Research on the Application of Machine Learning Technology in Hydrological Flood Prediction

Urban flooding disasters frequently occur in our country, severely affecting the national development process, anticipating the probability and severity of floods can effectively reduce the negative impacts caused by floods, the rapid progress of hydrology has accelerated the development of flood prediction research. Currently, a lot of machine learning methods are widely applied in the field of flood forecasting based on hydrology, which holds great significance for social development. First, the hydrological models currently used for flood forecasting are introduced. Then, the application of machine learning models in hydrology is elaborated. Finally, the problems and challenges faced by machine learning in flood prediction are analyzed and summarized, and prospects for future flood prediction technologies are discussed.

Authors

Institutions

Publication Details

Journal
Journal of Computer Signal and System Research
Published
2025-03-14
DOI
https://doi.org/10.71222/se6cyv71
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Application of Machine Learning Technology in Hydrological Flood Prediction

Yuan Gao
Journal of Computer Signal and System Research
Computational Physics and Python Applications
article

Research on the Application of Machine Learning Technology in Hydrological Flood Prediction

Yuan Gao
article en

Abstract

Urban flooding disasters frequently occur in our country, severely affecting the national development process, anticipating the probability and severity of floods can effectively reduce the negative impacts caused by floods, the rapid progress of hydrology has accelerated the development of flood prediction research. Currently, a lot of machine learning methods are widely applied in the field of flood forecasting based on hydrology, which holds great significance for social development. First, the hydrological models currently used for flood forecasting are introduced. Then, the application of machine learning models in hydrology is elaborated. Finally, the problems and challenges faced by machine learning in flood prediction are analyzed and summarized, and prospects for future flood prediction technologies are discussed.

Journal of Computer Signal and System ResearchVol. 2(2)
North China Electric Power University (CN)
Openalex Percentile: Top 98%
Computational Physics and Python Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.