Safavi, H. R., Golmohammadi, M. R., Sandoval-Solis, S., ( 2015), Expert Knowledge Based Modeling for Integrated Water Resources Planning and Management in the Zayandehrud River Basin, Journal of Hydrology, Vol. 528, 773-789, doi:10.1016/j.jhydrol.2015.07.
Expert knowledge based modeling for integrated water resources planning and management in the Zayandehrud River Basin
Hamid R. Safavi, Associate Professor, Dept. of Civil Engineering, Isfahan University of Technology, Isfahan, Iran, email@example.com
Mohammad H,. Golmohammadi, PhD. Candidate, Dept. of Civil Engineering, Isfahan University of Technology, Isfahan, Iran, firstname.lastname@example.org
Samuel Sandoval Solis, Assistant Professor, Dept. of LAWR, University of California at Davis, USA, email@example.com
This study highlights the need for water resource planning and management using expert knowledge to model known extreme hydrologic variability in complex hydrologic systems with lack of data. The Zayandehrud River Basin in Iran is used as an example of complex water system; this study provides a comprehensive description of the basin, including its water demands (municipal, agricultural, industrial and environmental) and water supply resources (rivers, inter-basin water transfer and aquifers). The objective of this study is to evaluate near future conditions of the basin (from Oct./2015 to Sep./2019) considering the current water management policies and climate change conditions, referred as Baseline scenario. A planning model for the Zayandehrud basin was built to evaluate the Baseline scenario, the period of hydrologic analysis is 21 years, (from Oct./1991 to Sep./2011); it was calibrated for 17 years and validated for 4 years using a Historic scenario that considered historic water supply, infrastructure and hydrologic conditions. Because the Zayandehrud model is a planning model and not a hydrologic model (rainfall–runoff model), an Adaptive Network-based Fuzzy Inference System (ANFIS) is used to generate synthetic natural flows considering temperature and precipitation as inputs. This model is an expert knowledge and data based model which has the benefits of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS). Outputs of the ANFIS model were compared to the Historic scenario results and are used in the Baseline scenario. Three metrics are used to evaluate the goodness of fit of the ANFIS model. Water supply results of the Baseline scenario are analyzed using five performance criteria: time-based and volumetric reliability, resilience, vulnerability and maximum deficit. One index, the Water Resources Sustainability Index is used to summarize the performance criteria results and to facilitate comparison among trade-offs. Results for the Baseline scenario show that water demands will be supplied at the cost of depletion of surface and groundwater resource, making this scenario undesirable, unsustainable and with the potential of irreversible negative impact in water sources. Hence, the current water management policy is not viable; there is a need for additional water management policies that reduce water demand through improving irrigation efficiency and reduction of groundwater extraction for sustainable water resources management in the Zayandehrud basin.
Integrated water resources management; Complex hydrologic systems; Expert knowledge; ANFIS; Zayandehrud basin