DOI: 10.5281/zenodo.4723395
title: Ecuador Flash Flood Susceptibility Index (FFSI) based on catchment hypsometry, drainage and surface characteristics

description: The flash-flood susceptibility index (FFSI) represents the relative potential of Ecuador catchments to generate a flash flood when significant local rainfall occurs. The FFSI is calculated for each HydroSHEDS level 12 catchment units (Lehner et al. 2008, Yamazaki et al. 2014) of Ecuador, using a weighted mean of 7 commonly used flash flood drivers related to the hypsometry, drainage network, and surface properties of catchments. <strong>- Hypsometry characteristics :</strong> 1-catchment mean slope and 2- mean curvature. Derived from NASA's Shuttle Radar Topography Mission (SRTM) 90 m Digital Elevation Model (DEM) v4.1 (Jarvis et al. 2008), and cleaned using the Zevenbergen and Thorne (1987) 2nd-degree polynomial adjustment algorithm. <strong>- Drainage network characteristics : </strong>1- Upslope contributing area of a basin, 2- Cumulative drainage density and 3- mean drainage strahler order. Extracted from the World Wildlife Fund (WWF) HydroSHEDS v1 global data, at a resolution of 15 arc-seconds, level-12 hydrological basins (Lehner et al. 2008, Yamazaki et al. 2014) and river routing networks (Lehner and Grill 2013). - <strong>Surface properties: </strong>1- mean Land Use Land Cover (LULC) Index calculated from Copernicus Global Land Operation products (Buchhorn et al., 2020) and 2- the mean ISRIC SoilGrid Sand Fraction to account for the infiltration potential of soils (Hengl et al. 2017). The weights of each indicators have been estimated from PCA analysis after normalization of the indicators For more details on the methods, see Kruczkiewicz et al. 2021. The final normalized FFSI results is available, as well as the discretized FFSI into an index (1-10) computed for this case study using a rule-based approach specific to the context of Ecuador and the normalized FFSI spatial distribution. The data are downloadable as ESRI Shapefile format. For each of the 1903 HydroSHED (level12) catchment of Ecuador, it contains the HydroSHED unique ID field, the 7 raw indicators, the final normalized FFSI and the reclassified FFSI (1-10).
description: This research was funded by the National Aeronautics and Space Administration, grant number 80NSSC18K0342 and 80NSSC18K1693. Kruczkiewicz, A., Bucherie, A., Ayala, F., Hultquist, C., Vergara, H., Mason, S., … de Sherbinin, A. (2021). Development of a flash flood confidence index from disaster reports and geophysical susceptibility. Remote Sensing, 13(14). https://doi.org/10.3390/rs13142764
description: {"references": ["Lehner, B., Verdin, K. and Jarvis, A.: HydroSHEDS technical documentation, version 1.0, World Wildl. Fund US, Washington, DC, 1\u201327, 2006.", "Yamazaki, D., O'Loughlin, F., Trigg, M. A., Miller, Z. F., Pavelsky, T. M. and Bates, P. D.: Development of the Global Width Database for Large Rivers, Water Resour. Res., 50(4), 3467\u20133480, doi:https://doi.org/10.1002/2013WR014664, 2014.", "Jarvis, A., Reuter, H., Nelson, A. and Guevara, E.: Hole-filled SRTM for the globe version 3, from the CGIAR-CSI SRTM 90m database, See http//srtm. csi. cgiar. org, 2008.", "Buchhorn, M., Lesiv, M., Tsendbazar, N.-E., Bertels, L. and Smets, B.: Copernicus Global Land Cover Layers\u2014Collection 2, , doi:10.5281/ZENODO.3243509, 2020.", "Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagoti\u0107, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S. and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS One, 12(2), e0169748 [online] Available from: https://doi.org/10.1371/journal.pone.0169748, 2017."]}