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Using satellite-based weather data as input to SWAT in a data poor catchment

机译:使用基于卫星的天气数据作为数据在数据不足的数据中的输入

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摘要

Satellite-based weather estimates are spatially and temporally continuous data that seamlessly capture weather variability across the globe. A need was identified to assess the usefulness and reliability of satellite-based weather estimates in the lower Vaal River Catchment due to the scarcity of weather data. We explored the utility of Climate Forecast System Reanalysis (CFSR) data for streamflow simulation in an important agricultural catchment in South Africa, using the Soil and Water Assessment Tool (SWAT). First, we compared CFSR precipitation against rain gauge measurements at an annual time step. Two models were set up, one with conventional gauge weather data obtained from the South African Weather Services (SAWS) and the Agricultural Research Council (ARC), and the other with CFSR data. Calibration and validation of the models were performed using Sequential Uncertainty Fitting ver.2 (SUFI-2) algorithm of the SWAT Calibration Uncertainties Program (SWAT- CUP) at five stream gauge sites, with the data split between 2003 to 2008 and 2009 to 2013 for calibration and validation respectively. A low statistical agreement between CFSR precipitation and rain gauge data was obtained. The model with gauge data slightly outperformed CFSR model before calibration and during validation, whereas CFSR performed better mainly during calibration. Overall, both models achieved fair simulations of streamflow and long-term monthly streamflow regime at both the main catchment outlet and interior sub-catchments. While conventional gauge data remain the most accurate and reliable data source, CFSR can play a role as an alternative data input where there is inadequate gauge data.
机译:基于卫星的天气估计是空间和时间上连续的数据,可在全球无缝地捕捉天气变异性。由于天气数据的稀缺,因此确定了评估卫星河流集水区卫星天气估计的有用性和可靠性。我们探讨了气候预测系统重新分析(CFSR)数据的效用,用于使用土壤和水评估工具(SWAT)在南非的重要农业集水中进行流流模拟。首先,我们将CFSR降水与雨量计量测量相比一年时间步长。建立了两种型号,其中一个具有常规规格的天气数据,从南非天气服务(锯)和农业研究委员会(ARC)以及另外具有CFSR数据。模型的校准和验证是使用五个流仪表网站上的SWAT校准不确定性程序(SWAT-Cup)的顺序不确定性拟合Ver.2(SUFI-2)算法进行,数据分为2003年至2008年至2013年至2013年分别用于校准和验证。获得了CFSR降水和雨量计数据之间的低统计协议。校准前和验证期间,具有规格数据的模型略高于CFSR模型,而CFSR主要在校准期间更好地执行。总的来说,两种模型都在主集水区出口和内部子集中度的流出和长期每月流出制度中实现了公平模拟。虽然传统的仪表数据仍然是最准确且可靠的数据源,但CFSR可以作为替代数据输入扮演角色,其中仪表数据不足。

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