All Issue

2026 Vol.31, Issue 5 Preview Page

Research Paper

Spatiotemporal Variability of Groundwater Level Residuals under Contrasting Aquifer Characteristics in the Yangsan Area

양산 지역 대수층 특성에 따른 지하수위 잔차의 시∙공간적 변동 특성 분석

Ga-Young Hwang1*
,
Sung-Ho Song2
,
Hwan-Ho Yong1
,
Hyoun Soon Yi2
황 가영1*
,
송 성호2
,
용 환호1
,
이 현순2
1Rural Research Institute, Korea Rural Community Corporation,
2Groundwater and Environment Engineering.
1한국농어촌공사 농어촌연구원
2㈜지엔이이엔지
*Corresponding Author
31 October 2026. pp. 87-99
PDF XML Citation
Abstract

This study applied regression kriging (RK) to separate broad-scale topographic controls from local groundwater-level variability in the Yangsan area and examined the spatiotemporal characteristics of groundwater level residuals in relation to local hydrogeological settings. The residual spatial structure remained relatively stable over the study period, whereas residual magnitude and spatial distribution varied among months. Although the overall mean residual anomaly was small, its magnitude and direction varied spatially within individual months, indicating spatially nonuniform local groundwater level responses. Comparison of the Lower Yangsan Stream and Hoeya Dam watersheds revealed broadly similar temporal patterns but distinct magnitudes and spatial distributions of residual anomalies. In the Lower Yangsan Stream watershed, where intrusive igneous rocks coexist with other hydrogeological units, positive and negative anomalies were spatially intermingled. In contrast, the Hoeya Dam watershed, dominated by nonporous volcanic rocks, exhibited more spatially extensive same-sign anomalies during certain periods, together with greater residual variability and spatial dispersion. These contrasting patterns suggest that local groundwater-level variations beyond broad-scale topographic controls may be associated with the composition of hydrogeological units and local aquifer structure. Groundwater level residuals can therefore provide useful information on localized variability, and their spatiotemporal analysis offers an approach for characterizing groundwater-system heterogeneity and localized groundwater responses.

Keywords
Groundwater level
Hydrogeological unit
Regression kriging
Residual anomaly
Spatiotemporal variation
References
1

Ahmadi, S.H. and Sedghamiz, A., 2007, Geostatistical analysis of spatial and temporal variations of groundwater level, Environ. Monit. Assess., 129(1-3), 277-294.

10.1007/s10661-006-9361-z
2

Baird, A.J. and Low, R.G., 2022, The water table: Its conceptual basis, its measurement and its usefulness as a hydrological variable, Hydrol. Process., 36(6), e14622.

10.1002/hyp.14622
3

Boezio, M.N.M., Costa, J.F.C.L., and Koppe, J.C., 2006, Kriging with an external drift versus collocated cokriging for water table mapping, Appl. Earth Sci., 115(3), 103-112.

10.1179/174327506X138896
4

Desbarats, A.J., Logan, C.E., Hinton, M.J., and Sharpe, D.R., 2002, On the kriging of water table elevations using collateral information from a digital elevation model, J. Hydrol., 255(1-4), 25-38.

10.1016/S0022-1694(01)00504-2
5

Freeze, R.A. and Cherry, J.A., 1979, Groundwater. Prentice-Hall Inc., Englewood Cliffs.

6

Healy, R.W. and Cook, P.G., 2002, Using groundwater levels to estimate recharge, Hydrogeol. J., 10(1), 91-109.

10.1007/s10040-001-0178-0
7

Hengl, T., Heuvelink, G.B.M., and Rossiter, D.G., 2007, About regression-kriging: From equations to case studies, Comput. Geosci., 33(10), 1301-1315.

10.1016/j.cageo.2007.05.001
8

Isaaks, E.H. and Srivastava, R.M., 1989, An introduction to applied geostatistics, Oxford University Press, New York, 561p.

9

Kurtzman, D., Nativ, R., and Adar, E.M., 2005, Correlating fracture trends and hydraulic head using semivariogram cloud analysis, Ground Water, 43(2), 250-258.

