Real-time Application and Statistical Evaluation of Reservoir Operating Rules Under Inflow Uncertainty in Monte Carlo Simulations

Authors

  • Muhammad Mujiburrakhman Department of Civil Engineering, Planning, and Design, Universitas Bangka Belitung, Bangka Regency, INDONESIA https://orcid.org/0009-0009-2156-9670
  • Rachmad Jayadi Department of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, INDONESIA
  • Istiarto Department of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, INDONESIA
  • Indra Nurdianyoto Division of Jasa ASA I, Jasa Tirta I Corporation, Malang, INDONESIA

DOI:

https://doi.org/10.22146/jcef.24906

Keywords:

Inflow uncertainty, Monte Carlo simulations, Real-time application of Reservoir Operating Rules, Reservoir operational performance, Thomas-Fiering model

Abstract

Reservoir Operating Rules (ROR) have been well-known in Indonesia as guidelines for reservoir operation that comprise the release rules and rule curves derived from the dependable inflow time series in dry, normal, and wet conditions. However, likely because of the incoherence of the original application concept of ROR, the real performance of ROR in reservoir operation has so far remained unclear. This paper proposes a practical application concept of ROR and evaluates the performance of its implementation for annual storage conservation and periodic demand satisfaction under inflow uncertainty in the integrated system of Segawe Regulating Weir, Wonorejo Multipurpose Dam, and Tiudan Regulating Dam. The release rules for the three hydraulic structures were integrated into a unified “Wonorejo ROR”throughoptimization of water allocation over 36 ten-day operational periods. The performance of the application of Wonorejo ROR was evaluated based on several operational success and failure events in Monte Carlo simulations, for which 1,000 years of unique and independent synthetic inflow time series were generated from the Thomas–Fiering model. Under the application concept of ROR, the release decisions for the three hydraulic structures were made in real-time solely based on the actual water level of Wonorejo Reservoir and the rule curves of Wonorejo ROR. For comparative purposes, the Monte Carlo simulations were carried out to evaluate two alternatives of Wonorejo ROR, namely ROR-D65 and ROR-D80, which had different dry inflow exceedance probabilities. Based on the specified events in the Monte Carlo simulations, ROR-D65 and ROR-D80 resulted in reliabilities of 76.4% and 81.3% for annual storage conservation, and the lowest reliabilities of 73.9% and 52.4% for periodic demand satisfaction, respectively. In addition, other reservoir operational performancesandacomprehensive interpretation oftheproposed applicationconcept of ROR arepresented in this paper.

References

Agastya, D. M., Jayadi, R. and Istiarto, I. (2023), Optimum water utilization of a cascade reservoirs case study of batujai and pengga reservoirs in central lombok district, west nusa tenggara province, in ‘AIP Conference Proceedings’, Vol. 2629, p. 060013. URL: https://doi.org/10.1063/5.0128877

Agastya, D., Yasa, I. W. and Negara, I. D. G. J. (2024), ‘Optimization of pengga reservoir in the mandalika special economic zone for irrigation and water supply’, Journal of the Civil Engineering Forum pp. 163–172. URL: https://doi.org/10.22146/jcef.7913

Ahmadi, M., Haddad, O. B. and Loáiciga, H. A. (2015), ‘Adaptive reservoir operation rules under climatic change’, Water Resources Management 29(4), 1247-1266. URL: https://doi.org/10.1007/s11269-014-0871-0

Aitken, G., Beevers, L. and Christie, M. A. (2022), ‘Multi-level monte carlo models for flood inundation uncertainty quantification’, Water Resources Research 58(11), e2022WR032599. URL: https://doi.org/10.1029/2022WR032599

Azmeri, A., Sundary, D., Mutiawati, C. and Rani, H. A. (2022), An update on reservoir operating rules following changes on the effective capacity due to land erosion, in ‘E3S Web of Conferences’, Vol. 340, p. 01008. URL: https://doi.org/10.1051/e3sconf/202234001008

