Using High-Resolution Satellite Rainfall Products to Simulate a Major Flash Flood Event in Northern Italy

Abstract

Effective flash flood warning procedures are usually hampered by observational limitations of precipitation over mountainous basins where flash floods occur. Satellite rainfall estimates are available over complex terrain regions, offering a potentially viable solution to the observational coverage problem. However, satellite estimates of heavy rainfall rates are associated with significant biases and random errors that nonlinearly propagate in hydrologic modeling, imposing severe limitations on the use of these products in flood forecasting. In this study, the use of three quasi-global and near-real-time high-resolution satellite rainfall products for simulating flash floods over complex terrain basins are investigated. The study uses a major flash flood event that occurred during 29 August 2003 on a medium size mountainous basin (623 km2) in the eastern Italian Alps. Comparison of satellite rainfall with rainfall derived from gauge-calibrated weather radar estimates showed that although satellite products suffer from large biases they could represent the temporal variability of basin-averaged precipitation. Propagation of satellite rainfall through a distributed hydrologic model revealed that systematic error in rainfall was severely magnified when transformed to error in runoff under dry initial soil conditions. Simulation hydrographs became meaningful only after recalibrating the model for each satellite rainfall input separately. However, the unrealistic values of model parameters after recalibration show that this approach is erroneous and that model recalibration using satellite rainfall data should be treated with care. Overall, this study highlights the need for improvement of satellite rainfall retrieval algorithms in order to allow a more appropriate use of satellite rainfall products for flash flood applications.

Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

“…This is because the gauge-based precipitation data were derived from sparsely distributed rain gauge records and are therefore inadequate for characterizing the actual rainfall regimes for model calibration. A few studies [6,21] found that recalibration can sometimes cause parameter values to exceed their reasonable ranges. To avoid this problem, we defined the searching space of each XAJ model parameter to be strictly within its physical range in the SCE-UA optimization algorithm.…”

Applications of Satellite-Based Rainfall Estimates in Flood Inundation Modeling—A Case Study in Mundeni Aru River Basin, Sri Lanka

“…Among them are: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN [2]); the Tropical Rainfall Measuring Mission (TRMM [3]); and the Global Satellite Mapping of Precipitation (GSMaP [4]). These datasets have been applied to numerical hydrological models to simulate floods in various locations of the world [5][6][7][8]. Within South Asia, Nanda et al [9] used an SRE dataset to develop a real-time flood-forecasting model for a basin in eastern India.…”

“…Some employed multiple SREs and then tested their validity by comparing stream discharge [5,[14][15][16][17][18]. Flood inundation extent and depth have also been simulated by applying solo SREs such as PERSIANN and TRMM to distributional flood models [8,19].…”

Flood hazard assessment and mapping in semi-arid piedmont areas: a case study in Beni Mellal, Morocco

“…Several studies have demonstrated the utility of TRMM datasets in estimating rainfall for hydrological modelling of medium-sized and large catchments (e.g. Hong et al 2007;Su et al 2008;Nikolopoulos et al 2013;Yong et al 2012). Less testing has been undertaken in smaller catchments (less than 100 km 2 ).…”