probabilistic forecast of climate change effects on hamadan-bahar aquifer

this study will evaluates climate change impacts on groundwater resources in hamadan-bahar alluvial aquifer in the west of iran. different climate models are weighted in the basis of their ability in predicting monthly observed climate data in the base study period (1970-2000). with respect to climate models weights and their predictions, precipitation and temperature changes in 10, 50 and 90 probability percentile are estimated. daily observation data of hamadan synoptic station and δp, δt under a2 emission scenario at 90 probability percentile, as a critical condition in groundwater recharge, have been imported to an stochastic weather generator, named lars-wg, and future precipitation and temperature data are produced for the study period (2015– 2045). multi layer perceptron artificial neural network and visual modflow are used for simulating daily run off and groundwater table respectively. simulated groundwater table indicates a significant depletion in groundwater table around 38 meters specially in the south-southwest of aquifer and at the end of modeling period aquifer saturated thickness will be less than 12 meters.