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

• 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: Energy.; Renewable energy resources.; Hydrology.; Water-supply.; Climate change.; Electric power production.; Renewable energy sources.; Alternate energy sources.; Green energy industries.; Renewable and Green Energy.; Hydrology/Water Resources.; Climate Change/Climate Change Impacts.; Energy Technology.; Water Industry/Water Technologies.
• Φυσική περιγραφή: X, 89 p. 58 illus., 5 illus. in color. online resource.
• ISBN: 9789812873446
• ISSN: 2194-7244

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.