Evaluation of discrepancies in spatial distribution of rainfall erosivity in the Czech Republic caused by different approaches using GIS and geostatistical tools

https://doi.org/10.17221/176/2015-SWRCitation:Brychta J., Janeček M. (2017): Evaluation of discrepancies in spatial distribution of rainfall erosivity in the Czech Republic caused by different approaches using GIS and geostatistical tools. Soil & Water Res., 12: 117-127.
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The study presents all approaches of rainfall erosivity factor (R) computation and estimation used in the Czech Republic (CR). A lot of distortions stem from the difference in erosive rainfall criteria, time period, tipping rain gauges errors, low temporal resolution of rainfall data, the type of interpolation method, and inappropriate covariates. Differences in resulting R values and their spatial distribution caused by the described approaches were analyzed using the geostatistical method of Empirical Bayesian Kriging and the tools of the geographic information system (GIS). Similarity with the highest temporal resolution approach using 1-min rainfall data was analyzed. Different types of covariates were tested for incorporation to the cokriging method. Only longitude exhibits high correlation with R and can be recommended for the CR conditions. By incorporating covariates such as elevation, with no or weak correlation with R, the results can be distorted even by 81%. Because of significant yearly variation of R factor values and not clearly confirmed methodology of R values calculation and their estimation at unmeasured places we recommend the R factor for agricultural land in the Czech Republic R = 40 MJ/ha·cm/h +/– 10% depends on geographic location.
Bonilla Carlos A., Vidal Karim L. (2011): Rainfall erosivity in Central Chile. Journal of Hydrology, 410, 126-133  https://doi.org/10.1016/j.jhydrol.2011.09.022
Dostál T. et al (2006): Partial Final Report of Project COST No. 1P04OC634.001 Methods and Ways of Predicting Surface Runoff, Erosion and Transport Processes in the Landscape. Prague, ČVUT. (in Czech)
Goovaerts P. (1999): Using elevation to aid the geostatistical mapping of rainfall erosivity. CATENA, 34, 227-242  https://doi.org/10.1016/S0341-8162(98)00116-7
Goovaerts P. (1999): Geostatistics in soil science: state-of-the-art and perspectives. Geoderma, 89, 1-45  https://doi.org/10.1016/S0016-7061(98)00078-0
Hanel Martin, Máca Petr, Bašta Petr, Vlnas Radek, Pech Pavel (2016): The rainfall erosivity factor in the Czech Republic and its uncertainty. Hydrology and Earth System Sciences, 20, 4307-4322  https://doi.org/10.5194/hess-20-4307-2016
Hermando D., Romana G.M. (2015): Estimating the rainfall erosivity factor from monthly precipitation data in the Madrid region (Spain). Journal of Hydrology and Hydromechanics, 63: 55–62.
Janeček M. et al. (1992): Protection of Agricultural Land from Erosion. Prague, UVTIZ. (in Czech)
Janeček M., Kubátová E., Tippl M. (2006): Revised determination of the rainfall-runoff erosivity factor R for application of USLE in the Czech Republic. Soil and Water Research, 1: 65–71.
Janeček M., Kubátová E., Procházková E. (2012a): The influence of precipitation and rainfall intensity on soil loss by water erosion. Vodní hospodářství, 62: 134–137. (in Czech)
Janeček M., Květon V., Kubátová E., Kobzová D. (2012b): Differention and regionalization of rainfall erosivity factor values in the Czech Republic. Soil and Water Research, 7: 1–9.
Janeček M. et al (2012c): Protection of agricultural land from erosion, VUMOP, Prague. (in Czech)
Janeček Miloslav, Květoň Vít, Kubátová Eliška, Kobzová Dominika, Vošmerová Michaela, Chlupsová Jana (2013): Values of rainfall erosivity factor for the Czech Republic. Journal of Hydrology and Hydromechanics, 61, -  https://doi.org/10.2478/johh-2013-0013
Krása J. (2004): Evaluation of Erosion Processes in Large River Basins with the Support of GIS. [Ph.D. Thesis.] Prague, Czech Technical University in Prague, Faculty of Civil Engineering. (in Czech)
Krása J., Středová H., Dostál T., Novotný I. (2014): Rainfall erosivity research on the territory of the Czech Republic. In: Rožnovský J., Litschmann T. (eds): Mendel a Climatology, Brno, Sept 3–5, 2014.
