On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions

Remote Sensing

Beatriz Revilla-Romero¹  Feyera A. Hirpa¹  Jutta Thielen-del Pozo¹  Peter Salamon¹  Robert Brakenridge²  Florian Pappenberger³  Tom De Groeve¹  Guy J-P. Schumann⁴  Magaly Koch⁴ 

[1] European Commission, Joint Research Centre, Ispra 21027, Italy; E-Mails:;Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, CO 80309, USA; E-Mail:;European Centre For medium-range Weather Forecast, Reading RG2 9AX, UK; E-Mail:European Commission, Joint Research Centre, Ispra 21027, Italy;

关键词: Global hydrology;    flood detection;    flood monitoring;    flood forecasting;    disaster response;    natural hazards;    GFDS;    MODIS;    GloFAS;   

DOI  :  10.3390/rs71115702

来源: mdpi

【 摘 要 】

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision-making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012–2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS) and the Global Flood Awareness System (GloFAS). Furthermore, we compared the GFDS flood maps with those from NASA’s two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results reveal that: (1) general agreement was found between the GFDS and MODIS flood detection systems, (2) large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and (3) the quantitative validation of global flood disasters in data-sparse regions is highly challenging. Overall, satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large-scale flood monitoring tools.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.