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Understanding the behavior of the river regime in watersheds is fundamental for water resources planning and management. Empirical hydrological models are powerful tools for this purpose, with the selection of input variables as one of the main steps of the modeling. Therefore, the objectives of this study were to select the best input variables using the genetic, recursive feature elimination, and vsurf algorithms, and to evaluate the performance of the random forest, artificial neural networks, support vector regression, and M5 model tree models in forecasting daily streamflow in Sono (SRB), Manuel Alves da Natividade (MRB), and Palma (PRB) River basins. Based on several performance indexes, the best model in all basins was the M5 model tree, which showed the best performances in SRB and PRB using the variables selected by the recursive feature elimination algorithm. The good performance of the evaluated models allows them to be used to assist different demands faced by the water resources management in the studied river basins, especially the M5 model tree model using streamflow lags, average rainfall, and evapotranspiration as inputs. HIGHLIGHTS The Recursive Feature Elimination was the best input feature selection algorithm.; The machine learning models were efficient in the daily streamflow forecasting.; The performance of the M5 model tree was better than the other models.; The models are potential tools to assist water resources management.;

Changes in precipitation and air temperature may produce different impacts on the hydrological regime, compromising water supply. This study focuses on climate change impacts in the Verde River Basin (VRB), a tropical headwater basin in southeast Brazil, located in the state of Minas Gerais. The Variable Infiltration Capacity model (VIC) was calibrated and validated in the Verde River Basin. The downscaling (Eta Regional Climate Model, at 20-km resolution) of three Global Circulation Models (CanESM2, HadGEM2-ES and MIROC5) were used to drive the VIC for a historical baseline (1961-2005) and three time-slices (2011-2040, 2041-2070 and 2071-2099), under RCPs 4.5 and 8.5 scenarios. The scenarios were used as input in the hydrological model after bias correction. The hydrological model (VIC) showed satisfactory statistical performance in calibration and validation, with CNS varying from 0.77 to 0.85 for daily and monthly discharges; however, it overestimated some peak flows and underestimated the recession flows. Multi-model ensemble means predict increases of the minimum and maximum monthly average temperature for the investigated area at the end of the century. The Eta-CanESM2 indicated greater warming, mainly for RCP8.5 at the end the century, whereas Eta-HadGEM2-ES showed higher reduction in the precipitation for RCP4.5 at the beginning of the century and for RCP8.5 at the end the century, negatively impacting the evapotranspiration and discharge. Among the Regional Climate Models (RCMs), the Eta-MIROC5 showed minor changes in the components of the hydrological cycle. This study suggests that Global Circulation Models represent an additional uncertainty, which should be accounted for in the climate change impact assessment.

The Brazilian Cerrado biome is the largest and richest tropical savanna in the world and is among the 25 biodiversity hotspots identified worldwide. However, the lack of adequate hydrological monitoring in this region has led to problems in the management of water resources. In order to provide tools for the adequate management of water resources in the Brazilian Cerrado biome region, this paper develops the regionalization of maximum, mean and minimum streamflows in the Tocantins River Basin (287,405.5 km2), fully located in the Brazilian Cerrado biome. The streamflow records of 32 gauging stations in the Tocantins River Basin are examined using the Mann-Kendall test and the hydrological homogeneity non-parametric index-flood method. One homogeneous region was identified for the estimate of the streamflows Qltm (long-term mean streamflow), Q90% (streamflow with 90% of exceeding time), Q95% (streamflow with 95% of exceeding time) and Q7,10 (minimum annual streamflow over 7 days and return period of 10 years). Two homogeneous regions were identified for maximum annual streamflow estimation and the Generalized Extreme Value distribution is found to describe the distribution of maximus events appropriately within the both regions. Regional models were developed for each streamflow of each region and evaluated by cross-validation. These models can be used for the estimation of maximum, mean and minimum streamflows in ungauged basins within the Tocantins River Basin within the area boundaries identified. Therefore, the results provided in this paper are valuable tools for practicing water-resource managers in the Brazilian Cerrado biome

