{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T11:02:40Z","timestamp":1768820560118,"version":"3.49.0"},"reference-count":72,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,1,14]],"date-time":"2015-01-14T00:00:00Z","timestamp":1421193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Vegetation resistance influences water flow in floodplains. Characterization of vegetation for hydraulic modeling includes the description of the spatial variability of vegetation type, height and density. In this research, we explored the use of dual polarized Radarsat-2 wide swath mode backscatter coefficients (\u03c3\u00b0) and Landsat 5 TM to derive spatial hydraulic roughness. The spatial roughness parameterization included four steps:  (i) land use classification from Landsat 5 TM; (ii) establishing a relationship between \u03c3\u00b0 statistics and vegetation parameters; (iii) relative surface roughness (Ks) determination from Synthetic Aperture Radar (SAR) backscatter temporal variability; (iv) derivation of the spatial distribution of the spatial hydraulic roughness both from Manning\u2019s roughness coefficient look up table (LUT) and relative surface roughness. Hydraulic simulations were performed using the FLO-2D hydrodynamic model to evaluate model performance under three different hydraulic modeling simulations results with different Manning\u2019s coefficient parameterizations, which includes SWL1, SWL2 and SWL3. SWL1 is simulated water levels with optimum floodplain roughness (np) with channel roughness nc = 0.03 m\u22121\/3\/s; SWL2 is simulated water levels with calibrated values for both floodplain roughness  np = 0.65 m\u22121\/3\/s and channel roughness nc = 0.021 m\u22121\/3\/s; and SWL3 is simulated water levels with calibrated channel roughness nc and spatial Manning\u2019s coefficients as derived with aid of relative surface roughness. The model performance was evaluated using  Nash-Sutcliffe model efficiency coefficient (E) and coefficient of determination (R2), based on water levels measured at a gauging station in the wetland. The overall performance of scenario SWL1 was characterized with E = 0.75 and R2 = 0.95, which was improved in SWL2 to E = 0.95 and R2 = 0.99. When spatially distributed Manning values derived from SAR relative surface values were parameterized in the model, the model also performed well and yielding E = 0.97 and R2 = 0.98. Improved model performance using spatial roughness shows that spatial roughness parameterization can support flood modeling and provide better flood wave simulation over the inundated riparian areas equally as calibrated models.<\/jats:p>","DOI":"10.3390\/rs70100836","type":"journal-article","created":{"date-parts":[[2015,1,14]],"date-time":"2015-01-14T10:33:15Z","timestamp":1421231595000},"page":"836-864","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Use of Radarsat-2 and Landsat TM Images for Spatial Parameterization of Manning\u2019s Roughness Coefficient in Hydraulic Modeling"],"prefix":"10.3390","volume":"7","author":[{"given":"Joseph","family":"Mtamba","sequence":"first","affiliation":[{"name":"Department of Water Resources Engineering, University of Dar es Salaam,  P.O. Box 35131, 14115 Dar es Salaam, Tanzania"},{"name":"Department of Water Resources, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, P.O. Box 6, AA Enschede7500, The Netherlands"}]},{"given":"Rogier","family":"Van der Velde","sequence":"additional","affiliation":[{"name":"Department of Water Resources, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, P.O. Box 6, AA Enschede7500, The Netherlands"}]},{"given":"Preksedis","family":"Ndomba","sequence":"additional","affiliation":[{"name":"Department of Water Resources Engineering, University of Dar es Salaam,  P.O. Box 35131, 14115 Dar es Salaam, Tanzania"}]},{"given":"Vekerdy","family":"Zolt\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Water Resources, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, P.O. Box 6, AA Enschede7500, The Netherlands"},{"name":"Department of Water and Waste Management, Szent Istv\u00e1n University, G\u00f6d\u00f6ll\u0151,  2100 P\u00e1ter K\u00e1roly utca 1., Hungary"}]},{"given":"Felix","family":"Mtalo","sequence":"additional","affiliation":[{"name":"Department of Water Resources Engineering, University of Dar es Salaam,  P.O. Box 35131, 14115 Dar es Salaam, Tanzania"}]}],"member":"1968","published-online":{"date-parts":[[2015,1,14]]},"reference":[{"key":"ref_1","first-page":"110","article-title":"The flood pulse concept in river flood plain systems","volume":"106","author":"Junk","year":"1989","journal-title":"Can. J. Fish. Aquat. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"769","DOI":"10.2307\/1313099","article-title":"The natural flow regime: A new paradigm for riverine conservation and restoration","volume":"47","author":"Poff","year":"1997","journal-title":"BioScience"},{"key":"ref_3","unstructured":"Postel, S.L., and Richter, B. 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