ABSTRACT Rainfall erosivity (R factor) is one of the six factors of the Universal Soil Loss Equation, being calculated based on the product of rainfall kinetic energy multiplied by its 30-minute maximum intensity. However, the lack of detailed and reliable rainfall data in many parts of the world has driven the use of other methods to estimate rainfall erosivity based on daily, monthly or annual data. These methods still need to be assessed to determine if their estimates are consistent with the standard method for calculating rainfall erosivity. This study aimed to select a consistent method for such replacement in Brazilian conditions without access the rainfall intensity data. The tested methods included: modified Fournier, MF; modified Fournier by Zhang, MF-Z; modified Fournier by Men, MF-M; Rainfall Disaggregation, RD; TRMM Satellite with modified Fournier coefficient, TRMM-F; and TRMM Satellite with monthly rainfall, TRMM-M. The rainfall data were obtained from the USP Meteorological Station, referring to the period from 2009 to 2015. The analyses were performed according to the Additive Main effects and Multiplicative Interaction (AMMI) model and Scott-Knott statistical tests. Considering the 1:1 line, all methods had a good adjustment, presenting similar behavior in relation to the standard method. The methods behaved differently for monthly and annual periods. The MF method proved to be capable of consistently replacing the standard method in all aforementioned situations. Considering the driest period, any method can be used. For annual rainfall erosivity estimation, the RD, MF, TRMM-F and TRMM-M methods can be applied; highlighting that the TRMM-based methods are optimal for locations without on-site rain gauges. Additionally, it was computed that the modified Fournier by Men and the modified Fournier by Zhang underestimated and overestimated the rainfall erosivity, respectively.

ABSTRACT Electromagnetic sensors are widely used to monitor soil water content (θ); however, site-specific calibrations are necessary for accurate measurements. This study compares regression models used for calibration of soil moisture sensors and investigates the relation between soil attributes and the adjusted parameters of the specific calibration equations. Undisturbed soil samples were collected in the A and B horizons of two Ultisols and two Inceptisols from the Mantiqueira Range in Southeastern Brazil. After saturation, the Theta Probe ML2X was used to obtain the soil dielectric constant (ε). Several readings were made, ranging from saturation to oven-dry. After each reading, the samples were weighted to calculate θ (m3 m–3). Fourteen regression models (linear, linearized, and nonlinear) were adjusted to the calibration data and checked for their residue distribution. Only the exponential model with three parameters met the regression assumptions regarding residue distribution. The stepwise regression was used to obtain multiple linear equations to estimate the adjusted parameters of the calibration model from soil attributes, with silt and clay contents providing the best relations. Both the specific and the general calibrations performed well, with RMSE values of 0.02 and 0.03 m3 m–3, respectively. Manufacturer calibration and equations from the literature were much less accurate, reinforcing the need to develop specific calibrations.

ABSTRACT Hydro-sedimentological models might be useful tools for investigating the effectiveness of soil and water conservation practices. However, evaluating the usefulness of such models requires that predictions are tested against observational data and that uncertainty from model parameterization is addressed. Here we aimed to evaluate the capacity of the SWAT model to simulate monthly streamflow and sediment load in the Posses creek catchment (12 km2), Southeast Brazil. The SUFI-2 algorithm from SWAT-CUP was applied for calibration, testing, uncertainty, and sensitivity analysis. The model was calibrated and initially tested using discharge and sediment load data, which were measured at the catchment outlet. Additionally, we used soil loss measurements from erosion plots within the catchment as independent data for model evaluation. Average monthly streamflow simulations obtained satisfactory results, with Nash-Sutcliffe coefficient (NSE) values of 0.75 and 0.51 for the calibration and testing periods, respectively. Sediment load simulations also displayed satisfactory results for calibration (NSE = 0.65) and testing (NSE = 0.52). However, the comparison with independent plot data revealed that SWAT severely overestimated hillslope erosion rates and compensated it with high sediment channel deposition. Moreover, the model was not sensitive to the parameters used for calculating hillslope sediment yields. Therefore, it should be used with caution for evaluating the interactions between land use, soil erosion, and sediment delivery. We found that the commonly used outlet-based approach for model calibration and testing can lead to internal misrepresentations, and models can reproduce the right answer for the wrong reasons.