Bachtiar, S., Limantara, L. M., Sholichin, M. and Soetopo, W. (2023), ‘Optimization of integrated reservoir for supporting the raw water supply’, Civil Engineering Journal 9(4), 860–872. URL: https://doi.org/10.28991/CEJ-2023-09-04-07

Box, G. E. P., Jenkins, G. M., Reinsel, G. C. and Ljung, G. M.(2016), TimeSeriesAnalysis: Forecasting and Control, Wiley Series in Probability and Statistics, 5 edn, John Wiley & Sons, Inc., Hoboken.

Chow, V. T. (1964), Handbook of Applied Hydrology: A Compendium of Water-Resources Technology, McGraw Hill Handbooks, McGraw-Hill, New York.

Chow, V. T., Maidment, D. R. and Mays, L. W. (1988), Applied Hydrology, international edn, McGraw-Hill Book Co., Singapore.

Clarke, R. T. (1994), Statistical Modelling in Hydrology, Wiley, Chichester.

European Small Hydropower Association (2004), Guide on How to Develop a Small Hydropower Plant, European Small Hydropower Association.

Faber, B. A. (2021), ‘Lecture 7 monte carlo simulation part 2’, https://www.youtube.com/watch?v=iZPGpi99s1s. Online; USCE Hydrologic Engineering Center; accessed 12 December 2025.

Fauziyah, A., Jayadi, R. and Pratiwi, E. P. A. (2023), Developing optimization model for multipurpose reservoir using linear programming method, in ‘AIP Conference Proceedings’, Vol. 2629, p. 060011. URL: https://doi.org/10.1063/5.0128875

Feng, M., Liu, P., Guo, S., Shi, L., Deng, C. and Ming, B. (2017), ‘Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the enkf’, Water Resources Research 53(8), 6885–6907. URL: https://doi.org/10.1002/2016WR020180

Giuliani, M., Herman, J. D., Castelletti, A. and Reed, P. (2014), ‘Many-objective reservoir policy identification and refinement to reduce policy inertia and myopia in water management’, Water Resources Research 50(4), 3355–3377. URL: https://doi.org/10.1002/2013WR014700

Gupta, H. V., Kling, H., Yilmaz, K. K. and Martinez, G. F. (2009), ‘Decomposition of the mean squared error and nse performance criteria: Implications for improving hydrological modelling’, Journal of Hydrology 377(1–2), 80–91. URL: https://doi.org/10.1016/j.jhydrol.2009.08.003

Haan, C. T. (2002), Statistical Methods in Hydrology, 2 edn, Iowa State Press, Ames.

Haditama, I. G. N. H. R., Aryastana, P., Yujana, C. A. and Candrayana, K. W. (2024), Water use optimization of benel reservoir in jembrana regency,baliprovince,in ‘IOP Conference Series: Earth and Environmental Science’, Vol. 1311, p. 012029. URL:https://doi.org/10.1088/1755-1315/1311/1/012029

Hashimoto, T., Stedinger, J. R. and Loucks, D. P. (1982), ‘Reliability, resiliency, and vulnerability criteria for water resource system performanceevaluation’,WaterResources Research 18(1), 14–20. URL: https://doi.org/10.1029/WR018i001p00014

Hyndman, R. J. and Athanasopoulos, G. (2018), Forecasting: Principles and Practice, OTexts.

