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2026 Vol.68, Issue 4 Preview Page
Prediction of Reservoir Inflow Using the FPHM Linked with Reservoir Water Level Observations

FPHM과 저수지 수위 관측 자료를 연계한 저수지 유입량 예측

Seokhun Kanga
,
Jung-Hun Songb†
강 석훈a
,
송 정헌b†
aGraduate Student, Department of Agriculture and Rural Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea
bAssistant Professor, Department of Agriculture and Rural Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea
† Corresponding author Tel.: +82-42-821-5796, Fax: +82-42-821-8877 E-mail: j.song@cnu.ac.kr
2026. pp. 15-35
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Abstract

Effective management of agricultural reservoirs relies on accurate knowledge of inflow and outflow. However, direct measurements are often unavailable for small and medium reservoirs operated by the Korea Rural Community Corporation (KRC). Water-level observations are more readily collected and can be used to estimate storage changes. By combining water-level observations with expert understanding of reservoir operations, indirect methods have been developed to reconstruct continuous inflow and outflow records. One such approach integrates hydrological models with water-level–based estimates. The Five-Parameter Hyperbolic Model (FPHM) is a recently developed lumped hydrological model with a parsimonious structure, but its application to agricultural reservoirs remains limited. This study evaluates the effectiveness of a framework that links FPHM with water-level–based inflow estimation. The framework was applied to four reservoirs, including Idong, Gopung, Gosam, and Cheongcheon, and the results were compared with those from a modified three-tank model. The results indicate that the FPHM reproduces reservoir inflow dynamics with comparable accuracy to the modified three-tank model, while showing reduced parameter-induced uncertainty under data-limited conditions. Through this comparison, we assess the applicability of FPHM for reconstructing reservoir inflow and supporting reservoir operation under data-scarce conditions.

Keywords
Reservoir inflow
reservoir water levels
Five-Parameter Hyperbolic Model (FPHM)
expert knowledge
References