ABSTRACT Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ecosystems, causing quantitative and qualitative reduction of groundwater, farmland productivity, and waterways sedimentation. Since the gully development on the surface begins with water flow and sheet erosion, accurate monitoring of the erosive processes in a gully system and its quantification is key for the development of effective strategies to control soil erosion in gullies. Here, we demonstrate the first use of unmanned aerial vehicle (UAV) and structure-from-motion/multiview-stereo photogrammetry to evaluate the relative contribution of the different types of erosion (sheet, rill, and gully sidewall) in the gully development. A gully located at Lavras, Brazil, was surveyed using a UAV equipped with a RGB camera. The Precision Maps (PM) variant of the Multiscale Model to Model Cloud Compare (M3C2) algorithm was used to calculate spatial changes in the soil surface topography and to quantify the volumes of sediments lost and gained in the gully system. The point clouds showed root mean square errors of order ~ 3 mm on xyz on check points. The spatial variation of precision along the gully ranged from 0.006 to 0.276 m, considering the M3C2-PM uncertainty values. The results revealed that the main source of sediment in the gully studied was due to the mass movement processes. Rills and laminar erosions contributed 8 and 3 %, respectively, to the total sediment yield, while the mass movements corresponded with most of the sediment generation in the gully. Of the total sediment produced in the system, only 24 % was stored in the gully, indicating its high activity and instability. For the first time, the sediment sources of a gully were quantified remotely and with millimetric precision. The UAV photogrammetry generated high-resolution measurements, allowing evaluation of the contribution of sheet erosion in the generation of sediment of the gully. This opens up new possibilities in the studies involving the dynamics of gullies, since the understanding of the spatial and temporal behaviour of the erosive processes are important in the development of control strategies and monitoring of the evolution of a gullies complex.

ABSTRACT In the tropics, water erosion is one of the most important factors leading to the degradation and deterioration of agricultural land. Olive orchards have a low canopy coverage, especially during the first years after planting, due to the low density of olive trees. Given the fast expansion of olive orchards in Brazil, this study aimed to evaluate the effect of cover vegetation on soil and water losses under natural rainfall. In addition, it was assessed the crop performance and the vegetation cover index in different management systems in olive orchards. The study was carried out in soil erosion plots, where water and sediment were sampled and measured over two crops season, under the following treatments: in the first season, bare soil with olive cultivation (OBS); olive trees intercropped with spontaneous vegetation (OSV); olive trees intercropped with jack beans (OJB); olive trees intercropped with millet (OM) and, as a control, only bare soil (BS). In the second season, the OM treatment was replaced by olive trees intercropped with sunn hemp (OSH). On bare soils, soil loss was the highest reaching 303.9 Mg ha-1 yr-1 and where the surface runoff amounted to 484.8 mm yr-1. However, in the absence of competition for resources with other crops, olive trees performed best under this system. The olive orchards planted in shallow and sloping soils without cover crops showed unsustainable soil loss, crusting, and sealing in the superficial soil layer, which can progress quickly for soil degradation in the future. The efficiency in the reduction of loss in relation to bare soil was 4.11 and 12.93 % for the soil loss and 12.15 and 25.17 % for water loss, respectively, for olive with spontaneous vegetation and olive with jack beans. Cover crops combined with olive trees, and reconciled with the crop performance aspects of cultivation in tropical regions, is of great relevance for improving sustainability, especially regarding the reduction of soil and water losses due to water erosion.

ABSTRACT Through the lack or non-use of conservationist criteria for adequate land use and management, the scarcity of natural resources becomes ever more evident. This study aimed to analyze the origin of the sediments in the Posses catchment, municipality of Extrema, state of Minas Gerais, Brazil, throughout the fingerprinting technique and portable X-ray fluorescence. Samples from soils under agriculture, pasture, and roads; and from the subsoil of theses land uses were taken in a widespread and representative manner from the entire Posses catchment. Lag deposits and river bed sediment samples were collected downstream from the catchment outlet. A total of 45 geochemical elements were analyzed in the samples by a portable X-ray fluorescence device (pXRF). The outlier test, Kruskal-Wallis test, multivariate discriminant analysis, and a mixing model were used to estimate the contribution of each source in relation to the sediments that arrive at the mouth of the catchment. The elements selected as geochemical tracers were Sr, Al2O3, Ba, Rb, Ti, Fe, and Zn, which combined correctly discriminated 81 % of the sediment sources. The largest and smallest proportion of sediment from the Posses catchment outlet comes from rural roads and agriculture, respectively. The contribution of the subsoil was higher for lag deposits or lower for river bed sediments, than the pasture. There was a low degree of uncertainty (<8 %) for predictions made by the model employed. The types of use, selected as potential sediment sources in the Posses catchment, are adequately discriminated through the geochemical tracers quantified through the pXRF. The fingerprinting technique estimates that the contributions to outlet sediments are dominated by rural roads, following by subsoil or pasture (depending on the type of sediment evaluated) and by agriculture. The sediment sampling strategies used in this study provided similar results for the period studied. Our results showed the potential of the fingerprinting technique and the pXRF for use as tools by the program of Payment for Environmental Services in the monitoring of catchment areas.

