Spatial and temporal variation of the rainfall erosivity factor in Polissya and Forest-Steppe of Ukraine
Abstract
The Poliss y a and the Forest-Steppe constitute a substantial portion of Ukraine's territory, exhibiting considerable potential for the advancement of agricultural and forestry activities. It is of the utmost importance that the economic utilisation of the territory is conducted in a manner that ensures the sustainability of ecological systems and the fulfilment of ecosystem functions. The question of how the dynamics of the erosion potential of precipitation affect crop yields at the regional level remains unanswered. This study identifies patterns of spatial and temporal variability in the erosion potential of precipitation and determines the impact of anthropogenic landscape modification due to agricultural production on soil erosion risks. The coefficient of atmospheric erosion exhibited a range of 179.9 ± 114.7 (in 2015) to 616.0 ± 468.9 (in 1974) MJ mm / ha h per year. The temporal dynamics of this indicator within each administrative district exhibited a positive or negative trend of change over time. The overall level of erosion from precipitation exhibited an upward trend in the western and northwestern regions of the study area. In the central and eastern regions of the study area, there is evidence of a decline in erosion over time. The spatially weighted principal components analysis postulates that the covariance structure varies in a spatial manner, thereby enabling the identification of areas with smaller spatial coverage where the structure is constant. The identified principal components indicate the presence of oscillating time trends, characterised by different frequency characteristics. The spatial characteristics of the principal components of higher-order numbers can be attributed to the influence of the geographical continentality factor. Polissya is distinguished by soils with a relatively high sand content, which frequently renders them unsuitable for agricultural use. Consequently, these regions exhibit a relatively high level of forest cover. The southern and eastern regions are distinguished by soil types with granulometric compositions that are conducive to agricultural productivity. This frequently coincides with the process of deforestation. The variations in precipitation that generate the patterns identified by principal components 3–5 can be attr i buted to the influence of different land cover types. This provides an explanation for the formation of patterns of variability in the rainfall erosion coefficient, which is consistent with the level of forest cover. The influence of coniferous vegetation gives rise to the emergence of factor 4, whereas factor 5 is induced by the influence of herbaceous vegetation. It is also crucial to consider the substantial impact of agricultural land on the formation of spatial patterns of erosion coefficient variability. This influence may be the result of a formal correlation between the variability of agricultural land in different biogeographic zones.References
Bezak, N., Ballabio, C., Mikoš, M., Petan, S., Borrelli, P., & Panagos, P. (2020). Reconstruction of past rainfall erosivity and trend detection based on the REDES database and reanalysis rainfall. Journal of Hydrology, 590, 125372.
Cedrez, C. B., & Hijmans, R. J. (2018). Methods for spatial prediction of crop yield potential. Agronomy Journal, 110(6), 2322–2330.
Christensen, O., Yang, S., Boberg, F., Fox Maule, C., Thejll, P., Olesen, M., Drews, M., Sørup, H., & Christensen, J. (2015). Scalability of regional climate change in Europe for high-end scenarios. Climate Research, 64(1), 25–38.
Cook, H. L. (1937). The nature and controlling variables of the water erosion process. Soil Science Society of America Journal, 1(C), 487–494.
Damos, P. (2016). A stepwise algorithm to detect significant time lags in ecological time series in terms of autocorrelation functions and ARMA model optimisation of pest population seasonal outbreaks. Stochastic Environmental Research and Risk Assessment, 30(7), 1961–1980.
Dash, S. S., & Maity, R. (2023). Effect of climate change on soil erosion indicates a dominance of rainfall over LULC changes. Journal of Hydrology: Regional Studies, 47, 101373.
Fernández, S., Cotos-Yáñez, T., Roca-Pardiñas, J., & Ordóñez, C. (2018). Geographically weighted principal components analysis to assess diffuse pollution sources of soil heavy metal: Application to rough mountain areas in Northwest Spain. Geoderma, 311, 120–129.
Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315.
Gámez-Balmaceda, E., López-Ramos, A., Martínez-Acosta, L., Medrano-Barboza, J. P., Remolina López, J. F., Seingier, G., Daesslé, L. W., & López-Lambraño, A. A. (2020). Rainfall intensity-duration-frequency relationship. case study: Depth-duration ratio in a semi-arid zone in Mexico. Hydrology, 7(4), 78.
Ganasri, B. P., & Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS – A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), 953–961.
Harris, P., Brunsdon, C., & Charlton, M. (2011). Geographically weighted principal components analysis. International Journal of Geographical Information Science, 25(10), 1717–1736.
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36.
Kim, J. B., Saunders, P., & Finn, J. T. (2005). Rapid assessment of soil erosion in the Rio Lempa Basin, Central America, using the universal soil loss equation and geographic information systems. Environmental Management, 36(6), 872–885.