REFERENCES

1
R. G. Allen, L. S. Pereira, D. Raes and M. Smith, Crop evapotranspiration - guidelines for computing crop water requirements (FAO irrigation and drainage paper No. 56), Rome, Italy. Food and Agriculture Organization of the United Nations. (1998)
2
K. Beven, Hydrological Processes, Towards an alternative blueprint for a physically based digitally simulated hydrologic response modelling system, 16(2); 189-206 (2002)10.1002/hyp.343
3
J. W. Choi, S. B. Cho, W. H. Hwang, B. K. Cho, D. B. Song and G. Kim, Korean Journal of Agricultural Science, Water stress level classification of sweet potato using infrared thermal imaging and plant growth indicators, 51(4); 751-763, (in Korean) (2024a)10.7744/kjoas.510425
4
Y. D. Choi, Y. Lee, H. An, H. Lim and Y. Hur, Korean Journal of Agricultural Science, Analysis of reservoir flood inflow and outflow: Case study of O-eo reservoir, 51(4); 699-714, (in Korean) (2024b)10.7744/kjoas.510422
5
L. Crochemore, C. Perrin, V. Andreassian, U. Ehret, S. P. Seibert, S. Grimaldi, H. Gupta and J. E. Paturel, Hydrological Sciences Journal, Comparing expert judgement and numerical criteria for hydrograph evaluation, 60(3); 402-423 (2015)10.1080/02626667.2014.903331
6
C. Deng, P. Liu, S. Guo, H. Wang and D. Wang, Journal of Hydrology, Estimation of nonfluctuating reservoir inflow from water level observations using methods based on flow continuity, 529; 1198-1210 (2015)10.1016/j.jhydrol.2015.09.037
7
P. Ditthakit, S. Pinthong, N. Salaeh, F. Binnui, L. Khwanchum and Q. B. Pham, Scientific Reports, Using machine learning methods for supporting GR2M model in runoff estimation in an ungauged basin, 11; 19955 (2021)10.1038/s41598-021-99164-5
8
Q. Duan, S. Sorooshian and V. K. Gupta, Journal of Hydrology, Optimal use of the SCE-UA global optimization method for calibrating watershed models, 158(3-4); 265-284 (1994)10.1016/0022-1694(94)90057-4
9
S. Gharari, H. V. Gupta, M. P. Clark, M. Hrachowitz, F. Fenicia, P. Matgen and H. H. G. Savenije, Water Resources Research, Understanding the information content in the hierarchy of model development decisions: Learning from data, 57(6); e2020WR027948 (2021)10.1029/2020wr027948
10
S. Gharari, M. Hrachowitz, F. Fenicia, H. Gao and H. H. G. Savenije, Hydrology and Earth System Sciences, Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, 18(12); 4839-4859 (2014a)10.5194/hess-18-4839-2014
11
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta and H. H. G. Savenije, Hydrology and Earth System Sciences, A constraint-based search algorithm for parameter identification of environmental models, 18(12); 4861-4870 (2014b)10.5194/hess-18-4861-2014
12
H. V. Gupta, H. Kling, K. K. Yilmaz and G. F. Martinez, Journal of Hydrology, Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, 377(1-2); 80-91 (2009)10.1016/j.jhydrol.2009.08.003
13
H. V. Gupta, S. Sorooshian and P. O. Yapo, Journal of Hydrologic Engineering, Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration, 4(2); 135-143 (1999)10.1061/(asce)1084-0699(1999)4:2(135)
14
M. Hrachowitz, O. Fovet, L. Ruiz, T. Euser, S. Gharari, R. Nijzink, J. Freer, H. H. G. Savenije and C. Gascuel-Odoux, Water Resources Research, Process consistency in models: The importance of system signatures, expert knowledge, and process complexity, 50(9); 7445-7469 (2014)10.1002/2014wr015484
15
K. S. Jeong, S. H. Go, W. K. Jo and J. H. Park, Korean Journal of Agricultural Science, Simplified image analysis for early detection of missing and low-vigor cabbage plants using UAV RGB imagery and deep learning, 52(1); 51-65 (2025)10.7744/kjoas.520105
16
Joint Ministries, The 1st master plans for national water management, Publication No. 11-1480000-001756-14. (in Korean), Sejong, Korea. Government of the Republic of Korea. (2021)
17
M. G. Kang, J. H. Lee and K. W. Park, Journal of Korea Water Resources Association, Parameter regionalization of a tank model for simulating runoffs from ungauged watersheds, 46(5); 519-530, (in Korean) (2013)10.3741/jkwra.2013.46.5.519
18
Y. G. Kang, J. Y. Lee, J. H. Kim, J. Choi, Y. J. Kim and T. K. Oh, Korean Journal of Agricultural Science, Combination of soil color information and machine learning technique for rapid quantification of soil organic matter, 53(1); 63-74, (in Korean) (2026)10.7744/kjoas.530106
19
H. J. Kim, Ph.D. diss., Development of two-parametric hyperbolic model for daily streamflow simulation, (in Korean), Seoul, Korea. Seoul National University. (2001)
20
H. Y. Kim, Ph.D. diss., Simulating daily inflow and release rates for irrigation reservoirs, (in Korean), Seoul, Korea. Seoul National University. (1988)
21
H. Y. Kim and S. W. Park, Journal of the Korean Society of Agricultural Engineers, Simulating daily inflow and release rates for irrigation reservoirs, I: Modelling inflow rates by a linear reservoir model, 30(1); 50-62, (in Korean). (1988)
22
H. Kling, M. Fuchs and M. Paulin, Journal of Hydrology, Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, 424(425); 264-277 (2012)10.1016/j.jhydrol.2012.01.011
23
P. Krause, D. P. Boyle and D. P. Bäse, Advances in Geosciences, Comparison of different efficiency criteria for hydrological model assessment, 5; 89-97 (2005)10.5194/adgeo-5-89-2005
