Next Article in Journal
Evaluation of Satellite and Reanalysis Soil Moisture Products over Southwest China Using Ground-Based Measurements
Next Article in Special Issue
Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices
Previous Article in Journal
Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications
Previous Article in Special Issue
Detection and Delineation of Localized Flooding from WorldView-2 Multispectral Data
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(11), 15702-15728; doi:10.3390/rs71115702

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

1
European Commission, Joint Research Centre, Ispra 21027, Italy
2
Faculty of Geosciences, Utrecht University, Utrecht 3508, The Netherlands
3
Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, CO 80309, USA
4
European Centre For medium-range Weather Forecast, Reading RG2 9AX, UK
5
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Guy J-P. Schumann, Magaly Koch and Prasad S. Thenkabail
Received: 25 August 2015 / Revised: 9 November 2015 / Accepted: 17 November 2015 / Published: 23 November 2015
(This article belongs to the Special Issue Remote Sensing in Flood Monitoring and Management)
View Full-Text   |   Download PDF [2081 KB, uploaded 23 November 2015]   |  

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. 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. View Full-Text
Keywords: Global hydrology; flood detection; flood monitoring; flood forecasting; disaster response; natural hazards; GFDS; MODIS; GloFAS Global hydrology; flood detection; flood monitoring; flood forecasting; disaster response; natural hazards; GFDS; MODIS; GloFAS
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

  • Supplementary File 1:

    default (ZIP, 8340 KB)

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Revilla-Romero, B.; Hirpa, F.A.; Pozo, J.T.-D.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; De Groeve, T. On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions. Remote Sens. 2015, 7, 15702-15728.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top