The Soil Conservation Service Curve Number Model is a conceptual model intended for estimating effective rainfall (ER). This model is grounded in a parameter – referred to as Curve Number (CN), which is determined from information on the characteristics of the watershed. The Standard Method (M1) for determining the CN is based on soil and land-use tables; however, some authors have proposed alternative methodologies for defining the CN value from monitored rainfall-runoff events, such as those described by Hawkins (1993) (M2), Soulis and Valiantzas (2012) (M3), and Soulis and Valiantzas (2013) (M4). The objective of this study was to evaluate the impact of using these methods for determination of the CN parameter on the estimation of ER, taking as reference forty rainfall-runoff events monitored between 2015 and 2018 in the Cadeia River Watershed, which has characteristics of the Pampa biome. The different methods assessed for definition of the CN parameter resulted in contrasting performances with respect to the estimation of ER for CRW, as the following findings: i) M1 gave ER values with little reliability, mainly due to the classification of antecedent moisture content classes; ii) M3 provided the best results in determining ER, followed by M2; and iii) the ER values estimated according to M4 differed from those observed, mainly for events with lower rainfall depths.

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.

Successful streamflow forecasts depend on an adequate performance evaluation of the hydrological model. In this study, the hydrological responses were compared using two hydrological models, physic-based and semi-distributed, Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC), using input data from the Verde River Watershed, located in the Minas Gerais state in southern Brazil. This is a study of one of the most important headwater watershed regions of Brazil (Mantiqueira Range). Both models were suitable for streamflow simulation, with values of R2 (determination coefficient) and NSE (Nash-Sutcliffe) higher than 0.8, NSELog higher than 0.35 (Nash–Sutcliffe Efficiency of the logarithmic values of discharge) and PBIAS (percentage deviation) less than 25%. The integration of SWAT and VIC models can be useful in different water-resource assessment studies. Therefore, based upon this study further investigations should be conducted using various hydrological models and climate, land-use and land-cover changes scenarios in the region.

Maximum and minimum streamflow are fundamental for water resource management, especially for water rights. However, lack of monitoring and scarce streamflow data limit such studies. Streamflow regionalization is a useful tool to overcome these limitations. The study developed models for regionalization of the maximum and minimum reference streamflows for the Mortes River Basin (MRB) (Water Resources Planning and Management Unit - GD2), Southern Minas Gerais State. The study used long-term streamflow historical series provided by the Brazilian National Water Agency (ANA). Previous exploratory analysis was performed, and it was observed that the streamflow series are stationary according to the Mann-Kendall test. The estimation of the streamflow for different return periods (RP) was performed by fitting Probability Density Functions (PDFs) that were tested by the Anderson-Darling (AD) test. The Generalized Extreme Values (GEV) and Wakeby were the most appropriate PDFs for maximum and minimum streamflows, respectively. The streamflow models were fitted using a power regression procedure, considering the drainage area of the watersheds as inputs. The fittings reached the coefficient of determination (R2) greater than 0.90. Thus, the streamflow regionalization models demonstrated good performance and are a potential tool to be used for water resource management in the studied basin.

ABSTRACT Since prolonged droughts have impacted Atlantic forests in Southeastern Brazil, further investigations to understand the effects of such stressful conditions in their hydrological behavior are required. This study aimed to assess the changes in the water balance of a semi-deciduous Atlantic forest remnant and how the forest responds to droughts. The Standardized Precipitation-Evapotranspiration Index was applied to identify droughts (from 1961 to 2019) and their severity in both the hydrological year and summer scales. Drought impacts on actual evapotranspiration, potential percolation, and soil water storage were assessed using Hydrus-1D, having net precipitation and potential evapotranspiration as inputs. Error analyses (< 10%) confirmed Hydrus-1D suitability for simulating soil moisture. Uncertainties regarding the soil saturated hydraulic conductivity are due to preferential flows, which are not accounted for in Richards’ equation. Drought intensification changed forest hydrology and triggered physiological responses to deal with it. Semi-deciduous Atlantic forests are adapted to dry conditions because of the existence of dry-affiliated species and the activation of physiological mechanisms. However, such adaptations responded differently regarding the drought scales. The intensification of summer droughts increased evapotranspiration and decreased the potential percolation. Leaf shedding changed the canopy structure in a two-year time lag as a response to the intensification of hydrological year droughts. Changes in forest hydrology are sudden and trigger physiological responses, such as leaf shedding, in a delayed process after droughts take place.