Krivoruchko K., Gribov A. (2014): Pragmatic Bayesian kriging for nonstationary and moderately non-Gaussian data. In: Mathematics of Planet Earth. Proc. 15th Annual Conf. Int. Association for Mathematical Geosciences. Springer: 61–64.
Lee Joon-Hak, Heo Jun-Haeng (2011): Evaluation of estimation methods for rainfall erosivity based on annual precipitation in Korea. Journal of Hydrology, 409, 30-48  https://doi.org/10.1016/j.jhydrol.2011.07.031
Mikhailova E. A., Bryant R. B., Schwager S. J., Smith S. D. (1997): Predicting Rainfall Erosivity in Honduras. Soil Science Society of America Journal, 61, 273-  https://doi.org/10.2136/sssaj1997.03615995006100010039x
Moral F.J. (2010): Comparison of different geostatistical approaches to map climate variables: application to precipitation. International Journal of Climatology, 30: 620–631.
Panagos Panos, Ballabio Cristiano, Borrelli Pasquale, Meusburger Katrin, Klik Andreas, Rousseva Svetla, Tadić Melita Perčec, Michaelides Silas, Hrabalíková Michaela, Olsen Preben, Aalto Juha, Lakatos Mónika, Rymszewicz Anna, Dumitrescu Alexandru, Beguería Santiago, Alewell Christine (2015): Rainfall erosivity in Europe. Science of The Total Environment, 511, 801-814  https://doi.org/10.1016/j.scitotenv.2015.01.008
Phillips Donald L, Dolph Jayne, Marks Danny (1992): A comparison of geostatistical procedures for spatial analysis of precipitation in mountainous terrain. Agricultural and Forest Meteorology, 58, 119-141  https://doi.org/10.1016/0168-1923(92)90114-J
Pilz Jürgen, Spöck Gunter (2008): Why do we need and how should we implement Bayesian kriging methods. Stochastic Environmental Research and Risk Assessment, 22, 621-632  https://doi.org/10.1007/s00477-007-0165-7
Renard Kenneth G., Freimund Jeremy R. (1994): Using monthly precipitation data to estimate the R-factor in the revised USLE. Journal of Hydrology, 157, 287-306  https://doi.org/10.1016/0022-1694(94)90110-4
Renard K.G., Foster G.R., Weesies G.A., Mccool D.K., Yoder D.C. (1997): Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). USDA Agriculture Handbook No. 703, Washington D.C., USDA-ARS.
Rogler H., Schwertmann U. (1981): Erosivitat der Niederschlage und Isoerodentkarte von Bayern. Zeitschrift für Kulturtechnik und Flurbereinigung, 22: 99–112.
Schwertmann U., Vogel W., Kainz M. (1987): Bodenerosion durch Wasser. Stuttgart, E. Ulmer Gmbh.
Sokolová I. (1992): Determining rainfall erosivity factor R for South Bohemian region. Pedologie a Meliorace, 28: 45–50. (in Czech)
Švehla F., Skořepa Z. (1995): Adjusting the data for determining the value of K and R factors in Wischmeier-Smith’s formula. Pozemkové úpravy, 11: 12–13. (in Czech)
Toman F., Sanetrník J., Filip J. (1993): The influence of climatic conditions on the factor of erosion efficiency of torrential rains. In: Proc. Agro-meteorological Conference 93, Brno, Nov 25–26, 1993: 67–69. (in Czech)
Torri D., Borselli L., Guzzeti F. et al. (2006): Soil erosion in Italy: an overview. In: Boardman J., Poesen J. (eds): Soil Erosion in Europe. New York, Wiley: 245–261.
Van Der Knijff J.M., Jones R.J.A., Montanarella L. (2000): Soil Erosion Risk Assessment in Europe. Ispra, European Soil Bureau.
Wischmeier W.H., Smith D.D. (1978): Predicting Rainfall Erosion Losses – A Guide to Conservation Planning. USDA Agricultural Handbook No. 537, Washington D.C., USDA.
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