Preprints
https://doi.org/10.5194/egusphere-2024-1438
https://doi.org/10.5194/egusphere-2024-1438
15 Jul 2024
 | 15 Jul 2024

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

Mahmut Tudaji, Yi Nan, and Fuqiang Tian

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 evaluated the benefits of using high-resolution rainfall and streamflow data in hydrological modeling across 63 small-to-medium-scale catchments in Southeastern China. We applied rainfall and streamflow data at various resolutions ranging from 1 to 24 hours 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 hours. (3) The advantages of sub-daily resolution data are more pronounced in catchments characterized by smaller drainage areas, significant diurnal streamflow variability, and a greater number of rain gauges. These findings provide basis for a more efficient rainfall and streamflow data acquisition.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Hydrology and Earth System Sciences. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Short summary
Common intuition holds that higher input data resolution leads to better results. To assess the...
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