{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T12:36:19Z","timestamp":1784550979714,"version":"3.55.0"},"reference-count":26,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T00:00:00Z","timestamp":1666569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Oceanic and Atmospheric Administration (NOAA) through the Cooperative Institute for Research to Operations in Hydrology (CIROH)","award":["A22-0305"],"award-info":[{"award-number":["A22-0305"]}]},{"name":"University of Alabama CyberSeed grant","award":["A22-0305"],"award-info":[{"award-number":["A22-0305"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Floodwater Depth Estimation Tool (FwDET) calculates water depth from a remote sensing-based inundation extent layer and a Digital Elevation Model (DEM). FwDET\u2019s low data requirement and high computational efficiency allow rapid and large-scale calculation of floodwater depth. Local biases in FwDET predictions, often manifested as sharp transitions or stripes in the water depth raster, can be attributed to spatial or resolution mismatches between the inundation map and the DEM. To alleviate these artifacts, we are introducing a boundary cell smoothing and slope filtering procedure in version 2.1 of FwDET (FwDET2.1). We present an optimization analysis that quantifies the effect of differing parameterization on the resulting water depth map. We then present an extensive intercomparison analysis in which 16 DEMs are used as input for FwDET Google Earth Engine (FwDET-GEE) implementation. We compare FwDET2.1 to FwDET2.0 using a simulated flood and a large remote sensing derived flood map (Irrawaddy River in Myanmar). The results show that FwDET2.1 results are sensitive to the smoothing and filtering values for medium and coarse resolution DEMs, but much less sensitive when using a finer resolution DEM (e.g., 10 m NED). A combination of ten smoothing iterations and a slope threshold of 0.5% was found to be optimal for most DEMs. The accuracy of FwDET2.1 improved when using finer resolution DEMs except for the MERIT DEM (90 m), which was found to be superior to all the 30 m global DEMs used.<\/jats:p>","DOI":"10.3390\/rs14215313","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"5313","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Sensitivity of Remote Sensing Floodwater Depth Calculation to Boundary Filtering and Digital Elevation Model Selections"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3354-2864","authenticated-orcid":false,"given":"Sagy","family":"Cohen","sequence":"first","affiliation":[{"name":"Department of Geography, The University of Alabama, Tuscaloosa, AL 35487, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5724-4482","authenticated-orcid":false,"given":"Brad G.","family":"Peter","sequence":"additional","affiliation":[{"name":"Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8805-0923","authenticated-orcid":false,"given":"Arjen","family":"Haag","sequence":"additional","affiliation":[{"name":"Deltares, 2600 MH Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dinuke","family":"Munasinghe","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8128-7530","authenticated-orcid":false,"given":"Nishani","family":"Moragoda","sequence":"additional","affiliation":[{"name":"Department of Geography, The University of Alabama, Tuscaloosa, AL 35487, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anuska","family":"Narayanan","sequence":"additional","affiliation":[{"name":"Department of Geography, The University of Alabama, Tuscaloosa, AL 35487, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sera","family":"May","sequence":"additional","affiliation":[{"name":"Department of Geography, The University of Alabama, Tuscaloosa, AL 35487, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.envsci.2018.03.014","article-title":"A global network for operational flood risk reduction","volume":"84","author":"Alfieri","year":"2018","journal-title":"Environ. 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