Remote Sensing-Based Extension of GRDC River Discharge Time Series

The quantification of river discharge is essential for understanding global freshwater dynamics. However, the Global Runoff Data Center (GRDC) dataset has faced a decline in the number of active gauges since the 1980s, leaving only 14% of gauges active as of 2020. We develop the Remote Sensing-based Extension for the GRDC (RSEG) dataset that can ingest legacy gauge discharge and remote sensing observations. We employ a stochastic nonparametric mapping algorithm to extend the monthly discharge time series for inactive GRDC stations, benefiting from satellite imagery- and altimetry-derived river width and water height observations. After a rigorous quality assessment of our estimated discharge, involving statistical validation, tests and visual inspection, results in the salvation of discharge records for 3377 out of 6015 GRDC stations with an average monthly discharge exceeding 10 m³/s. The RSEG dataset regains monitoring capability for 83% of global river discharge measured by GRDC stations, equivalent to 7895 km³/month, providing valuable insight into Earth's river systems with comprehensive and up-to-date information.

河流径流量的量化对于理解全球淡水动态至关重要。然而，自20世纪80年代以来，全球径流数据中心（GRDC）数据集的活跃测站数量有所下降，截至2020年仅剩14%的测站处于活跃状态。本研究开发了基于遥感扩展的GRDC（RSEG）数据集，能够吸纳历史测站径流数据和遥感观测数据。我们采用随机非参数映射算法，对非活跃GRDC站点的月径流时间序列进行扩展，并利用卫星图像和测高仪获取的河流宽度和水位观测数据。经过严格的径流估算质量评估，包括统计验证、测试和视觉检查，成功挽救了6015个GRDC测站中3377个的径流记录，其平均月径流量超过10立方米每秒。RSEG数据集恢复了GRDC测站所测全球83%的河流径流监测能力，相当于每月7895立方千米，为地球河流系统提供了全面且最新的见解。