ABSTRACT Globally, soil degradation by water erosion has become one of the major environmental problems in tropical regions, especially under the severe environmental conditions of the Andes. This study aims to detail the soil risk to degradation by water erosion in a water producer basin located in the Tropical Colombian Andes (Combeima River basin), applying the RUSLE model, discussing how to minimize the erosion processes under its environmental conditions (steep slope, climatic variability, soil classes and properties diversity, and alternative land uses). RUSLE was applied with the support of GIS to estimate current and potential risk to soil erosion in the basin, allowing the identification of areas more prone to degradation. It was found that currently, 50.5% of the basin’s area presents, on average, annual soil losses greater than 25 Mg ha-1 yr-1, meaning a very high risk to water erosion, with 30.4% showing a severe risk (> 100 Mg ha-1 yr-1). It was possible to conclude that the current land uses and soil management systems have not been effective in mitigating soil erosion, mainly when situated in steep topography. Therefore, it is necessary sustainable planning for the conservation of soil, water, organic carbon, plant nutrients, and other elements (not-nutrients) in this tropical Andes region.

Abstract Mathematical models have been widely used to quantify hydrological processes for various practical purposes. These models depend on geomorphological attributes which are derived from relief information represented by Digital Elevation Models (DEM). The objective of this study was to evaluate the influence of relief information sources (ASTER, SRTM-30, SRTM-90, and TOPO) over geomorphological characterization of five Brazilian watersheds. Geoprocessing tools were applied for extraction of the following geomorphological attributes for each DEM: drainage area, perimeter, and watershed slope; length and slope of the main stream; total length of streams; bifurcation, stream length and stream area ratios; and length of the highest order stream. The differences in the values of attributes were calculated in relation to the reference DEM (TOPO). It was found that: i) slope of main stream and bifurcation ratio were the most sensitive parameters regarding the relief information source; ii) flat watersheds were more susceptible to altimetric errors; iii) ASTER did not adequately represent drainage networks for flat watersheds; and iv) the differences in the geomorphological attributes increased as drainage area decreased. The results indicate that DEM may exert influence on the use of hydrological models that depend on geomorphological attributes.

ABSTRACT Hydrosedimentological modeling is a useful tool to predict the water dynamic in a basin and for water resources management. This study aimed to i) evaluate the ability of Soil and Water Assessment Tool (SWAT) to model sediment load and continuous monthly streamflow in the Mortes River Basin (MRB) in Southeastern Brazil; ii) estimate the sediment yield spatially distributed by sub-basins; iii) estimate the sediment load export to the Funil Hydroelectric Power Plant reservoir (FHPP), located in the MRB outlet. For the sensitivity analysis, calibration, and uncertainty analysis of the model, a semi-automatic calibration in SWAT-CUP version 5.1.6 software with the “Sequential Uncertainty Fitting” algorithm was used. To evaluate the ability of SWAT to reproduce the continuous MRB monthly streamflow and sediment load, statistical indexes, and graphical analyses were used to compare the simulated and observed data. For the sediment evaluation, a spatial and temporal comparison of sediment yield maps was used as well as the sediment yield observed in sub-basins, aiming to identify the areas with a more significant contribution to the sediment generation in the basin. The results demonstrated that SWAT performed satisfactorily in simulating both monthly sediment load and streamflow. For discharge calibration, 99 % of the measured data were bracketed by the 95 % prediction uncertainty (95PPU), and for validation, 97 % of the data were bracketed by the 95PPU, which indicates proper bracketing of the measured data within model prediction uncertainty. Uncertainty analysis indicated that 95PPU could capture 78 % of the sediment loads measured during the calibration and 72 % of the measured data during the validation period at MRB. The hydrologic response unit with pasture and Argissolos (Ultisols), Neossolos Litólicos (Entisols), and Cambissolos (Inceptisols) combined with undulated relief were the main areas responsible for the highest sediment contributions. The sediment load delivered to the reservoir from its filling 2002 to 2015 was estimated in 6,682,704 m3 (16,706,761 Mg) (density of 2.5-Mg m-3) which value corresponded to 2.6 % of storage capacity (water plus sediment) in 14 years. These results are strategic since to become feasible identifying priority areas for soil and water conservation practices as well as useful information for water resources planning and management in the studied basin.

