A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models
Mapping vulnerability of water resources (VWR) is crucial for the sustainable management of water resources, particularly in freshwater-scarce coastal plains. This research aims to construct a coupled novel framework technique for assessing VWR using hydrochemical properties and data-driven models,...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier Ltd.
2022
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| Online Access: | http://eprints.utm.my/102956/1/AbuRezaMdTowfiqul2022_ACoupledNovelFrameworkforAssessingVulnerability.pdf |
| _version_ | 1796867366028574720 |
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| author | Md. Towfiqul Islam, Abu Reza Pal, Subodh Chandra Chakrabortty, Rabin M. Idris, Abubakr Salam, Roquia Islam, Md. Saiful Zahid, Anwar Shahid, Shamsuddin Ismail, Zulhilmi |
| author_facet | Md. Towfiqul Islam, Abu Reza Pal, Subodh Chandra Chakrabortty, Rabin M. Idris, Abubakr Salam, Roquia Islam, Md. Saiful Zahid, Anwar Shahid, Shamsuddin Ismail, Zulhilmi |
| author_sort | Md. Towfiqul Islam, Abu Reza |
| collection | ePrints |
| description | Mapping vulnerability of water resources (VWR) is crucial for the sustainable management of water resources, particularly in freshwater-scarce coastal plains. This research aims to construct a coupled novel framework technique for assessing VWR using hydrochemical properties and data-driven models, e.g., Boosted Regression Tree (BRT), Random Forest (RF) with Support Vector Regression (SVR) as a classic model through k-fold cross-validation (CV). A total of 380 groundwater samples were collected during the dry and wet seasons to construct an inventory map. The models were used to demarcate the vulnerable zones from sixteen vulnerability causal factors using a 4-fold CV approach. Obtained results were validated using the area under the curve (AUC) of receiver operating characteristic (ROC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The results showed the excellent capability of the models to identify the VWR zones in the coastal plain. The RF model showed higher performance (AUC = 0.93, NPV = 0.89, PPV = 0.86, specificity = 0.85, sensitivity = 0.90) than others models. The south-central and southwestern areas had a higher VWR due to salinity, NO3−, F− and As pollution in the coastal plain. Groundwater As, NO3− and F− pollution should be urgently monitored and possibly controlled in areas of high VWR. Decision-makers and water managers can utilize the VWR maps, derived usinga coupled novel framework, to achieve sustainable groundwater management and prevent anthropogenic activities at the regional scale. |
| first_indexed | 2024-03-05T21:26:09Z |
| format | Article |
| id | utm.eprints-102956 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T21:26:09Z |
| publishDate | 2022 |
| publisher | Elsevier Ltd. |
| record_format | dspace |
| spelling | utm.eprints-1029562023-10-12T08:24:25Z http://eprints.utm.my/102956/ A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models Md. Towfiqul Islam, Abu Reza Pal, Subodh Chandra Chakrabortty, Rabin M. Idris, Abubakr Salam, Roquia Islam, Md. Saiful Zahid, Anwar Shahid, Shamsuddin Ismail, Zulhilmi TC Hydraulic engineering. Ocean engineering Mapping vulnerability of water resources (VWR) is crucial for the sustainable management of water resources, particularly in freshwater-scarce coastal plains. This research aims to construct a coupled novel framework technique for assessing VWR using hydrochemical properties and data-driven models, e.g., Boosted Regression Tree (BRT), Random Forest (RF) with Support Vector Regression (SVR) as a classic model through k-fold cross-validation (CV). A total of 380 groundwater samples were collected during the dry and wet seasons to construct an inventory map. The models were used to demarcate the vulnerable zones from sixteen vulnerability causal factors using a 4-fold CV approach. Obtained results were validated using the area under the curve (AUC) of receiver operating characteristic (ROC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The results showed the excellent capability of the models to identify the VWR zones in the coastal plain. The RF model showed higher performance (AUC = 0.93, NPV = 0.89, PPV = 0.86, specificity = 0.85, sensitivity = 0.90) than others models. The south-central and southwestern areas had a higher VWR due to salinity, NO3−, F− and As pollution in the coastal plain. Groundwater As, NO3− and F− pollution should be urgently monitored and possibly controlled in areas of high VWR. Decision-makers and water managers can utilize the VWR maps, derived usinga coupled novel framework, to achieve sustainable groundwater management and prevent anthropogenic activities at the regional scale. Elsevier Ltd. 2022-02 Article PeerReviewed application/pdf en http://eprints.utm.my/102956/1/AbuRezaMdTowfiqul2022_ACoupledNovelFrameworkforAssessingVulnerability.pdf Md. Towfiqul Islam, Abu Reza and Pal, Subodh Chandra and Chakrabortty, Rabin and M. Idris, Abubakr and Salam, Roquia and Islam, Md. Saiful and Zahid, Anwar and Shahid, Shamsuddin and Ismail, Zulhilmi (2022) A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models. Journal of Cleaner Production, 336 (130407). pp. 1-15. ISSN 0959-6526 http://dx.doi.org/10.1016/j.jclepro.2022.130407 DOI: 10.1016/j.jclepro.2022.130407 |
| spellingShingle | TC Hydraulic engineering. Ocean engineering Md. Towfiqul Islam, Abu Reza Pal, Subodh Chandra Chakrabortty, Rabin M. Idris, Abubakr Salam, Roquia Islam, Md. Saiful Zahid, Anwar Shahid, Shamsuddin Ismail, Zulhilmi A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title | A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title_full | A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title_fullStr | A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title_full_unstemmed | A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title_short | A coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data-driven models |
| title_sort | coupled novel framework for assessing vulnerability of water resources using hydrochemical analysis and data driven models |
| topic | TC Hydraulic engineering. Ocean engineering |
| url | http://eprints.utm.my/102956/1/AbuRezaMdTowfiqul2022_ACoupledNovelFrameworkforAssessingVulnerability.pdf |
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