10.1111/j.1745-6584.2005.0010.x
10

Lee, J.M., Ko, K.S., and Woo, N.C., 2020, Characterization of groundwater level and water quality by classification of aquifer types in South Korea, Econ. Environ. Geol., 53(5), 619-629.

11

Lee, J.Y. and Lee, K.K., 2000, Use of hydrologic time series data for identification of recharge mechanism in a fractured bedrock aquifer system, J. Hydrol., 229(3-4), 190-201.

10.1016/S0022-1694(00)00158-X
12

Lorenzo-Lacruz, J., Garcia, C., and Morán-Tejeda, E., 2017, Groundwater level responses to precipitation variability in Mediterranean insular aquifers, J. Hydrol., 552, 516-531.

10.1016/j.jhydrol.2017.07.011
13

Ministry of Construction and Transportation (MOCT) and Korea Water Resources Corporation (K-water), 2007, Groundwater Basic Investigation Report for Yangsan Area, K-water, Daejeon, Republic of Korea. (in Korean)

14

Neuman, S.P. and Jacobson, E.A., 1984, Analysis of nonintrinsic spatial variability by residual kriging with application to regional groundwater levels, J. Int. Assoc. Math. Geol., 16(5), 499-521.

10.1007/BF01886329
15

Peeters, L., Fasbender, D., Batelaan, O., and Dassargues, A., 2010, Bayesian data fusion for water table interpolation: Incorporating a hydrogeological conceptual model in kriging, Water Resour. Res., 46, W08532.

10.1029/2009WR008353
16

Ruybal, C.J., Hogue, T.S., and McCray, J.E., 2019, Evaluation of groundwater levels in the Arapahoe aquifer using spatiotemporal regression kriging, Water Resour. Res., 55(4), 2820-2837.

10.1029/2018WR023437
17

Song, S.H., Hwang, G.Y., and Yong, H.H., 2026, Integrated PCA-cluster framework for classifying groundwater level variation types in rural area, J. Soil Groundwater Environ., 31(2), 16-26.

18

Theodoridou, P.G., Varouchakis, E.A., and Karatzas, G.P., 2017, Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools, J. Hydrol., 555, 242-252.

10.1016/j.jhydrol.2017.10.027
19

Tonkin, M.J. and Larson, S.P., 2002, Kriging water levels with a regional-linear and point-logarithmic drift, Ground Water, 40(2), 185-193.

10.1111/j.1745-6584.2002.tb02503.x
20

Yangsan-si and KRC (Korea Rural Community Corporation), 2025, Report on the Operation and Management of the Auxiliary Groundwater Monitoring Network and Old Downtown Groundwater Level Stations, KRC Gyeongnam Regional Headquarter.

21

Yu, S., Jung, J., Piao, J., Kim, H.R., Moon, S.H., Kim, H.C., Kim, Y., Suk, H., Moon, H.S., Ko, K.S., and Ha, K., 2026, Hydraulic and hydrochemical characterization of hydrogeological units in South Korea: national-scale statistical analysis, J. Soil Groundwater Environ., 31(3), 28-52.

22

Zhu, K., Cui, Z., Jiang, B., Yang, G., Chen, Z., Meng, Q., and Yao, Y., 2013, A DEM-based residual kriging model for estimating groundwater levels within a large-scale domain: A study for the Fuyang River Basin, Clean Technol. Environ. Policy, 15(4), 687-698.

10.1007/s10098-012-0563-5
Information
  • Publisher :The Korean Society of Soil and Groundwater Environment
  • Publisher(Ko) :한국지하수토양환경학회
  • Journal Title :Journal of Soil and Groundwater Environment
  • Journal Title(Ko) :지하수토양환경
  • Volume : 31
  • No :5
  • Pages :87-99
  • Received Date : 2026-09-15
  • Revised Date : 2026-10-08
  • Accepted Date : 2026-10-27
  • DOI :https://doi.org/10.7857/JSGE.2026.31.5.087
Journal Informaiton Journal of Soil and Groundwater Environment Journal of Soil and Groundwater Environment
Online Submission
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close