Assessing Land Degradation Risk Through the Long‐term Analysis of Erosivity: A Case Study in Southern Spain

Abstract

Despite the high variability of the precipitation regime characterizing the Mediterranean area, the records of rainfall depth are usually not appropriate for long-term calculations of erosivity and soil losses, because they do not reveal details of short lengths or long durations (daily, monthly). In this work, we present a simple approach to calculate annual erosivity through monthly precipitation records. The study area (olive groves on steep slopes) has a high erosion risk associated to the main soil land use, combined with an irregular and erosive rainfall regime. The relationships between rainfall data at intervals of 10 min for a period of 3 years, daily rainfall records over 10 years and a long-term monthly dataset of 60 years were checked to calculate the annual erosivity values through daily data, Fourier's index and modified Fourier's index values. A good, adjusted linear relationship between modified Fourier's index and the erosivity was found, which allowed us to optimize the use of the 60-year monthly data series and to carry out a long-term analysis of the erosivity quantiles in the study area. The estimated mean erosivity showed a return period of between 2 and 5 years and a variation coefficient of over 50 per cent, which illustrate its high variability and frequency. This approach to calculate erosivity and the use of quantiles could be applied in other areas with month-long data series in order to study and model the erosion risk using suitable temporal periods. Correlation: r = 0 -999; r = 0 -998 Correlation: r = 0 -781; r = 0 -661 P -meas (mm) P -AEMET (mm) -AEMET (mm) Figure 3. Analysis of daily precipitation (P d ) at the Puente Genil and AEMET-Santaella stations: (a) correlation analysis of the accumulated daily values of rainfall depth; (b) correlation analysis of the daily rainfall depth. r P , Pearson correlation coefficient; r Sp , Spearman correlation coefficient. 182 E. V. TAGUAS ET AL.

Variation in Soil Organic Carbon and Nitrogen Stocks Along a Toposequence in a Traditional Mediterranean Olive Grove

“…Indeed, many authors have pointed out that soil erosion, that is, the principal problem associated with olive production (Fleskens & Stroosnijder, 2007), and a consequent loss of fertility, which affects the SOC contents amongst other nutrients, are significant in olive groves. The main causes of soil erosion in olive groves are the steep gradients of the terrain, the Mediterranean climate, which typically has long periods of drought followed by torrential storms, and a lack of soil cover, caused by traditional tillage practices (Gómez et al, 2004;Pastor 2004;Taguas et al, 2013). López (1990) estimated an annual average of soil erosion in olive groves in 80 Mg ha À1 .…”

Large‐scale Modeling of Soil Erosion with RUSLE for Conservationist Planning of Degraded Cultivated Brazilian Pastures

“…However in Brazil and worldwide, there is a lack of rain‐gage‐based rainfall data. Thus, several studies using modified fournier index were developed for estimating the R factor based on the pluviometric data (Oliveira et al ., ; Taguas et al ., ). One of the most used models in Brazil was developed by Lombardi Neto and Moldenhauer () using 1954–1975 time series data of precipitation in Campinas, Sao Paulo.…”

Estimating long-term sediment export using a seasonal rainfall-dependent hydrological model in the Glonn River basin, Germany

“…Long-term records of runoff and sediment yield are scarce, which makes the control of precipitation patterns on soil degradation very challenging (Taguas et al, 2013). The access to long records of subdaily input rainfall data for modeling is also critical because data of this type are only available for a few, geographically scattered stations .…”