Projetos hidráulicos e a gestão da água demandam dados hidrológicos confiáveis. A bacia hidrográfica do rio Araguaia-Tocantins, além do uso agrícola, apresenta grande potencial para exploração hidroelétrica. No entanto, a rede de monitoramento fluviométrico na bacia hidrográfica do rio Araguaia apresenta densidade reduzida de estações, o que implica na falta de dados hidrológicos. A regionalização de vazões de referência é uma técnica que pode ajudar a contornar essa insuficiência de dados, propiciando a estimativa de vazões a partir de variáveis explicativas de fácil obtenção. Neste contexto, objetivou-se desenvolver funções regionais para vazão máxima (Qmax) aplicáveis a diferentes Períodos de Retorno (RP), vazão média em longo prazo (Qmlt) e vazão com 95% de permanência (Q95) para as sub-bacias de alto e médio curso do rio Araguaia. Adotou-se a metodologia da vazão adimensional e a área de drenagem como variável explicativa. Os modelos regressivos testados foram o linear, potencial e quociente. Empregou-se para verificação da qualidade dos modelos regionais a validação-cruzada leave-one-out. Utilizou-se 10 distribuições estatística de 2 a 5 parâmetros. (i) Obtiveram-se resultados satisfatórios para todas as vazões de referência. (ii) A técnica de validação cruzada mostrou-se essencial para a seleção do modelo mais robusto. (iii) O modelo de quociente mostrou-se superior ao modelo potencial e linear na maioria dos casos.

Hydroelectricity is responsible for the greatest fraction of the electric energy generated in Brazil. The water footprint of hydropower plants (WFP) is an important indicator of the sustainable and efficient use of water resources. In this context, WFP of the Sobradinho Hydropower Plant was determined for the period from 2003 to 2012, taking into account the reservoir’s historical variation for the flooded area. To accomplish this, monthly series of electric energy production, flooded area, evaporation and evapotranspiration rates were used. Average gross and net evaporation were 2,031 and 1,577 mm year-1, respectively. The average power generation of this facility in the analyzed period was 462 MW, and the flooded area of its reservoir presented an average value of 3,054 km². Based on the monthly data, the gross and net water footprints were, respectively, 417 and 325 m³ GJ-1. Based on these results, it can be concluded that the changes in the reservoir’s area exert direct and important influence on the WFP estimates of the Sobradinho hydropower plant. The WFP estimates in this study were different from other studies that adopted a constant value of 4,214 km² for this reservoir’s area, which is taken based on the normal water level of the plant operation.

In order to design effective Brazilian hydraulic structures, it is necessary to obtain data relating to short-duration intense rainfall from historical series of daily rainfall. This recurring need can be fulfilled by rainfall disaggregation methodology. The objective of this study was to determine the intense rainfall disaggregation constants for the State of Tocantins and to compare these constants with those obtained for other regions of Brazil. For the modeling of the frequency of intense rainfall of different durations of less than 24 hours, the Gumbel probability distribution (GPD) was employed using rainfall series from 10 locations in Tocantins state. The results showed that the GPD was adequate by the Kolmogorov-Smirnov and Chi-square tests. The disaggregation constants presented low variability values for different return periods (from 10 to 100 years); the values for Tocantins state are: h12h/h24h=0.93, h6h/h24h=0.86, h4h/h24h=0.82, h3h/h24h=0.78, h2h/h24h=0.72, h1h/h24h=0.61, h50min/h1h=0.92, h40min/h1h=0.83, h30min/h1h=0.68, h20min/h30min=0.76 e h10min/h30min=0.46. The comparison of the results with those from studies developed for other Brazilian regions showed variations of up to -62.30%, allowing us to conclude that the use of local constants is important in the process of rainfall disaggregation.

