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Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)

  • WATER RESOURCES AND THE REGIME OF WATER BODIES
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Abstract

The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 km2. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand km2, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models.

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REFERENCES

  1. Bugaets, A.N., Gartsman, B.I., Krasnopeev, S.M., and Bugaets, N.D., An experience of updated hydrological network data processing using the CUAHSI HIS ODM Data Management System, Russ. Meteorol. Hydrol., 2013, no. 5, pp. 359–366.

  2. Bugaets, A.N., Pshenichnikova, N.F., Tereshkina, A.A., Krasnopeev, S.M., and Gartsman, B.I., Analysis of the spatial differentiation of the soil cover in the south of the Far East of Russia by the example of the Komarovka River Basin, Eurasian Soil Sci., 2015, no. 3, pp. 231–239.

  3. Vinogradov, Yu.B., Matematicheskoe modelirovanie protsessov formirovaniya stoka (Mathematical Modeling of Runoff Formation Processes), Leningrad: Gidrometeoizdat, 1988.

  4. Lupakov, S.Yu. and Bugaets, A.N., Analysis of floods in small catchments using HBV conceptual hydrological model, Rus. Meteorol. Hydrol., 2022, no. 1, pp. 59–66.

  5. Lupakov, S.Yu., Bugaets, A.N., and Shamov, V.V., Application of different structures of HBV model to studying runoff formation processes: case study of experimental catchments, Water Resour., 2021, vol. 48, pp. 512–521.

    Article  Google Scholar 

  6. Motovilov, Yu.G. and Gel’fan, A.N., Modeli formirovaniya stoka v zadachakh gidrologii rechnykh basseinov (Runoff Formation Models in Problems of River Basin Hydrology), Moscow: RAN, 2018. https://doi.org/10.31857/S9785907036222000001

  7. Simonov, Yu.A., Semenova, N.K., and Khristoforov, A.V., Short-range streamflow forecasting of the Kama River based on the HBV model application, Russ. Meteorol. Hydrol., 2021, no. 6, pp. 388–395.

  8. Ayzel, G., Runoff predictions in ungauged Arctic basins using conceptual models forced by reanalysis data, Water Resour., 2018, vol. 45 (S2), pp. S1–S7. https://doi.org/10.1134/S0097807818060180

    Article  Google Scholar 

  9. Ayzel, G. and Abramov, D., OPENFORECAST: an assessment of the operational run in 2020–2021, Geosci. (Switzerland), 2022, vol. 12, no. 2, p. 67. https://doi.org/10.3390/geosciences12020067

    Article  Google Scholar 

  10. Bergstrom, S., Development and Application of a Conceptual Runoff Model for Scandinavian Catchments, Norrkoping, Sweden: Univ. Lund. Bull., 1976.

    Google Scholar 

  11. Beven, K., Rainfall-Runoff Modelling. The Primer, Chichester: Ltd. John Wiley & Sons, 2001. https://doi.org/10.1002/9781119951001

    Book  Google Scholar 

  12. Bugaets, A.N., Gartsman, B.I., Gonchukov, L.V., Lupakov, S.Y., Shamov, V.V., Pshenichnikova, N.F., and Tereshkina, A.A., Modeling the hydrological regime of small testbed catchments based on field observations: a case study of the Pravaya Sokolovka River, the Upper Ussuri River basin, Water Resour., 2019, vol. 42 (S2), pp. S8–S16. https://doi.org/10.1134/S0097807819080037

    Article  Google Scholar 

  13. Bugaets, A.N., Gonchukov, L.V., Sokolov, O.V., Gartsman, B.I., and Krasnopeev, S.M., Information system to support regional hydrological monitoring and forecasting, Water Resour., 2018, vol. 45 (S1), pp. S59–S66. https://doi.org/10.1134/S0097807818050329

    Article  Google Scholar 

  14. Clark, M.P., Kavetski, D., and Fenicia, F., Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 2011, vol. 47. W09301. https://doi.org/10.1029/2010wr009827

    Article  Google Scholar 

  15. Gassman, P.W., Reyes, M.R., Green, C.H., and Arnold, J.G., The soil and water assessment tool: historical development, applications, and future research and directions, Am. Soc. Agricultural Biol. Engineers, 2007, vol. 50, no. 4, pp. 1211–1250. https://doi.org/10.13031/2013.23637

