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2018 | OriginalPaper | Buchkapitel

Flood Assessment of Lolab Valley from Watershed Characterization Using Remote Sensing and GIS Techniques

verfasst von : Mannan Bashir Wani, Syed Ahmad Ali, Umair Ali

Erschienen in: Hydrologic Modeling

Verlag: Springer Singapore

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Abstract

The estimation of basin characteristics from the morphometric parameters assists in understanding the physical behavior of the watershed with respect to flooding. The remote sensing and geographical information system (GIS) are used for extraction of drainage boundary and order using ASTER digital elevation model (DEM), to evaluate the drainage characteristics. Additionally, sub-watershed-wise drainage parameters were analyzed to delineate the major influencing catchments with respect to flooding. The morphometric analysis for all the twelve sub-watersheds of the Lolab basin reveals that the sub-watersheds LSB 2, 4, 5, 10, 11 and LSB 12 are having the greater tendency to peak discharge in a short period of time because of high relief ratio (Rh), high ruggedness number, and less time of concentration (Tc). The sub-watersheds LSB1 and LSB11 having the highest drainage density (Dd), stream frequency (Fs), mean bifurcation ratio (Rbm), and infiltration number (If) cause greater runoff influence on the mainstream in the catchment. The LSB 3, 6 and LSB 7 sub-watersheds having higher form factor (Ff), medium drainage density (Dd), texture ratio (T), relief ratio (Rh), and time of concentration (Tc) cause moderate runoff influence toward mainstream. The study points out that DEM used in GIS environment for systematic analysis of drainage parameters offers valuable information about Lolab Basin with regard to flood assessment. This work will help in mitigating the hazard caused by flooding with respect to nature and human society. Thus, drainage characterization using remote sensing and GIS has made substantial contribution in flood monitoring and damage assessment.

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Metadaten
Titel
Flood Assessment of Lolab Valley from Watershed Characterization Using Remote Sensing and GIS Techniques
verfasst von
Mannan Bashir Wani
Syed Ahmad Ali
Umair Ali
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-5801-1_26