Ilich, N. (2024), ‘Dynamic reservoir rule curves their creation and utilization’, Journal of Hydrology X 22, 100166. URL: https://doi.org/10.1016/j.hydroa.2023.100166

Iqbal, K., Abduh, M. and Variadi (2023), ‘Simulation of multi reservoir operation rules with interconnected tunnel and water transfer’, Aceh International Journal of Science and Technology 12(2), 285–296. URL: https://doi.org/10.13170/aijst.12.2.32532

Janssen, H. (2013), ‘Monte-carlo based uncertainty analysis: Sampling efficiency and sampling convergence’, Reliability Engineering & System Safety 109, 123–132. URL: https://doi.org/10.1016/j.ress.2012.08.003

Jibat, E., Senbeta, F., Zeleke, T. and Hagos, F. (2024), ‘The role and interplay of institutions in water governance in the central rift valley of ethiopia’, F1000Research 12, 1434. URL: https://doi.org/10.12688/f1000research.138939.2

Kangrang, A., Prasanchum, H. and Hormwichian, R. (2018), ‘Development of future rule curves for multipurpose reservoir operation using conditional genetic and tabu searchalgorithms’, AdvancesinCivil Engineering 2018(1), 6474870. URL: https://doi.org/10.1155/2018/6474870

Kasprzyk, J. R., Nataraj, S., Reed, P. M. and Lempert, R. J. (2013), ‘Many objective robust decision making for complex environmental systems undergoing change’, Environmental Modelling & Software 42, 55–71. URL: https://doi.org/10.1016/j.envsoft.2012.12.007

Kindler, J. (1977), ‘The monte carlo approach to optimization of the operation rules for a system of storage reservoirs’, Hydrological Sciences Bulletin 22(1), 203-214. URL: https://doi.org/10.1080/02626667709491705

Kosasaeng, S. and Kangrang, A. (2023), ‘Optimum reservoir operation of a networking reservoirs system using conditional atom search optimization and a conditional genetic algorithm’, Heliyon 9(3), e14467. URL: https://doi.org/10.1016/j.heliyon.2023.e14467

Kottegoda, N. T. and Rosso, R. (2008), Applied Statistics for Civil and Environmental Engineers, Blackwell Publishing Ltd.

Koutsoyiannis, D. (2000), ‘A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series’, Water Resources Research 36(6), 1519–1533. URL: https://doi.org/10.1029/2000WR900044

Koutsoyiannis, D. andMontanari, A.(2007), ‘Statistical analysis of hydroclimatic time series: Uncertainty and insights’, Water Resources Research 43(5), W05429. URL: https://doi.org/10.1029/2006WR005592

Lai, V., Huang, Y. F., Koo, C. H., Ahmed, A. N. and El Shafie, A. (2022), ‘A review of reservoir operation optimisations: from traditional models to metaheuristic algorithms’, Archives of Computational Methods in Engineering 29(5), 3435–3457. URL: https://doi.org/10.1007/s11831-021-09701-8

Li, D., Chen, Y., Lyu, L. and Cai, X. (2024), ‘Uncovering historical reservoir operation rules and patterns: Insights from 452 large reservoirs in the contiguous united states’, Water Resources Research 60(8), e2023WR036686. URL: https://doi.org/10.1029/2023WR036686

Liu, Y., Qin, H., Zhang, Z., Yao, L., Wang, Y., Li, J., Liu, G. and Zhou, J. (2019), ‘Deriving reservoir operation rule based on bayesian deep learning method considering multiple uncertainties’, Journal of Hydrology 579, 124207. URL: https://doi.org/10.1016/j.jhydrol.2019.124207

Loucks, D. P. and van Beek, E. (2017), Water Resource Systems Planning and Management, Springer International Publishing, Cham. URL: https://doi.org/10.1007/978-3-319-44234-1

Maia, A. G., Camargo-Valero, M. A., Trigg, M. A. and Khan, A. (2024), ‘Uncertainty and sensitivity analysis in reservoir modeling: a monte carlo simulation approach’, Water Resources Management 38(8), 2835-2850. URL: https://doi.org/10.1007/s11269-024-03794-z

Mateus, C. and Tullos, D. (2017), ‘Reliability, sensitivity, and uncertainty of reservoir performanceunderclimate variability in basins with different hydrogeologic settings in northwestern united states’, International Journal of River Basin Management 15(1), 21–37. URL: https://doi.org/10.1080/15715124.2016.1247361

