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Urban flood susceptibility analysis of Saroor Nagar Watershed of India using Geomatics-based multi-criteria analysis framework.
- Source :
- Environmental Science & Pollution Research; Oct2023, Vol. 30 Issue 49, p107021-107040, 20p
- Publication Year :
- 2023
-
Abstract
- During the monsoon season, flooding is common in several parts of India, and urban areas are becoming more prone to flooding even during less intense rainfall events as a result of the encroachment of waterbodies and natural drainage channels, increased impervious areas, and subsequent decrease in infiltration capabilities. In the years 2000, 2008, 2016, 2019, 2020, and 2021, severe flood events in our study area, the Saroor Nagar urban watershed in Telangana state, caused human loss, economic devastation, and environmental devastation. Although flood risk cannot be completely eliminated, it can be significantly reduced by developing a flood hazard model to identify flood-prone areas in a watershed, which can assist decision makers seeking comprehensive flood risk management. The flood hazard map is created by integrating Geomatics with multi-criteria decision analysis and the analytical hierarchy process (AHP). Topographic wetness index (TWI), digital elevation model (DEM), slope, precipitation, drainage density, distance to waterbody, soil, and land use land cover (LULC) were the flooding causative elements considered in this study. The resulting flood risk map is divided into four distinct categories that reflect flood danger levels of low, moderate, high, and extremely high. The flood risk map revealed that the moderate risk zone decreased from 50.2 to 45.7% of the study area between 2008 and 2020, while the high-risk zone increased from 45.2 to 52.8%. The flood susceptibility map is validated using crowdsourcing techniques. The findings demonstrated that a Geographic Information System (GIS)-based multi-criteria analysis framework for flood hazard analysis could be effectively used to aid disaster management decision-making. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09441344
- Volume :
- 30
- Issue :
- 49
- Database :
- Complementary Index
- Journal :
- Environmental Science & Pollution Research
- Publication Type :
- Academic Journal
- Accession number :
- 173270459
- Full Text :
- https://doi.org/10.1007/s11356-022-24672-4