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Cartografía del potencial de agua subterránea utilizando un nuevo modelo de conjuntos de minería de datos

Kordestani, Mojtaba Dolat; Naghibi, Seyed Amir LU ; Hashemi, Hossein LU ; Ahmadi, Kourosh; Kalantar, Bahareh and Pradhan, Biswajeet (2019) In Hydrogeology Journal 27(1). p.211-224
Abstract

Freshwater scarcity is an ever-increasing problem throughout the arid and semi-arid countries, and it often results in poverty. Thus, it is necessary to enhance understanding of freshwater resources availability, particularly for groundwater, and to be able to implement functional water resources plans. This study introduces a novel statistical approach combined with a data-mining ensemble model, through implementing evidential belief function and boosted regression tree (EBF-BRT) algorithms for groundwater potential mapping of the Lordegan aquifer in central Iran. To do so, spring locations are determined and partitioned into two groups for training and validating the individual and ensemble methods. In the next step, 12... (More)

Freshwater scarcity is an ever-increasing problem throughout the arid and semi-arid countries, and it often results in poverty. Thus, it is necessary to enhance understanding of freshwater resources availability, particularly for groundwater, and to be able to implement functional water resources plans. This study introduces a novel statistical approach combined with a data-mining ensemble model, through implementing evidential belief function and boosted regression tree (EBF-BRT) algorithms for groundwater potential mapping of the Lordegan aquifer in central Iran. To do so, spring locations are determined and partitioned into two groups for training and validating the individual and ensemble methods. In the next step, 12 groundwater-conditioning factors (GCFs), including topographical and hydrogeological factors, are prepared for the modeling process. The mentioned factors are employed in the application of the EBF model. Then, the EBF values of the GCFs are implemented as input to the BRT algorithm. The results of the modeling process are plotted to produce spring (groundwater) potential maps. To verify the results, the receiver operating characteristics (ROC) test is applied to the model’s output. The findings of the test indicated that the areas under the ROC curves are 75 and 82% for the EBF and EBF-BRT models, respectively. Therefore, it can be inferred that the combination of the two techniques could increase the efficacy of these methods in groundwater potential mapping.

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Please use this url to cite or link to this publication:
author
organization
alternative title
Groundwater potential mapping using a novel data-mining ensemble model
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Data mining, Geographic information system (GIS), Groundwater management, Iran
in
Hydrogeology Journal
volume
27
issue
1
pages
211 - 224
publisher
Springer
external identifiers
  • scopus:85053244132
ISSN
1431-2174
DOI
10.1007/s10040-018-1848-5
language
Spanish
LU publication?
yes
id
367a6848-c7f7-4fac-a778-87cdabcb7201
date added to LUP
2018-11-06 15:08:33
date last changed
2019-06-11 03:56:26
@article{367a6848-c7f7-4fac-a778-87cdabcb7201,
  abstract     = {<p>Freshwater scarcity is an ever-increasing problem throughout the arid and semi-arid countries, and it often results in poverty. Thus, it is necessary to enhance understanding of freshwater resources availability, particularly for groundwater, and to be able to implement functional water resources plans. This study introduces a novel statistical approach combined with a data-mining ensemble model, through implementing evidential belief function and boosted regression tree (EBF-BRT) algorithms for groundwater potential mapping of the Lordegan aquifer in central Iran. To do so, spring locations are determined and partitioned into two groups for training and validating the individual and ensemble methods. In the next step, 12 groundwater-conditioning factors (GCFs), including topographical and hydrogeological factors, are prepared for the modeling process. The mentioned factors are employed in the application of the EBF model. Then, the EBF values of the GCFs are implemented as input to the BRT algorithm. The results of the modeling process are plotted to produce spring (groundwater) potential maps. To verify the results, the receiver operating characteristics (ROC) test is applied to the model’s output. The findings of the test indicated that the areas under the ROC curves are 75 and 82% for the EBF and EBF-BRT models, respectively. Therefore, it can be inferred that the combination of the two techniques could increase the efficacy of these methods in groundwater potential mapping.</p>},
  author       = {Kordestani, Mojtaba Dolat and Naghibi, Seyed Amir and Hashemi, Hossein and Ahmadi, Kourosh and Kalantar, Bahareh and Pradhan, Biswajeet},
  issn         = {1431-2174},
  keyword      = {Data mining,Geographic information system (GIS),Groundwater management,Iran},
  language     = {spa},
  number       = {1},
  pages        = {211--224},
  publisher    = {Springer},
  series       = {Hydrogeology Journal},
  title        = {Cartografía del potencial de agua subterránea utilizando un nuevo modelo de conjuntos de minería de datos},
  url          = {http://dx.doi.org/10.1007/s10040-018-1848-5},
  volume       = {27},
  year         = {2019},
}