• Feasibility Test for Hydraulic Conductivity Characterization of Small Basin-Scale Aquifers Based on Geostatistical Evolution Strategy Using Naturally Imposed Hydraulic Stress

  • Eungyu Park*

  • Department of Geology, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, South Korea

  • 자연 수리자극을 이용한 소유역 규모 대수층 수리전도도 특성화: 지구통계 진화전략 역산해석 기법의 적용 가능성 시험

  • 박 은 규

  • 경북대학교 지구시스템과학부

References
  • 1. 박은규, 2020, 지구통계학적 진화전략 역산해석 기법의 소개 및 가상 대수층 수리전도도 분포 예측에의 적용, 자원환경지질, 53(6), 1-11.
  •  
  • 2. Deutsch, C.V. and Journel, A.G., 1992, Geostatistical software library and user¡¯s guide. Oxford University Press, New York.
  •  
  • 3. Evensen, G., 2003, The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dyn., 53(4), 343-367.
  •  
  • 4. Graymore, M.L., Sipe, N.G., and Rickson, R.E., 2008, Regional sustainability: how usefulare current tools of sustainability assess-ment at the regional scale?, Ecol. Econom., 67(3), 362-372.
  •  
  • 5. Hansen, N. and Ostermeier, A., 2001, Completely derandomized self-adaptation in evolution strategies, Evol. Comput., 9(2), 159-195.
  •  
  • 6. Harbaugh, A.W., 2005, MODFLOW-2005, the U.S. Geological Survey modular ground-watermodel - the Ground-Water Flow Pro-cess: U.S. Geological Survey Techniques and Methods 6-A16.
  •  
  • 7. Houtekamer, P.L. and Mitchell, H.L., 1998, Data assimilation using an ensemble Kalman filter technique, Mon. Weather Rev., 126(3), 796-811.
  •  
  • 8. Kitanidis, P.K., 1995, Quasi‐linear geostatistical theory for inversing, Water Resour. Res., 31(10), 2411-2419.
  •  
  • 9. Mu, Y.X., Zhu, L., Shen, T.Q., Zhang, M., and Zha, Y.Y., 2020, Influence of correlation scale errors on aquifer hydraulic conductiv-ity inversion precision, Water Sci. Eng., 13(3), 243-252.
  •  
  • 10. Park, E., 2020, A geostatistical evolution strategy for subsurface characterization: Theory and validation through hypothetical two‐dimensional hydraulic conductivity fields, Water Resour. Res., 56.
  •  
  • 11. Sánchez-León, E., Erdal, D., Leven, C., and Cirpka, O.A., 2020, Comparison of Two Ensemble Kalman-Based Methods for Estimat-ing Aquifer Parameters from Virtual 2-D Hydraulic and Tracer Tomographic Tests, Geosciences, 10(7), 276.
  •  
  • 12. Wang, Z., Bovik, A.C., Sheikh, H.R., and Simoncelli, E.P., 2004, Image quality assessment: from error visibility to structural similar-ity, IEEE Trans. Image Process., 13(4), 600-612.
  •  
  • 13. Yeh, T.C.J., Jin, M., and Hanna, S., 1996, An iterative stochastic inverse method: Conditional effective transmissivity and hydraulic head fields, Water Resour. Res., 32(1), 85-92.
  •  
  • 14. Yeh, T.C.J., Lee, C.H., Hsu, K.C., Illman, W.A., Barrash, W., Cai, X., Daniels, J., Sudicky, E., Wan, L., Li, G., and Winter, C.L., 2008, A view toward the future of subsurface characterization: CAT scanning groundwater basins, Water Resour. Res., 44(3).
  •  

This Article

  • 2020; 25(4): 87-97

    Published on Dec 31, 2020

  • 10.7857/JSGE.2020.25.4.087
  • Received on Nov 30, 2020
  • Revised on Dec 6, 2020
  • Accepted on Dec 16, 2020

Correspondence to

  • Eungyu Park*

  • Department of Geology, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, South Korea

  • E-mail: egpark@knu.ac.kr