
Water Resources Management, Journal Year: 2025, Volume and Issue: unknown
Published: April 23, 2025
Language: Английский
Water Resources Management, Journal Year: 2025, Volume and Issue: unknown
Published: April 23, 2025
Language: Английский
Water Resources Management, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 11, 2025
Language: Английский
Citations
1Water, Journal Year: 2025, Volume and Issue: 17(4), P. 489 - 489
Published: Feb. 9, 2025
Flood disasters pose one of the greatest threats to humanity. Effectively addressing this challenge requires improving accuracy flood simulation. Taking Xunhe watershed in Shandong Province as study area, Random Forest model was utilized classify historical events within based on rainfall conditions, such varying durations, intensities, and total precipitations. Multiple sets hydrological parameters were established conduct classification simulation, reducing error caused by using a single parameter set for entire watershed. The results indicate that can be applied simulation Compared unclassified simulations, method proposed leads an improvement Nash coefficient 0.06 0.14, reduction relative peak discharge 3% 11.24% volume 1.46% 9.44%. has certain applicability errors under different scenarios watershed, providing new insights control disaster efforts.
Language: Английский
Citations
0Modeling Earth Systems and Environment, Journal Year: 2025, Volume and Issue: 11(2)
Published: Feb. 21, 2025
Language: Английский
Citations
0Water Resources Management, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Language: Английский
Citations
0Water Resources Management, Journal Year: 2025, Volume and Issue: unknown
Published: April 23, 2025
Language: Английский
Citations
0