Developing a Model for the Integrated Management of Water and Soil Resources in the Hableh-Rud River Basin Using the System Dynamics Approach

In this research, System Dynamics (SD) modeling was developed for facilitates the integrated and sustainable management of water and soil resources and improving the understanding of watershed systems in the Hableh-Rud River Basin. Reference diagrams were created to represent causal relationships and feedbacks. The conceptual model, included physical, economic, and social sub-systems, was created based by causal relationships and feedbacks. The model of stocks and flows run in the Vensim software environment. The model is comprised of Model verification was carried out through extreme condition tests and behavior reproduction test. Having the Nash-Sutcliff and R2 coefficients with greater values than 0.62 and 0.63, respectively, the SD model satisfactorily simulates all variables. Different scenarios of vegetation management, climate, water resources management, and cropping patterns were compared to the outputs of the existing condition. The results of scenario analyses for a 30-year period show that the agricultural water use efficiency scenario, as the best scenario, increases groundwater and water infiltration volume by 14.3 and 11.1 percent, respectively. With regard to the erosion and sedimentation variables, rangeland restoration activities were chosen as the best scenario, with 7.12 and 5.24 percent reduction. The greatest reduction in nitrogen and phosphorous loss, 8% and 6.4% reduction could be achieved by implementing the rangeland restoration scenario. From an economic perspective, payment for 50% of the ecosystem services, with about 46 percent improvement compared to the current condition, was determined as the best scenario. Stakeholders expressed their highest willingness to participate in the farm management activities with the accumulated score of 85.6 for public acceptance index. The SD model is a beneficial approach for stakeholders understanding of the causal relationships and feedbacks in the system.