{"title":"Estimation of flood influencing characteristics of watershed and their impact on flooding in data-scarce region","authors":"V. Rana, T. Suryanarayana","doi":"10.1080/19475683.2021.1960603","DOIUrl":null,"url":null,"abstract":"ABSTRACT The research is focused on the integrated use of satellite remote sensing, Geographic Information System (GIS), and extensive field observation techniques for a better understanding of the impacts of watershed characteristics on hydrological processes and floods. It aims to create a methodology for assessing flood hazards and risk on a regional and local scale so that protective measures can be designed. Floods have occurred in the study area for many years, causing serious damage to infrastructure and civic structures. The present study evaluates the linear, aerial and relief morphometric parameters using the Cartosat-1 digital elevation model (30 metres) along with the curve number for assessing the flood influencing characteristics of the Vishwamitri River’s sub-watersheds. The study prioritizes five sub-watersheds as high, medium, and low based on their flood influencing characteristics and compound value, as a result, needs the highest priority for flood mitigation measures. The sub-watersheds I and IV of Vishwamitri watershed have been categorized into high priority, sub-watersheds II and V into moderate priority, and sub-watershed III into low priority. The geologic stage of development and erosion proneness of the watershed is quantified by hypsometric integral bearing value as 0.04, indicating the landscape to be in monadnock phase in landscape evolution indicative of a marked old stage in the basin’s evolution. Moreover, the ability of the rain-on-grid model at the watershed scale to simulate flood events and predict flood-prone areas, considering multiple rain gauge data, which will facilitate more accurate flood inundation where ground-based observational data are unavailable is shown.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"49 1","pages":"397 - 418"},"PeriodicalIF":2.7000,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of GIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19475683.2021.1960603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 7
Abstract
ABSTRACT The research is focused on the integrated use of satellite remote sensing, Geographic Information System (GIS), and extensive field observation techniques for a better understanding of the impacts of watershed characteristics on hydrological processes and floods. It aims to create a methodology for assessing flood hazards and risk on a regional and local scale so that protective measures can be designed. Floods have occurred in the study area for many years, causing serious damage to infrastructure and civic structures. The present study evaluates the linear, aerial and relief morphometric parameters using the Cartosat-1 digital elevation model (30 metres) along with the curve number for assessing the flood influencing characteristics of the Vishwamitri River’s sub-watersheds. The study prioritizes five sub-watersheds as high, medium, and low based on their flood influencing characteristics and compound value, as a result, needs the highest priority for flood mitigation measures. The sub-watersheds I and IV of Vishwamitri watershed have been categorized into high priority, sub-watersheds II and V into moderate priority, and sub-watershed III into low priority. The geologic stage of development and erosion proneness of the watershed is quantified by hypsometric integral bearing value as 0.04, indicating the landscape to be in monadnock phase in landscape evolution indicative of a marked old stage in the basin’s evolution. Moreover, the ability of the rain-on-grid model at the watershed scale to simulate flood events and predict flood-prone areas, considering multiple rain gauge data, which will facilitate more accurate flood inundation where ground-based observational data are unavailable is shown.