PDF
Full
Outline
Taking four small and medium-sized watersheds in the mountainous city (Chongqing) as the research objects, the application prospects of multi-source rainfall data in short-term hydrological forecasting were explored. The GPM-IMERG remote sensing precipitation data was introduced as the source of the satellite precipitation data, and the Mean Bias Correction (MBC) method, Linear Regression Model (LRM) and Geographically Weighted Regression (GWR) method were used to realize the fusion with the ground station measured data. A leave-one-out validation method was used to evaluate the accuracy of the fused precipitation data, and the SWAT model was applied to simulate the runoff of the selected basins using the precipitation data corrected by MBC, LRM, GWR, the original IMERG-early, and the measured data. The results show that the GWR was the best fused effect. The topography had great influence on the accuracy of the IMERG-early data and the fusion method. The accuracy of the fusion method was relatively high in low elevation regions, while in mountainous areas, the accuracy became low comparatively. The results showed a better agreement between the SWAT model and the measured runoff process using all kinds of precipitation data, in which the model using precipitation data corrected by GWR method was more accurate. Results can be referenced for hydrological forecast in similar small basins in the future.
PDF
112
29
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
