Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China

Abstract

The temporal resolution of forcing and calibration data substantially influences the performance of hydrological models. This impact varies among regions according to the climatic and landscape characteristics of the watersheds. In this study, we evaluate the benefits of using high-resolution rainfall and streamflow data in hydrological modeling across 63 small-to-medium-scale catchments in southeast China. We applied rainfall and streamflow data at various resolutions ranging from 1 to 24 h to drive and calibrate a well-established hydrological model. Our findings reveal that (1) utilizing sub-daily rainfall data significantly enhances the accuracy of daily streamflow forecasts, with notable improvements observed when models transition from daily to sub-daily resolutions; (2) forcing and calibrating the model by rainfall and streamflow data with sub-daily resolution data markedly improve hourly streamflow forecasts compared to daily data, but the enhancements become negligible when the resolution exceeds 6 h; and (3) the advantages of sub-daily resolution data are more pronounced in catchments characterized by a smaller drainage area, significant diurnal streamflow variability, and greater number of rain gauges. These findings provide basis for a more efficient rainfall and streamflow data acquisition.