Assessment of sustainability index for rural water management using ANN
The current study proposes a sustainability index (SI) measure based on artificial neural networks (ANN) and globally accepted parameters. Some of the available methods for SI measurement are multi-criteria analysis, external costs, energy analysis, and ecological footprint methods. However, validit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-02-01
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| Series: | Water Supply |
| Subjects: | |
| Online Access: | http://ws.iwaponline.com/content/22/2/1421 |
| _version_ | 1828490602146168832 |
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| author | R. Raghavendra Kumar Gaurav Kumar Rajiv Gupta |
| author_facet | R. Raghavendra Kumar Gaurav Kumar Rajiv Gupta |
| author_sort | R. Raghavendra Kumar |
| collection | DOAJ |
| description | The current study proposes a sustainability index (SI) measure based on artificial neural networks (ANN) and globally accepted parameters. Some of the available methods for SI measurement are multi-criteria analysis, external costs, energy analysis, and ecological footprint methods. However, validity remains a concern due to a system's needs, criteria, and requirements. Generally, sustainability is assessed in economic, environmental, and social issues, which varies across regions and countries. Most of the studies accept sub-indices but to a limited extent. Therefore, the proposed study develops an SI evaluation method based on the idea of multi-sustainability incorporating operations, institutions, risks, and climate factors besides economic, environmental, and social issues. All these issues might not be applicable to a single project but may help to develop a complete index when applied. The present study considered different scenarios in building a method to calculate SI using ANN. The results obtained by the ANN model for various input parameters helped to identify the best water conservation strategy. Sensitivity analysis was also performed to determine the uncertainty contribution/significance of the input variables for the water scarcity in the study region. The developed model in the study is tested on a rural water management system. HIGHLIGHTS
Numerous approaches were performed regarding Sustainability Index (SI), but in the current study SI using multiple factors was assessed.;
Artificial Neural Networks (ANN) model was trained and developed for future scenarios.;
Current research work has a case study application on a community in a village.;
Determination of SI was helpful in following and setting up a rainwater harvesting method at a selected village.; |
| first_indexed | 2024-12-11T10:46:21Z |
| format | Article |
| id | doaj.art-a5ad139bbf004718a129704bd86d6015 |
| institution | Directory Open Access Journal |
| issn | 1606-9749 1607-0798 |
| language | English |
| last_indexed | 2024-12-11T10:46:21Z |
| publishDate | 2022-02-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Supply |
| spelling | doaj.art-a5ad139bbf004718a129704bd86d60152022-12-22T01:10:27ZengIWA PublishingWater Supply1606-97491607-07982022-02-012221421143310.2166/ws.2021.346346Assessment of sustainability index for rural water management using ANNR. Raghavendra Kumar0Gaurav Kumar1Rajiv Gupta2 Department of Civil Engineering, Birla Institute of Technology & Science Pilani, Jhunjhunu, Rajasthan 333031, India Department of Civil Engineering, Birla Institute of Technology & Science Pilani, Jhunjhunu, Rajasthan 333031, India Department of Civil Engineering, Birla Institute of Technology & Science Pilani, Jhunjhunu, Rajasthan 333031, India The current study proposes a sustainability index (SI) measure based on artificial neural networks (ANN) and globally accepted parameters. Some of the available methods for SI measurement are multi-criteria analysis, external costs, energy analysis, and ecological footprint methods. However, validity remains a concern due to a system's needs, criteria, and requirements. Generally, sustainability is assessed in economic, environmental, and social issues, which varies across regions and countries. Most of the studies accept sub-indices but to a limited extent. Therefore, the proposed study develops an SI evaluation method based on the idea of multi-sustainability incorporating operations, institutions, risks, and climate factors besides economic, environmental, and social issues. All these issues might not be applicable to a single project but may help to develop a complete index when applied. The present study considered different scenarios in building a method to calculate SI using ANN. The results obtained by the ANN model for various input parameters helped to identify the best water conservation strategy. Sensitivity analysis was also performed to determine the uncertainty contribution/significance of the input variables for the water scarcity in the study region. The developed model in the study is tested on a rural water management system. HIGHLIGHTS Numerous approaches were performed regarding Sustainability Index (SI), but in the current study SI using multiple factors was assessed.; Artificial Neural Networks (ANN) model was trained and developed for future scenarios.; Current research work has a case study application on a community in a village.; Determination of SI was helpful in following and setting up a rainwater harvesting method at a selected village.;http://ws.iwaponline.com/content/22/2/1421artificial intelligencerural areasscenario developmentsustainability indexwater resource management |
| spellingShingle | R. Raghavendra Kumar Gaurav Kumar Rajiv Gupta Assessment of sustainability index for rural water management using ANN Water Supply artificial intelligence rural areas scenario development sustainability index water resource management |
| title | Assessment of sustainability index for rural water management using ANN |
| title_full | Assessment of sustainability index for rural water management using ANN |
| title_fullStr | Assessment of sustainability index for rural water management using ANN |
| title_full_unstemmed | Assessment of sustainability index for rural water management using ANN |
| title_short | Assessment of sustainability index for rural water management using ANN |
| title_sort | assessment of sustainability index for rural water management using ann |
| topic | artificial intelligence rural areas scenario development sustainability index water resource management |
| url | http://ws.iwaponline.com/content/22/2/1421 |
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