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Title: Landuse change impact on sub-watersheds prioritization by analytical hierarchy process (AHP)
Authors: Kundu S.
Khare, Deepak
Mondal A.
Published in: Ecological Informatics
Abstract: Landuse change analysis is considered as elementary in planning and land management of a basin. The present study provides information of change in landuse in 1990, 2000, 2011, and future prediction of the year 2020, 2030, 2040 and 2050 of different sub-watersheds within a basin, which is a part of the Narmada river basin in central India. The major objectives involve landuse prediction by Markov Chain model and sub-watershed prioritization using analytical hierarchy process (AHP) to identify and manage environmentally unstable areas in future. Different landuse categories are used as factors in prioritization analysis. Landuse of 2011 indicates a transition of about 312 km2 of forest area to agricultural land and 10.64 km2 to settlement in 2020, which increases to 678 km2 and 21.29 km2 in 2050 respectively. There is also a transition of forest to scattered forest and grasslands and increase in the areas of the rocky surface. AHP is applied to identify sub-watersheds of highest priority, which indicates the sub-watersheds 5 and 6 are of very high priority in 2011 along with 1, 2, 3, 4 and 7 that are in most places plain areas used for agriculture and settlements. Sub-watersheds 8 and 9, which are forest areas, are observed to be of medium to low priority in future. However, 2050 projects high priority for all the sub-watersheds that calls for efficient landuse management and decision. Most of the northern sub-watersheds of 1 to 7 and 12 of south need high priority. © 2017 Elsevier B.V.
Citation: Ecological Informatics (2017), 42(): 100-113
Issue Date: 2017
Publisher: Elsevier B.V.
Keywords: Analytical hierarchy process (AHP)
Future prediction
Landuse change
Markov Chain model
Sub-watershed prioritization
ISSN: 15749541
Author Scopus IDs: 56185410500
Author Affiliations: Kundu, S., School of Earth Ocean and Environment, University of South Carolina, Columbia, SC, United States
Khare, D., Department of Water Resources Development & Management, Indian Institute of Technology, Roorkee, India
Mondal, A., School of Earth Ocean and Environment, University of South Carolina, Columbia, SC, United States
Funding Details: The authors are thankful to National Remote Sensing Centre (NRSC) of the Government of India for the IRS data and USGS of the Government of U.S.A. for the Landsat. The authors also express sincere thanks to the University Grant Commission (UGC) ( 20-06/20
Corresponding Author: Mondal, A.; School of Earth Ocean and Environment, University of South CarolinaUnited States; email:
Appears in Collections:Journal Publications [WR]

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