ABSTRACT Brazil is a large country that depends on the hydroelectricity generation hydropower dams. The Upper Grande River Basin (UGRB) is one of the most important Brazilian hydrological regions in terms of water availability and electric energy production. Therefore, studies of water availability are indispensable for a better and more successful decision making in water resources management in the region. This study objective to approach the land-use influence on the soil hydrology in the Upper Grande River Basin, a strategic headwater basin of southeastern Brazil. This study uses hydrological indicators (baseflow/runoff (BF/R) and overland flow/runoff (OF/R)) extracted from eight watersheds, varying the size and localization in the region, to support the results found. Soil saturated hydraulic conductivity (Ko) was determined in situ using a constant flow permeameter, totaling 224 sampled points. Five machine learning algorithms were compared in their performance to predict Ko (Random Forest, Support Vector Machine, Gradient Boosting, Linear Regression, Regularization) using terrain attributes as covariates. The tested methods for predicting Ko resulted in a relatively low coefficient of determination (R2) due to the high spatial variability of this soil hydrologic attribute. The hydrological indicator BF/R was sensitive to land-use changes in the watersheds. The greatest Ko values were associated with native forest and the least values area associated with pasture and rupestrian field.

This study was carried out in an Atlantic forest remnant in Southeastern Brazil and aimed to spatially model the soil water content (SWC) and net precipitation (NP) on a monthly time scale and to assess the spatial behavior of these hydrological variables in the different seasons. NP is defined by summing throughfall and stemflow, which have been collected after each rain event and accumulated monthly. Soil moisture measurements were carried out monthly up to a depth of 1.00 m and then integrated to obtain the SWC. The exponential semivariogram model was fitted for both hydrological variables, and the goodness-of-fit was assessed by a cross-validation procedure, spatial dependence degree (SDD) and spatial dependence index (SDI). This model provided adequate performance for SWC and NP mapping according to the cross-validation statistics. Based on the SDD, both variables have been classified as a ‘strong spatial dependence structure’. Nevertheless, when the SDI was assessed, NP showed less spatial dependence, while the SWC maintained almost the same performance. Kriging maps pictured the regional climate seasonality due to higher values of both variables in spring and summer than in autumn and winter seasons. However, correlations between NP and SWC are not expressive in the studied period.

The free aquifer recharge is a process of major importance in groundwater hydrology because it represents the renewable reserves of the water source. A good estimate of this variable is therefore critical to the proper management of water resources, particularly in light of climate variability inherent to the climate regime, as well as the increasing of surface water pollution and increased demand for good quality water groundwater. This study used a water balance model in soil to estimate the potential recharge (Rp) of the unconfined aquifer and the other components of the hydrological cycle. The model was applied in two watershed headwaters of the Rio Grande in Minas Gerais, Brazil: the Lavrinha River Basin (BHRL) and the Marcela River Basin (BHRM). The BHRL presents higher values of Rp, with an annual average of 895 mm, which corresponds to 40% of rainfall, while at the BHRM these values were 393.3 mm and 25%, respectively. The base runoff values confirm the greater recharge in BRHL, where this hydrograph component corresponded to 76% of the total discharge, compared with 40% for BHRM. The BALSEQ model allowed us to capture this difference, but the results were satisfactory for only one of the years in the BHRL and for the entire period for the BHRM, which reinforces the need to use this model for long time periods.

ABSTRACT The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.

ABSTRACT This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm). Mean prediction of error and root mean square of prediction error were used to assess the prediction methods. Two watersheds with contrasting soil-landscape features were studied, for which the prediction methods were performed differently. A multiple linear stepwise regression model was performed with RK using digital terrain models (DTMs) and remote sensing images in order to choose the best auxiliary covariates. Different pedogenic factors and land uses control soil property distributions in each watershed, and soil properties often display contrasting scales of variability. Environmental covariables and predictive methods can be useful in one site study, but inappropriate in another one. A better linear correlation was found at Lavrinha Creek Watershed, suggesting a relationship between contemporaneous landforms and soil properties, and RK outperformed OK. In most cases, RK did not outperform OK at the Marcela Creek Watershed due to lack of linear correlation between covariates and soil properties. Since alternatives of simple OK have been sought, other prediction methods should also be tested, considering not only the linear relationships between covariate and soil properties, but also the systematic pattern of soil property distributions over that landscape.

