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| DOI：10.13522/j.cnki.ggps.2022287 |
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| Research and Application of A New Hydrographic Datasets: A Case Study in Dongting River Basin |
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HUANG Zequn, LIAO Chunhua, CHEN Yugui, CHEN Weitian,
ZHAO Enrong, LUO Hongmei, XIE Ruiheng
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1. Hunan Meteorological Service Center, Changsha 410118, China; 2. Key Laboratory for Meteorological Prevention and Mitigation of Disasters in Hunan Province, Changsha 410118, China; 3. School of Atmospheric Science, Sun Yat-sen University,
Zhuhai 519082, China; 4. Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies,
Guangzhou 510275, China; 5. Hunan Meteorological Observatory, Changsha 410118, China
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| Abstract: |
| 【Objective】High-resolution hydrographic datasets have become increasingly accessible which will have a significant impact on hydrological modelling such as runoff and flood inundation. In this paper, we present a new hydrographic dataset.【Method】The new raster hydrographic map, including flow direction and accumulation, drainage areas and flow distance, was developed using GIS and python programs for the Dongting River Basin, based on the latest multi-error-removed improved-terrain digital elevation model (MERIT DEM). It shows a robust performance in visual inspection, basin area, flow distance and model evaluation. The quality of the dataset was comprehensively evaluated using methods such as river network visualization analysis, comparison of basin area and river length, and hydrological modeling.【Result】The new hydrographic databases developed from the latest MERIT DEM show great difference in flow direction, river network structure and river length from those derived from the traditional databases, HydroSHEDS. The results obtained from the associated hydrological model indicate that daily and monthly Nash coefficients calculated from the new dataset are 0.41 and 0.52, respectively, better than those calculated from HydroSHEDS.【Conclusion】The newly developed hydrographic dataset provides a more accurate representation of the locations of the rivers, thereby reducing the uncertainties in predicting runoffs and potential flooding. This dataset is now available for academic research and educational use. |
| Key words: DEM; flow direction; river network; basin delineation; hydrometeorological services |
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