André Quintão de Almeida

Hydrological simulation using SWAT model in headwater basin in Southeast Brazil

Hydrological models are important tools that have been used in water resource planning and management. Thus, the aim of this work was to calibrate and validate in a daily time scale, the SWAT model (Soil and Water Assessment Tool) to the watershed of the Galo creek , located in Espirito Santo State. To conduct the study we used georeferenced maps of relief, soil type and use, in addition to historical daily time series of basin climate and flow. In modeling were used time series corresponding to the periods Jan 1, 1995 to Dec 31, 2000 and Jan 1, 2001 to Dec 20, 2003 for calibration and validation, respectively. Model performance evaluation was done using the Nash-Sutcliffe coefficient (ENS) and the percentage of bias (PBIAS). SWAT evaluation was also done in the simulation of the following hydrological variables: maximum and minimum annual daily flowsand minimum reference flows, Q90 and Q95, based on mean absolute error. ENS and PBIAS were, respectively, 0.65 and 7.2% and 0.70 and 14.1%, for calibration and validation, indicating a satisfactory performance for the model. SWAT adequately simulated minimum annual daily flow and the reference flows, Q90 and Q95; it was not suitable in the simulation of maximum annual daily flows.

Impacts of deforestation on water balance components of a watershed on the Brazilian East Coast

The Brazilian East coast was intensely affected by deforestation, which drastically cut back the original biome. The possible impacts of this process on water resources are still unknown. The purpose of this study was an evaluation of the impacts of deforestation on the main water balance components of the Galo creek watershed, in the State of Espirito Santo, on the East coast of Brazil. Considering the real conditions of the watershed, the SWAT model was calibrated with data from 1997 to 2000 and validated for the period between 2001 and 2003. The calibration and validation processes were evaluated by the Nash-Sutcliffe efficiency coefficient and by the statistical parameters (determination coefficient, slope coefficient and F test) of the regression model adjusted for estimated and measured flow data. After calibration and validation of the model, new simulations were carried out for three different land use scenarios: a scenario in compliance with the law (C1), assuming the preservation of PPAs (permanent preservation areas); an optimistic scenario (C2), which considers the watershed to be almost entirely covered by native vegetation; and a pessimistic scenario (C3), in which the watershed would be almost entirely covered by pasture. The scenarios C1, C2 and C3 represent a soil cover of native forest of 76, 97 and 0 %, respectively. The results were compared with the simulation, considering the real scenario (C0) with 54 % forest cover. The Nash-Sutcliffe coefficients were 0.65 and 0.70 for calibration and validation, respectively, indicating satisfactory results in the flow simulation. A mean reduction of 10 % of the native forest cover would cause a mean annual increase of approximately 11.5 mm in total runoff at the watershed outlet. Reforestation would ensure minimum flows in the dry period and regulate the maximum flow of the main watercourse of the watershed.

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertainty that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.

Geoestatística no estudo de modelagem temporal da precipitação

Geostatistics analysis is a powerful tool which has been used in studies of spatial dependence. With respect to the temporal dependence, few analysis are performed with this kind of methodology. In this study, the geostatistics technique was used to adjust a model to a series of temporal values of precipitation and its performance to predict data was also evaluated. The study was carried out at the Rio Itapemirim Basin in a series of monthly precipitation from 1940 to 2006. The adjusted model was compared to the Box and Jenkins model. The best geostatistics model adjusted was the one which used with 96 neighbors in the prediction and mean relative absolute error of 80.46. Geostatistics methodology showed better results for estimating the monthly precipitation in relation to the SARIMA model (2,1,1)(0,1,1)12.

Determinação do tempo térmico para o desenvolvimento de mudas de eucalipto na fase de enraizamento

The genus Eucalyptus is important in commercial forest plantations due to its rapid growth and ability to adapt to Brazilian climatic conditions. Among the most important stages for production of eucalyptus seedlings, through vegetative propagation, rooting is highlighted due to its requirements for water, nutrients and management which may compromise the quality of seedlings growing demand in Brazilian silviculture. This study aimed to determine the thermal sum to the rooting of clonal cuttings of eucalyptus (Eucalyptus grandis x E. urophylla) and generate equations to estimate the biomass accumulation in the same stage of production, based on the concept of degree-days (thermal time). The study was conducted in an acclimatized greenhouse in the Seedling Nursery of the Department of Forestry, Universidade Federal de Vicosa, Minas Gerais State, Brazil. At the start of rooting, the mean fresh weight of seedlings was 0.76 ± 0.17 g and the dry biomass was 0.17 ± 0.04 g. At the end of rooting, the means of fresh and dry biomass of seedlings were 1.49 ± 0.43 g and 0.21 ± 0.06 g, respectively. For rooting of eucalyptus seedlings 316.42 degree-days were necessary.

