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http://dx.doi.org/10.9720/kseg.2012.22.2.207

Understanding of Surface Water-Groundwater Connectivity in an Alluvial Plain using Statistical Methods  

Kim, Gyoo-Bum (Geo-Water+ Research Center, K-water Research Institute)
Son, Young-Chul (Geo-Water+ Research Center, K-water Research Institute)
Lee, Seung-Hyun (Geo-Water+ Research Center, K-water Research Institute)
Jeong, An-Chul (Geo-Water+ Research Center, K-water Research Institute)
Cha, Eun-Jee (Geo-Water+ Research Center, K-water Research Institute)
Ko, Min-Jeong (Geo-Water+ Research Center, K-water Research Institute)
Publication Information
The Journal of Engineering Geology / v.22, no.2, 2012 , pp. 207-221 More about this Journal
Abstract
A statistical analysis of time series of water level at 27 groundwater monitoring wells was conducted to analyze the surface water-groundwater connectivity in the wide alluvial plains surrounding the Nakdong River, Korea. Change in groundwater level is strongly related to river water level, yielding an average cross-correlation coefficient of 0.601, which is much higher than that between rainfall and groundwater level (0.125). Principal component analysis of groundwater level indicates that wells in the study area can be classified into two groups: wells in Group A are located close to a river, have water levels closely related to river level, and generally show a large increase in groundwater level during heavy rainfall. On the other hand, wells in Group B located far from a river are relatively less related to river level. Including hydrologic and statistical analyses, geochemical analysis and temperature monitoring are additionally required to reveal the relationship between surface water level and groundwater level, and to assess the possibility of groundwater flooding.
Keywords
Groundwater monitoring; Surface water-groundwater connectivity; Principal component analysis; Cross-correlation Coefficient;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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