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Groundwater augmentation through the site selection of floodwater spreading using a data mining approach (case study : Mashhad Plain, Iran)

Naghibi, Seyed Amir ; Vafakhah, Mehdi ; Hashemi, Hossein LU orcid ; Pradhan, Biswajeet and Alavi, Seyed Jalil (2018) In Water 10(10).
Abstract

It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for... (More)

It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Artificial recharge, Data mining, Floodwater spreading, GIS, Groundwater
in
Water
volume
10
issue
10
article number
1405
publisher
MDPI AG
external identifiers
  • scopus:85054711916
ISSN
2073-4441
DOI
10.3390/w10101405
language
English
LU publication?
yes
id
f0c0cb1a-f84b-4465-892b-6c4926f021a0
date added to LUP
2018-10-30 13:08:27
date last changed
2023-09-08 10:21:47
@article{f0c0cb1a-f84b-4465-892b-6c4926f021a0,
  abstract     = {{<p>It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.</p>}},
  author       = {{Naghibi, Seyed Amir and Vafakhah, Mehdi and Hashemi, Hossein and Pradhan, Biswajeet and Alavi, Seyed Jalil}},
  issn         = {{2073-4441}},
  keywords     = {{Artificial recharge; Data mining; Floodwater spreading; GIS; Groundwater}},
  language     = {{eng}},
  number       = {{10}},
  publisher    = {{MDPI AG}},
  series       = {{Water}},
  title        = {{Groundwater augmentation through the site selection of floodwater spreading using a data mining approach (case study : Mashhad Plain, Iran)}},
  url          = {{http://dx.doi.org/10.3390/w10101405}},
  doi          = {{10.3390/w10101405}},
  volume       = {{10}},
  year         = {{2018}},
}