• A Groundwater Potential Map for the Nakdonggang River Basin
  • Soonyoung Yu·Jaehoon Jung·Jize Piao·Hee Sun Moon·Heejun Suk·Yongcheol Kim*·Dong-Chan Koh·Kyung-Seok Ko·Hyoung-Chan Kim·Sang-Ho Moon·Jehyun Shin·Byoung Ohan Shim·Hanna Choi·Kyoochul Ha

  • Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon 34132, Korea

  • 낙동강권역의 지하수 산출 유망도 평가
  • 유순영·정재훈·박길택·문희선·석희준·김용철*·고동찬·고경석·김형찬

  • 한국지질자원연구원

  • This article is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


A groundwater potential map (GPM) was built for the Nakdonggang River Basin based on ten variables, including hydrogeologic unit, fault-line density, depth to groundwater, distance to surface water, lineament density, slope, stream drainage density, soil drainage, land cover, and annual rainfall. To integrate the thematic layers for GPM, the criteria were first weighted using the Analytic Hierarchical Process (AHP) and then overlaid using the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) model. Finally, the groundwater potential was categorized into five classes (very high (VH), high (H), moderate (M), low (L), very low (VL)) and verified by examining the specific capacity of individual wells on each class. The wells in the area categorized as VH showed the highest median specific capacity (5.2 m3/day/m), while the wells with specific capacity < 1.39 m3/day/m were distributed in the areas categorized as L or VL. The accuracy of GPM generated in the work looked acceptable, although the specific capacity data were not enough to verify GPM in the studied large watershed. To create GPMs for the determination of high-yield well locations, the resolution and reliability of thematic maps should be improved. Criterion values for groundwater potential should be established when machine learning or statistical models are used in the GPM evaluation process.

Keywords: Nakdonggang River Basin, Groundwater potential map, AHP, TOPSIS, Validation

This Article

  • 2023; 28(6): 71-89

    Published on Dec 31, 2023

  • 10.7857/JSGE.2023.28.6.071
  • Received on Nov 30, 2023
  • Revised on Dec 10, 2023
  • Accepted on Dec 15, 2023

Correspondence to

  • Yongcheol Kim
  • Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon 34132, Korea

  • E-mail: yckim@kigam.re.kr