Richarde Marques da Silva

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff–erosion model in the Mamuaba catchment, Brazil

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

Análise da variabilidade espaço-temporal e identificação do padrão da precipitação na bacia do Rio Tapacurá, Pernambuco

The study aimed to evaluate the space-time variability of rainfall for the period 1970-2000, in Tapacura river basin, located in Pernambuco State. Many statistical parameters were used to analyze the monthly and annual rainfall, such as mean standard deviation, normalized deviation, fitted equation and coefficient of variability. The study showed a major concentration of rainfall between March and July, when 60% of annual rainfall occurred, and that the dry season occurred between August to February. The annual variability showed a significant decrease of the rainfall in order of -20% compared to the mean rainfall. About rainfall spatial variability, it was verified that it decreases at the direction East-West, and that the periods with low rainfall depths have higher coefficient of variation.

Multispectral image unsupervised segmentation using watershed transformation and cross-entropy minimization in different land use

A general-purpose unsupervised segmentation algorithm based on cross-entropy minimization by pixel was developed; this algorithm, known as the SCEMA (Segmentation Cross-Entropy Minimization Algorithm), starts from an initial segmentation and iteratively searches the best statistical model, estimating the probability density of the image to reduce the cross-entropy with respect to the previous iteration. The SCEMA was tested using satellite images from the Landsat Thematic Mapper sensor of Landsat 5 for the Amazon region (12 images for testing and 15 for validation). Theme classes identified in the image were (1) water, (2) vegetation, and (3) agriculture. Using the Kappa index and other statistics parameters, the comparison of classifications is made with the following segmentation methods: (1) cross-entropy minimization by pixel, (2) cross-entropy minimization by region, (3) K-means, and (4) maximum likelihood. The results indicate that cross-entropy minimization by pixel results in a consistent segmenta...A general-purpose unsupervised segmentation algorithm based on cross-entropy minimization by pixel was developed; this algorithm, known as the SCEMA (Segmentation Cross-Entropy Minimization Algorithm), starts from an initial segmentation and iteratively searches the best statistical model, estimating the probability density of the image to reduce the cross-entropy with respect to the previous iteration. The SCEMA was tested using satellite images from the Landsat Thematic Mapper sensor of Landsat 5 for the Amazon region (12 images for testing and 15 for validation). Theme classes identified in the image were (1) water, (2) vegetation, and (3) agriculture. Using the Kappa index and other statistics parameters, the comparison of classifications is made with the following segmentation methods: (1) cross-entropy minimization by pixel, (2) cross-entropy minimization by region, (3) K-means, and (4) maximum likelihood. The results indicate that cross-entropy minimization by pixel results in a consistent segmentation of images. The algorithm also compares favorably to other well-known image segmentation methods, and the numerical test results illustrate the efficiency of our approach for image segmentation.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Estimativa da produção de sedimentos mediante uso de um modelo hidrossedimentológico acoplado a um SIG

Kineros is a runoff-erosion model used to compute runoff and sediment yield in urban and rural basins. In this paper, the model was applied to the Pirapama river basin, located in the coastal zone of the State of Pernambuco. The obtained results were linked to a GIS in order to temporally and spatially identify the areas susceptible to the erosion process within the Pirapama river basin. The model was calibrated with daily rainfall data from two raingauges for the period from 1990 to 2001. From the coupling of the modeling results into a GIS, it was possible to identify the main areas susceptible to the erosion process. The sediment yield results showed that the planes with the largest erosion yield produced more than 200 t ha-1 year-1 (653,079 t in an area of 67.87 km², 11.3% of the total area). These results also showed that a large part of the basin is indeed susceptible to the erosion process. This study shows that the Kineros model is applicable to basins larger than 100 km² and that its coupling to a GIS proved useful to identify and analyze the main areas with sediment yield within the basin. Thus, the model can be considered as a promising tool for simulation of the sediment yield in basins in northeastern Brazil.

Análise espacial da endemia hansênica no município de Bayeux (PB) mediante técnicas de SIG

Current society creates risks that affect the population unequally, and in the Brazilian municipality of Bayeux, located in Paraiba State, between 2001 and 2011. The disease incidence data were statistically analyzed and mapped through techniques of GIS and field trips using GPS. The results showed that the affected cases were found distributed in almost all parts of this urban area, and its most significant presence in the neighborhoods of Rio do Meio (32 cases - 15.2%), Centro (29 cases - 13.7%), Imaculada (28 cases - 13.3%) e Mario Andreazza (28 cases - 13.3%). The study of the spatial distribution of leprosy using GIS techniques proved to be effective and valuable to mapping of cases in the Bayeux and for for understanding the epidemiological and the ordination of actions in order to block the spread of the disease.

