Simulating Rainfall for Flood Forecasting in the Upper Minjiang River

The accuracy and timeliness of precipitation inputs have significant impact on flood forecasting. Upstream Minjiang River Basin is characterized by complex terrain and highly variable climatic conditions, posing a significant challenge for runoff forecasting. This study proposes a combined forecasting approach integrating numerical weather prediction (NWP) models with hydrodynamic models to enhance flood process simulation. The most appropriate initial field data for the Weather Research and Forecasting Model (WRF) exist in time and space resolution. Compared with the measured series, the characteristics of precipitation forecasting are summarized from practical and scientific perspectives. InfoWorks ICM is then used to implement runoff generation calculations and flooding processes. The results indicate that the WRF model effectively simulates the spatial distribution and peak timing of precipitation in the upper Minjiang River. The model systematically underestimates both peak rainfall intensity and cumulative precipitation compared to observations. Initial field data with 0.25° spatial resolution and 3 h temporal intervals demonstrate good performance and the 10–14 h forecast period exhibits superior predictive capability in numerical simulations. Updates to elevation and land use conditions yield increased cumulative rainfall estimates, though simulated peaks remain lower than measured values. The runoff results could indicate peak flow but rely on the precipitation inputs.

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Publication Details

Journal
Water
Published
2025-12-19
DOI
https://doi.org/10.3390/w18010004
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Simulating Rainfall for Flood Forecasting in the Upper Minjiang River

Water
Hydrology and Watershed Management Studies
article

Simulating Rainfall for Flood Forecasting in the Upper Minjiang River

article en

Abstract

The accuracy and timeliness of precipitation inputs have significant impact on flood forecasting. Upstream Minjiang River Basin is characterized by complex terrain and highly variable climatic conditions, posing a significant challenge for runoff forecasting. This study proposes a combined forecasting approach integrating numerical weather prediction (NWP) models with hydrodynamic models to enhance flood process simulation. The most appropriate initial field data for the Weather Research and Forecasting Model (WRF) exist in time and space resolution. Compared with the measured series, the characteristics of precipitation forecasting are summarized from practical and scientific perspectives. InfoWorks ICM is then used to implement runoff generation calculations and flooding processes. The results indicate that the WRF model effectively simulates the spatial distribution and peak timing of precipitation in the upper Minjiang River. The model systematically underestimates both peak rainfall intensity and cumulative precipitation compared to observations. Initial field data with 0.25° spatial resolution and 3 h temporal intervals demonstrate good performance and the 10–14 h forecast period exhibits superior predictive capability in numerical simulations. Updates to elevation and land use conditions yield increased cumulative rainfall estimates, though simulated peaks remain lower than measured values. The runoff results could indicate peak flow but rely on the precipitation inputs.

WaterVol. 18(1)
North China University of Water Resources and Electric Power (CN), Zhengzhou University (CN), Beijing University of Civil Engineering and Architecture (CN)
National Natural Science Foundation of China, Natural Science Foundation of Henan Province, Beijing University of Civil Engineering and Architecture
Climate action
Openalex Percentile: Top 38%
Hydrology and Watershed Management Studies
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