In recent years, delineation of groundwater\nproductivity zones plays an increasingly important role in\nsustainable management of groundwater resource\nthroughout the world. In this study, groundwater productivity\nindex of northeastern Wasit Governorate was delineated\nusing probabilistic frequency ratio (FR) and\nShannonââ?¬â?¢s entropy models in framework of GIS. Eight\nfactors believed to influence the groundwater occurrence in\nthe study area were selected and used as the input data.\nThese factors were elevation (m), slope angle (degree),\ngeology, soil, aquifer transmissivity (m2/d), storativity\n(dimensionless), distance to river (m), and distance to faults\n(m). In the first step, borehole location inventory map consisting\nof 68 boreholes with relatively high yield ([8 l/sec)\nwas prepared. 47 boreholes (70 %) were used as training data\nand the remaining 21 (30 %) were used for validation. The\npredictive capability of each model was determined using\nrelative operating characteristic technique. The results of\nthe analysis indicate that the FR model with a success rate\nof 87.4 % and prediction rate 86.9 % performed slightly\nbetter than Shannonââ?¬â?¢s entropy model with success rate of\n84.4 % and prediction rate of 82.4 %. The resultant\ngroundwater productivity index was classified into five\nclasses using natural break classification scheme: very low,\nlow, moderate, high, and very high. The highââ?¬â??very high\nclasses for FR and Shannonââ?¬â?¢s entropy models occurred\nwithin 30 % (217 km2) and 31 % (220 km2), respectively\nindicating low productivity conditions of the aquifer system.\nFrom final results, both of the models were capable to\nprospect GWPI with very good results, but FR was better\nin terms of success and prediction rates. Results of this\nstudy could be helpful for better management of groundwater\nresources in the study area and give planners and\ndecision makers an opportunity to prepare appropriate\ngroundwater investment plans.
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