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Influence of spatial resolution of radar images on the parameterization and performance of SWAT model

机译:雷达图像空间分辨对SWAT模型参数化和性能的影响

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摘要

Recent advances in environmental monitoring improve data quality and availability in space and time, but questions about their beneficial use in water resources analysis and modeling still remain. This study assesses the dependency of the parameterization and performance of a watershed-scale simulation model, the Soil and Water Assessment Tool (SWAT), on high-quality (rainfall) data at different spatial resolutions. The SWAT model was applied to the upstream of the Yeongsan River in Korea which remained relatively unexploited, and was calibrated and validated with the observed daily flow and monthly sediment data for the periods of 2012-2013 and 2014, respectively. Results showed that the radar rainfall estimates, derived using bias adjustment factors A(1) and A(2) which allowed the number and magnitude of storm events to be corrected, respectively, fitted excellently with the standard gauging data (R-2=0.97-0.98). Interestingly, the recommended parameter sets for steam flow were significantly different among the rainfall data-sets at different resolutions, but not for sediment concentration. The prediction accuracy of the model was, on average, higher not only during the calibration period than for the short-term validation period, but also using all the radar data-sets than using the standard gauging data. These results demonstrate that although we cannot recommend the best input among the new rainfall products in this preliminary study, the optimal parameter sets developed from many local and regional studies using the SWAT model need to be revisited fundamentally.
机译:环境监测的最新进展提高了空间和时间的数据质量和可用性,但有关其在水资源分析和建模中的有益用途的问题仍然存在。本研究评估流域型仿真模型,水平型仿真模型,土壤和水评估工具(SWAT)的参数化和性能在不同空间分辨率下的高质量(降雨)数据上的依赖性。 SWAT模型应用于韩国云山河上游,留下相对未开发的,并分别校准了2012 - 2013年至2014年期间的日常流量和月度沉积物数据。结果表明,使用偏置调整因子A(1)和A(2)来源的雷达降雨估计,其允许分别校正风暴事件的数量和幅度,以标准测量数据非常适合(R-2 = 0.97 -0.98)。有趣的是,在不同分辨率的降雨数据集中,蒸汽流的推荐参数集明显不同,但不适用于沉积物浓度。模型的预测精度平均不仅在校准期间比短期验证时段更高,而且使用所有雷达数据集而不是使用标准测量数据。这些结果表明,虽然我们不能推荐新的降雨产品中的最佳输入,但从许多本地和使用SWAT模型的区域和区域研究中开发的最佳参数集需要从根本上重新审视。

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