iForest - Biogeosciences and Forestry


The impact of land use on future water balance - A simple approach for analysing climate change effects

András Herceg   , Péter Kalicz, Zoltán Gribovszki

iForest - Biogeosciences and Forestry, Volume 14, Issue 2, Pages 175-185 (2021)
doi: https://doi.org/10.3832/ifor3540-014
Published: Apr 13, 2021 - Copyright © 2021 SISEF

Research Articles

Regional climate change projections for Europe agree in predicting a statistically significant warming in all seasons. The most significant climate change effect is its impact on water cycle through altering precipitation patterns and evapotranspiration processes at multiple scales. The anticipated changes in the distribution and precipitation amounts together with continuously increasing temperatures may induce a higher rate of water consumption in plants, which can generate changes in soil moisture, groundwater, and the water cycle. Thus, climate change can cause changes in the water balance equations structure. A Thornthwaite-type monthly step water balance model was established to compare the water balance in three different surface land cover types: (i) a natural forested area; (ii) a parcel with mixed surface cover; (iii) an agricultural area. The key parameter of the model is the water storage capacity of the soil. Maximal rooting depth of the given area is also determinable during the calibration process using actual evapotranspiration (AET) and soil physical data. The locally calibrated model was employed for assessing future AET and soil moisture of selected land cover types using data from four bias-corrected regional climate models. The projections demonstrate increasing actual evapotranspiration values in each surface cover type at the end of the 21st century. Regarding the 10th percentile minimum soil moisture values, the forested area displayed an increasing trend, while the agricultural field and mixed parcel showed a strong decrease. The 30-year monthly means of evapotranspiration shows the maximum values in June and July, while the minimum soil moisture in September. Water stress analysis indicates water stress is expected to occur only in the agricultural field during the 21st century. The comparison of the three surface covers reveals that forest has the greatest soil water storage capacity due to the highest rooting depth. Thus, according to the projections for 21st century, less water stress is predicted to occur at the forested area compared to the other two surface covers which shows shallow rooting depth.


Water Balance, Climate Change, Plant Available Water, Evapotranspiration, Soil Moisture, Water Stress

Authors’ address

András Herceg
Péter Kalicz 0000-0003-0010-9519
Zoltán Gribovszki 0000-0003-3061-8912
Institute of Geomatics and Civil Engineering, University of Sopron, Sopron (Hungary)

Corresponding author

András Herceg


Herceg A, Kalicz P, Gribovszki Z (2021). The impact of land use on future water balance - A simple approach for analysing climate change effects. iForest 14: 175-185. - doi: 10.3832/ifor3540-014

Academic Editor

Raffaele Lafortezza

Paper history

Received: Jun 01, 2020
Accepted: Feb 05, 2021

First online: Apr 13, 2021
Publication Date: Apr 30, 2021
Publication Time: 2.23 months

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 5141
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 2819
Abstract Page Views: 350
PDF Downloads: 1565
Citation/Reference Downloads: 2
XML Downloads: 405

Web Metrics
Days since publication: 1141
Overall contacts: 5141
Avg. contacts per week: 31.54

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Nov 2020)

(No citations were found up to date. Please come back later)


Publication Metrics

by Dimensions ©

Articles citing this article

List of the papers citing this article based on CrossRef Cited-by.

