the total water requirement of the central region was not met. It also reduced the unmet need from 17.26 MCM in the reference scenario to 16.29 MCM in Scenario 4.

According to the results shown in Table 6, the supply factor was the same as that in the reference scenario with no change in scenarios that projected 5% and 10% increases in drainage recycling compared to the reference scenario in June, July, and August when the need of the eastern region was not fully met through the Sefidroud irrigation and drainage network. The volume of unmet need remains 6.43 MCM.

According to the comparison of the results of an increase in network efficiency and the drain water reuse scenarios shown in Tables 5 and 6, it should be noted that increasing the network efficiency is more effective than the drain water reuse in Foumanat region. The Sefidroud irrigation and drainage network requires higher costs, while increasing drainage recycling is achieved through management measures. Therefore, the scenario of the increasing drain water reuse can be considered as a feasible and cost-effective solution to the present situation.

Based on the results shown in Table 7 in Scenario 5 (change in rice water requirement due to climate change) in the future periods, the supply coefficients of Foumanat area in May, June, July, and August compared to the reference scenario are 8.81, 8.82, 7.39, and 6.73%, respectively. In Scenario 5, the unmet need in May increased to 18.74 MCM compared to the reference scenario; further, in June, July, and August, the unmet need increased by 18.74, 20.82, and 8.34 MCM, respectively.

In Scenario 5, the supply coefficient of demand for the central region decreased by 0.3, 0, 7.33, and 25.71% in the months of May, June, July, and August, respectively (Table 7). In the scenario, the unmet need in May increased by 0.93 MCM, compared to the reference scenario. For the months of June, July, and August, the increase in unmet need was equal to zero, 21.67, and 30.41 MCM, respectively. In total, the unmet need increased from 17.26 MCM in the reference scenario to 70.26 MCM.

According to the results of Table 7 in Scenario 5, the supply coefficient of the eastern region in May, June, July, and August decreased by 0.3, 0, 0, and 0%, respectively, compared to the reference scenario. In Scenario 5, the unmet need in May increased to 0.55 MCM, compared to the reference scenario. Overall, the unmet need increased from 6.43 MCM in the reference scenario to 6.98 MCM.

Table 8 shows the agricultural demand amount (MCM) and percentage of Foumanat region (F), central region (G), and eastern region (D) in the reference scenarios and the scenario of dam release reduction in monthly crop seasons, respectively. The results of a 10% change in monthly dam release (Scenario 6) showed that Foumanat area supply coefficient decreased by 0.34, 0, 0, and 2.73% in May, June, July, and August, respectively (Table 8). A 20% change in the monthly dam release (Scenario 7) reduces Foumanat area supply coefficient in May, June, July, and August by 0.69, 0.01, 0.2, and 5.44%, respectively.

The results showed that with a 10% change in the monthly dam release, the coefficient of supply for the central area in May, June, July, and August decreased by 0.44%, 0, 8.25, and 21.21%, respectively. A 20% change in the monthly dam release reduced the coefficient of supply for the central area in May, June, June, and August by 7.83, 10.01, 21.68, and 24.63%, respectively.

To investigate the impact of dam release rate per month for irrigation of paddy fields in the eastern region, scenarios of the 10% reduction of dam release volume (Scenario 6) and the 20% reduction of dam release volume (Scenario 7) were considered. The results showed that with a 10% change in the monthly dam release, the supply coefficient of the eastern region needs to decrease by 0.22% in May. A 20% change in the monthly dam release reduced the demand coefficient of the eastern region in May and July by 0.49 and 0.21%, respectively.

Tables 9, 10, and 11 show the results of the combined scenarios for all three regions. By designing and implementing the hybrid scenarios, it was concluded that the application of combined different water management strategies (increasing network efficiency and increasing agricultural drainage reuse) could better capture water from different sources. Aghaie et al. (2013) and Salehpour (2016) reported also these results in their studies.

Identifying superior scenarios in each region

The results of scenario evaluation indices in determining the superior scenarios among the main scenarios defined in the research showed that in the need nodes of the Foumanat, central, and eastern regions, Scenario 2 (a 10% increase in network efficiency) is the best scenario characterized by the highest reliability index (RE) values of 98.85, 98.85, and 99.14, the coefficients of variation of supply-to-demand ratio at demand points (CV) of 7.29, 6.41, and 4.01%, and the lowest water deficit index (IWD) values of 14.63, 16.21, and 6.43 MCM. The next superior scenarios include Scenario 1 (a 5% increase in network efficiency) and Scenario 4 (a 10% increase in agricultural drainage reuse). The results of all scenarios are listed in Table 12.

Table 12 Reference scenario indicators and main scenarios of Sefidroud irrigation and drainage network needs estimates
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Conclusion

Currently, the main problem in the agricultural sector of Guilan province, which is a province with high water potential, is due to inadequate management rather than water scarcity. Achieving sustainable development goals and overcoming the challenges of the water sector in the province need investments in the province’s internal water resources infrastructure, an increase in the use of groundwater resources, and improvement of existing water resources management. For this reason, this study attempts to examine the impact of potential changes in the future on the basis of climate change discussions in the region by considering different scenarios, either individually or in combination, and provide solutions for the problems.

According to the results of WEAP, the Sefidroud irrigation and drainage network cannot meet all the needs in any of the three areas; however, the water potential of the province can partially address the water scarcity issues. However, at least, the downstream environmental requirement is met by priority allocation in this study in all months of the year. According to the evaluation indicators, a 10% increase in network efficiency is the best scenario. There are a number of suggested solutions for implementing total efficiency enhancement scenarios in the network. It should be noted that, after nearly 50 years of operation of the Sefidroud irrigation and drainage network, the canals of grades 3 and 4 remain still unpaved. Covering irrigation canals is one of the best solutions. The hydroflume can also be used for the header canal of the fields, as it increases the transfer efficiency. Restoration and dredging of irrigation canals and proper maintenance of canals are other suitable solutions to increase the efficiency of the whole network.

In downstream paddy fields, upstream drain water, being not qualitatively restricted, can be used for irrigation. Scenarios 3 and 4 can be implemented through this method. By volumetric water delivering, farmers will tend to save water, which in turn requires the creation of water user association. These organizations play a central role in allocating water to each paddy field fairly. The organizations perform the task of maintaining the irrigation canals.