NDLI: Integrated Remote Sensing and Geographic Information System Based RUSLE Modelling for Estimation of Soil Loss in Western Himalaya, India

Content Provider	Springer Nature Link
Author	Kumar, Amit Devi, Mamta Deshmukh, Benidhar
Copyright Year	2014
Abstract	Soil loss due to water erosion was estimated in Kangra region of western Himalaya using revised universal soil loss equation modelling (RUSLE) in conjunction with Remote Sensing (RS) and Geographic Information Systems (GIS). The various parameters such as rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C) and support practice factor (P) were derived using standard techniques. The study revealed that forest cover, crop land and scrub/grass land constitute 87.4 % of soil erosion susceptible area. The rate of depletion of soil was estimated at 25.63 t/ha/yr. It was highest in stony/barren land (60.3 t/ha/yr) and lowest in case of tea garden (16.09 t/ha/yr). It was felt that there is a need of implementation of soil and water conservation measures in the region to curb the soil loss. The undulating nature of terrain was observed as the main contributing factor for soil erosion. It was concluded that RS and GIS based RUSLE model can be efficiently used in mountainous regions to determine the status and extent of soil erosion.
Starting Page	3307
Ending Page	3317
Page Count	11
File Format	PDF
ISSN	09204741
Journal	Water Resources Management
Volume Number	28
Issue Number	10
e-ISSN	15731650
Language	English
Publisher	Springer Netherlands
Publisher Date	2014-05-27
Publisher Institution	European Water Resources Association (EWRA)
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Conservation practices DEM Length of slope NDVI Rainfall erosivity Soil erodibility Support parameter Soil loss Hydrogeology Hydrology/Water Resources Geotechnical Engineering & Applied Earth Sciences Atmospheric Sciences Civil Engineering Environment
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology Civil and Structural Engineering

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