1 Department of Geoinformatics, Physical and Environmental Geography, University of Szeged, Hungary;

2 Faculty of Water Resources, Hanoi University of Natural Resources and Environment, Vietnam;

3 Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Hungary;

*Corresponding author:


The indicators of climate change in Central Europe, Hungary is showing a trend of decrease in rainfall, increase in temperature and especially extreme weather that is becoming more usual and unpredictable. The current study presents the application of the MIKE SHE model to examine the role of unsaturated soil settings and the effects of climate change on various hydrological parameters and water balance components. The input data has been provided by Lower-Tisza District Water Directorate. The one-at-a-time method utilized in this study allows for the investigation of the impact of various input parameter combinations on the estimated values of different hydrological parameters and water balance components. The findings demonstrated that the level of detailedness of the soil as an input parameter significantly influences the results of the modelled groundwater circulation and therefore the dynamics of the water regime. According to the simulation results of the temperature increase, the water table can be regarded as the primary water supply that replenishes the streams. The simulation results show that the groundwater table and evapotranspiration are the two main driving forces in the Dong-ér catchment's water regime. These findings will be used as a reference for water resource management and irrigation infrastructure planning in the context of complex climate change contexts.


Cite this paper

Tran, Q.H.; Fehér, Z.Z. Estimation of the water regime under different climate scenarios and the importance of the thoroughness of the soil as input layer in a small watershed in Central-Hungary. VN J. Hydrometeorol. 2022, 12, 39-56.


1. IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, 2021. Online available at:
2. Rakonczai, J.; Ladányi, Zs.; Blanka, V.; Fehér, Z.S.; Kovács, F. A Globális környezeti válzozások fontosabb magyarországi hatásai. -In: RAKONCZAI, J. (ed.): Elfogyasztott jövőnk? Globális környezeti és geopolitikai kihívásaink, Budapesti Corvinus Egyetem, Budapest, 2021, pp. 275.
3. OMSZ. 2019 is the warmest year since 1901 in Hungary (in Hungarian), 2020. Online available at:
4. Unger, J., Gál, T.; Rakonczai, Mucsi, Szatmári, J.; Tobak, Z.; van Leeuwen, B.; Fiala, K. Modeling of the urban heat island pattern based on the relationship between surface and air temperatures. Q. J. Hung. Meteorogical Serv. 2010, 4(114), 287–302.
5. Gál, T.; Skrabit, N.; Molnár, G.; Unger, J. Projections of the urban and intra-urban scale thermal effects of climate change int he 21st century for cities in Carpathian Basin. Hung. Geog. Bull. 2021, 70(1), 19–33.
6. Fricke, C.; Pongrácz, R.; Unger, J. Comparision of daily and monthly infra-urban thermal reactions based on LCZ classification using surface and air temperature data. Geog. Pannonica 2022, 26(1), 1–11.
7. Szép, T. A klímaváltozás erdészeti ökonómiai vonatkozásai. Economic aspects of forestry in climate change. PhD doctoral dissertation, 2010. .
8. Janik, G.; Hirka, A.; Koltay, A.; Juhász, J.; Csóka, Gy. 50 év biotikus kárai a magyar bükkösökben (50 years biotic damages in the Hungarian beech forests). Erdészeti Tudományos Közlemények [Forestry Scientific Publications]. 2016, (6)1, 45–60.
9. Tölgyesi, Cs.; Török, P.; Hábenczyus, A.A.; Bátori, Z.; Valkó, O.; Deák, B.; Tóthmérész, B.; Erdős, L.; Kelemen, A. Underground deserts below fertility islands? Woody species desiccate lower soil layers in sandy drylands. Ecography 2020, 43(6), 848–859.
10. OVF. Effects of climate change, hydrometeorological extremes (in Hungarian), 2016. Online available at:
11. Singh, A. Conjunctive use of water resources for sustainable irrigated agriculture. J. Hydrol. 2014, 519, 1688–1697.
12. Ladányi, Zs. Climate change impact in a sample area of Danube-Tisza Interfluve. In: Kiss, T. (Ed.): Natural geographical processes and forms. Natural Geography Studies of the 9th National Conference of Geographical Doctoral Students, 2010, 93–98. (in Hungarian). Online available at:
13. EU Water Framework Directive. 2004, 1–4. Doi:10.2779/50903.
14. OVF. Tisza River Basin Management Plan by General Directorate of Water Management, 2015. (in Hungarian).
15. Sipos, Gy.; Právecz T. Identification of water retention areas on the Dong-ér catchment using GIS. In: Blanka, V., Ladányi, Zs. (Ed.) Drought and Water Management in South Hungary and Vojvodina. University of Szeged, 2014, 157–167.
16. Tran, Q.H.; Fehér, Z.Zs. Water balance calculation capability of hydrological models. Acta Agraria Kaposváriensis 2022, 26(1), 37–53. Doi:10.31914/aak.2877.
17. Graham, D.N.; Butts, M. Flexible, integrated watershed modelling with MIKE SHE. In: Singh, V.P.; Frevert, D.K. (Ed). In Watershed Models. CRC Press. 2005, 245–272. Doi:10.1201/9781420037432.ch10.
18. Nagy, Zs.; Pálfi, G.; Priváczkiné Hajdú, Zs.; Benyhe, B. Operation of canal systems and multi-purpose water management – Dong-ér catchment (in Hungarian) In: Ladányi, Zs., Blanka, V. (Ed.) Monitoring, risks and management of drought and inland excess water in South Hungary and Vojvodina. University of Szeged. 2019, 83–96.
19. DHI. MIKE SHE Volume 1: User guide. 2017. Online available at:
20. Hamby, D.M. A review of techniques for parameter sensitivity analysis of environmental models. Environ. Monit. Assess. 1994, 32, 135–154. Doi:
21. Ibarra, S.; Romero, R.; Poulin, A.; Glaus, M.; Cervantes, E.; Bravo, J.; Pérez, R.; Castillo, E. Sensitivity analysis in hydrological modelling for the Gulf of México. Procedia Eng. 2016, 154, 1152–1162. Doi: 10.1016/j.proeng.2016.07.531.
22. Bahremnad, A.; de Smedt, F. Distributed Hydrological Modeling and Sensitivity Analysis in Torysa Watershed, Slovakia. Water Resour. Manage. 2007, 22, 393–408. Doi: 10.1007/s11269-007-9168-x.
23. van Leeuwen, B.; Právetz, T.; Liptay Z.Á.; Tobak, Z. Physically based hydrological modelling of inland excess water. Carpathian J. Earth Environ. Sci. 2016, 11(2), 497–510.
24. Dövényi, Z. (Ed). Magyarország kistájainak katasztere. [Cadastre of the small area of Hungary] MTA Földrajztudományi Kutatóintézet. Budapest. 2010. ISBN 978-963-9545-29-8.
25. Kozák, P. Changes in surface runoff on the south-eastern slope of the Danube-Tisza Interfluve Sand Ridge in the context of climate change. In: Farsang, A., Ladányi, Zs., Mucsi, L. (Ed.) Climate change challenges – From global to local. GeoLitera 2020, 109–115. (In Hungarian).
26. Mérnöki, K.K.; Iroda, K.F.T. Harmonized activities related to extreme water management events – especially flood, inland inundation and drought (in Hungarian). 2013. HUSRB/1203/121/145/01, Ref. No.: T-51/2013.
27. Právetz, T.; Sipos, G.; Benyhe, B.; Blanka, V. (). Modelling runoff on a small lowland catchment, Hungarian Great Plains. J. Environ. Geogr. 2015, 8(1–2), 49–58. Doi: 10.1515/jengeo-2015-0006.
28. IPCC. Global Warming of 1.5˚C. Thematic Reports. 2018.
29. Fehér, Z.Z.S. Large scale geostatistical modelling of the shallow groundwater time series on the Southern Great Hungarian Plain. Two approaches for spatiotemporal stochastic simulation of a non-complete monitoring dataset. PhD Thesis. University of Szeged. 2019. Doi:
30. Szatmári, J.; van Leeuwen, B. (Ed.). Inland Excess Water – Belvíz – Suvišne Unutrašnje Vode, Szeged, University of Szeged. Novi Sad, University of Novi Sad. 2013. Doi: 10.13140/2.1.5143.3920.
31. OMSZ. To the margin of the IPCC Thematic Report assessing a 1.5 degree global temperature rise. 2018. (In Hungarian).,5_fokos_globalis_homerseklet-emelkedest_ertekelo_Tematikus_Jelentesenek_margojara.
32. Fiala, K.; Barta, K.; Benyhe, B.; Fehérváry, I.; Lábdy, J.; Sipos, Gy.; Győrffy, L. Operational drought and water scarcity monitoring system (In Hungarian). Hungarian J. Hydrol. 2018, 98, 14–24.
33. EEA. Corine Land Cover 2018. European Environmental Agency. 2018.
34. Aune-Lundberg, L.; Geir-Harald, S. The content and accuracy of the CORINE Land Cover dataset for Norway. Int. J. Appl. Earth Obs. Geoinf. 2020, 96(102266), 1–10. Doi: 10.1016/j.jag.2020.102266.
35. Feranec, J.; Soukup, T.; Hazeu, G.; Jaffrain, G. (Ed.). European landscape dynamics. Corine land cover data, CRC-Press. Boca Raton. 2016, 9–14.
36. Myneni, R.; Knyazikhin, Y.; Park, T. MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC. 2015.
37. van Genuchten, M.Th.; Leij, J.F.; Yates, R.S. The RETC Code for Quantifying the Hydraulic Functions of Unsaturated Soils. U.S. Salinity Laboratory U.S. Department of Agriculture, Agricultural Research Service Riverside, California. 1991, EPA/600/2-91/065.
38. Pásztor, L.; Laborczi, A.; Takács, K.; Illés, G.; Szabó, J.; Szatmári, G. Progress in the elaboration of GSM conform DSM products and their functional utilization in Hungary. Geoderma Reg. 2020, 21, e00269.
39. Fetter, C.W. Applied Hydrogeology. 3rd Edition, Macmillan College Publishing Company, New York, 1994.