Abstract
Soil erosion is affected by rainfall, among other factors, and it is likely to increase in the future due to climate change impacts, resulting in higher rainfall intensities. This paper evaluates the impact of the missing values ratio on the computation of the rainfall erosivity factor, R, and erosivity density, ED. The paper also investigates the temporal trends and defines regions of Greece with a similar monthly distribution of ED using an unsupervised method. Preprocessed and free from noise and errors rainfall data from 108 stations across Greece were extracted from the Greek National Bank of Hydrological and Meteorological Information. The rainfall data were analyzed and erosive rainfalls were identified, their return period was determined using intensity–duration–frequency curves and R and ED values were computed. The impact of missing data in the computation of annual values of R and ED was investigated using a Monte Carlo simulation. The findings indicated that missing rainfall data resulted in a linear underestimation of R, while ED is more robust. The trends in ED timeseries were evaluated using the Kendall’s Tau test and their autocorrelation and partial autocorrelation were computed for a small subset of stations using criteria based on the quality of data. Furthermore, cluster analysis was applied to a larger subset of stations to define regions of Greece with similar monthly distribution of ED. The findings of this study indicate that: (a) ED should be preferred for the assessment of erosivity in Greece over the direct computation of R, (b) ED timeseries are found to be stationary for the majority of the selected stations, in contrast to reported precipitation trends for the same time period, (c) Greece is divided into three clusters/areas of stations with distinct monthly distributions of ED.
Highlights
It is plausible that future climate change would increase the intensity of rainfall in Europe, as indicated by the European research project EURO-CORDEX [1]
The findings of this study indicate that: (a) erosivity density (ED) should be preferred for the assessment of erosivity in Greece over the direct computation of R, (b) ED timeseries are found to be stationary for the majority of the selected stations, in contrast to reported precipitation trends for the same time period, (c) Greece is divided into three clusters/areas of stations with distinct monthly distributions of ED
Incomplete data can be used to compute ED and achieve acceptable accuracy on Stationarity the estimationofofEDR.was found for the majority of the selected stations in Greece
Summary
It is plausible that future climate change would increase the intensity of rainfall in Europe, as indicated by the European research project EURO-CORDEX [1]. This expected increase in rainfall intensity will result in increased potential soil erosion rates [2]. Since the most significant process responsible for soil loss is related to rainfall intensity, any possible increase of future rainfall intensity will directly affect and intensify this desertification process [4]. The Universal Soil Loss Equation, USLE [5], and its computerized revisions RUSLE [6] and RUSLE2 [7] have been used worldwide, and one of its empirically based factors, rainfall erosivity R, is based on rainfall intensities.
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