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...
| Main Author: | Roy, Uttam K., |
|---|---|
| Other Authors: | Majumder, Mrinmoy,, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
2016.
|
| Physical Description: |
1 online resource (x, 89 pages) : illustrations (some color). |
| Series: |
SpringerBriefs in water science and technology.
|
| Subjects: |
| Summary: |
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. |
|---|---|
| Item Description: |
Includes bibliographical references. 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. |
| Physical Description: |
1 online resource (x, 89 pages) : illustrations (some color). |
| Bibliography: |
Includes bibliographical references. |
| ISBN: |
9789812873446 9812873449 |
| ISSN: |
2194-7244. |