PERDAS DE ÁGUA E SEDIMENTO EM DIFERENTES SISTEMAS DE MANEJO NO SEMIÁRIDO DA PARAÍBA

Resumen pt: O presente trabalho busca descrever as perdas de agua e sedimentos na Bacia Experimental de Sao Joao do Cariri - BESJC. A BESJC esta nas coordenadas -7o ...

Modelagem geoestatística dos casos de dengue e da variação termopluviométrica em João Pessoa, Brasil

Dengue is a viral disease whose incidence has increased considerably in recent decades. This study aimed to investigate the climatic factors associated with the incidence of dengue fever in the city of Joao Pessoa, Paraiba State, in the period between 2007 and 2011. The analysis has included thermo-rainfall collected in INMET, and the cases of dengue obtained in the Health Department of the municipality. In total were reported 9,467 confirmed cases of dengue, as follows: 33.2% in 2007, 8.8% in 2008, 2.6% in 2009, 12.4% in 2010, and 42.9% in 2011. The highest incidences of dengue cases occur in the south part of the city. It was found by correlating time-lag that rainfall and relative humidity are the climatic variables that favor the occurrence of dengue in Joao Pessoa.

Correlation of dengue incidence and rainfall occurrence using wavelet transform for João Pessoa city

Dengue, a reemerging disease, is one of the most important viral diseases transmitted by mosquitoes. In this study, 55,680 cases of dengue between 2007 and 2015 were reported in Paraíba State, among which, 30% were reported in João Pessoa city, with peaks in 2015, 2011 and 2013. Weather is considered to be a key factor in the temporal and spatial distribution of vector-transmitted diseases. Thus, the relationship between rainfall occurrence and dengue incidences reported from 2007 to 2015 in João Pessoa city, Paraíba State, Brazil, was analyzed by means of wavelet transform, when a frequency analysis of both rainfall and dengue incidence signals was performed. To determine the relationship between rainfall and the incidence of dengue cases, a sample cross correlation function was performed to identify lags in the rainfall and temperature variables that might be useful predictors of dengue incidence. The total rainfall within 90 days presented the most significant association with the number of dengue cases, whereas temperature was not found to be a useful predictor. The correlation between rainfall and the occurrence of dengue cases showed that the number of cases increased in the first few months after the rainy season. Wavelet analysis showed that in addition to the annual frequency presented in both time series, the dengue time series also presented the 3-year frequency from 2010. Cross wavelet analysis revealed that such an annual frequency of both time series was in phase; however, after 2010, it was also possible to observe 45° up phase arrows, which indicated that rainfall in the present year led to an increased dengue incidence the following year. Thus, this approach to analyze surveillance data might be useful for developing public health policies for dengue prevention and control.

ESTIMATIVA DA PRODUÇÃO DE SEDIMENTOS NA BACIA DO RESERVATÓRIO EPITÁCIO PESSOA – PB

Entender e representar o comportamento do ciclo hidrologico de uma bacia hidrografica e de grande importância para uma gestao eficiente dos seus recursos e a utilizacao de modelos hidrologicos vem para contribuir nesse sentido. Diante disso, esse trabalho tem por objetivo realizar a estimativa da producao de sedimentos na bacia hidrografica do Reservatorio Epitacio Pessoa na Paraiba, uma bacia que vem sofrendo com longos periodos de escassez hidrica e a producao de sedimentos. O estudo foi realizado para o periodo de 2001 a 2014, utilizando o modelo SWAT. A vazao media simulada para o periodo foi de 12,87 m³/s e a producao media estimada de sedimentos para a bacia foi de 0,03 (ton.ha-1.ano-1) durante os 14 anos analisados. Com base nas estimativas, o total de sedimentos que foram depositados no reservatorio foi de aproximadamente 434 mil toneladas em 14 anos. Com isso, faz-se necessaria a utilizacao de politicas para diminuir a producao de sedimentos da bacia e consequentemente minimizar o processo de assoreamento do reservatorio Epitacio Pessoa, que ao longo dos anos vem causando a diminuicao da sua capacidade total de armazenamento, que originalmente era de 535.680.000 m³ (DNOCS, 1963), e hoje segundo a AESA e de 411.686.287 m³.