All Issue

2025 Vol.58, Issue 2 Preview Page

Research Article

Evaluation of dam operations during drought using multi-objective optimization and multi-criteria decision-making approaches

다중 목적 최적화 기법 및 다기준 의사결정 방법을 활용한 가뭄 시 댐 운영 평가

Yong Shin Leeab*
,
Shin Uk Kangc
,
Si Jung Choid
이 용신ab*
,
강 신욱c
,
최 시중d
aPh.D Course, Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UK
bSenior Manager, K-water, Human Resources Development Institute, Daejeon, Korea
cHead Researcher, Water Resources & Environmental Research Center, K-water Research Institute, Daejeon, Korea
dSenior Researcher, Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology, Goyang, Korea
aUniversity of Bristol, Department of Civil Engineering 박사과정
bK-water 인재개발원 차장
cK-water연구원 수자원환경연구소 수석연구원
d한국건설기술연구원 수자원하천연구본부 수석연구원
*Corresponding Author
28 February 2025. pp. 169-182
PDF XML Citation
Abstract

Due to the increasing impact of extreme weather events attributed to climate change, operating dams in a stable and efficient manner has become increasingly challenging. Prolonged droughts, in particular, cause significant socio-economic damage, highlighting the critical need to enhance current dam operations. This study introduces a novel methodology for dam operations that leverages deterministic inflow scenarios and ensemble inflow forecasts to optimize water supply schedules, integrating various decision-making frameworks. A dam simulation was conducted for Andong-Imha and Hapcheon dams, focusing on a prolonged drought period from 2014 to 2018. Our findings indicate that operations based on deterministic inflow scenarios tend to emphasize storage availability, while ensemble forecasts are effective in reducing supply deficits. Furthermore, our results demonstrate that dam operation performance varies significantly depending on the selected multi-criteria decision-making (MCDM) method, highlighting the critical role of operators' decision-making in the dam operation process. Further studies should focus on verifying the effectiveness of our methodology by applying it to various drought events and dams.

Keywords
Seasonal flow forecasts
Multi-objective optimization
Multi-criteria decision-making

기후변화로 극한 기후현상이 빈번해짐에 따라, 댐을 안정적으로 운영하는 것은 더욱 어려워지고 있다. 특히, 장기적으로 이어지는 가뭄은 사회·경제 전반에 걸쳐 큰 피해를 일으키므로, 이에 대비한 댐 운영 방법을 모색·고도화하는 것은 매우 중요한 일이다. 본 연구는 결정론적 유입 시나리오 및 앙상블 유입 전망 정보를 기반으로, 용수공급 스케줄을 최적화하고 다양한 의사결정 방법론을 적용하여 댐을 운영하는 새로운 댐 운영 방법론을 제시한다. 2014년부터 2018년까지의 장기 가뭄에 대해, 낙동강 유역의 안동-임하댐 및 합천댐을 대상으로 모의운영 한 결과, 결정론적 댐 유입 시나리오를 활용하는 것은 저수량 확보 중심의 운영결과를 나타내지만, 앙상블 전망을 활용할 경우 공급 부족을 줄이는 데 효과가 있음을 확인하였다. 또한, 다기준 의사결정 방법에 따라 댐 운영의 결과가 크게 달라지는 것을 확인하였는데, 이는 댐 운영과정에서 운영자의 의사결정의 중요성을 나타낸다. 향후, 다양한 가뭄 사상 및 댐에 대해 본 연구를 통해 제시된 댐 운영 방법론을 적용하여 그 활용성 및 효과를 지속 검증해 나가야 할 것이다.

키워드
계절 유량 전망
다중 목적 최적화
다기준 의사결정
References
1

Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. United Nations Food and Agriculture Organization, Irrigation and Drainage Paper 56. Rome, Italy.

2

Al Shalabi, L., and Shaaban, Z. (2006). "Normalization as a preprocessing engine for data mining and the approach of preference matrix." 2006 International Conference on Dependability of Computer Systems, Szklarska Poreba, Poland, pp. 207-214.

10.1109/DEPCOS-RELCOMEX.2006.38
3

Arnal, L., Cloke, H.L., Stephens, E., Wetterhall, F., Prudhomme, C., Neumann, J., Krzeminski, B., and Pappenberger, F. (2018). "Skilful seasonal forecasts of streamflow over Europe?" Hydrology and Earth System Sciences, Vol. 22, pp. 2057-2072.

10.5194/hess-22-2057-2018
4

Bauer, P., Thorpe, A., and Brunet, G. (2015). "The quiet revolution of numerical weather prediction." Nature, Vol. 525, pp. 47-55.

10.1038/nature1495626333465
5

Chen, C.-T. (2000). "Extensions of the TOPSIS for group decision- making under fuzzy environment." Fuzzy Sets and Systems, Vol. 114, No. 1, pp. 1-9.

10.1016/S0165-0114(97)00377-1
6

Das, I. (1999). "On characterizing the 'knee' of the Pareto curve based on Normal-Boundary Intersection." Structural Optimization, Vol. 18, No. 2, pp. 107-115.

