چكيده به لاتين
Achieving a reliable tool for management, design and operation of water resources systems requires a comprehensive perception of natural and human processes and therefor modeling tools are being used. On the other hand, in order to apply models, they must be verified, calibrated and validated. One of the most important and widely used water resources planning models over the last decade is WEAP software, which is capable of simulating hydrological processes and allocating water resources in a catchment. Simulating rainfall-runoff in WEAP model is done by a method known as soil moisture. However, policymakers in agriculture and environment sectors are always looking for designing and analyzing the impacts of environmental policies, so that they can help solving existing problems. Currently regional scales agricultural models are used as a tool for supporting decisions on policymaking. These models need access to a wide range of agricultural production decisions with the possibility of simulating global change, climatic, economic and political scenarios. A significant group of regional scales agricultural models are considered as optimization and calibrated through positive mathematical programming (PMP). Basic assumption in PMP is that observed behavioral reactions provide a basis for model calibration. Thus, in order to expand the prevalent perspective from a unilateral survey of hydrological processes to an integrated hydroeconomic perspective in a basin, it is essential to consider surface and subsurface water withdrawal components for agriculture, drinking and industry in hydrological model and also consider effects of farmer’s decisions on maximizing profits. In this regards through present study, an integrated water resources model has been developed to simulate rainfall-runoff processes, farmer’s decisions on crop patterns and also maximizing benefits. The chief component of a hydrological module includes water balance within different components of a hydrological system in a watershed including roots, reservoirs, rivers and economic module consists of the calculation of economic net benefits derived from the outputs of an agricultural module. In this study, a sensitivity analysis of model outputs relative to using precipitation data gathered through different interpolation methods (such as Thiessen polygons, inverse distance weighting and Kriging) has been accomplished. Then two algorithms named PEST and GA had been used for automatic calibration of soil moisture method and also compared with each other. Mahabad River located in Urmia Lake Basin has been chosen as case study. Results illustrate relatively good calibration of studied sub basins with both algorithms and certainly dominance of genetic algorithm on PEST. Subsequently, the agricultural and economic modeling was done in MATLAB software by using NSGAII algorithm and calibrated with a multi-objective perspective. Results of hydrological modeling indicate the potential of soil moisture method in simulating rainfall-runoff hydrological processes of Mahabad River. Likewise with the results of agricultural and economic modules and analyzing farmer’s behavioral reactions which is evident in the estimated resources allocation (such as soil and water) in the base year, we can see that positive mathematical programming has provided a proper basis for model calibration.
