• Title/Summary/Keyword: 주거지의 지형적 특성

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Prediction of Nitrate Contamination of Groundwater in the Northern Nonsan area Using Multiple Regression Analysis (다중 회귀 분석을 이용한 논산 북부 지역 지하수의 질산성 질소 오염 예측)

  • Kim, Eun-Young;Koh, Dong-Chan;Ko, Kyung-Seok;Yeo, In-Wook
    • Journal of Soil and Groundwater Environment
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    • v.13 no.5
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    • pp.57-73
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    • 2008
  • Nitrate concentrations were measured up to 49 mg/L (as $NO_3$-N) and 22% of the samples exceeded drinking water standard in shallow and bedrock groundwater of the northern Nonsan area. Nitrate concentrations showed a significant difference among land use groups. To predict nitrate concentration in groundwater, multiple regression analysis was carried out using hydrogeologic parameters of soil media, topography and land use which were categorized as several groups, well depth and altitude, and field parameters of temperature, pH, DO and EC. Hydrogeologic parameters were quantified as area proportions of each category within circular buffers centering at wells. Regression was performed to all the combination of variables and the most relevant model was selected based on adjusted coefficient of determination (Adj. $R^2$). Regression using hydrogelogic parameters with varying buffer radii show highest Adj. $R^2$ at 50m and 300m for shallow and bedrock groundwater, respectively. Shallow groundwater has higher Adj. $R^2$ than bedrock groundwater indicating higher susceptibility to hydrogeologic properties of surface environment near the well. Land use and soil media was major explanatory variables for shallow and bedrock groundwater, respectively and residential area was a major variable in both shallow and bedrock groundwater. Regression involving hydrogeologic parameters and field parameters showed that EC, paddy and pH were major variables in shallow groundwater whereas DO, EC and natural area were in bedrock groundwater. Field parameters have much higher explanatory power over the hydrogeologic parameters suggesting field parameters which are routinely measured can provide important information on each well in assessment of nitrate contamination. The most relevant buffer radii can be applied to estimation of travel time of contaminants in surface environment to wells.