Titlebook: Vulnerability of Watersheds to Climate Change Assessed by Neural Network and Analytical Hierarchy Pr; Uttam Roy,Mrinmoy Majumder Book 2016

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Results and Discussions,Yenisei River Basin were found to be the most and the least vulnerable watersheds, but in face of climate change River Mississippi in the USA becomes the most vulnerable in B2 scenario and the least vulnerable in A2 scenario.

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Conclusion,ters were ignored. This two limitations can be overcome by the introduction of uniformity while rating the watersheds. The temporal variations can be removed by the introduction of some time parameters in the objective function.

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Book 2016 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.

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Climate Change and Its Impacts,users to predict globally and locally the future climatic parameters like rainfall and temperature. Intergovernmental Panel on Climate Change Scenarios was developed so that the status of the word can be simulated based on the different scenarios like industrial, environmental and mixed.

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2194-7244 watersheds. Analytical Hierarchy Process and Artificial Neural Networks are used in a cascading manner to develop the model for prediction of the vulnerability index.978-981-287-343-9978-981-287-344-6Series ISSN 2194-7244 Series E-ISSN 2194-7252

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