Koshelev, O., Koshelev, V., Fedushko, M., & Zhukov, O. (2021). Annual course of temperature and precipitation as proximal predictors of birds’ responses to climatic changes on the species and community level. Folia Oecologica, 48(2), 118–135.
Kunakh, O. M., Yorkina, N. V., Turovtseva, N. M., Bredikhina, J. L., Balyuk, J. O., & Golovnya, A. V. (2021). Effect of urban park reconstruction on physical soil properties. Ecologia Balkanica, 13(2), 57–73.
Kunakh, O., & Zhukov, O. (2024). Spatial organization of the soil macrofauna community of an oak forest in the steppe zone of Ukraine. Studia Biologica, 18(3), 99–120.
Lloyd, C. D. (2010). Analysing population characteristics using geographically weighted principal components analysis: A case study of Northern Ireland in 2001. Computers, Environment and Urban Systems, 34(5), 389–399.
Majewski, M., & Szpikowski, J. (2024). Effect of rainfall parameters on soil erosion in Chwalimski Brook catchment, NW Poland. Geomorphology, 454, 109167.
Mykhailyuk, T., Lisovets, O., & Tutova, H. (2023). Steppe vegetation islands in the gully landscape system: Hemeroby, naturalness and phytoindication of ecological regimes. Regulatory Mechanisms in Biosystems, 14(4), 581–594.
Nearing, M. A. (2001). Potential changes in rainfall erosivity in the US with climate change during the 21st century. Journal of Soil and Water Conservation, 56, 229–232.
Nearing, M. A., Yin, S. Q,, Borrelli, P., & Polyakov, V. O. (2017). Rainfall erosivity: An historical review. Catena, 157, 357–362.
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., & Alewell, C. (2015). Rainfall erosivity in Europe. Science of the Total Environment, 511, 801–814.
Panagos, P., Ballabio, C., Meusburger, K., Spinoni, J., Alewell, C., & Borrelli, P. (2017). Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets. Journal of Hydrology, 548, 251–262.
Pandey, S., Kumar, P., Zlatic, M., Nautiyal, R., & Panwar, V. P. (2021). Recent advances in assessment of soil erosion vulnerability in a watershed. International Soil and Water Conservation Research, 9(3), 305–318.
Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz, D., McNair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R., & Blair, R. (1995). Environmental and economic costs of soil erosion and conservation benefits. Science, 267(5201), 1117–1123.
Renard, K. G., & Freimund, J. R. (1994). Using monthly precipitation data to estimate the R-factor in the revised USLE. Journal of Hydrology, 157(1–4), 287–306.
Renschler, C. S., Mannaerts, C., & Diekkrüger, B. (1999). Evaluating spatial and temporal variability in soil erosion risk – rainfall erosivity and soil loss ratios in Andalusia, Spain. Catena, 34(3–4), 209–225.
Rieke-Zapp, D. H., & Nearing, M. A. (2005). Digital close range photogrammetry for measurement of soil erosion. Photogrammetric Record, 20(109), 69–87.
Shiono, T., Ogawa, S., Miyamoto, T., & Kameyama, K. (2013). Expected impacts of climate change on rainfall erosivity of farmlands in Japan. Ecological Engineering, 61, 678–689.
Westra, S., Fowler, H. J., Evans, J. P., Alexander, L. V., Berg, P., Johnson, F., Kendon, E. J., Lenderink, G., & Roberts, N. M. (2014). Future changes to the intensity and frequency of short-duration extreme rainfall. Reviews of Geophysics, 52(3), 522–555.
Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion loss: A guide to conservation planning. Agricultural Handbook No. 537. US Department of Agriculture – Agricultural Research Service.
Yakovenko, V., Kunakh, O., Tutova, H., & Zhukov, O. (2023). Diversity of soils in the Dnipro River valley (based on the example of the Dnipro-Orilsky Nature Reserve). Folia Oecologica, 50(2), 119–133.
Yorkina, N., Goncharenko, I., Lisovets, O., & Zhukov, O. (2022). Assessment of naturalness: The response of social behavior types of plants to anthropogenic impact. Ekológia (Bratislava), 41(2), 135–146.
Zerihun, M., Mohammedyasin, M. S., Sewnet, D., Adem, A. A., & Lakew, M. (2018). Assessment of soil erosion using RUSLE, GIS and remote sensing in NW Ethiopia. Geoderma Regional, 12, 83–90.
Zymaroieva, A., Zhukov, O., Fedoniuk, T., Pinkina, T., & Hurelia, V. (2021). The relationship between landscape diversity and crops productivity: Landscape scale study. Journal of Landscape Ecology, 14(1), 39–58.