10.1007/BF01195985
7

Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). "A fast and elitist multiobjective genetic algorithm: NSGA-II." IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197.

10.1109/4235.996017
8

Ehsani, N., Vörösmarty, C.J., Fekete, B.M., and Stakhiv, E.Z. (2017). "Reservoir operations under climate change: Storage capacity options to mitigate risk." Journal of Hydrology, Vol. 555, pp. 435-446.

10.1016/j.jhydrol.2017.09.008
9

Fishburn, P.C. (1967). "Additive utilities with finite sets: Applications in the management sciences." Naval Research Logistics Quarterly, Vol. 14, No. 1, pp. 1-13.

10.1002/nav.3800140102
10

Goodarzi, M., Jabbarian Amiri, B., Azarneyvand, H., Khazaee, M., and Mahdianzadeh, N. (2020). "Assessing the performance of a hydrological Tank model at various spatial scales." Journal of Water Management Modeling, Vol. 29, pp. 1-8.

10.14796/JWMM.C472
11

Greuell, W., Franssen, W.H.P., Biemans, H., and Hutjes, R.W.A. (2018). "Seasonal streamflow forecasts for Europe - Part I: Hindcast verification with pseudo- and real observations." Hydrology and Earth System Sciences, Vol. 22, pp. 3453-3472.

10.5194/hess-22-3453-2018
12

Hwang, C.L., and Yoon, K. (1981). Multiple attribute decision making: Methods and applications, A state-of-the-art survey. Springer-Verlag, New York, NY, U.S.

10.1007/978-3-642-48318-9_3
13

Jin, Y., Jung, T., Lee, S., and Kang, S. (2016). "Reservoir operations of Hapcheon Dam applying a discrete hedging rule and ensemble streamflow prediction to cope with droughts." Journal of Korean Society of Hazard Mitigation, Vol. 16, pp. 93-101.

10.9798/KOSHAM.2016.16.1.93
14

Kang, M.S., Yu, M., and Yi, J. (2014). "Prediction of Andong reservoir inflow using ensemble technique." Journal of the Korean Society of Civil Engineers, Vol. 34, pp.795-804.

10.12652/Ksce.2014.34.3.0795
15

Karamouz, M., and Araghinejad, S. (2008). "Drought mitigation through long-term operation of reservoirs: Case study." Journal of Irrigation and Drainage Engineering, Vol. 134, No. 4, pp. 471-478.

10.1061/(ASCE)0733-9437(2008)134:4(471)
16

Kim, Y., Chung, E.S., Won, G.J., and Gil, K. (2015). "Robust parameter estimation framework of a rainfall-runoff model using Pareto optimum and minimax regret approach." Water, Vol. 7, pp. 1246-1263.

10.3390/w7031246
17

Lee, S., Kim, J., Bae, J.H., Lee, G., Yang, D., Hong, J., and Lim, K.J. (2023a). "Development of multi-inflow prediction ensemble model based on auto-sklearn using combined approach: Case study of Soyang River Dam." Hydrology, Vol. 10, No. 4, pp. 1-18.

10.3390/hydrology10040090
18

Lee, Y., Peñuela, A., Pianosi, F., and Rico‐Ramirez, M.A. (2023b). "Catchment‐scale skill assessment of seasonal precipitation forecasts across South Korea." International Journal of Climatology, Vol. 43, pp. 5092-5111.

10.1002/joc.8134
19

Lee, Y., Pianosi F., Peñuela, A., and Rico-Ramirez, M.A. (2024a). "Skill of seasonal flow forecasts at catchment scale: An assessment across South Korea." Hydrology and Earth System Science, Vol. 28, pp. 3261-3279.

10.5194/hess-28-3261-2024
20

Lee, Y., Pianosi F., Peñuela, A., and Rico-Ramirez, M.A. (2024b). "Value of seasonal flow forecasts for enhancing reservoir operation and drought management in South Korea." EGUsphere [preprint]. doi: 10.5194/egusphere-2024-1985.

10.5194/egusphere-2024-1985
21

Lee, Y.S., and Kang, S.U. (2024). "Assessing the skill of seasonal flow forecasts from ECMWF for predicting inflows to multipurpose dams in South Korea." Journal of Korea Water Resources Association, Vol. 57, pp. 571-583.

22

Li, L., Chung, E.S., and Jun, K.S. (2017). "Robust parameter set selection of unsteady flow model using Pareto optimums and minimax regret approach." Journal of Korea Water Resources Association, Vol. 50, pp. 121-128.

10.3741/JKWRA.2017.50.3.191
23

Li, L., Chung, E.S., and Jun, K.S. (2018). "Robust parameter set selection of a hydrodynamic model based on multi-site calibration and multi-objective optimization." Water Resources Management, Vol. 32, pp. 3979-3995.