Mudanças do Uso e de Cobertura da Terra na Região Semiárida de Sergipe

This study performed a temporal analysis of the land use and coverage in the semiarid region of Sergipe. We used Landsat-5 TM and Landsat-8 OLI satellite images acquired in 1992, 2003 and 2013. The maximum likelihood algorithm was used to detect six classes of land use and land coverage. We used a high spatial resolution Spot-5 scene as reference data to validate the assigned land use and coverage classification. Our results indicate that deforestation of native vegetation increased approximately 26% in the study area. The Caatinga vegetation was the most impacted, mostly converted to pastureland. In addition, it was observed that the deforestation increase in the study area negatively affected the preserved Caatinga secondary regrowth.

Modelagem do balanço hídrico em microbacia cultivada com plantio comercial de Eucalyptus grandis x urophylla no leste de Minas Gerais, Brasil

In Brazil, the number of commercial plantations of forest species has increased considerably in recent decades. However, the potential impacts of this increase on water resources are still unknown. The objective of the present study was to model the water balance in a watershed, home to a commercial plantation of the Eucalyptus grandis x urophylla hybrid in eastern Minas Gerais, Brazil. This study was conducted in an experimental watershed with total area of 40 ha during the hydrological year extending from october 2009 to september 2010. The main source of water entering the system, via rainfall, was monitored as part of meteorological data by an automatic station installed within the study area. The main water outlets were estimated by the modified Penman-Monteith equation and by measuring the runoff generated at the basin output. Of the total precipitation (1123 mm) during the year, 9% (106 mm) was lost via interception, 66% (740 mm) via crop transpiration and 11% (119 mm) by soil evaporation, which together correspond to approximately 86 % of water entering the watershed. Of the total outflow generated (~ 147 mm), only 4.29 mm (0.4%) were converted into surface runoff. It can be concluded that during the hydrological year analyzed, the balance between the main water inputs and outputs in the watershed was equalized, without jeopardizing the availability of water in the natural waterway.

Índice de Área Foliar de Eucalyptus Estimado por Índices de Vegetação Utilizando Imagens TM - Landsat 5

The objective of the present study was to fit regression models to the measured leaf area in eucalyptus forests and vegetation indices derived from Landsat-5 TM images. The study was carried out in commercial plantations located in the basin of the Doce River, Minas Gerais state, between 2008 and 2011. Leaf area was measured in the field, non-destructively, with the LAI-2000 device. The following indices were used: Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Simple Ratio (SR). The best model was adjusted from the NDVI, with a correlation coefficient of 0.73 and root mean square error of 0.37 m² m–2 (19%). We conclude that the leaf area index can be estimated by the regression models fit to the vegetation indices derived from the Landsat - 5 TM images.

Mudanças do Uso e de Cobertura da Terra na Região Semiárida de Sergipe / Land Use and Land Cover Changes in the Sergipe Semiarid Region

This study performed a temporal analysis of the land use and coverage in the semiarid region of Sergipe. We used Landsat-5 TM and Landsat-8 OLI satellite images acquired in 1992, 2003 and 2013. The maximum likelihood algorithm was used to detect six classes of land use and land coverage. We used a high spatial resolution Spot-5 scene as reference data to validate the assigned land use and coverage classification. Our results indicate that deforestation of native vegetation increased approximately 26% in the study area. The Caatinga vegetation was the most impacted, mostly converted to pastureland. In addition, it was observed that the deforestation increase in the study area negatively affected the preserved Caatinga secondary regrowth.

Estimativa da batimetria do açude do Saco-PE com auxílio de dados orbitais

The bathymetry of a water body can be measured in the field using bathymetric probes; however this process is costly and time-consuming. Thus, the main objective of this study was to fit bathymetry estimation models of a lake from satellite data. The study was conducted in the Saco reservoir, located in the Pajeu river basin near the city of Serra Talhada - PE, Brazil. Regression models were adjusted between the bathymetry values collected with a probe, the green and near infrared spectral bands of the Landsat 5 TM satellite and the normalized difference water index. Evaluation of the adjusted models was performed by analysis of the coefficient of determination, mean squared error and model efficiency. The bathymetry of the reservoir varied between 0.3 and 10 meters deep. The best fits were found when using the power and exponential models, with coefficients of determination greater than 0.46 and model efficiency close to one. It can be concluded that the bathymetry models adjusted to the remote sensing data provided a satisfactory accuracy for estimating bathymetry values of the Saco reservoir, especially in the shallow regions of the lake.