Browsing by Author "Berihun, Eyerusalem"
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Item Optimization of Rain Gauge Network Using Entropy Geo-Statistics and Remote Sensing Case of Upper Awash River Basin Ethiopia(Addis Ababa University, 2021-09-12) Berihun, Eyerusalem; Atanaw, Fasikaw (PhD)An adequate rain gauge network gives immediate and precise rainfall data that are crucial for the effective and economical water resource development and management. This study was aimed at assessing the adequacy of the currently existing rain gauge network and optimization of the required rain gauge network in the Upper Awash river basin, central-east part of Ethiopia. A proposed model composed of Multi-Criteria Decision Analysis (MCDA), Kriging-based Geo-statistics, remote sensing and entropy methods were used. These methods were applied to obtain an optimal rain gauge network in 22,664 square km. currently; there are 16 existing rain gauge stations in the study area. A monthly average rainfall data was used for preliminarily checking the adequacy of the existing rain gauge network. The MCDA method with the Analytical Hierarchical Approach (AHP) was used for selection of a suitable site for rain gauge stations considering land use, slope, road accessibility, drainage network and orographic effects. The results from the preliminary checking for adequacy revealed that the existing rain gauging stations are not adequate enough; with estimation error of 7% demanded 148 additional rain gauges. The rain gauge suitability mapping using Multi Criteria Decision Analysis (MCDA) was used for locating the new additional stations. Considering maximum redundant information to be 60%, an additional 136 rain gauge stations were proposed. Finally by using 136 RGS again checked maximum redundant information then out of those stations only 49 rain gauge stations gives priority to be installed and an existing rain gauges of 16 totally 65 stations were required in the Upper Awash river basin . The results of the study showed that a combined use of the MCDA, the geo-statistical, remote sensing and entropy methods can highly improve the optimal spatial distribution and number of rain gauges in a network.