Aber J, Neilson R, Mcnulty S, Lenihan J, Bachelet D, Drapek R (2009)
Forest processes and global environmental change: predicting the effects of individual and multiple stressors. BioScience 51: 735-751.
CrossRef | Gscholar
Allen RG, Pereira LS, Raes D, Smith M (1998)
Crop evapotranspiration: guidelines for computing crop water requirements. In: “FAO Irrigation and drainage paper 56”. FAO - Food and agriculture organization of the United Nations, Rome, Italy, pp. 3-13.
Online | Gscholar
Baumgartner A, Liebscher HJ (1995)
Allgemeine Hydrologie, Quantitative Hydrologie, In: “Lehrbuche der Hydrologie, Band 1” [General Hydrology, Quantitative Hydrology, In: “Textbooks of Hydrology”, vol. 1]. Berlin, Stuttgart, Germany, pp. 320-350. [in German]
Bormann H, Breuer L, Graeff T, Huisman J (2007)
Analysing the effects of soil properties changes associated with land use changes on the simulated water balance: a comparison of three hydrological catchment models for scenario analysis. Ecological Modelling 209: 29-40.
CrossRef | Gscholar
Christensen JH, Christensen OB (2007)
A summary of the PRUDENCE model projections of changes in European climate by the end of this century, Climatic Change 81: 7-30.
CrossRef | Gscholar
Csáki P, Gyimóthy K, Kalicz P, Szolgay J, Zagyvainé KKA, Gribovszki Z (2020)
Multi-model climatic water balance prediction in the Zala River Basin (Hungary) based on a modified Budyko framework. Journal of Hydrology and Hydromechanics 68 (2): 200-210.
CrossRef | Gscholar
Cui Y, Chen X, Gao J, Yan B, Tang G, Hong Y (2018)
Global water cycle and remote sensing big data: overview, challenge, and opportunities. Big Earth Data 2 (3): 282-297.
CrossRef | Gscholar
Czimber K (2018)
Agroclimate decision support system. Project TÁMOP-4. 2. 2. A-11/1/KONV-012-0013 “The impact assessment of projected climate change and adaptation options in the forestry and agricultural sectors”. University of West Hungary, Sopron, Hungary.
Online | Gscholar
Dingman SL (2002)
Physical hydrology (2nd edn). Prentice Hall, Upper Saddle River, NJ, USA, pp. 646.
Dobor L, Barcza Z, Hlásny T, Havasi A (2013)
Creation of the FORESEE database to support climate change related impact studies, In: Proceedings of the “International Scientific Conference for PhD Students”. Györ (Hungary) 19-20 Mar 2013. University of West Hungary Press, Sopron, Hungary, pp. 1-5.
Dövényi Z (2010)
Magyarország kistájainak katasztere - második, átdolgozott és bövített kiadás [Inventory of microregions in Hungary]. Hungarian Academy of Sciences, Geographical Institute, Budapest, Hungary, pp 299, pp. 345-347. [in Hungarian]
Granier A, Breda N, Biron P, Villette S (1999)
A lumped water balance model to evaluate duration and intensity of drought constraints in forest stands. Ecological Modelling 116 (2-3): 269-283.
CrossRef | Gscholar
Gulyás K, Bidló A, Horváth A (2015)
Estimation of water stress by comparing the Thornthwaite water balance model with a tree ring width analysis. In: Proceedings of the Conference “HydroCarpath 2015, Catchment Processes in Regional Hydrology”. Nyugat-magyarországi Egyetem Kiadó, Sopron (Hungary) 29 Oct 2016, pp. 6.
Online | Gscholar
Gálos B, Führer E, Czimber K, Gulyás K, Bidló A, Hänsler A, Jacob D, Mátyás C (2015)
Climatic threats determining future adaptive forest management - a case study of Zala County. IDOJÁRÁS, Quarterly Journal of the Hungarian Meteorological Service, vol. 119, no. 4, pp. 425-441.
Online | Gscholar
Gáspár L, Karoliny M, Tóth C (2017)
