Flood Forecasting Using Satellite Images and Rainfall-Runoff Model in No Data Areas

Document Type : Original Article

Authors

1 Department of Civil Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran

2 Department of civil engineering, Razi university, Kermanshah

3 Department of Water Engineering, Faculty of Science and Agricultural Engineering, Razi University, Kermanshah, Iran

10.22125/iwe.2020.114964

Abstract

One of the most important issues discussed in hydrology and flood analysis are flood discharge estimation and the development of its hydrograph, using hydrological models. Today, satellite precipitation products with different spatial and temporal resolutions, have overcome the common problems and constraints in supplying rainfall data. Therefore, the aim of this study is the investigation and application of the TRMM satellite rainfall data as the input for hydrological models used for flood simulation in Gharehsoo watershed. For this purpose, first, the conceptual model of the basin was developed in the HEC-GeoHMS software and the performance of the HEC-HMS software was evaluated in flood hydrograph simulation. The TRMM satellite data was used to estimate the rainfall in parts of the basin lacking a rain gauge station. The accuracy of satellite precipitation data was compared with observation values ​​over the years 2013-2003. The results showed that the HEC-HMS model was suitable for estimating the peak discharge and flood volume for the catchment area, so that the difference between the observational and computational peak discharge was less than 7%, and the difference between the observational and computational flood volume was less than 10%. The examination of TRMM satellite images showed that the highest correlation was observed amongst the monthly data, with correlation coefficient values of 0.25-0.99 and the daily rainfall data was not sufficiently accurate. Also, taking into account the effect of the height of the site, the precipitation values obtained from the TRMM satellite images can be used with acceptable accuracy and an average error of less than 20%.

Keywords


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