RESUMO A erosão hídrica é o processo que mais afeta negativamente os solos tropicais. Isso causa perdas de solos agricultáveis e reduz a capacidade de suporte aos ecossistemas. Estimativas das perdas de solo por erosão hídrica são fundamentais para avaliar os impactos dos diversos sistemas de produção adotados. Para tanto, melhorar as estimativas de perdas de solo por meio da adequação dos modelos para diferentes ambientes edafoclimáticos são necessárias para que as estimativas do modelo reflitam as diferenças geográficas e climáticas locais. Este estudo visou adaptar, aplicar e avaliar as potencialidades do Método de Erosão Potencial em Latossolos da Sub-bacia Hidrográfica do Ribeirão Caçús, Sul do Estado de Minas Gerais. Foram processados em Sistemas de Informação Geográfica dados geológicos, topográficos, pedológicos, climáticos e de uso e ocupação do solo. Os dados foram comparados aos obtidos pela Equação Universal de Perdas de Solo Revisada. O resultado do coeficiente de intensidade de erosão, Z, foi de 0,28, indicando ligeira intensidade de erosão. As perdas de solo médias estimadas foram de 31 Mg ha-1 ano-1 pelo Método de Erosão Potencial e 36 Mg ha-1 ano-1 pela Equação Universal de Perdas de Solo Revisada, ambas acima da tolerância de perdas de solo. A aplicação e comparação dos modelos supracitados, indicou que o Método de Erosão Potencial apresentou excelente desempenho, podendo ser aplicado para estimativas das taxas de produção de sedimentos por erosão hídrica em solos tropicais.

ABSTRACT The water erosion process has a considerable negative effect on tropical soils, causes soil losses from arable land and reduces the capacity to support surrounding ecosystems. Estimating soil losses caused by water erosion is fundamental for evaluating the impacts of various production systems. Therefore, improving soil loss estimates via the adaptation of models for different edaphoclimatic environments is necessary for estimating local geographic and climatic differences. This study aimed to adapt, apply and evaluate the potentialities of the Potential Erosion Method for Latosols of the Hydrographic Subbasin of Caçús Stream, southern Minas Gerais State. Geological, topographic, pedological, climatic and land use and occupation data were processed via Geographic Information Systems and compared with those obtained by the Revised Universal Soil Loss Equation. The erosion intensity coefficient, Z, was 0.28, indicating weak erosion intensity, and the estimated average soil losses were 31 Mg ha-1 year-1 by the Potential Erosion Method and 36 Mg ha-1 year-1 by the Revised Universal Soil Loss Equation, which were both above the soil loss tolerance. The model results and comparisons indicated that the Potential Erosion Method has excellent performance and can be applied to estimate sediment production via water erosion in tropical soils.

ABSTRACT The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contribute to increase the accessibility, accuracy, and resolution of Digital Elevation Models (DEMs) used for soil erosion monitoring. This study aimed to evaluate the use of four DEMs obtained over a year to monitor erosion processes in an erosion-degraded area, with occurrence of rill and gully erosions, and its correlation with accumulated rainfall during the studied period. The DEMs of Geomorphic Change Detection (GCD) of horizontal and vertical resolutions of 0.10 and 0.06 m were obtained. It was possible to detect events of erosion and deposition volumes of the order of 2 m3, with a volumetric error of ∼50 %, in rills and gullies in the initial stage denominated R and GS-I, respectively. Events of the order of 100 m3, with a volumetric error around 14 % were found for advanced gullies, a segment denominated GS-II. In the three studied erosion situations, the deposition volume increased with the accumulated rainfall. The segments R and GS-I presented an inverse relationship between erosion volume and accumulated rainfall during the studied period. This behaviour can be explained by the dynamics of the deposition and erosion volumes during the erosion process. In the GS-II segment, erosion and deposition volumes were proportional and a direct relation with the cumulative rainfall over the studied period and a low percentage of volumetric error were found.