BCRRA Predicting subgrade soil strength using FWD and meteorological time series data. In: Proceedings of the “10th International Conference on the Bearing Capacity of Roads, Railways and Airfields (BCRRA 2017)” (Loizos A, Al-Qadi I, Scarpas T eds). Athens (Greece) 28-30 June 2017. Taylor & Francis Group, London, UK, pp. 2117-2125.
Götz B, Hadatsch S, Kratochvil R, Vabitsch A, Freyer B (2000)
Biologische Landwirtschaft im Marchfeld. Potenziale zur Entlastung des Natur- und Landschaftshaushaltes [Organic farming in Marchfeld. Potential for relieving the natural and landscape balance]. Umweltbundesamt GmbH, Vienna, pp. 34-36. [in German]
Hamon WR (1963)
Computation of direct runoff amounts from storm rainfall. International Association of Scientific Hydrology 63: 52-62.
Online | Gscholar
Hlásny T, Mátyás C, Seidl R, Kulla L, Merganičová K, Trombik J, Dobor L, Barcza Z, Konôpka B (2014)
Climate change increases the drought risk in Central European forests: what are the options for adaptation? Central European Forestry Journal 60: 5-18.
CrossRef | Gscholar
IPCC (2019)
Technical Summary, 2019. In: “Climate Change and Land. An IPCC Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems” (Shukla PR, Skea J, Calvo Buendia E, Masson-Delmotte V, Pörtner H-O, Roberts DC, Zhai P, Slade R, Connors S, van Diemen R, Ferrat M, Haughey E, Luz S, Neogi S, Pathak M, Petzold J, Portugal Pereira J, Vyas P, Huntley E, Kissick K, Belkacemi M, Malley J. eds). IPCC, Japan, pp. 37-74.
Online | Gscholar
Keables MJ, Mehta S (2010)
A soil water climatology for Kansas. Great Plains Research 20 (2): 229-248.
Online | Gscholar
Keve G, Nováky B (2010)
Klímaváltozás hatásának vizsgálata a Bácsbokodi-Kígyós csatorna vízgyüjtöjén Budyko-modell alkalmazásával [Investigation of the impact of climate change in the catchment of the Bácsbokodi-Kígyós canal using the Budyko model]. In: “A Magyar Hidrológiai Társaság XXVIII, Országos Vándorgyülése”. Sopron (Hungary) 7-9 Jul 2010. Magyar Hidrológiai Társaság, Budapest, pp. 1207-1225. [in Hungarian]
Kisházi P, Ivancsics J (1985)
Sopron Környéki Üledékek Összefoglaló Földtani Értékelése [Geological assessement of sediments in the neighbourhood of Sopron]. Manuscript, Sopron, Hungary, pp. 48. [in Hungarian]
Kjellström E, Nikulin G, Hansson U, Strandberg G, Ullerstig A (2011)
21st century changes in the European climate: uncertainties derived from an ensemble of regional climate model simulations. Tellus A 63: 24-40.
CrossRef | Gscholar
Kovács A (2011)
Tó- és területi párolgás becslésének pontosítása és magyarországi alkalmazásai [Specifying lake and areal evapotranspiration rates in Hungary]. PhD thesis, Vásárhelyi Doctoral School of Civil Engineering and Earth Sciences, Budapest University of Technology and Economics, Budapest, Hungary, pp. 92-94. [in Hungarian]
Lutz JA, Wagtendonk JW, Franklin JF (2010)
Climatic water deficit, tree species ranges, and climate change in Yosemite National Park, Journal of Biogeography 37: 936-950.
CrossRef | Gscholar
Maidment DR (1993)
Handbook of hydrology, McGraw-Hill Education, New York, USA, pp. 563-567.
Mas-Pla J, Menció A (2019)
Groundwater nitrate pollution and climate change: learnings from a water balance-based analysis of several aquifers in a western Mediterranean region (Catalonia). Environmental Science and Pollution Research 26: 2184-2202.
CrossRef | Gscholar
Mingteh CS (2006)
Forest hydrology: an introduction to water and forests (2nd edn). Austin State University, Austin, TX, USA, , pp. 181.
Muggeo VMR (2008)
Segmented: an R package to fit regression models with broken-line relationships. R News, vol. 8/1, pp. 20-25.
Mátyás C, Berki I, Bidló A, Csóka G, Czimber K, Führer E, Gálos B, Gribovszki Z, Illés G, Hirka A, Somogyi Z (2018)
