Assessment of Climate Change Impacts on the Water Resources of Megech River Catchment, Abbay Basin, Ethiopia

Endalkachew Abebe, A. Kebede
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引用次数: 19

Abstract

This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological variables at a daily resolution using SDSM model version 5.11. We noticed that statistical downscaling smooth out the bias between REMO output and observed data. According to the projected climate data, the maximum temperature is likely to have an increasing trend +0.57°C while the minimum temperature shows a decreasing trends ﹣0.61°C. There is no clear trend for precipitation, both increasing and decreasing trend observed in the catchment. The HBV-Light hydrological model was successfully calibrated (1991-1995) and validated (1998-2000) using current climatic inputs and observed river flows. The overall performances of the model was good at monthly time scale both on calibration (NSE = 0.91) and validation (NSE = 0.86). Future discharge (2015-2050) was simulated using statistically downscaled 20 ensembles climate scenario data for both A1B and B1 scenarios. HBV-Light model simulation results showed a reduction of the peak discharge in August and September.
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气候变化对埃塞俄比亚Abbay盆地Megech河流域水资源影响的评估
本研究旨在评估气候变化对Megech河流域水资源的影响。在这项研究中,使用SDSM模型版本5.11,将大规模区域气候模型(REMO)的输出在统计上缩小为每日分辨率的计量变量。我们注意到,统计降尺度消除了REMO输出和观测数据之间的偏差。根据预测的气候数据,最高温度可能有+0.57°C的上升趋势,而最低温度则有下降趋势﹣0.61°C。集水区的降水量没有明显的增加和减少趋势。HBV Light水文模型已成功校准(1991-1995年),并使用当前气候输入和观测到的河流流量进行了验证(1998-2000年)。该模型在校准(NSE=0.91)和验证(NSE=0.86)方面的月度时间尺度上的总体性能良好。使用A1B和B1情景的统计缩减的20个集合气候情景数据模拟了未来排放(2015-2050)。HBV Light模型模拟结果显示,8月和9月的高峰出院人数有所减少。
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