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Improved Remotely Sensed Total Basin Discharge and Its Seasonal Error Characterization in the Yangtze River Basin

机译:长江流域改进的遥感总流域流量及其季节误差特征

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摘要

Total basin discharge is a critical component for the understanding of surface water exchange at the land–ocean interface. A continuous decline in the number of global hydrological stations over the past fifteen years has promoted the estimation of total basin discharge using remote sensing. Previous remotely sensed total basin discharge of the Yangtze River basin, expressed in terms of runoff, was estimated via the water balance equation, using a combination of remote sensing and modeled data products of various qualities. Nevertheless, the modeled data products are presented with large uncertainties and the seasonal error characteristics of the remotely sensed total basin discharge have rarely been investigated. In this study, we conducted total basin discharge estimation of the Yangtze River Basin, based purely on remotely sensed data. This estimation considered the period between January 2003 and December 2012 at a monthly temporal scale and was based on precipitation data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite, evapotranspiration data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, and terrestrial water storage data collected from the Gravity Recovery and Climate Experiment (GRACE) satellite. A seasonal accuracy assessment was performed to detect poor performances and highlight any deficiencies in the modeled data products derived from the discharge estimation. Comparison of our estimated runoff results based purely on remotely sensed data, and the most accurate results of a previous study against the observed runoff revealed a Pearson correlation coefficient (PCC) of 0.89 and 0.74, and a root-mean-square error (RMSE) of 11.69 mm/month and 14.30 mm/month, respectively. We identified some deficiencies in capturing the maximum and the minimum of runoff rates during both summer and winter, due to an underestimation and overestimation of evapotranspiration, respectively.
机译:流域总排量是了解陆海界面地表水交换的关键组成部分。在过去的十五年中,全球水文站数量的持续减少促进了利用遥感技术估算流域总流量。长江流域以前的遥感总流向径流量用径流表示,是通过水平衡方程,结合遥感和各种质量数据模型得出的。然而,建模数据产品存在很大的不确定性,很少研究遥感总流域流量的季节误差特征。在这项研究中,我们仅基于遥感数据对长江流域的总流域流量进行了估算。该估算以每月时间尺度考虑了2003年1月至2012年12月之间的时间段,并基于从热带降雨测量任务(TRMM)卫星收集的降水数据,从中分辨率成像分光辐射计(MODIS)卫星收集的蒸散数据以及地面从重力恢复和气候实验(GRACE)卫星收集的水存储数据。进行了季节性准确度评估,以检测不良的性能并突出显示由流量估算得出的建模数据产品中的任何缺陷。我们仅基于遥感数据估算的径流结果的比较,以及先前研究与观测到的径流的最准确结果显示,皮尔森相关系数(PCC)为0.89和0.74,并且均方根误差(RMSE)分别为11.69毫米/月和14.30毫米/月。我们发现,由于分别低估和高估了蒸散量,在夏季和冬季捕获最大和最小径流量时存在一些不足。

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