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:: Volume 3, Issue 4 ( Autumn, 2016) ::
Environ. health eng. manag. 2016, 3(4): 173-182 Back to browse issues page
Integration of artificial neural network and geographic information system applications in simulating groundwater quality
Vahid Gholami , Marhemat Sebghati , Zabihollah Yousefi *
*Corresponding Author: Professor, Department of Environmental Health Engineering, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran , zyousefi2004@gmail.com
Abstract:   (2833 Views)

 Background: Although experiments on water quality are time consuming and expensive, models are often employed as supplement to simulate water quality. Artificial neural network (ANN) is an efficient tool in hydrologic studies, yet it cannot predetermine its results in the forms of maps and geo-referenced data.

Methods: In this study, ANN was applied to simulate groundwater quality and geographic information system (GIS) was used as pre-processing and post-processing tool in simulating water quality in the Mazandaran Plain (Caspian southern coasts, Iran). Groundwater quality was simulated using multi-layer perceptron (MLP) network. The determination of groundwater quality index (GWQI) and the estimation of effective factors in groundwater quality were also undertaken. After modeling in ANN, the model validation was carried out. Also, the study area was divided with the pixels 1×1 km (raster format) in GIS medium. Then, the model input layers were combined and a raster layer which comprised the model inputs values and geographic coordinate was generated. Using geographic coordinate, the values of pixels (model inputs) were inputted into ANN (Neuro Solutions software). Groundwater quality was simulated using the validated optimum network in the sites without water quality experiments. In the next step, the results of ANN simulation were entered into GIS medium and groundwater quality map was generated based on the simulated results of ANN.

Results: The results revealed that the integration of capabilities of ANN and GIS have high accuracy and efficiency in the simulation of groundwater quality.

Conclusion: This method can be employed in an extensive area to simulate hydrologic parameters.

Keywords: Water quality, GWQI, MLP, Mazandaran Plain
eprint link: http://eprints.kmu.ac.ir/id/eprint/26077
Full-Text [PDF 2169 kb]   (1487 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/10/1 | Accepted: 2016/10/1 | Published: 2016/10/1
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Gholami V, Sebghati M, Yousefi Z. Integration of artificial neural network and geographic information system applications in simulating groundwater quality. Environ. health eng. manag.. 2016; 3 (4) :173-182
URL: http://ehemj.com/article-1-202-en.html


Volume 3, Issue 4 ( Autumn, 2016) Back to browse issues page
مجله مدیریت و مهندسی بهداشت محیط Environmental Health Engineering And Management Journal
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