A condutividade hidráulica saturada do solo (K0) é de grande importância para a hidrologia, especialmente no contexto da infiltração, onde apresenta grande influência nas condições de geração de escoamento superficial direto, tendo como consequências a formação de inundações, erosão do solo e transporte de sedimentos. Além disso, tem papel fundamental na agricultura, por contribuir na infiltração e disponibilização de água para as plantas, e também na conservação do solo e do meio ambiente. Diante do exposto, o objetivo deste trabalho foi estimar e analisar o comportamento da condutividade hidráulica saturada do solo associada aos seus atributos físicos e declividade e avaliar o escoamento superficial direto, em uma área de floresta de Cedrus deodara, em Madrid, na Espanha. Para tanto, foram realizados testes de infiltração com o método dos anéis concêntricos em três pontos na área de estudo, a fim de obter dados que foram ajustados pelo modelo de Horton para estimar a condutividade hidráulica saturada do solo, e também foram realizados testes com um simulador de chuvas a fim de determinar o coeficiente de escoamento superficial. Foram retiradas amostras deformadas do solo para determinação de seus atributos físicos. Os resultados mostraram que o modelo de Horton foi adequado para estimar a condutividade hidráulica saturada do solo. Os valores dos atributos físicos do solo e a declividade influenciaram a condutividade hidráulica saturada do solo. A matéria orgânica associada à declividade do solo proporcionaram os maiores valores de K0. O escoamento superficial direto apresentou relação inversa à condutividade hidráulica saturada do solo.

ABSTRACT Models have been used by man for thousands of years to control his environment in a favorable way to better human living conditions. The use of hydrologic models has been a widely effective tool in order to support decision makers dealing with watersheds related to several economic and social activities, like public water supply, energy generation, and water availability for agriculture, among others. The purpose of this review is to briefly discuss some models on soil and water movement on landscapes (RUSLE, WEPP, GeoWEPP, LASH, DHSVM and AnnAGNPS) to provide information about them to help and serve in a proper manner in order to discuss particular problems related to hydrology and soil erosion processes. Models have been changed and evaluated significantly in recent years, highlighting the use of remote sense, GIS and automatic calibration process, allowing them capable of simulating watersheds under a given land-use and climate change effects. However, hydrology models have almost the same physical structure, which is not enough for simulating problems related to the long-term effects of different land-uses. That has been our challenge for next future: to understand entirely the hydrology cycle, having as reference the critical zone, in which the hydrological processes act together from canopy to the bottom of aquifers.

Compreender as correlações existentes entre variáveis ambientais e a distribuição das espécies em uma floresta, sua dinâmica e estoque de carbono é um dos principais objetivos em ecologia florestal. Nesse sentido o presente trabalho objetivou correlacionar aspectos da vegetação com variáveis topo-edafo-climáticas em um remanescente florestal em Bocaina de Minas, Serra da Mantiqueira, MG. Técnicas multivariadas de ordenação (PCA e CCA) e regressões múltiplas foram utilizadas para representar essas correlações. Altitude teve destaque como fator ambiental síntese, compreendendo vários gradientes existentes na área (em especial edáfico e de conservação) sendo, portanto, a variável que mais explicou distribuição de espécies, dinâmica florestal e estoque de carbono na área.

The estimation of surface flow into direct surface flow and base flow is fundamental for understanding the hydrologic behavior of basins, being possible, among other features, the capability of discharges maintenance during the dry seasons. Analysis of the related base flow with hydrogeological classes can contribute to understand the hydrological processes involved. This work aimed to estimate the base flow for eight fluviometric stations that were chosen according to the hydro geologic systems observed in the State of Minas Gerais. A numerical filter was employed in order to evaluate the relationship between hydrogeology and water flow regime. Daily discharge data sets, between October/1981 and September/1991, were used in the study. In all cases, the base flow accounted for over 50% of the water flow in rivers. The hydrogeological systems "xistosa", "pelítica" and "cobertura detrítica" presented smaller amount of base flow in the rivers discharge than other hydrogeological systems and obtained the same statistical classification. Based on the results we concluded that hydrogeology exerts indirect influence on the relationship between the base flow and river discharge.

ABSTRACTUnderstanding soil formation processes across different landscapes is needed to predict how soil properties will respond to land use change. This study aimed to characterize mountainous Inceptisols (Cambisols) under high altitude subtropical climate in southeastern Brazil, by soil physical, chemical and micromorphological analyses, under native forest and pasture. The soil under pasture had a greater bulk density than under forest, resulting in a severe reduction of macroporosity. At two depths, coarse quartz grains are angular, suggesting absence of transportational processes, thus confirming an autochthonous pedogenesis from the underlying gneissic rock. Most feldspars were weathered beyond recognition, but mineral alteration was commonly seen across cleavage plans and edges of micas. The micromorphological results suggest an intermediate stage of mineral weathering and soil development, which is in accordance with properties expected to be found in Inceptisols.

