...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Water >Increasing the Accuracy of Runoff and Streamflow Simulation in the Nzoia Basin, Western Kenya, through the Incorporation of Satellite-Derived CHIRPS Data
【24h】

Increasing the Accuracy of Runoff and Streamflow Simulation in the Nzoia Basin, Western Kenya, through the Incorporation of Satellite-Derived CHIRPS Data

机译：通过合并卫星衍生的CHIRPS数据，提高肯尼亚西部恩佐亚盆地径流和水流模拟的准确性

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Hydrologic models will be an increasingly important tool for water resource managers as water availability dwindles and water security concerns become more pertinent in data-scarce regions. Fortunately, newly available satellite remote sensing technology provides an opportunity for improving the spatial resolution and quality of input data to hydrologic models in such regions. In particular, the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) dataset provides quasi-global high resolution precipitation information derived from a blend of in situ and active and passive remote sensing data sources. We piloted the incorporation of the CHIRPS dataset into the Soil and Water Assessment Tool (SWAT), a hydrologic model. Comparisons of results between estimation of streamflow using in situ rainfall gauge station data, the Climate Forecast System Reanalysis (CFSR) dataset, and the CHIRPS dataset in the data-scarce Nzoia Basin in western Kenya over the temporal range 1990–2000 were reported. Simulated streamflow estimates were poor with rainfall gauge station data but improved significantly with the CFSR and CHIRPS datasets. However, the use of the CHIRPS dataset in comparison with the CFSR dataset provided an improved statistical performance following model calibration with the exception of one streamflow gauge station in higher elevation regions. Overall, the use of the CHIRPS dataset had the greatest linear correlation, relative variability, and normalized bias despite overall average Nash-Sutcliffe Efficiency (NSE) and R 2 values.
机译：水文模型将成为水资源管理者越来越重要的工具，因为在数据稀缺的地区，水的可用量日益减少，水安全问题也变得越来越重要。幸运的是，新近可用的卫星遥感技术为改善此类地区水文模型输入数据的空间分辨率和质量提供了机会。尤其是，气候危害小组的带站数据的红外降水（CHIRPS）数据集提供了从原地与主动和被动遥感数据源混合而来的准全球高分辨率降水信息。我们尝试将CHIRPS数据集纳入水土模型土壤和水评估工具（SWAT）。据报道，在1990-2000年时间范围内，肯尼亚西部数据稀缺的恩佐亚盆地，利用现场雨量计站数据，气候预测系统再分析（CFSR）数据集和CHIRPS数据集估算了径流。降雨仪站数据模拟的流量估算很差，而CFSR和CHIRPS数据集的模拟流量估算则明显改善。但是，与CFSR数据集相比，CHIRPS数据集的使用在模型校准后提供了改进的统计性能，但高海拔地区只有一个流量测量站。总体而言，尽管总体平均Nash-Sutcliffe效率（NSE）和R 2值均高，但使用CHIRPS数据集具有最大的线性相关性，相对变异性和归一化偏差。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号