ABSTRACT Erosion prediction models are a useful tool for soil use planning and soil conservation. This study aimed to apply the Universal Soil Loss Equation (USLE) in an experimental sub-basin located in the municipality of Teixeira de Freitas, in the southern end of the state of Bahia, Brazil. The following variables were calculated: rainfall erosivity factor, using the precipitation data; soil erodibility factor, by the correlation between erosivity and soil losses obtained from a standard plot installed in the field; topographic factor; vegetation cover and management factor; and conservation practices factor. The product of these factors corresponded to the soil losses in the sub-basin. Data from erosion plots were used to validate the model. The USLE predicted higher soil losses than that observed in the plots, and the eucalyptus proved to be efficient at reducing soil losses by erosion.

Resumo A erosão é a principal causa de degradação do solo, comprometendo a produtividade e a sustentabilidade do solo. A matéria orgânica do solo (MOS) é um indicador chave da qualidade; deste modo, o presente estudo objetivou avaliar o efeito de diferentes manejos da oliveira na matéria orgânica e em suas frações presentes no solo (Cambissolo) e no sedimento de erosão, no sul de Minas Gerais. Foram instaladas parcelas com 5 tratamentos: solo descoberto, cultura de oliveira em solo descoberto, oliveira em consórcio com feijão-de-porco, oliveira em consórcio com milheto e oliveira com vegetação espontânea, além de uma área contígua de vegetação nativa como referência. O carbono do solo e do sedimento foi determinado via oxidação úmida com aquecimento externo, enquanto o fracionamento da MOS e do sedimento foi realizado com base na granulometria. O Índice de Manejo de Carbono (IMC) foi determinado por meio das proporções das frações da MOS. Os resultados indicaram que a MOS associada aos minerais é a mais presente no solo e no sedimento de erosão, independentemente do manejo adotado. O IMC apontou os sistemas oliveira com milheto e oliveira sob vegetação espontânea como os mais favoráveis ao estoque de carbono no solo.

Abstract Erosion is the main cause of soil degradation, compromising soil productivity and sustainability. As soil organic matter (SOM) is a key indicator of quality, this study aimed to evaluate the effect of different olive tree managements on SOM and its soil fractions in soil (Inceptisol) and erosion sediments. Five treatments were installed: bare soil, olive cultivation in bare soil, olive tree intercropped with jack bean, olive tree intercropped with pearl millet, and olive tree cultivated with spontaneous vegetation; a contiguous area of native vegetation was used as reference. Carbon in soil and sediment were determined by wet oxidation with external heating, while the fractionation of SOM was performed based on granulometry. The Carbon Management Index (CMI) was determined by the proportions of SOM fractions. The results indicated that SOM associated with minerals is the most present in soil and sediment erosion, regardless of the adopted management. Results on CMI showed that the systems olive tree intercropped with pearl millet or with spontaneous vegetation are the most favorable to increase the carbon stock in the soil.

ABSTRACT Several soil conservation practices are used to reduce water erosion and ensure sustainable agriculture. An effective crop management practice is intercropping, in which two or more crops with different architectures and vegetative cycles are grown simultaneously in the same area. We hypothesized that intercropping of corn and jack-bean increases soil cover and reduce soil erosion by water in comparison to monocropping. The objective of this study was to evaluate the effects of different crop systems on soil cover and on soil erosion by water. Soil and water losses from a Typic Hapludox were measured under the following systems: corn cultivation (CO), jack-bean cultivation (JB), intercropping of corn and jack-bean (IC), and bare soil (BS), as a reference for maximum erosion rates. For each crop system, erosion plots with dimensions of 12 × 4 m were set up in the field on a 0.12 m m−1 slope gradient. The experiment was carried out under natural rainfall, over three crop seasons (November to March) from 2011 to 2014. The soil cover index of the systems was monitored during crop growth, and rainfall erosivity for the crop seasons was calculated according to the EI30 index to interpret soil and water losses. A set of linear mixed models was fitted to relate soil losses to rainfall erosivity, crop systems, and soil cover. The average rainfall erosivity in the study area was 6,132 MJ mm ha−1 h−1 per crop season. The results indicate that water losses are directly related to erosivity and are less influenced by soil cover and cultivation systems than the soil losses. A linear maximum value of the soil cover index was achieved 70 days after sowing. Intercropping exhibited greater soil cover than single crops. Total soil losses from the three seasons display the trend: BS > CO > JB > IC. The best fitted model of the linear mixed models indicates that soil loss responses are strongly correlated with rainfall erosivity and soil cover, which nullified the influence of the crop systems in the model.

