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

Abstract

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. OPEN ACCESSRemote Sens. 2015, 7 15703Overall, 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.

Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets

“…For a few decades, satellite remote sensing (SRS) has opened up new avenues for the development of spatial hydrology (Cui et al, 2018;Engman & Gurney, 1991;Lettenmaier et al, 2015;McCabe et al, 2017;Mendoza et al, 2002;Pasetto et al, 2018;Schmugge et al, 2002). The increasing and unprecedented availability of SRS data at increasingly finer spatial and temporal resolutions has triggered the development of large-domain water management applications including flood and drought monitoring (Hapuarachchi et al, 2011;Klemas, 2014;Revilla-Romero et al, 2015;Senay et al, 2015;Sheffield et al, 2012;Su et al, 2017;Teng et al, 2017;Wu et al, 2014). The use of SRS data in water resources monitoring is promising, and it has led to an increasing number of studies on a variety of topics in hydrology, including precipitation, evaporation, and soil moisture estimation (Cazenave et al, 2016;Chen & Wang, 2018;Cui et al, 2019;National Academies of Sciences, Engineering, and Medicine, 2019;Schultz & Engman, 2012).…”

Estimating Floodwater Depths from Flood Inundation Maps and Topography

“…Near-real-time observations of flood extent are useful for first responders, relief agencies, civil leaders, and recovery managers (Horritt et al, 2007;Merz et al, 2007;Schumann et al, 2010;Mason et al, 2012). Detailed maps of past flood events can be useful for flood risk policymakers as well as for scientists developing and maintaining modeling-based flood prediction and analysis applications (Hostache et al, 2009;Revilla-Romero et al, 2015).…”

The Effect of Reference Climatology on Global Flood Forecasting

“…Second, the spatial location of the flood event might be inaccurately matched with the flood point on the river network in the forecasting model (Revilla-Romero et al 2015b). The spatial extent of the area affected by the floods (which is not necessarily flooded area) was estimated by the DFO based on information acquired from news sources (Brakenridge 2014).…”