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Journal ArticleDOI

Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS

TLDR
In this article, a standard methodology has been applied to delineate groundwater resource potential zonation based on integrated analytical hierarchy process (AHP), geographic information system (GIS), and remote sensing (RS) techniques in Kurdistan plain, Iran.
Abstract
Multi-criteria decision analysis (MCDA) as an advantageous tool has been applied by various researchers to improve their management ability. Management of groundwater resource, especially under data-scarce and arid areas, encountered a lot of problems and issues which drives the planers to use of MCDA. In this research, a standard methodology has been applied to delineate groundwater resource potential zonation based on integrated analytical hierarchy process (AHP), geographic information system (GIS), and remote sensing (RS) techniques in Kurdistan plain, Iran. At first, the effective thematic layers on the groundwater potential such as rainfall, lithology, drainage density, lineament density, and slope percent were derived from the spatial geodatabase. Then, the assigned weights of thematic layers based on expert knowledge were normalized by eigenvector technique of AHP. To prepare the groundwater potential index, the weighted linear combination (WLC) method was applied in GIS. Finally, the receiver operating characteristic (ROC) curve was drawn for groundwater potential map, and the area under curve (AUC) was computed. Results indicated that the rainfall and slope percent factors have taken the highest and lowest weights, respectively. Validation of results showed that the AHP method (AUC = 73.66 %) performed fairly good predication accuracy. Such findings revealed that in the regions suffering from data scarcity through the MCDM methodology, the planners would be able to having accurate knowledge on groundwater resources based on geospatial data analysis. Therefore, the developing scenario for future planning of groundwater exploration can be achieved in an efficient manner.

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Citations
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Journal ArticleDOI

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

TL;DR: The BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively, and Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.
Journal ArticleDOI

Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran

TL;DR: In this paper, the application of random forest (RF) and maximum entropy (ME) models for groundwater potential mapping is investigated at Mehran Region, Iran and the results of the GPMs were quantitatively validated using observed groundwater dataset and the receiver operating characteristic (ROC) method.
Journal ArticleDOI

A novel hybrid artificial intelligence approach for flood susceptibility assessment

TL;DR: Results indicate that the proposed Bagging-LMT model can be used for sustainable management of flood-prone areas and outperformed all state-of-the-art benchmark soft computing models.
Journal ArticleDOI

Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS

TL;DR: This study investigates the analytical hierarchy process (AHP), frequency ratio (FR), and certainty factor (CF) models for groundwater potential mapping using geographical information system (GIS) at Varamin Plain, Tehran province, Iran and finds that the FR model performs better than AHP and CF models.
Journal ArticleDOI

Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran

TL;DR: In this article, the authors investigated the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran.
References
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Book

GIS and Multicriteria Decision Analysis

TL;DR: This book discusses Geographical Data, Information, and Decision Making, and Multicriteria Decision Analysis, as well as Spatial Decision Support Systems, which addresses the role of spatial data and information in decision making.
Book

Artificial Intelligence: A Guide to Intelligent Systems

TL;DR: The book demonstrates that most ideas behind intelligent systems are simple and straightforward, and the reader needs no prerequisites associated with knowledge of any programming language.
Journal ArticleDOI

Tectonics of the zagros orogenic belt of iran - new data and interpretations

Mehdi Alavi
- 30 Jan 1994 - 
TL;DR: The Zagros orogenic belt of Iran is the result of the opening and closure of the Neo-Tethys oceanic realm, and consists, from northeast to southwest, of three parallel tectonic subdivisions: 1) the Urumieh-Dokhtar Magmatic Assemblage; 2. (2) the Sanandaj-Sirjan Zone; and 3. (3) the zagros simply folded belt.
Journal ArticleDOI

Validation of Spatial Prediction Models for Landslide Hazard Mapping

TL;DR: In this paper, the authors discuss the problem of providing measures of significance of prediction results when the predictions were generated from spatial databases for landslide hazard mapping, and propose a method to validate the results of some models over other ones, or of particular experiments.
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