Estimation of the Changes in the Rainfall Erosivity in Hungary

Gábor Mezősi 1  and Teodóra Bata 1
  • 1 Department of Physical Geography and Geoinformatics, University of Szeged, Egyetem u. 2-6, H-6722 Szeged, Hungary

Abstract

According to the forecasts of numerous regional models (eg. REMO, ALADIN, PREGIS), the number of predicted rainfall events decreases, but they are not accompanied by considerably less precipitation. It represents an increase in rainfall intensity. It is logical to ask (if the limitations of the models make it possible) to what extent rainfall intensity is likely to change and where these changes are likely to occur in the long run. Rain intensity is considered to be one of the key causes of soil erosion. If we know which areas are affected by more intense rain erosion, we can identify the areas that are likely to be affected by stronger soil erosion, and we can also choose effective measures to reduce erosion. This information is necessary to achieve the neutral erosion effect as targeted by the EU. We collected the precipitation data of four stations every 30 minute between 2000 and 2013, and we calculated the estimated level of intensity characterizing the Carpathian Basin. Based on these data, we calculated the correlation of the measured data of intensity with the values of the MFI index (the correlation was 0.75). According to a combination of regional climate models, precipitation data could be estimated until 2100, and by calculating the statistical relationship between the previous correlation and this data sequence, we could estimate the spatial and temporal changes of rainfall intensity.

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  • Arnoldus, H.M.J. 1980. An approximation of the rainfall factor in the Universal Soil Loss Equation. In: De Boodt, M., Gabriels, D. (Eds.): Assessment of Erosion. John Wiley & Sons, Chichister, 127–132.

  • Blanka, V., Mezősi, G., Meyer, B. 2013. Projected changes in the drought hazard in Hungary due to climate change, Idõjárás, J.Hungarian Meteorol. Serv., 117, 219–237.

  • Borrelli, P., Diodato, N., Panago, P. 2016. Rainfall erosivity in Italy: a national scale spatio-temporal assessment. International Journal of Digital Earth, 2016 (online first) DOI: 10.1080/17538947.2016.1148203

  • Centeri, Cs. 2002. Az általános talajveszteség becslési egyenlet (USLE) K tényezőjének vizsgálata. PhD dissertation. Szent István University. Gödöllő

  • Deumlich D, Funk R, Frielinghaus M.O., Schmidt, W.A., Nitzsche. O. 2006. Basics of effective erosion control in German agriculture. Journal of Plant Nutrition and Soil Science, 169, 370–381. DOI: 10.1002/jpln.200621983

  • van Dijk AI, Bruijnzeel LA, Rosewell CJ 2002 Rainfall intensity – kinetic energy relationships: a critical literature appraisal. J. Hydrol 261, 1–23. DOI: 10.1016/s0022-1694(02)00020-3

  • Diodato, N., Bellochi. G. 2007. Estimating monthly (R)USLE climate in-put in a Mediterranean region using limited data. J. Hydrol., 345, 224–236. DOI: 10.1016/j.jhydrol.2007.08.008

  • Eltaif, N.I., Gharaibeh, M.A., Al-Zaitawi, F., Alhamad, M.N. 2010. Approximation of rainfall erosivity factors in North Jordan. Pedosphere 20 (6): 711—717. DOI: 10.1016/s1002-0160(10)60061-6

  • Fournier, F. 1960. Climat et érosion. La relation entre l'érosion du sol par l'eau et les précipitations atmosphériques. [Relationship between soil erosion by water and rainfall]. Presses Universitaires de France, Paris. (In French.)

  • Goovaerts, P. 1999. Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89 (1–2), 1–4. DOI: 10.1016/s0016-7061(98)00078-0

  • Hernando, D., Romana, M.G. 2015. Estimating the rainfall erosivity factor from monthly precipitation data in the Madrid Region (Spain). J. Hydrol. Hydromech., 63 (1), 55–62. DOI: 10.1515/johh-2015-0003

  • Jenece, M., Kubatova, E., Trippl, M. 2006. Revised Determination of the Rainfall-runoff Erosivity Factor R for Application of USLE in Czech Republic. Soil and Water Res. 2, 65–71.

