Many researchers have reported relationships of physical and chemical properties with water erosion; however, little is known about microbiological properties in this context. Thus, the aim of this study was to evaluate soil properties in relation to erosion in areas with different cropping system practices under no-tillage in the Brazilian Cerrado. The experiment has been carried out since 2014 in a Typic Haplustox under soybean (S) and maize (M) monoculture, maize/soybean annual rotation (MS), maize/brachiaria/soybean/brachiaria rotation (MBSB), two of those treatments with high input of fertilizer (MBSB-HI and MS-HI), and bare soil (BS). Soil losses were quantified in erosion plots. The design was completely randomized. The greater vegetation cover crop, provided by intercropping/succession with brachiaria, increased microbial biomass carbon. The lack of vegetation cover affected the basal soil respiration and metabolic quotient. Basal soil respiration proved to be inversely related to soil and water losses. Vegetation cover was a key factor regulating water erosion. Penetration resistance and aggregate stability correlated with soil and water losses. Thus, not only physical and chemical, but also biological properties are deeply affected by erosion, aiding in early monitoring of water erosion. Soil quality improvement in ecologically supported management contributes to mitigating erosion.

The Brazilian Cerrado biome (BCB) is among 25 biodiversity hotspots identified worldwide, and covers the recharge area of important aquifers and rivers in South America. The increase in deforestation has been threatening water availability in this region. In order to assist in the water-resource management of the BCB, this study models the daily streamflow in a basin of the Cerrado, using two approaches: a process-based model (Soil and Water Assessment Tool - SWAT) and the data-driven model (Artificial Neural Network - ANN). The performance of the models was evaluated by the Nash-Sutcliffe coefficient (NSE), coefficient of determination (R2) and flow-duration-curves (FDC). The results indicate that SWAT (NSE > 0.61; R2 > 0.68) and ANN (NSE > 0.91; R2 > 0.79) models are suitable tools in daily streamflow modeling of the studied basin, with the ANN model being the most accurate. Based on FDC, the ANN model was also better than the SWAT model for all frequencies evaluated. Thus, the ANN model is a promising new approach for daily streamflow modelling in this region. Moreover, the results of this study can help water-resource managers in planning and implementing appropriate water allocation and conservation measures in the Brazilian Cerrado biome.

This study aimed to evaluate the influence of magnetized water use on lettuce irrigation management responses, and based on the generated data, to evaluate by simulation the influence of soil water retention curve type on the lettuce irrigation management responses. This work was divided into three stages: 1 – determination of field and laboratory soil water retention curves; 2 – lettuce crop irrigation management experiment using soil water retention curve with field data, evaluating different soil water tensions to start irrigation and different water types (magnetically treated water, and non-treated water); and 3 – estimation of the irrigation management responses (simulation) using the soil water retention curve performed in the laboratory (using non-treated water), compared with the experimental results (stage 2). The use of magnetically treated water determined the soil moisture maintenance for a longer time and fewer irrigation events, leading to less water being applied and electricity consumption. The use of the soil water retention curve derived from the field data determined less water and electric energy consumption in Lucy Brown lettuce irrigation, in comparison with the simulated use of the soil water retention curve from laboratory data.

Rainfall simulators are an important tool in many areas of geosciences. The authors of most of the studies published with rainfall simulators try to get the most uniform distribution of precipitation as possible. However, since this is very difficult, indexes are used to assess the greater or lesser uniformity of precipitation in the plot area under study. One of the most used indexes is the Christiansen uniformity coefficient. In this work, changes in the geometry of the wetted area of the plot were analyzed to improve the uniformity of precipitation. This was evaluated through the intensity of precipitation and Christiansen uniformity coefficient in the wet area. The tests were carried out using two models of spray nozzles and different operating pressures. The initial plot geometry was 0.7 x 1.0 m (0.7 m2). The Christiansen uniformity coefficient results were classified as low, while the best performance in terms of precipitation uniformity was obtained at a pressure of 48.3 kPa. Non-uniform precipitation was observable near the outer limits of the plot. Based on the best Christiansen uniformity coefficient results, it was proposed to reduce the effective area of the experimental plot from 0.70 to 0.56 m2, leading to a precipitation intensity of 114.07 and 149.20 mm·h−1, and a Christiansen uniformity coefficient of 81.6 and 83.8%, with the two models of spray nozzles. The results showed that adjusting the geometry of the plot can lead, in a simple and fast way, to a better uniformity of artificial rainfall.