Sustainability of forest cover under climate change on the temperate-continental xeric limits. Forests 9 (8): 489.
CrossRef | Gscholar
Nachtnebel HP, Dokulil M, Kuhn M, Loiskandl W, Sailer R, Schöner W (2014)
Influence of climate change on the hydrosphere. In: “Austrian Assessment Report Climate Change 2014 (AAR14)”. Austrian Panel on Climate Change (APCC), Austrian Academy of Sciences Press, Vienna, Austria, pp. 411-466.
Nistor M, Gualtieri A, Cheval S, Dezsi S, Botan V (2016)
Climate change effects on crop evapotranspiration in the Carpathian Region during 1961-2010. Meteorological Applications 23: 462-469.
CrossRef | Gscholar
Nolz R, Cepuder P, Kammerer G (2014)
Determining soil water-balance components using an irrigated grass lysimeter in NE Austria. Journal of Plant Nutrition and Soil Science 177: 237-244.
CrossRef | Gscholar
Nolz R, Cepuder P, Eitzinger J (2016)
Comparison of lysimeter based and calculated ASCE reference evapotranspiration in a subhumid climate, Theoretical and Applied Climatology 124: 315-324.
CrossRef | Gscholar
Nováky B, Bálint G (2013)
Shifts and modification of the hydrological regime under climate change in Hungary. In: “Climate Change - Realities, Impacts Over Ice Cap, Sea Level and Risks” (Bharat Raj Singh ed). IntechOpen Ltd, London, UK, web site.
CrossRef | Gscholar
Pongrácz R, Bartholy J, Miklós E (2011)
Analysis of projected climate change for Hungary using ENSEMBLES simulations. Applied Ecology and Environmental Research 9 (4): 387-398.
CrossRef | Gscholar
R Core Team (2012)
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Online | Gscholar
Rao LY, Sun G, Ford CR, Vose JM (2011)
Modeling potential evapotranspiration of two forested watersheds in the southern Appalachians. Soil and Water Division of ASABE, American Society of Agricultural and Biological Engineers, vol 54 (6): 2067-2078.
Remrová M, Císlerová M (2010)
Analysis of climate change effects on evapotranspiration in the watershed Uhlírská in the Jizera mountains. Soil and Water Resources 5 (1): 28-38.
CrossRef | Gscholar
Stagl J, Mayr E, Koch H, Hattermann FF, Huang S (2014)
Effects of climate change on the hydrological cycle in Central and Eastern Europe. In: “Managing Protected Areas in Central and Eastern Europe under Climate Change” (Rannow S, Neubert M eds). Springer, Dordrecht, Netherlands, pp. 31-43.
CrossRef | Gscholar
Sun GK, Alstad J, Chen S, Chen CR, Ford G, Lin C, Liu N, Lu SG, McNulty H, Miao A, Noormets JM, Vose B, Wilske M, Zeppel Y, Zhang Z (2011)
A general projective model for estimating monthly ecosystem evapotranspiration. Ecohydrology 4 (2): 245-255.
CrossRef | Gscholar
Szilágyi J, Józsa J (2009)
Estimating spatially distributed monthly evapotranspiration rates by linear transformations of MODIS daytime landsurface temperature data. Hydrology and Earth System Sciences 13 (5): 629--637.
CrossRef | Gscholar
Szilágyi J, Kovacs A, Józsa J (2011)
A calibration-free evapotranspiration mapping (CREMAP) technique. In: “Evapotranspiration” (Labedzki L ed). INTECH, Rijeka, Croatia, pp. 257-274.
Thornthwaite CW, Mather JR (1955)
The water balance. Climatological Laboratory Publication no. 8, Drexel Institute of Technology, Philadelphia, PA, USA, pp. 104.
Van Der Linden P, Mitchell JFB (2009)
ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office, Hadley Centre, Exeter, UK, pp. 160.
Var Der Linden EC, Haarsma RJ, Van Der Schrier G (2019)
Impact of climate model resolution on soil moisture projections in central-western Europe. Hydrology and Earth System Sciences 23: 191-206.
CrossRef | Gscholar

This website uses cookies to ensure you get the best experience on our website. More info