Study region: The study was conducted in the Rio Grande do Sul state – Brazil. Study focus: Studies about heavy rainfall events are crucial for proper flood management in river basins and for the design of hydraulic infrastructure. In Brazil, the lack of runoff monitoring is evident, therefore, designers commonly use rainfall intensity–duration–frequency (IDF) relationships to derive streamflow-related information. In order to aid the adjustment of IDF relationships, the probabilistic modeling of extreme rainfall is often employed. The objective of this study was to evaluate whether the GEV and Kappa multiparameter probability distributions have more satisfying performance than traditional two-parameter distributions such as Gumbel and Log-Normal in the modeling of extreme rainfall events in southern Brazil. Such distributions were adjusted by the L-moments method and the goodness-of-fit was verified by the Kolmogorov–Smirnov, Chi-Square, Filliben and Anderson–Darling tests. New hydrological insights for the region: The Anderson–Darling and Filliben tests were the most restrictive in this study. Based on the Anderson–Darling test, it was found that the Kappa distribution presented the best performance, followed by the GEV. This finding provides evidence that these multiparameter distributions result, for the region of study, in greater accuracy for the generation of intensity–duration–frequency curves and the prediction of peak streamflows and design hydrographs. As a result, this finding can support the design of hydraulic structures and flood management in river basins.

The Normalized Difference Vegetation Index (NDVI) is often used to extract information from vegetated areas since it is directly related to vegetation parameters such as percent of ground cover, photosynthetic activity of the plant and leaf area index. The aim of this paper was to analyze the potencial of semivariograms generated from NDVI values to detect changes in vegetated areas, analyzing their behavior (shape) and derived metrics (range, sill and nugget). Semivariograms were generated from NDVI values derived from Landsat TM images of May 2010, June 2010 and July 2011. The study area is located in the northern state of Minas Gerais, Brazil, and is covered by Brazilian savannas vegetation, totalizing 1,596 ha. Semivariograms were generated after the exploratory data analysis. Models were fitted, validated and their metrics analyzed. The results showed a very clear trend where the shape of semivariograms, sill and range were different when deforestation occurred and were similar when the area had not been changed. The model that generated best fit was the Gaussian, however, the three models tested showed behavior that makes it possible to detect changes in vegetation. It suggests that further researches should explore the degree to which the semivariogram can be used to quantify this spatial variability as well as to analyze the influence of sazonality for changing detection in vegetated areas.

ABSTRACT The scarcity of field data to develop soil maps through a pedological survey is one of the main limitations to using distributed hydrological models, especially in small and medium-sized watersheds. The aim of this study was to compare a distributed hydrological model prediction to a soil map based on a pedological survey and a moisture zone map obtained using the Height Above the Nearest Drainage - HAND model. The Distributed Hydrology Soil Vegetation Model - DHSVM, which is a physically-based and distributed hydrological model, was applied to a mountainous watershed, located in the region of the Mantiqueira Range in the south of Minas Gerais in southeastern Brazil, and was compared to both maps mentioned above, taking the soil map developed by the pedological survey as a reference. Daily weather and streamflow data-sets were used for DHSVM calibration and validation using the two different maps (soil and moisture zone maps) as inputs. In both simulations, the DHSVM performed well, with outputs indicating a good relationship between topographical and hydrological characteristics from the two types of maps. Thus, the moisture zone map obtained by the HAND model can also be successfully used in distributed hydrological modeling, especially for mountainous regions in southeastern Brazil.

