Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
How do data-mining models consider arsenic contamination in sediments and variables importance?
Tarbiat Modares Univ, Fac Nat Resources, Dept Watershed Management & Engn, Tehran, Iran..
Tarbiat Modares Univ, Fac Nat Resources, Dept Watershed Management & Engn, Tehran, Iran.;Lund Univ, Ctr Middle Eastern Studies, Lund, Sweden.;Lund Univ, Dept Water Resources Engn, Lund, Sweden..
Shiraz Univ, Coll Agr, Dept Nat Resources & Environm Engn, Shiraz, Iran..ORCID iD: 0000-0003-2328-2998
Tarbiat Modares Univ, Fac Nat Resources, Dept Watershed Management & Engn, Tehran, Iran..
Show others and affiliations
2019 (English)In: Environmental Monitoring & Assessment, ISSN 0167-6369, E-ISSN 1573-2959, Vol. 191, no 12, article id 777Article in journal (Refereed) Published
Abstract [en]

Arsenic (As) is one of the most important dangerous elements as more than 100 million of people are exposed to risk, globally. The permissible threshold of As for drinking water is 10 mu g/L according to both the WHO's drinking water guidelines and the Iranian national standard. However, several studies have indicated that As concentrations exceed this threshold value in several regions of Iran. This research evaluates an As-susceptible region, the Tajan River watershed, using the following data-mining models: multivariate adaptive regression splines (MARS), functional data analysis (FDA), support vector machine (SVM), generalized linear model (GLM), multivariate discriminant analysis (MDA), and gradient boosting machine (GBM). This study considers 12 factors for elevated As concentrations: land use, drainage density, profile curvature, plan curvature, slope length, slope degree, topographic wetness index, erosion, village density, distance from villages, precipitation, and lithology. The susceptibility mapping was conducted using training (70%) and validation (30%). The results of As contamination in sediment showed that classifications into 4 levels of concentration are very similar for two models of GLM and FDA. The GBM calculated the areas of highest arsenic contamination risk by MARS and SVM with percentages of 30.0% and 28.7%, respectively. FDA, GLM, MARS, and MDA models calculated the areas of lowest risk to be 3.3%, 23.0%, 72.0%, 25.2%, and 26.1%, respectively. The results of ROC curve reveal that the MARS, SVM, and MDA had the highest accuracies with area under the curve ROC values of 84.6%, 78.9%, and 79.5%, respectively. Land use, lithology, erosion, and elevation were the most important predictors of contamination potential with a value of 0.6, 0.59, 0.57, and 0.56, respectively. These are the most important factors. Finally, these data-mining methods can be used as appropriate, inexpensive, and feasible options to identify As-susceptible areas and can guide managers to reduce contamination in sediment of the environment and the food chain.

Place, publisher, year, edition, pages
SPRINGER , 2019. Vol. 191, no 12, article id 777
Keywords [en]
Arsenic, Data-mining, GIS-based mapping, LVQ, Human health, Iran
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:kth:diva-266304DOI: 10.1007/s10661-019-7979-xISI: 000499739900001PubMedID: 31781968Scopus ID: 2-s2.0-85075754389OAI: oai:DiVA.org:kth-266304DiVA, id: diva2:1383060
Note

QC 20200107

Available from: 2020-01-07 Created: 2020-01-07 Last updated: 2020-01-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records BETA

Bhattacharya, Prosun

Search in DiVA

By author/editor
Pourghasemi, Hamid RezaBhattacharya, Prosun
By organisation
Sustainable development, Environmental science and Engineering
In the same journal
Environmental Monitoring & Assessment
Earth and Related Environmental Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf