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Suitability of global precipitation estimates for hydrologic prediction in the main watersheds of Upper Awash basin

机译:全球降水量估算值对上灌水盆地主要流域水文预报的适用性

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摘要

Unavailability of optimum network of rain gauges and lack of well-organized precipitation data are one of the main challenges in hydrologic and climate-related studies. This study aims to evaluate the performance of three global precipitation data obtained from the Climate Forecast System Reanalysis (CFSR), Climate Prediction Center (CPC) and Tropical Rainfall Measuring Mission (TRMM) for hydrologic prediction at four main watersheds in the Upper Awash basin. Statistical indices and graphical efficiency measures were used to examine the CFSR-NCEP, CPC-NOAA, and TRMM data with the gauged data on mean annual, monthly, and daily basis at Upper Basin (UB) and Lower Basin (LB) area. The performance of global precipitation estimates was encouraging. Moreover, the spatial map of annual precipitation products demonstrated comparable spatial patterns with observed annual precipitation. The Soil and Water Assessment Tool (SWAT) model was used for hydrological simulation, and the hydrologic simulation efficiency of gauged data and global precipitation revealed good performance with R-2 and NS value of>0.5 for daily, and>0.7 for monthly scale simulations. However, lower to satisfactory model performance was obtained at the daily simulation in the Mojo and Akaki watersheds. The CPC-NOAA precipitation data was found superior in capturing the hydrologic variability. In relatively smaller watersheds, the suitability of global precipitation was lower due to the limited number of data points resulted from the coarse resolution of the data sources. Improvement in the satellite meteorology and climate reanalysis data could substantially increase the availability of alternative climate data for hydrologic studies.
机译:无法获得最佳的雨量计网络以及缺乏井井有条的降水数据是水文和气候相关研究的主要挑战之一。这项研究旨在评估从气候预测系统再分析(CFSR),气候预测中心(CPC)和热带雨量测量任务(TRMM)获得的三个全球降水数据的性能,这些数据用于对上灌水盆地的四个主要流域进行水文预测。统计指标和图形效率度量用于检查CFSR-NCEP,CPC-NOAA和TRMM数据,以及上流域(UB)和下流域(LB)区域的年均,月度和日均测量数据。全球降水估计数的表现令人鼓舞。此外,年降水量产品的空间图显示了与观测到的年降水量相当的空间格局。使用土壤和水评估工具(SWAT)模型进行水文模拟,实测数据和全球降水的水文模拟效率显示出良好的性能,R-2和NS值每天> 0.5,月度规模仿真> 0.7 。但是,在Mojo和Akaki流域的日常模拟中获得了较低至令人满意的模型性能。发现CPC-NOAA降水数据在捕获水文变异性方面表现优异。在相对较小的流域,由于数据源的粗分辨率导致数据点数量有限,因此全球降水的适用性较低。卫星气象学和气候再分析数据的改进可大大增加水文研究替代气候数据的可利用性。

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