24
KRC (Korea Rural Community Corporation), Hydraulics and hydrology analysis system (K-HAS) v1.2.3 user manual, (in Korean), Naju, Korea. Korea Rural Community Corporation. (2023)
25
Y. H. Lee, J. S. Han, T. M. Yeom, S. H. Park, S. W. Song, B. R. Yun, C. H. Kim and D. W. Lee, Korean Journal of Agricultural Science, Development of overtopping protection system using gabion retaining wall in deteriorated agricultural reservoir embankment, 51(4); 715-731, (in Korean) (2024)10.7744/kjoas.510423
26
MAFRA (Ministry of Agriculture, Food and Rural Affairs), 2024 Agricultural production infrastructure maintenance statistical yearbook, (in Korean), Sejong, Korea. Ministry of Agriculture, Food and Rural Affairs. (2025)
27
P. A. Melo, L. A. Alvarenga, J. Tomasella and A. C. N. Santos, Journal of Water and Climate Change, Uncertainty analysis on long-term runoff projection from the Budyko framework and a conceptual hydrological model, 15(8); 3850-3867 (2024)10.2166/wcc.2024.127
28
J. E. Nash and J. V. Sutcliffe, Journal of Hydrology, River flow forecasting through conceptual models part I—A discussion of principles, 10(3); 282-290 (1970)10.1016/0022-1694(70)90255-6
29
R. C. Nijzink, S. Almeida, I. G. Pechlivanidis, R. Capell, D. Gustafsson, B. Arheimer, J. Parajka, J. Freer, D. Han, T. Wagener, R. R. P. van Nooijen, H. H. G. Savenije and M. Hrachowitz, Water Resources Research, Constraining conceptual hydrological models with multiple information sources, 54(10); 8332-8362 (2018)10.1029/2017wr021895
30
L. Oudin, V. Andreassian, T. Mathevet, C. Perrin and C. Michel, Water Resources Research, Dynamic averaging of rainfall-runoff model simulations from complementary model parameterizations, 42(7) (2006)10.1029/2005wr004636
31
S. W. Park, Journal of the Korean Association of Hydrological Sciences, A tank model shell program for simulating daily streamflow from small watersheds, 26(3); 47-61, (in Korean) (1993)
32
L. Santos, G. Thirel and C. Perrin, Hydrology and Earth System Sciences, Pitfalls in using log-transformed flows within the KGE criterion, 22(8); 4583-4591 (2018)10.5194/hess-22-4583-2018
33
J. Seibert and J. J. McDonnell, Water Resources Research, On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, 38(11); 1241 (2002)10.1029/2001wr000978
34
J. H. Song, Ph.D. diss., Hydrologic analysis system with multi-objective optimization for agricultural watersheds, (in Korean)., Seoul, Korea. Seoul National University. (2017)
35
J. H. Song and H. Kim, Journal of Hydrology, Impact of precipitation station density and homogeneous regions on hydrological modeling performance, 661; 133618 (2025)10.1016/j.jhydrol.2025.133618
36
J. H. Song, M. S. Kang, I. Song and S. M. Jun, Journal of Irrigation and Drainage Engineering, Water balance in irrigation reservoirs considering flood control and irrigation efficiency variation, 142(4); 04016003 (2016)10.1061/(asce)ir.1943-4774.0000989
37
J. H. Song, Y. Her and M. S. Kang, Water, Regionalization of a rainfall-runoff model: Limitations and potentials, 11(11); 2257 (2019b)10.3390/w11112257
38
J. H. Song, Y. Her and M. S. Kang, Water Resources Research, Estimating reservoir inflow and outflow from water level observations using expert knowledge: Dealing with an ill-posed water balance equation in reservoir management, 58(2); e2020WR028183 (2022a)10.1029/2020wr028183
39
J. H. Song, Y. Her and T. Guo, Scientific Reports, Quantifying the contribution of direct runoff and baseflow to nitrogen loading in the Western Lake Erie Basins, 12; 9216 (2022b)10.1038/s41598-022-12740-1
40
J. H. Song, Y. Her, J. Park and M. S. Kang, Journal of Hydrology, Exploring parsimonious daily rainfall-runoff model structure using the hyperbolic tangent function and tank model, 574; 574-587 (2019a)10.1016/j.jhydrol.2019.04.054
41
M. Sugawara, Hydrological Sciences Bulletin, Automatic calibration of the tank model / L’étalonnage automatique d'un modèle à cisterne, 24(3); 375-388 (1979)10.1080/02626667909491876
42
D. Tian, X. He, P. Srivastava and L. Kalin, Stochastic Environmental Research and Risk Assessment, A hybrid framework for forecasting monthly reservoir inflow based on machine learning techniques with dynamic climate forecasts, satellite-based data, and climate phenomenon information, 36; 2353-2375 (2022)10.1007/s00477-021-02023-y
43
J. M. Volk, J. L. Huntington, F. S. Melton, R. Allen, M. Anderson, J. B. Fisher, A. Kilic, A. Ruhoff, G. B. Senay, B. Minor, C. Morton, T. Ott, L. Johnson, B. Comini de Andrade, W. Carrara, C. T. Doherty, C. Dunkerly, M. Friedrichs, A. Guzman, C. Hain, G. Halverson, Y. Kang, K. Knipper, L. Laipelt, S. Ortega-Salazar, C. Pearson, G. E. L. Parrish, A. Purdy, P. ReVelle, T. Wang and Y. Yang, Nature Water, Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications, 2; 193-205 (2024)10.1038/s44221-023-00181-7
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 68
  • No :4
  • Pages :15-35
  • Received Date : 2026-03-05
  • Revised Date : 2026-04-07
  • Accepted Date : 2026-04-08
  • DOI :https://doi.org/10.5389/KSAE.2026.68.4.015
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