Abstract
Abstract. Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall, because of improved spatial and temporal resolution.
Highlights
Accurate measurement of precipitation is key for dependable hydrologic predictions (Guo et al, 2015)
The Correlation Coefficient (CC) for Tropical Rainfall Measuring Mission (TRMM) and Centre Morphing technique (CMORPH) decreases with decreasing timestep
Shen et al (2010) evaluated performance of TRMM and CMORPH in China at different timescales such as daily, 12, 6, 3 h and found out that CC increases with increase in timestep which is similar to the finding of this study
Summary
Accurate measurement of precipitation is key for dependable hydrologic predictions (Guo et al, 2015). Nowadays satellite rainfall products such as Climate Prediction Centre Morphing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) are produced at a spatial resolution of 8 km and temporal resolution of 3 h. Due to their indirect nature of measurements, satellite rainfall estimates (SREs) contain errors which can be divided into two groups; (i) systematic (bias) and (ii) random errors (Liu, 2015). Flash floods occur within a short period of time such that daily time scale used in previous studies may not be adequate
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