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Data Analysis, Discharge Classifications, and Predictions of Hydrological Parameters for the Management of Rawal Dam in Pakistan

机译:巴基斯坦拉瓦尔大坝管理的数据分析,流量分类和水文参数预测

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Rawal Dam is a strategic asset for the twin cities of Islamabad and Rawalpindi in Pakistan being the main source of drinking as well as agricultural water supplies. The low-lying areas of the reservoir are being affected by reservoir storage and spillways' discharge. For the effective management, modeling techniques would not only be cost effective but also help the water managers in predicting the future scenarios of water discharge. In this paper, last twelve years (2001-2012) trends of hydrological parameters, attribute selection, discharge classification in terms of spillway gates opening, and prediction methods for the forecasting of hydrological parameters at the Rawal Dam is presented. Our research suggests that August is a crucial month for inflow and spillways discharge. Similarly, September and October are critical for level and total storage capacity which are critical parameters for discharge management. J48 tree classification technique gave better results for discharge management. Finally, in order to forecast the critical parameters, the improved SVM technique for water level and the regression technique for storage capacity has been found to be more accurate.
机译:拉瓦尔水坝是巴基斯坦伊斯兰堡和拉瓦尔品第这两个城市的战略资产,是巴基斯坦饮用水和农业用水的主要来源。水库的低洼地区受到水库储存和溢洪道排放的影响。为了进行有效的管理,建模技术不仅具有成本效益,而且还可以帮助水管理人员预测未来的排水情况。本文介绍了过去十二年(2001-2012年)的水文参数趋势,属性选择,溢洪道闸门开度方面的流量分类以及拉瓦尔大坝水文参数预测的预测方法。我们的研究表明,八月是流入和溢洪道排放的关键月份。同样,9月和10月对于水位和总存储容量至关重要,而这是排放管理的关键参数。 J48树分类技术为排放管理提供了更好的结果。最后,为了预测关键参数,发现改进的水位支持向量机技术和存储容量回归技术更加准确。

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