{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T21:33:28Z","timestamp":1782423208237,"version":"3.54.5"},"reference-count":41,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2014,5,30]],"date-time":"2014-05-30T00:00:00Z","timestamp":1401408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Water"],"abstract":"<jats:p>This study aims at providing expertise for preparing public-based flood mapping and estimating flood risks in growing urban areas. To model and predict the magnitude of flood risk areas, an integrated Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) analysis techniques are used for the case of Eldoret Municipality in Kenya. The flood risk vulnerability mapping follows a multi-parametric approach and integrates some of the flooding causative factors such as rainfall distribution, elevation and slope, drainage network and density, land-use\/land-cover and soil type. From the vulnerability mapping, urban flood risk index (UFRI) for the case study area, which is determined by the degree of vulnerability and exposure is also derived. The results are validated using flood depth measurements, with a minimum average difference of 0.01 m and a maximum average difference of 0.37 m in depth of observed flooding in the different flood prone areas. Similarly with respect to area extents, a maximum error of not more than 8% was observed in the highly vulnerable flood zones. In addition, the Consistency Ratio which shows an acceptable level of 0.09 was calculated and further validated the strength of the proposed approach.<\/jats:p>","DOI":"10.3390\/w6061515","type":"journal-article","created":{"date-parts":[[2014,5,30]],"date-time":"2014-05-30T12:00:34Z","timestamp":1401451234000},"page":"1515-1545","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":537,"title":["Urban Flood Vulnerability and Risk Mapping Using Integrated Multi-Parametric AHP and GIS: Methodological Overview and Case Study Assessment"],"prefix":"10.3390","volume":"6","author":[{"given":"Yashon","family":"Ouma","sequence":"first","affiliation":[{"name":"Department of Civil and Structural Engineering, Moi University, P.O. Box 3900,  Eldoret 30100, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryutaro","family":"Tateishi","sequence":"additional","affiliation":[{"name":"Centre for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi, Inage,  Chiba 263-8522, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TGRS.2010.2057513","article-title":"Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins","volume":"49","author":"Khan","year":"2011","journal-title":"IEEE Trans. Geosci. 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