  • Jordán, Gy., van Rompey, A., Szilassi, P., Csillag, G. 2004. Digitális domborzatmodell alkalmazása GIS környezetben a Káli- medence talajerózió vizsgálatában. HUNDEM, Miskolc. http://www.uni-miskolc.hu/~fkt/hundem/Cikkek/Jor-dan%20Gy%20-%20A%20von%20Rompey%20-%20Szilassi%20P%20-%20Csillag%20G.pdf

  • Kertész Á., Richter, G. 1997. Results. Soil loss in the Örvényesi watershed In: The Balaton project. ESSC Newsletter 1997. 2-3. Bedford. European Society for Soil Conservation, 22–26.

  • van der Knijff, J.M., Jones, R.J.A., Montanarella, L. 2000. European Commission directorate general JRC joint research centre Space Applications Institute European Soil Bureau Soil Erosion Risk Assessment. p.38 http://www.unisdr.org/files/1581_ereurnew2.pdf

  • Lakatos, M., Szentirmai, T., Bihari, Z. 2011. Application of gridded daily data series for calculation of extreme temperature and precipitation indices in Hungary. Idojaras 115 (1-2), 99–109.

  • Lo, A., El-Swaify, S.A., Dangler, E.W., Shinshiro, L. 1985. EI30 as an erosivity index in Hawaii. In: El-Swaify S.A., Moldenhauer W.C. & Lo A. (eds), Soil erosion and conservation. Soil Conservation Society of America, Ankeny, 384–392.

  • Mezősi, G., Meyer, B.C., Loibl, W., Aubrecht, Ch., Csorba, P., Bata, T. 2013. Assessment of regional climate change impacts on Hungarian landscapes. Regional Environmental Change 13, 4 797–811. DOI: 10.1007/s10113-012-0326-1

  • Onchev, N.G. 1985. Universal index for calculating rainfall erosivity. In: El-Swaify, S.A., Moldenhauer, W.C., Lo, A. (Eds.): Soil erosion and conservation. Soil Conservation Society of America, Ankeny, 424–431.

  • Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M.P., Michaelides, S., Hrabalíková, M., Olsen, P., Aalto, J., Lakatos, M., Rymszewicz, A., Dumitrescu, A., Beguería, S., Alew, Ch. 2015. Rainfall erosivity in Europe. Science of the Total Environment 511, 801–814. DOI: 10.1016/j.scitotenv.2015.01.008

  • Renard, K.G., Freimund, J.R. 1994. Using monthly precipitation data to estimate the R-factor in the revised USLE. J. Hydrol., 157, 287–306. DOI: 10.1016/0022-1694(94)90110-4

  • Sauerborn, P., Klein, A., Botschek, J., Skowronek, A. 1999. Future rainfall erosivity derived from large-scale climate models — methods and scenarios for a humid region. Geoderma 93. 269–27. DOI: 10.1016/s0016-7061(99)00068-3

  • Stefanovics, P. 1992. Talajtan. Mezőgazda Kiadó, Budapest.

  • Szabó, P., Horányi, A., Krüzselyi, I., Szépszó, G. 2011. The climate modelling at Hungarian Meteorological Survey: ALADIN and REMO. 36. Meteorológiai Tudományos Napok OMSZ, Budapest, 87–101.

  • Szűcs, P. 2012. Az erózió lépték függése. PhD dissertation. Pannon Egyetem Keszthely p. 146.

  • Wischmeier, W.H. 1959. A rainfall erosion index for a Universal Soil-Loss Equation. Soil Sci. Soc. Am. Proc. 23 (3), 246–249. DOI: 10.2136/sssaj1959.03615995002300030027x

  • Wischmeier, W.H., Smith, D.D. 1978. Predicting rainfall erosion losses. A guide to conservation planning. Agriculture Handbook No. 537. U.S. Department of Agriculture, Washington, D.C

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