Waterlogging Risk Mapping Using Remote Sensing and Field Data (Case Study: Qazvin)

Document Type : Research Paper

Authors

• Hamed Mansoori
• Vahid Yazdani

Abstract

Protecting the quality of groundwater due to frequent usage of this resource in various sectors including agriculture, industry and drinking water is of great importance. One of the ways to prevent pollution of groundwater is identifying the vulnerable aquifers and land management. In this paper, four indicators, namely :(AVI, GOD, DRASTIC and SINTACS) have been used to delineate volnerable areas on Qazvin plain of groundwater pollution. The data and information used in this article include satellite images for mapping land use and designated wetlands areas, maps whit scale of 1: 25,000 for georeferencing satellite images and control points, groundwater depth information during different years, amount of rainfall in the region, transmissivity capability and apparent resistivity of the aquifer layer, depth to bedrock, soil texture, surface area, soil permeability, slope (use the map DEM), the thickness and the texture of aquifer layer, hydraulic conductivity parameters, soil texture of the unsaturated area, net recharge parameters and land use. Because of the importance of wetlands and land use parameters in determining the potential risk and vulnerability, these conditions have been identified using satellite imagery.Threshold method and control points, were used to determine the inunalated areas of the plain hosbeen.The phreatic surfacehas was composition and the ordinary kriging method which was achieved below the critical level. As the normal vulnerability factor contains effective parameters, it was selected as an indicator for vulnerability classification was selected. Vulnerability classes based on these indices were divided into 6 categories, without the risk of contamination, very low vulnerability, low, low-to-moderate, moderate-to-high and high, whit the contribution of each class to the total area was 2.38, 20.73, 72.22, 20.5, 5.95 and 0.05 percent, respectively.

Keywords

• aquifer vulnerability and risk
• Sensitivity analysis
• Remote sensing
• wetland
• GIS

20.1001.1.20086377.1396.10.35.5.7

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