Vulnerability of Watersheds to Climate Change Assessed by Neural Network and Analytical Hierarchy Process

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 wat...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Roy, Uttam (Συγγραφέας), Majumder, Mrinmoy (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2016.
Σειρά:SpringerBriefs in Water Science and Technology,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 02897nam a22005775i 4500
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024 7 |a 10.1007/978-981-287-344-6  |2 doi 
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100 1 |a Roy, Uttam.  |e author. 
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. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2016. 
300 |a X, 89 p. 58 illus., 5 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
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 Energy. 
650 0 |a Renewable energy resources. 
650 0 |a Hydrology. 
650 0 |a Water-supply. 
650 0 |a Climate change. 
650 0 |a Electric power production. 
650 0 |a Renewable energy sources. 
650 0 |a Alternate energy sources. 
650 0 |a Green energy industries. 
650 1 4 |a Energy. 
650 2 4 |a Renewable and Green Energy. 
650 2 4 |a Hydrology/Water Resources. 
650 2 4 |a Climate Change/Climate Change Impacts. 
650 2 4 |a Energy Technology. 
650 2 4 |a Water Industry/Water Technologies. 
700 1 |a Majumder, Mrinmoy.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9789812873439 
830 0 |a SpringerBriefs in Water Science and Technology,  |x 2194-7244 
856 4 0 |u http://dx.doi.org/10.1007/978-981-287-344-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-EES 
950 |a Earth and Environmental Science (Springer-11646)