Soil moisture temporal variability is an important concept in understanding forest management. The objective of this study was to analyse the effect of planting density on soil profile moisture in a clonal Eucalyptus plantation. Soil moisture was observed every 15 days at 25 points distributed throughout the eucalyptus stand between November 2013 and October 2015 to characterize the moisture according to the following three types of spacings: 3 x 2, 3 x 3, and 3 x 5 m. At each point, the 0 - 10, 10 - 20, 20 - 30, 30 – 40, and 60 - 100 cm layers were evaluated using a Profile Probe PR2 model. Soil moisture showed high spatial variability in the 0 - 10 cm layer, whereas from 30 to 100 cm deep, the moisture tended to become more homogeneous throughout the area. The dry periods presented greater temporal soil moisture stability when compared to the rainy seasons. The 3 x 2 m spacing has greater temporal soil moisture stability when compared to the others, while the 3 x 3 m spacing presented greater temporal variability.

ABSTRACT The proper design of hydraulic structures depends on estimates of maximum stream flows. The scarce stream flow monitoring in Brazil has led to the use of regionalization methods. The main objective of this study was to develop a tool via regional function to estimate maximum stream flows and their corresponding return periods (RP) with the aid of techniques based on the L-moments method, seeking for adequate hydrologic engineering applications and flood risk management. Annual maximum stream flow historical series were adjusted to traditional 2-parameter probability density functions (PDFs) (Normal, 2-parameter Log-Normal, Gumbel, Gamma) and multiparameter PDFs (GEV and Kappa), based on the L-moments method, which were used in the development of the regional function employing the dimensionless curve method. The regional function’s predictive capability was determined by cross-validation for different RPs. It can be concluded that the approach based on L-moments was successfully used to adjust the regional function. In addition, the regional function: i) was improved when using the aforementioned multiparameter PDFs and ii) was framed as optimum for RP of up to 100 years and considered useful for practical engineering projects and flood risk management.

The aim of this study was to analyze trends in precipitation and temperature on Trindade Island, South Atlantic Ocean. Time series from 1984 to 2008 for precipitation and from 1958 to 2008 for air temperature were analyzed. The regression analysis and Mann-Kendall test were used to test the trend in annual and seasonal scale of precipitation – January, April, July and October, which represents the middle months of summer, autumn, winter and spring, respectively, as well as for maximum and minimum air temperature. Results indicated that for precipitation time series there was no significant trend, while for minimum air temperature there was a significant trend to decay. In addition, no significant trend was found for maximum air temperature.

A importância das áreas de preservação permanente (APP) encontra-se na função ambiental de manter, preservar e conservar os recursos hídricos e ecossistemas existentes nas bacias hidrográficas. Objetivou-se com o presente trabalho delimitar e quantificar as APP’s de cursos d’água e áreas antropizadas nos limites destas na bacia hidrográfica do rio Formoso, TO. As APP's foram delimitadas considerando-se os limites determinados pelo Código Florestal Brasileiro, sendo amostradas as APP’s dos cursos d'água principais de nível hierárquico 4. O traçado manual da rede de drenagem, a delimitação automática das APP’s e a classificação visual dos conflitos de uso do solo a partir de imagens LANDSAT 5 TM dos anos de 1985, 1998 e 2011 foram realizadas no Sistema de Informações Geográficas ArcGIS. Constatou-se que as APP's dos cursos d’água amostradas no presente estudo representam 1,14% (24.491,35 ha) da área de drenagem da bacia do rio Formoso. Para o ano de 1985 quantificou-se uma área de 3.616,48 ha de conflitos de uso do solo na bacia, passando para 3.341,25 ha em 1998 e 3.345,37 ha em 2011. Tendo-se em vista a intensiva expansão agrícola observada na bacia do rio Formoso nas últimas décadas, a retração da área de conflitos de uso do solo entre 1985 e 1998 e sua posterior manutenção, pode ser associada às alterações na legislação ambiental.

The knowledge of rainfall distribution and behavior at certain area is indispensable at irrigation systems design and management, as well rainfall tracking regarding soil conservation aspects. Thus the objective of this research was the comparison and statistical adequacy of probability distribution models applied to probable rainfall studies, to determine which probability model is more appropriate to distinct seasons (monthly, fortnightly and decendial) and to estimate probable rainfall for different probability levels on Lambari region, South of Minas Gerais state, Brazil. Log-normal at 3 parameters and Gamma were the most adequate for monthly and decendial periods, for fortnight periods Gamma was the most adequate, with annual average values of monthly, fortnightly and decendial rainfall to 75% probability level of 82.4, 72.1, and 42.4 mm, respectively.