10.1007/s11269-018-2031-4
24

Li, W., Zhang, G., Zhang, T., and Huang, S. (2020). "Knee point- guided multiobjective optimization algorithm for microgrid dynamic energy management." Complexity, Vol. 2020, pp. 1-11.

10.1155/2020/8877008
25

Loucks, D.P., and van Beek, E. (2017). Water resource systems planning and management: An introduction to methods, models, and applications. Springer Nature, Cham, Germany.

10.1007/978-3-319-44234-1_4
26

Lu, L., Anderson-Cook, C.M., and Robinson, T.J. (2011). "Optimization of designed experiments based on multiple criteria utilizing a pareto frontier." Technometrics, Vol. 53, No. 4, pp. 353-365.

10.1198/TECH.2011.10087
27

Malekmohammadi, B., Zahraie, B., and Kerachian, R. (2011). "Ranking solutions of multi-objective reservoir operation optimization models using multi-criteria decision analysis." Expert Systems with Applications, Vol. 38, No. 6, pp. 7851-7863.

10.1016/j.eswa.2010.12.119
28

Ministry of Environment (ME) (2024). Water and the future 2024.

29

Nebro, A.J., Galeano-Brajones, J., Luna, F., and Coello Coello, C.A. (2022). "Is NSGA-II ready for large-scale multi-objective optimization?" Mathematical and Computational Applications, Vol. 27, No. 6, 103.

10.3390/mca27060103
30

Ni, X., Dong, Z., Jiang, Y., Xie, W., Yao, H., and Chen, M. (2022). "A subjective-objective integrated multi-objective decision- making method for reservoir operation featuring trade-offs among non-inferior solutions themselves." Journal of Hydrology, Vol. 613, 128430.

10.1016/j.jhydrol.2022.128430
31

Ou, X., Gharabaghi, B., McBean, E., and Doherty, C.(2017). "Investigation of the tank model for urban storm water management." Journal of Water Management Modeling, Vol. 25, pp. 1-5.

10.14796/JWMM.C421
32

Peñuela, A., Hutton, C., and Pianosi, F. (2020). "Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK." Hydrology and Earth System Sciences, Vol. 24, pp. 6059-6073.

10.5194/hess-24-6059-2020
33

Sheffield, J., Wood, E.F., and Roderick, M.L. (2012). "Little change in global drought over the past 60 years." Nature, Vol. 491, No. 7424, pp. 435-438.

10.1038/nature1157523151587
34

United Nations (UN) (2022). Droughts in numbers 2022 (restoration for readiness and resilience). COP-15, Côte d'Ivoire.

35

Velasquez, M., and Hester, P.T. (2013). "An analysis of multi-criteria decision-making methods." International Journal of Operations Research, Vol. 2, pp. 56-66.

36

Wang, Z., and Rangaiah, G.P. (2017). "Application and analysis of methods for selecting an optimal solution from the pareto- optimal front obtained by multiobjective optimization." Industrial & Engineering Chemistry Research, Vol. 56, No. 2, pp. 560-574.

10.1021/acs.iecr.6b03453
37

World Meteorological Organization (WMO) (2021). Drought report calls for new management approach, accessed 10 November 2024, <https://public.wmo.int/en/media/news/drought-report-calls-new-management-approach>.

38

Yeh, W.W-G. (1985). "Reservoir management and operations models: A state-of-the-art review." Water Resources Research, Vol. 21, pp. 1797-1818.

10.1029/WR021i012p01797
39

Yossef, N.C., Winsemius, H., Weerts, A., van Beek, R., and Bierkens, M.F.P. (2013). "Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing." Water Resources Research, Vol. 49, pp. 4687-4699.

10.1002/wrcr.20350
40

Zhang, X., Hao, Z., Singh, V.P., Zhang, Y., Feng, S., Xu, Y., and Hao, F. (2022). "Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors." Science of The Total Environment, Vol. 838, 156021.

10.1016/j.scitotenv.2022.15602135588839
41

Zhou, A., Qu, B.-Y., Li, H., Zhao, S.-Z., Suganthan, P.N., and Zhang, Q. (2011). "Multiobjective evolutionary algorithms: A survey of the state of the art." Swarm and Evolutionary Computation, Vol. 1, No. 1, pp. 32-49.

10.1016/j.swevo.2011.03.001
42

Zhu, F., Zhong, P., Xu, B., Wu, Y., and Zhang, Y. (2015). "A multi- criteria decision-making model dealing with correlation among criteria for reservoir flood control operation." Journal of Hydroinformatics, Vol. 18, No. 3, pp. 531-543.

10.2166/hydro.2015.055
Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 58
  • No :2
  • Pages :169-182
  • Received Date : 2024-11-09
  • Revised Date : 2024-12-26
  • Accepted Date : 2025-01-07
  • DOI :https://doi.org/10.3741/JKWRA.2025.58.2.169
Journal Informaiton Journal of Korea Water Resources Association Journal of Korea Water Resources Association
Online Submission
Archives
  • scopus
  • KCI-수자원
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close