Studying Climate Change Condition by Wavelet-Ann and System Dynamics Approaches; Zola Reservoir, Iran

Nowadays assuming stationary patterns in water resources studies is abolished due to the climate change. In this paper, changes and their impacts are studied in Zolchay sub-basin in Northwestern Iran. Zolachay River supply the irrigation demands of watershed, water need for Salmas city, aquaculture industry and then flow to the important ecosystem of Urmia Lake. As Urmia Lake basin has faced serious droughts in recent years then studying its recharging sources like Zolachay is very important. Precipitation and temperature changes are simulated by using GCM model of IPCC AR4 in three emission scenarios of A1B, A2 and B1 with the stochastic model of LARS-WG for the years of 2011-2030. To analyze the impact of climatic changes on surface water resources, an Artificial Neural Network (ANN) approach is used to develop rainfall-runoff model of watershed in monthly time scale. Inputs of ANN model are decomposed by wavelet transform to robust the performance of the model.Reservoir of Zola Dam and its operation are simulated by system dynamics approach. The results of this study indicate a temporal change and rise in precipitation. Hence, hydrograph of the watershed would have a temporal and quantitative change. In addition to changes in runoff of the watershed, development of the watershed is considered in studying future of Zolachay. The results show a reduction in outflow to Urmia Lake and rise in dependence to groundwater resources to supply agricultural demands in future.

Keywords:

Climate Change , ANN , Wavelet , System Dynamics , Reservoir