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Vulnerability of watersheds to clima...

Roy, Uttam.

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Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process

Record Type:	Electronic resources : Monograph/item
Title/Author:	Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process/ by Uttam Roy, Mrinmoy Majumder.
Author:	Roy, Uttam.
other author:	Majumder, Mrinmoy.
Published:	Singapore :Springer Singapore : : 2016.,
Description:	x, 89 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Climate Change and its Impacts -- Watershed Vulnerabilities -- Methodology -- Results and Discussions.
Contained By:	Springer eBooks
Subject:	Watersheds. -
Online resource:	http://dx.doi.org/10.1007/978-981-287-344-6
ISBN:	9789812873446$q(electronic bk.)

Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process
Roy, Uttam.

Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process[electronic resource] /by Uttam Roy, Mrinmoy Majumder. - Singapore :Springer Singapore :2016. - x, 89 p. :ill., digital ;24 cm. - SpringerBriefs in water science and technology,2194-7244. - SpringerBriefs in water science and technology..

Introduction -- Climate Change and its Impacts -- Watershed Vulnerabilities -- Methodology -- Results and Discussions.

The increase in GHG gases in the atmosphere due to expansions in industrial and vehicular concentration is attributed to warming of the climate world wide. The resultant change in climatic pattern can induce abnormalities in the hydrological cycle. As a result, the regular functionality of river watersheds will also be affected. This Brief highlights a new methodology to rank the watersheds in terms of its vulnerability to change in climate. This Brief introduces a Vulnerability Index which will be directly proportional to the climatic impacts of the watersheds. Analytical Hierarchy Process and Artificial Neural Networks are used in a cascading manner to develop the model for prediction of the vulnerability index.

ISBN: 9789812873446$q(electronic bk.)

Standard No.: 10.1007/978-981-287-344-6doiSubjects--Topical Terms:

544815
Watersheds.

LC Class. No.: GB980

Dewey Class. No.: 333.73

Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process
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245 1 0 $a Vulnerability of watersheds to climate change assessed by neural network and analytical hierarchy process $h [electronic resource] / $c by Uttam Roy, Mrinmoy Majumder.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2016.
300 $a x, 89 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in water science and technology, $x 2194-7244
505 0 $a Introduction -- Climate Change and its Impacts -- Watershed Vulnerabilities -- Methodology -- Results and Discussions.
520 $a The increase in GHG gases in the atmosphere due to expansions in industrial and vehicular concentration is attributed to warming of the climate world wide. The resultant change in climatic pattern can induce abnormalities in the hydrological cycle. As a result, the regular functionality of river watersheds will also be affected. This Brief highlights a new methodology to rank the watersheds in terms of its vulnerability to change in climate. This Brief introduces a Vulnerability Index which will be directly proportional to the climatic impacts of the watersheds. Analytical Hierarchy Process and Artificial Neural Networks are used in a cascading manner to develop the model for prediction of the vulnerability index.
650 0 $a Watersheds. $3 544815
650 0 $a Watershed ecology. $3 900597
650 0 $a Climatology. $3 544649
650 1 4 $a Energy. $3 876794
650 2 4 $a Renewable and Green Energy. $3 928108
650 2 4 $a Hydrology/Water Resources. $3 2055722
650 2 4 $a Climate Change/Climate Change Impacts. $3 2036591
650 2 4 $a Energy Technology. $3 1001977
650 2 4 $a Water Industry/Water Technologies. $3 2056740
700 1 $a Majumder, Mrinmoy. $3 1085817
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856 4 0 $u http://dx.doi.org/10.1007/978-981-287-344-6
950 $a Earth and Environmental Science (Springer-11646)