Merging Satellite and Gauge Rainfalls for Flood Forecasting of Two Catchments Under Different Climate Conditions

Xinyi Min,Ningpeng Dong,Chuanguo Yang

doi:10.3390/w12030802

Abstract

As satellite rainfall data has the advantages of wide spatial coverage and high spatial and temporal resolution, it is an important means to solve the problem of flood forecasting in ungauged basins (PUB). In this paper, two catchments under different conditions, Xin’an River Basin and Wuding River Basin, were selected as the representatives of humid and arid regions, respectively, and four kinds of satellite rainfall data of TRMM 3B42RT, TRMM 3B42V7, GPM IMERG Early, and GPM IMERG Late were selected to evaluate the monitoring accuracy of rainfall processes in the two catchments on hourly scale. Then, these satellite rainfall data were respectively integrated with the gauged data. HEC-HMS (The Hydrologic Engineering Center's-Hydrologic Modeling System) model was calibrated and validated to simulate flood events in the two catchments. Then, improvement effect of the rainfall merging on flood forecasting was evaluated. According to the research results, in most cases, the Nash–Sutcliffe efficiency coefficients of the simulated streamflow from initial TRMM (Tropical Rainfall Measuring Mission) and GPM (Global Precipitation Measurement) satellite rainfall data were negative at the two catchments. By merging gauge and TRMM rainfall, the Nash–Sutcliffe efficiency coefficient is mostly around 0.7, and the correlation coefficient is as high as 0.9 for streamflow simulation in the Xin'an River basin. For the streamflow simulated by merging gauge and GPM rainfall in Wuding River basin, the Nash–Sutcliffe efficiency coefficient is about 0.8, and the correlation coefficient is more than 0.9, which indicate good flood forecasting accuracy. Generally, higher performance statistics were obtained in the Xin'an River Basin than the Wuding River Basin. Compared with the streamflow simulated by the initial satellite rainfalls, significant improvement was obtained by the merged rainfall data, which indicates a good prospect for application of satellite rainfall in hydrological forecasting. In the future, it is necessary to further improve the monitoring accuracy of satellite rainfall products and to develop the method of merging multi-source rainfall data, so as to better applications in PUB and other hydrological researches.

Highlights

Flood disaster is one of the most serious natural disasters in China which poses a threat to the safety of people’s life and property and disturbs the construction of a harmonious society [1].The effects of flood disaster on human society economic development include human health, life property, economic income, living environment, mental disorder, ecological environment, and otherWater 2020, 12, 802; doi:10.3390/w12030802 www.mdpi.com/journal/waterWater 2020, 12, 802 direct and indirect impacts [2].The research of flood forecasting, so as to avoid huge losses by flood disasters has become an important part of hydrological study
The results indicated that it is of great significance for real-time flood forecasting in areas without data if the GPM satellite rainfall was calibrated by a few rainfall stations in the region
Xin’an River Catchment From the Mean Errors (ME); it can be seen that both TRMM 3B42 RT and V7 satellite rainfall underestimate the rainfall amounts in the flood events while the GPM IMERG satellite products are obviously overestimated

Summary

Introduction

Water 2020, 12, 802 direct and indirect impacts [2].The research of flood forecasting, so as to avoid huge losses by flood disasters has become an important part of hydrological study. Flood prevention engineering has been strengthened in medium and small basins, and the construction of nonengineering facilities such as hydrologic monitoring and flood forecasting were improved to provide decision basis for flood control command [3]. The rainfall-runoff models are widely used to flood forecasting in medium and small basins, and the simulation results are acceptable. The rainfall data in hydrological forecasting research mainly come from the rainfall stations [11], but the distribution of rainfall stations is often uneven because of economic and terrain constraints. Hydrologists and managers have faced a notable challenge on flood forecasting in ungauged basin [13]

Methods

Results

Conclusion