ABSTRACT Water erosion is one of the main environmental impacts of land use. When soil and water losses occur, nutrients essential for the growth and maintenance of plants are removed, with harmful outcomes on the sustainability of agriculture and the environment. In addition, they lead to other deleterious effects, such as sedimentation and eutrophication of water bodies. Estimation of soil losses due to water erosion in sub-basins is essential for prediction of soil degradation, especially in areas of semi-intensive cultivation, such as coffee fields. Thus, the aim of this study was to estimate soil losses in relation to the limit of soil loss tolerance in Oxisols (Latossolos Vermelhos Distróficos) under coffee cultivation. This study was conducted from March 2015 to January 2017 in the Córrego da Laje Hydrographic Sub-basin in the municipality of Alfenas in the southern region of Minas Gerais, southeastern Brazil. Soil losses due to water erosion were estimated from the revised universal soil loss equation and compared to soil loss tolerance. Morphological, physical, and chemical properties of the soil were used, as well as geoprocessing techniques, remote-sensing images, and data from the literature. The results show potential soil losses from 0.01 to 18.77 Mg ha-1 yr-1, with an average of 1.52 Mg ha-1 yr-1. The soil loss tolerance ranged from 5.19 to 5.90 Mg ha-1 yr-1, with 7.35 % of the area having larger losses. Areas with steeper slopes and no sustainable practices have soil losses above the tolerance level and are thus a priority for adoption of measures to mitigate erosive effects. The revised universal soil loss equation enabled water erosion modeling and identification of areas with the highest rates of potential soil loss in watersheds.

RESUMO Identificar e classificar áreas quanto ao risco de perda de nutrientes são passos importantes para o manejo integrado de bacia hidrográfica. O objetivo deste estudo foi aplicar o modelo Índice P na bacia hidrográfica das Posses, Extrema-MG. O Índice P foi empregado sobre as condições atuais de uso da terra na bacia hidrográfica das Posses e na simulação de dois cenários: cenário 1, o fertilizante P foi aplicado para todos os usos, exceto para florestas nativas e, cenário 2, além do fertilizante P ser aplicado da mesma forma que no cenário 1, considerou-se que as Áreas de Proteção Ambiental referentes as matas ciliares e nascentes fossem totalmente restituídas. Considerando o uso atual, quase toda a bacia hidrográfica (91,4%) apresentou baixo risco de perda de P. O maior Índice de P foi associado a lavouras e plantações de eucalipto. No cenário 1, as pastagem apresentaram Índice P baixo (15,1%), médio (45,5%), alto (27,1%) e muito alto (12,3%). No cenário 2, as Áreas de Proteção Ambiental promoveram uma redução de 37,6% no risco de perda de P do cenário 1. Dessa forma, os resultados do modelo indicam que o reflorestamento de matas ciliares pode reduzir o risco de perdas de P no caso do aumento do uso de fertilizantes. O Índice P é uma potencial ferramenta para promoção do uso criterioso de fertilizantes e de práticas conservacionistas na bacia hidrográfica das Posses.

ABSTRACT Identifying and ranking nutrient loss risk areas are important steps towards integrated catchment management. This study aimed to apply the P index model at the Posses catchment, south of the state of Minas Gerais, Brazil. We applied the P index for the current land use at the Posses catchment and for two hypothetical scenarios: scenario 1, in which P fertilizer was applied to all land uses, except for native forests; and scenario 2, which considered the use of P fertilizer as in scenario 1, and that the Environmental Protection Areas referring to the riparian forests and springs were totally restored. Considering current land use, almost the whole catchment area (91.4%) displayed a low P loss risk. The highest P index was associated to croplands and eucalyptus plantations. Regarding scenario 1, areas under pasture fell into the low (15.1%), medium (45.5%), high (27.1%) and very high (12.3%) P index categories. Environmental Protection Areas on scenario 2 decreased the P loss risk from the scenario 1 in 37.6%. Hence, the model outputs indicate that the reforestation of buffer zones can decrease P loss risk in the case increasing use of P fertilizer. The P index model is a potential support tool to promote judicious use of fertilizers and conservation practices at the Posses catchment.

