Abstract
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.
Highlights
Total basin discharge (TBD) is a fundamental water balance component of river basins [1,2] and it has been traditionally measured at in-situ hydrological stations near estuary mouths
This study aims to address such issues; we applied a purely remotely sensed data-driven method based on the land water balance equation and able to estimate R
We found that all the peak-to-peak correlations were larger than 0.92: our pure data-driven method resulted in a correlation of 0.96, while the methods used in [44] and [37] resulted in correlation coefficients of 0.92 and 0.93, respectively
Summary
Total basin discharge (TBD) is a fundamental water balance component of river basins [1,2] and it has been traditionally measured at in-situ hydrological stations near estuary mouths. Continuous TBD time series are necessary for the monitoring of hydrological extremes (i.e., droughts and floods) in deltaic regions. Such monitoring is important for better water management, allowing an increase in water usage efficiency and minimizing unpredictable human, agricultural, and economic. A comprehensive global river water discharge (RWD) observing network has not been established yet [8]; the number of in-situ stations has been decreasing since the late 1970s due to the absence of sufficient funding for the upgrade and maintenance of facilities [9,10].
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