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Applying constant precipitation intensity, which does not occur in natural events, is one of the main limitations concerning rainfall simulators in soil erosion studies. The present work evaluated the InfiAsper rainfall simulator operating with a new control panel to program rainfalls with different precipitation intensities (PI). Infiltration rates and soil and water losses were evaluated in a Distrophic Acrisol (clay loam texture) with simulated rainfalls of 30 mm and duration of 40 min, considering advanced (AD), intermediate (IN), delayed (DE), and inverted intermediate (II) patterns, all with PI peaks of 110 mm h−1, and a constant (CT) pattern. The experimental design was in randomized blocks with five treatments (rainfall patterns) and experimental units measuring 2.5 × 2.5 m. The simulator worked satisfactorily, applying the rainfall according to the preconfigured programs. The simulated rainfall with the CT and II patterns did not promote runoff nor soil loss. Infiltration and runoff rates varied according to the applied rainfall pattern, reaching 97.8 and 27.3 mm h−1 (AD), 82.1 and 39.5 mm h−1 (IN), and 76.2 and 49.7 mm h−1 (DE), respectively. Soil loss and surface runoff totaled each 4.77 g m−2 and 3.9 mm (AD), 6.70 g m−2 and 6.8 mm (IN), and 6.03 g m−2 and 7.0 mm (DE). The InfiAsper simulator modified enables varying precipitation intensity besides obtaining satisfactory results in the field and information consistent with the expected characteristics of natural rainfall patterns. In the intermediate and delayed rainfall patterns, soil and water losses are higher than in the advanced.

Rainfall simulators are important pieces of equipment to investigate hydrological processes and soil erosion. Here, we investigated the operational characteristics, the rainfall characteristics, and the soil erosion process under collecting plots and rainfall patterns using the InfiAsper simulator. We evaluated the standard plot of the simulator in a rectangular shape (1.0 × 0.7 m), as well as a circular plot (0.8 m diameter), and four precipitation patterns, characterized as advanced (AV), intermediate (IN), delayed (DL), and constant (CT). In the laboratory, uniformity and water consumption tests were carried out for shutter-disk rotations from 138 to 804 rpm, and in the field, simulated rains were applied on a Dystric Acrisol. Rains with different patterns were simulated and presented a uniformity coefficient above 83% for the circular plot and 78.2% for the rectangular plot. The soil erosion varied as a function of the precipitation patterns and, to a lesser extent, according to the shape of the experimental plot. However, runoff and soil loss in AV were 2.1 and 3.5 times greater when using a circular plot. Concerning IN and DL, the length of the rectangular plot may have influenced the formation of small furrows throughout most of the simulated rainfall event, providing greater runoff (13.1 mm) and soil loss (13.6 g m−2). The results obtained are promising, but plots with different shapes associated with rainfall patterns simulated by InfiAsper must be evaluated in other classes and soil use and cover conditions.

We present a new approach for calculating the C-factor of RUSLE considering the effect of low-reflectance vegetation cover areas on the reduction of the effects on erosion caused by rainfall seasonality. For this, we propose the coefficients Cr2 (rescaled 2) and C-PC (Precipitation Correction), which represent the C-factor, and an adaptation in NDVI calculation, according to the seasonality of precipitation (NDVI-PC). The Cr2 factor is used when there is no seasonal effect of rainfall on vegetation, while the C-PC factor is calculated for localities under the influence of seasonality, from NDVI-PC. The proposed approaches were tested using different satellites images in the Palmares-Ribeirão do Saco watershed, Rio de Janeiro, Brazil. The values of Cr2 and C-PC factors were compared to the Cr factor (rescaled) and to mean values from the literature for different land covers. Our results indicated that the Cr2 factor represents an improvement in accuracy in relation to Cr by considering specific values of the studied area to normalize the data without generalizations. Furthermore, the C-PC factor is able to simulate the effect of seasonality, providing more realistics values of soil loss by the RUSLE as a function of the proportion of area affected by the rainfall seasonality obtained from NDVI-PC. We conclude that both Cr2 and C-PC factors generate values similar of the C-factor observed in the literature, and therefore are able to provide better soil loss estimation than that using the Cr factor.