Predicting Eastern Mediterranean Flash Floods Using Support Vector Machines with Precipitable Water Vapor, Pressure, and Lightning Data
Open Access
- 2 June 2023
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 15 (11), 2916
- https://doi.org/10.3390/rs15112916
Abstract
Flash floods in the Eastern Mediterranean (EM) region are considered among the most destructive natural hazards, which pose a significant challenge to model due to their high complexity. Machine learning (ML) methods have made a significant contribution to the advancement of flash flood prediction systems by providing cost-effective solutions with improved performance, enabling the modeling of the complex mathematical expressions underlying physical processes of flash floods. Thus, the development of ML methods for flash flood prediction holds the potential to mitigate risks, inform policy recommendations, minimize loss of human life, and reduce property damage caused by flash floods. Here, we present a novel approach for improving flash flood predictions in the EM region using Support Vector Machines (SVMs) with a combination of precipitable water vapor (PWV) data, derived from ground-based global navigation satellite system (GNSS) receivers, along with surface pressure measurements, and nearby lightning occurrence data to predict flash floods in an arid region of the EM. The SVM model was trained on historical data from 2004 to 2019 and was used to forecast the likelihood of flash floods in the region. The study found that integrating nearby lightning data with the other variables significantly improved the accuracy of flash flood prediction compared to using only PWV and surface pressure measurements. The results of the SVM model were validated using observed flash flood events, and the model was found to have a high predictive accuracy with an area under the receiver operating characteristic curve of 0.93 for the test set. The study provides valuable insights into the potential of utilizing a combination of meteorological and lightning data for improving flash flood forecasting in the Eastern Mediterranean region.Funding Information
- Israel Science Foundation (1602/19)
This publication has 54 references indexed in Scilit:
- Lightning activity, rainfall and flash flooding – occasional or interrelated events? A case study in the island of CreteNatural Hazards and Earth System Sciences, 2012
- Flash flood prediction using an uncalibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditionsJournal of Hydrology, 2010
- Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, RomaniaJournal of Hydrology, 2010
- Characterization of a Mediterranean flash flood event using rain gauges, radar, GIS and lightning dataAdvances in Geosciences, 2008
- The significance of spatial rainfall representation for flood runoff estimation: A numerical evaluation based on the Lee catchment, UKJournal of Hydrology, 2007
- Spatial characteristics of radar-derived convective rain cells over southern IsraelMeteorologische Zeitschrift, 2006
- Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model dataGeophysical Research Letters, 2006
- Spatial characteristics of thunderstorm rainfall fields and their relation to runoffJournal of Hydrology, 2003
- Measurement and analysis of small-scale convective storm rainfall variabilityJournal of Hydrology, 1995
- GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable WaterJournal of Applied Meteorology and Climatology, 1994