An application of MC-SDSS for water supply management during a drought crisis

Abstract

Climate change influences many countries' rainfall patterns and temperatures. In Iran, population growth has increased water demands. Tabriz is the capital of East Azerbaijan province, in northwestern Iran. A large proportion of the water required for this city is supplied from dams; thus, it is important to find alternatives to supply water for this city, which is the largest industrial city in northwestern Iran. In this paper, the groundwater quality was assessed using 70 wells in Tabriz Township. This work seeks to define the spatial distribution of groundwater quality parameters such as chloride, electrical conductivity (EC), pH, hardness, and sulfate using Geographic Information Systems (GIS) and geostatistics; map groundwater quality for drinking purposes employing multiple-criteria decision-making (MCDM), such as the Analytical Hierarchy Process (AHP) and fuzzy logic, in the study area; and develop an Spatial Decision Support System (SDSS) for managing a water crisis in the region. The map produced by the AHP is more accurate than the map produced using fuzzy logic because in the AHP, priorities were assigned to each parameter based on the weights given by water quality experts. The final map indicates that the groundwater quality increases from the north to the south and from the west to the east within the study area. During critical conditions, the groundwater quality maps and the presented SDSS core can be utilized by East Azerbaijan Regional Water Company to develop an SDSS to drill new wells or to select existing wells to supply drinking water to Tabriz City.

Decision Tree-Based Data Mining and Rule Induction for Identifying High Quality Groundwater Zones to Water Supply Management: a Novel Hybrid Use of Data Mining and GIS

“…Tabriz is located in a semi-arid region and has a high population circa 1.5 million. Tabriz water demands are mainly supplied from two dams located at 30 and 200 Km distances from Tabriz, with smaller contributions from certain wells located at a distance of 25Km from Tabriz (Jeihouni et al 2015). Recent drought years have threatened the water supply from permanent rivers for Tabriz.…”

“…Recent drought years have threatened the water supply from permanent rivers for Tabriz. The importance of locating high quality groundwater resources at near distances of Tabriz has been thoroughly discussed by Jeihouni et al (2015).…”

“…DSS assists decision makers in optimizing their decisions (Turban 1993). Moreover, Geographic Information System (GIS) is highlighted as quite an effective tool apropos of its spatial decision support role and function in developing GIS-based spatial DSS (SDSS) (Jeihouni et al 2015).…”

“…Nas and Berktay (2010) generated a water quality map for drinking purpose by a simple overlaying of thematic maps of pH, electrical conductivity (EC), chloride, sulfate, hardness, and nitrate. Jeihouni et al (2015) have developed a Multiple-criteria Spatial Decision Support System (MC-SDSS) where they used pH, EC, chloride, sulfate, and hardness as water quality parameters and employed Analytical Hierarchy Process (AHP) as a multiple-criteria decision-making (MCDM) technique to generate water quality map based on the importance of each parameter. In this approach, the importance of each parameter was determined by experts and the significance of each parameter range, when within the permissible limit, was covered by the weight of parameter.…”

Spatial analysis of groundwater electrical conductivity using ordinary kriging and artificial intelligence methods (Case study: Tabriz plain, Iran)

“…Kriging has been broadly used in geology, hydrology, environmental monitoring, atmospheric sciences and pedology for interpolation of spatial data (McBratney et al, 1982;Stein, 1999;poon et al, 2000;Gringarten and deutsch, 2001;Jost and et al, 2005;Kholghi and hosseini, 2009;Oliver and webster, 2014;Jeihouni et al, 2015).…”