Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique
نویسندگان
چکیده
In arid and semi-arid lands like Iran water is scarce, not all the wastewater can be treated. Hence, groundwater remains primary principal source of supply for human consumption. Therefore, this study attempted to spatially assess potential in an aquifer a region using geographic information systems (GIS)-based statistical modeling. To end, 75 agricultural wells across Marvdasht Plain were sampled, samples’ electrical conductivity (EC) was measured. model quality, multiple linear regression (MLR) component (PCR) coupled with elven environmental parameters (soil-topographical parameters) employed. The results showed that soil EC (SEC) Beta = 0.78 selected as most influential factor affecting (GEC). CaCO3 samples length-steepness (LS factor) second third effective parameters. SEC r 0.89 0.79 LS 0.69 also characterized PC1. According performance criteria, MLR R2 0.94, root mean square error (RMSE) 450 µScm?1 (ME) 125 provided better predicting GEC. GEC map indicated 16% suitable agriculture. It concluded GIS, combined methods, could predict quality regions.
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ژورنال
عنوان ژورنال: Sustainability
سال: 2021
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su13073788