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In general, the sustainability of the water supply system is indicative of an adaptive operational approach, wherein the decision-maker adjusts the system's performance based on the availability of water resources in a given time frame. In light of this, a novel framework is proposed in this study to evaluate sustainability, including three key indicators: resilience, reliability, and vulnerability. To address stressors that may lead to system failure, a multisectoral water allocation optimization is undertaken. In order to account for the future implications of climate change on the hydrological cycle, a simulation step, is incorporated, utilizing the Soil and Water Assessment Tool (SWAT) under various emission scenarios (RCP4.5 and RCP8.5), prior to integrating the streamflow data into our proposed optimal framework. To calibrate and validate historical data (2014–2019) and simulate future streamflow patterns (2025–2085), the Sistan Basin, located in an arid region of Iran, is analyzed as a case study. In light of the anticipated adverse impacts on the water supply system, certain adaptation measures, such as demand shrinkage scenarios, are considered to further appraise the proposed framework. Based on the final output, it is evident that the agricultural and industrial sectors, being the primary water consumers, are more susceptible to negative impacts resulting from the reduction in system sustainability. This susceptibility is primarily attributed to their highest vulnerability and comparatively lower reliability. [ABSTRACT FROM AUTHOR]

• Proposing a SWAT based Bi-objective framework to examine consumer satisfaction of regional water allocation system. • Applying different scenarios associated with climate patterns to analyze consumer satisfaction degree. • Proposing alternative demand projection to improve consumer satisfaction degrees. • Although much research has been cited to examine the level of consumer satisfaction, there is little framework to develop strategic models to improve consumer satisfaction, taking into account future climate patterns. • Applying a real case study in Iran affected by drought to examine the proposed framework. A long-term perspective of climate change patterns leads to the strategic management of limited water resources and consequently achieves the maximum level of social satisfaction between the various sectors in a water allocation system. Therefore, this study first adopts Soil &Water Assessment Tool (SWAT) to simulate future climate change patterns [2020–2050 and 2051–2080] under Representative Concentration Pathway (RCPs) scenarios, and then the extracted SWAT output is applied as the initial data in a bi-level programming model in which the manager of the upper level (MUL) tries to maximize the level of social satisfaction between sub-areas while the lower level manager (MLL) focuses on maximization of multi-sectoral social satisfaction. Also, historical data collected from Zayandehrud basin, Iran as a case study are considered for calibration, validation, and subsequently projecting the runoff data for mentioned periods. Based on the output related to the regional hydrological cycle under the [RCP4.5/2020–2080 & RCP8.5/2020–2080] scenarios, the study area is strongly affected by drought and relative temperature increase. Accordingly, due to the shrinkage of water resources in the basin, the highest degree of consumer satisfaction is related to the domestic sector as the smallest recipient of water resources. Thus, with the development of adaptation measures such as the use of demand reduction leverage for the effective use of limited water resources, the challenge of demand dissatisfaction for both the industrial and agricultural sectors is significantly improved. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to evaluate the impact of land cover resolution, in comparison with the digital elevation model (DEM) resolution, on hydrological modeling outputs. Three different basins in the various resolutions of DEM (12.5, 25, 50, 100, 500 and 1,000 m) and land-use maps (250, 1,000 and 2,500 m) were collected in this study, and the hydrological modeling process was performed using the Soil and Water Assessment Tool (SWAT) model. The soil type resolution was 1,000 m for all basins, and the runoff modeling was done based on the Soil Conservation Service Curve Number (SCS-CN) method. The final model outputs showed that the DEM cell size variations affect significantly the topographical characteristics of a catchment such as area, mean slope, river network and time to concentration which alter the flood modeling outputs especially in hilly watersheds (mean slope more than 15%) up to 15% for a DEM cell size of 1,000 m in comparison to 12.5 m. Also, the resolution and spatial distribution of land cover maps which directly specify SCS-CN values, can change the output simulated runoff results up to 49% for a land cover cell size of 2,500 m in comparison to 250 m. These results indicated that the quality of the land cover map is more important than the quality of DEM in hydrological modeling. Also, the results showed that for an identical land-use cell size, the differences between model outputs using DEM cell sizes less than 100 m were not very significant. Furthermore, in all models by increasing the DEM cell size, the simulated runoff depth was decreased. [ABSTRACT FROM AUTHOR]