RESUMO Modelos de terreno de rios são usados para análise de mudanças geomorfológicas e para simulações hidrológicas. Estes modelos são interpolados a partir de pontos batimétricos. A batimetria fluvial é geralmente conduzida através de seções transversais, o que pode acarretar em uma malha amostral esparsa. Métodos híbridos de krigagem, como krigagem por regressão (KR) e co-krigagem (CK), empregam a correlação com preditores auxiliares, além da auto-correlação entre variáveis, na predição da variável resposta. Neste estudo, sugere-se que a distância ortogonal de um ponto até a linha de centro do talvegue de um rio pode ser usada como covariável para KR e CK. Considerando-se que a variabilidade da cota do leito do rio é abrupta transversalmente a direção do fluxo, espera-se que quanto maior a distância euclidiana de um ponto até o talvegue, maior será sua elevação. O objetivo deste estudo foi avaliar o uso da covariável proposta em métodos híbridos de krigagem para a predição espacial da topografia do leito de rios. Para tanto, foi realizada uma validação externa, em que seções transversais foram usadas para interpolação e dados levantados entre as seções consistiram na amostra de teste. Os resultados da KR e CK foram comparados aos da krigagem ordinária. A KR apresentou a menor REQM. No mapa resultante da KR, o talvegue foi preservado nas lacunas não amostradas entre as seções, enquanto os demais métodos subestimaram a profundidade do talvegue nestes espaços. Assim, conclui-se que a KR pode melhorar a predição espacial de dados batimétricos fluviais.

ABSTRACT Terrain models that represent riverbed topography are used for analyzing geomorphologic changes, calculating water storage capacity, and making hydrologic simulations. These models are generated by interpolating bathymetry points. River bathymetry is usually surveyed through cross-sections, which may lead to a sparse sampling pattern. Hybrid kriging methods, such as regression kriging (RK) and co-kriging (CK) employ the correlation with auxiliary predictors, as well as inter-variable correlation, to improve the predictions of the target variable. In this study, we use the orthogonal distance of a (x, y) point to the river centerline as a covariate for RK and CK. Given that riverbed elevation variability is abrupt transversely to the flow direction, it is expected that the greater the Euclidean distance of a point to the thalweg, the greater the bed elevation will be. The aim of this study was to evaluate if the use of the proposed covariate improves the spatial prediction of riverbed topography. In order to asses such premise, we perform an external validation. Transversal cross-sections are used to make the spatial predictions, and the point data surveyed between sections are used for testing. We compare the results from CK and RK to the ones obtained from ordinary kriging (OK). The validation indicates that RK yields the lowest RMSE among the interpolators. RK predictions represent the thalweg between cross-sections, whereas the other methods under-predict the river thalweg depth. Therefore, we conclude that RK provides a simple approach for enhancing the quality of the spatial prediction from sparse bathymetry data.

ABSTRACT The Jaguarí River Basin forms the main water supply sources for the São Paulo Metropolitan Region and other cities in the state. Since the kinetic energy of rainfall is the driving force of water erosion, the main cause of land and water degradation, we tested the hypothesis of correlation between the erosive potential of rainfall (erosivity) and geographical coordinates and altitude for the purpose of predicting the spatial and temporal distribution of the rainfall erosivity index (EI30) in the basin. An equation was used to estimate the (EI30) in accordance with the average monthly and total annual rainfall at rainfall stations with data available for the study area. In the regression kriging technique, the deterministic part was modeled using multiple linear regression between the dependent variable (EI30) and environmental predictor variables: latitude, longitude, and altitude. From the result of equations and the maps generated, a direct correlation between erosivity and altitude could be observed. Erosivity has a markedly seasonal behavior in accordance with the rainy season from October to March. This season concentrates 86 % of the estimated EI30 values, with monthly maximum values of up to 2,342 MJ mm ha-1 h-1 month-1 between December and January, and minimum of 34 MJ mm ha-1 h-1 month-1 in August. The highest values were found in the Mantiqueira Range region (annual average of up to 12,000 MJ mm ha-1 h-1), a region that should be prioritized in soil and water conservation efforts. From this validation, good precision and accuracy of the model was observed for the long period of the annual average, which is the main factor used in soil loss prediction models.