    Article  Google Scholar 

  16. Haddeland, I., Clark, D.B., Franssen, et al., Multimodel estimate of the global terrestrial water balance: setup and first results, Hydrometeorology, 2011, vol. 12, pp. 869–884. https://doi.org/10.1175/2011JHM1324.1

    Book  Google Scholar 

  17. Klemes, V. Operational testing of hydrologic simulation models, Hydrol. Sci. J., 1986, vol. 31, pp. 13–24. https://doi.org/10.1080/02626668609491024

    Article  Google Scholar 

  18. Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., and Veith, T.L., Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Trans. ASABE, 2007, vol. 50, pp. 885–900. https://doi.org/10.13031/2013.23153

    Article  Google Scholar 

  19. Mroczkowski, M., Raper, G.P., and Kuczera, G., The quest for more powerful validation of conceptual catchment models, Water Resour. Res., 1997, vol. 26, pp. 2275–2286. https://doi.org/10.1029/97WR01922

    Article  Google Scholar 

  20. Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andreassian, V., Anctil, F., and Loumagne, C., Which potential evapotranspiration input for a lumped rainfall–runoff model?, Pt 2, Towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling, J. Hydrol., 2005, vol. 303, pp. 290–306. https://doi.org/10.1016/j.jhydrol.2004.08.026

    Article  Google Scholar 

  21. Perrin, C., Michel, C., and Andreassian, V., Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 2003, vol. 279, pp. 275–289. https://doi.org/10.1016/S0022-1694(03)00225-7

    Article  Google Scholar 

  22. Rango A. and Martinec, J., Revisiting the degree-day method for snowmelt computations, Water Resour. Bull., 1995, vol. 31, pp. 657–669. https://doi.org/10.1111/j.1752-1688.1995.tb03392.x

    Article  Google Scholar 

  23. Seibert, J. and Bergstrom, S., A retrospective on hydrological catchment modelling based on half a century with the HBV model, Hydrol. Earth Syst. Sci., 2022, vol. 26, pp. 1371–1388. https://doi.org/10.5194/hess-26-1371-2022

    Article  Google Scholar 

  24. Seibert, J. and Vis, M., Teaching hydrological modelling with a user-friendly catchment-runoff-model software package, Hydrol. Earth Syst. Sci., 2012, vol. 16, pp. 3315–3325. https://doi.org/10.5194/hess-16-3315-2012

    Article  Google Scholar 

  25. Uhlenbrook, S., Seibert, J., Leibundgut, C., and Rodhe, A., Prediction uncertainty of conceptual rainfall-runoff models caused by problems in identifying model parameters and structure, Hydrol. Sci. J., 1999, vol. 44, no. 5, pp. 779–797. https://doi.org/10.1080/02626669909492273

    Article  Google Scholar 

  26. Valery, A., Modélisation précipitations-débit sous influence nivale, élaboration d’un module neige et évaluation sur 380 bassins versants, Paris: Cemagref, 2010.

    Google Scholar 

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Funding

This study was supported by the RF Ministry of Science and Education under the Governmental Order to PGI FEB RAS, subject 122011400135-0; the analysis of the simulation results was carried out under the Governmental Order to WPI RAS, subject 122041100259.

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Authors and Affiliations

  1. Pacific Geographical Institute, Far-Eastern Branch, Russian Academy of Sciences, 690041, Vladivostok, Russia

    S. Yu. Lupakov, A. N. Bugaets & N. D. Bugaets

  2. Far-Eastern Regional Research Hydrometeorological Institute, 690091, Vladivostok, Russia

    L. V. Gonchukov & O. V. Sokolov

  3. Water Problems Institute, Russian Academy of Sciences, 117971, Moscow, Russia

    L. V. Gonchukov

Authors
  1. S. Yu. Lupakov
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  2. A. N. Bugaets
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  3. L. V. Gonchukov
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  4. O. V. Sokolov
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  5. N. D. Bugaets
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Correspondence to S. Yu. Lupakov.

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Lupakov, S.Y., Bugaets, A.N., Gonchukov, L.V. et al. Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia). Water Resour 50, 806–815 (2023). https://doi.org/10.1134/S0097807823700136

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