Men, B., Wu, Z., Li, Y. and Liu, H. (2019), ‘Reservoir operation policy based on joint hedging rules’, Water 11(3), 419. URL: https://doi.org/10.3390/w11030419

Montanari, A. and Koutsoyiannis, D. (2014), ‘Modeling and mitigating natural hazards: Stationarity is immortal!’, Water Resources Research 50(12), 9748–9756. URL: https://doi.org/10.1002/2014WR016092

Mujiburrakhman, M., Jayadi, R., Istiarto and Nurdianyoto, I.(2024), An optimization model for integrated water allocation in the parallel system of segawe regulating weir and wonorejo multipurpose dam, tulungagung, east java, in ‘IOP Conference Series: Earth and Environmental Science’, Vol. 1343, p. 012021. URL:https://doi.org/10.1088/1755-1315/1343/1/012021

Munson, B. R., Rothmayer, A. P. and Okiishi, T. H. (2012), Fundamentals of Fluid Mechanics, Blackwell Handbooks in Linguistics, 7 edn, John Wiley & Sons, Inc., Hoboken.

Nash, J. E. and Sutcliffe, J. V. (1970), ‘River flow forecasting through conceptual models part i — a discussion of principles’, Journal of Hydrology 10(3), 282–290. URL: https://doi.org/10.1016/0022-1694(70)90255-6

Pusat Pendidikan dan Pelatihan SDA dan Konstruksi (2017), Modul 08 operasi waduk (module 08 reservoir operation), in ‘Pelatihan Alokasi Air (Water Allocation Training)’, Kementerian PUPR, Badan Pengembangan Sumber Daya Manusia, Pusat Pendidikan dan Pelatihan SDA dan Konstruksi, Bandung.

Putranto, Y. D., Harisuseno, D. and Prayogo, T. B. (2023), ‘Study of tiu kulit dam reservoir operational pattern simulation in sumbawa island’, Civil and Environmental Science 6(2), 134–145. URL: https://doi.org/10.21776/civense.v6i2.402

Rediasti, F. N. K., Jayadi, R. and Triatmodjo, B. (2023), ‘Optimizing the use of meninting multipurpose reservoir water in west lombok district’, Journal of the Civil Engineering Forum pp. 217–226. URL: https://doi.org/10.22146/jcef.7161

Salas, J. D., Delleur, J. W., Yevjevich, V. M. and Lane, W.L.(1980), AppliedModelingofHydrologicTimeSeries, Water Resources Publication, Water Resources Publications, Littleton.

Santosa, R. R. A., Pratiwi, E. P. A. and Istiarto (2025), ‘Establishing semantok reservoir operation rules to obtain the highest crop intensity in semantok irrigation area’, Jurnal Pendidikan Penelitian IPA 11(8), 1180-1192. URL: https://doi.org/10.29303/jppipa.v11i8.11669

Santoso, B., Limantara, L. M., Soetopo, W. and Wahyuni, S. (2021), ‘Optimization model of batutegi reservoir operation pattern by using the simulation method ofcropping patternforobtainingtheeconomic expected value’, Journal of Southwest Jiaotong University 56(3), 284–294. URL: https://doi.org/10.35741/issn.0258-2724.56.3.24

Sastrawan, A., Makrup, L., Ruzardi, R. and Fadilah, S. (2023), Optimization of the mrica reservoir management at banjarnegara regency using a deterministicdynamic program (for electricity production and irrigation water), in ‘Proceedings of the 7th International Conference in Sustainable Built Environment’, Universitas Islam Indonesia, pp. 221–234. URL: https://doi.org/10.20885/icsbe.vol4.art21

Shumway, R. H. and Stoffer, D. S. (2017), Time Series Analysis and Its Applications: WithRExamples,Springer Texts in Statistics, Springer International Publishing.

Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., Quichimbo, E. A. and Michaelides, K. (2021), ‘Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981-present’, Scientific Data 8(1), 224. URL: https://doi.org/10.1038/s41597-021-01003-9

Soentoro, E. A., Perwira, E., Suryadi, Y. and Winskayati (2018), Optimization of irrigation water use to increase the benefit of agricultural products, in ‘MATEC Web of Conferences’, Vol. 159, p. 01026. URL: https://doi.org/10.1051/matecconf/201815901026

Tang, R., Zhang, J., Wang, Y. and Zhang, X. (2024), ‘Study on the basic form of reservoir operation rule curves for water supply and power generation’, Water 16(2), 276. URL: https://doi.org/10.3390/w16020276

Thomas, H. A. J. and Fiering, M. B. (1962), Mathematical synthesis of streamflow sequences for the analysis of river basins by simulation, in ‘Design of Water-Resource Systems’, Harvard University Press, pp. 459–493. URL: https://doi.org/10.4159/harvard.9780674421042.c15

van Dijk, A. I. J. M., Peña Arancibia, J. L., Wood, E. F., Sheffield, J. and Beck, H. E. (2013), ‘Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide’, Water Resources Research 49(5), 2729–2746. URL: https://doi.org/10.1002/wrcr.20251

Vatankhah, A. R. (2014), ‘Comment on “gene expression programming analysis of implicit colebrook–white equation in turbulent flow friction factor calculation”’, Journal of Petroleum Science and Engineering 124, 402-405. URL: https://doi.org/10.1016/j.petrol.2013.12.001

Vogel, R. M., Lall, U., Cai, X., Rajagopalan, B., Weiskel, P. K., Hooper, R. P. and Matalas, N. C. (2015), ‘Hydrology: The interdisciplinary science of water’, Water Resources Research 51(6), 4409–4430. URL: https://doi.org/10.1002/2015WR017049

Wahyuni, S., Sisinggih, D., Elhuda, I., Souma, K. and Dasylva, I. Z. (2024), ‘Optimization of reservoir release operation using genetic algorithm method’, Results in Engineering 23, 102610. URL: https://doi.org/10.1016/j.rineng.2024.102610

Waluyadi, H., Juwono, P. T., Soetopo, W., Rispiningtati, Limantara, L.M.andLegono,D.(2021),‘Optimization model of reservoir operating pattern based on the adaptive inflow for climate change’, Journal of Southwest Jiaotong University 56(2), 491–511. URL: https://doi.org/10.35741/issn.0258-2724.56.2.40

Wan, W., Zhao, J. and Wang, J. (2019), ‘Revisiting water supply rule curves with hedging theory for climate change adaptation’, Sustainability 11(7), 1827. URL: https://doi.org/10.3390/su11071827

Yaghoubi, B., Hosseini, S. A., Nazif, S. and Daghighi, A. (2020), ‘Development of reservoir’s optimum operation rules considering water quality issues and climatic change data analysis’, Sustainable Cities and Society 63, 102467. URL: https://doi.org/10.1016/j.scs.2020.102467

You, J. and Cai, X. (2008), ‘Hedging rule for reservoir operations: 1. a theoretical analysis’, Water Resources Research 44(1), W01415. URL: https://doi.org/10.1029/2006WR005481

Zhao, Z., Zhang, Q., Zhang, J., Sun, Y., Wang, Y., Yang, Z., Song, S., Lu, X. and Zhuo, L. (2026), ‘Impacts of inflow forecast uncertainties on economic and environmental co-benefits for cascade reservoirs optimal scheduling’, Journal of Hydrology 664, 134504. URL: https://doi.org/10.1016/j.jhydrol.2025.134504

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2026-06-18

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Mujiburrakhman, M., Jayadi, R., Istiarto, & Nurdianyoto, I. (2026). Real-time Application and Statistical Evaluation of Reservoir Operating Rules Under Inflow Uncertainty in Monte Carlo Simulations. Journal of the Civil Engineering Forum, 12(3), 305–322. https://doi.org/10.22146/jcef.24906

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