RESUMO: Para investigar alterações no albedo, no Índice de Vegetação por Diferença Normalizada (NDVI), no saldo de radiação e no fluxo de calor no solo, em decorrência do regime pluviométrico no semiárido cearense, desenvolveu-se um estudo na bacia do Rio Trussu -Ceará, empregando-se sensoriamento remoto. Foram utilizadas duas imagens Landsat 7 ETM+, datadas de 25-10-2000 e 24-7-2001, sendo as variáveis estimadas pelo emprego do algoritmo SEBAL (Surface Energy Balance Algorithms for Land). Os resultados mostraram que as variáveis investigadas apresentaram alterações entre as duas estações, sendo os maiores valores de albedo registrados na estação seca. O NDVI apresentou maior sensibilidade ao regime hídrico, mostrando alto potencial de recuperação da vegetação ao efeito da precipitação. As margens do Rio Trussu apresentaram NDVI superior a 0,39, sendo indicativo de preservação da mata ciliar. A vegetação da bacia mostrou alto poder resiliente expresso pelo incremento nos valores de NDVI para o ano de 2001. A estação chuvosa exerceu também influência marcante sobre o saldo de radiação e fluxo de calor no solo, confirmando o efeito da estação climática na modificação do balanço de energia sobre a bacia. PALAVRAS-CHAVE:albedo, NDVI, sensoriamento remoto, saldo de radiação. BIOPHYSICS VARIABLES SEASONALITY ON SURFACE IN SEMIARID REGIONS BY USING REMOTE SENSING ABSTRACT:To investigate the rainfall regime effects over the albedo, NDVI (normalized difference vegetation index), net radiation and soil heat flux in a semiarid region (Northeast of Brazil), a study in the Trussu watershed was developed by using remote sensing. The study focuses on two images (Landsat 7 ETM+) provided by Instituto Nacional de Pesquisas Espaciais (INPE), from October 25, 2000 and July 24, 2001, each of them having a different rainfall regime (dry and wet seasons). The images were analyzed by using the SEBAL algorithm (surface energy balance algorithm for land). The results showed that the amount of rainfall affected the investigated variables, and the highest values of albedo were registered during the dry season. The NDVI presented high sensibility to rainfall regime, pointing out a high vegetation potential recover during the rainfall season. The NDVI along the Trussu River was up to 0.39, expressing the repair zone preservation. The watershed vegetation showed a high resilience power expressed by NDVI values in the year of 2001. Net radiation and soil heat flux were greater in the dry season, in this way expressing the effect of humidity on the energy balance.
Resumo-A perda de solo por erosão é um dos problemas ambientais mais sérios da atualidade e tem causado a degradação de vários recursos, principalmente do solo e da água. Objetivou-se com este trabalho, estimar a perda de solos por erosão em uma microbacia localizada no semiárido do Estado do Ceará, efetuada com a combinação de ferramentas de Sistemas Informações Geográficas (SIG) com modelo quantitativo de perda de solo, através da Equação Universal de Perdas de Solos, USLE. A microbacia foi delimitada através do modelo numérico do terreno. Usando a ferramenta ArcHydro do software ArcMap 9.1, estimou-se a rede de drenagem. A perda de solo em 74% da microbacia estudada, apresenta valor menor que 11 t ha -1 ano -1 em áreas mais planas e vegetadas. Observou-se que mais de 90% da área apresentou perda de solo abaixo de 37 t ha -1 ano -1 , sendo esta característica bastante influenciada pelo relevo, visto que a microbacia apresenta relevo suave -ondulado em mais de 83% da área total. 66% da área apresenta baixa susceptibilidade à erosão (<10 t ha -1 ano -1 ), estando associada a esta região cobertura vegetal e baixos valores do fator topográfico. A utilização de integrada de SIG e USLE permitiu a realização de uma análise rápida e dinâmica da área em estudo, além de apontar as áreas de maior vulnerabilidade ao processo de perda de solo dentro da Bacia.Palavras-chave -Erosão. Relevo. Cobertura Vegetal. SIG.Abstract -Nowadays soil loss by erosion is one of the most serious environmental problems which has caused the degradation of various resources, especially soil and water. The aim of this study was to predict the soil loss due to erosion at a small watershed located in the Semiarid region of Ceara State, Brazil, through an arrangement of Geographic Information System tools with a quantitative model of soil loss, by the Universal Soil Loss Equation, USLE. The watershed delimitation was performed using the Digital Elevation Model. The density of drainage network was estimated using the extension ArcHydro/ ArcMap 9.1. The soil loss in 74% of the studied small watershed presents a value smaller than 11 t ha -1 year -1 in more plain and vegetated areas. It was observe that more than 90% of the area presented a soil loss below 37 t ha -1 year -1 , this characteristic being severely influenced by the local geography, which is smooth and low sloped in more than 83% of the area of the small watershed. 66% of the area presents a low vulnerability to erosion (<10 t ha -1 year -1 ), this being associated with cover vegetation of this region and low values of slope factors. The integrated use of GIS and USLE has allowed a fast and dynamic analysis of the study area, beyond identifying most vulnerable areas to the soil loss process within the basin.
RESUMO:Em face da importância em conhecer a evapotranspiração (ET) para uso racional da água na irrigação no contexto atual de escassez desse recurso, algoritmos de estimativa da ET a nível regional foram desenvolvidos utilizando-se de ferramentas de sensoriamento remoto. Este estudo objetivou aplicar o algoritmo SEBAL (Surface Energy Balance Algorithms for Land) em três imagens do satélite Landsat 5, do segundo semestre de 2006. As imagens correspondem a áreas irrigadas, floresta nativa densa e a Caatinga do Estado do Ceará (Baixo Acaraú, Chapada do Apodi e Chapada do Araripe). Este algoritmo calcula a evapotranspiração horária a partir do fluxo de calor latente, estimado como resíduo do balanço de energia na superfície. Os valores de ET obtidos nas três regiões foram superiores a 0,60 mm h -1 nas áreas irrigadas ou de vegetação nativa densa. As áreas de vegetação nativa menos densa apresentaram taxa da ET horária de 0,35 a 0,60 mm h -1 , e valores quase nulos em áreas degradadas. A análise das médias de evapotranspiração horária pelo teste de Tukey a 5% de probabilidade permitiu evidenciar uma variabilidade significativa local, bem como regional no Estado do Ceará. PALAVRAS-CHAVE:sensoriamento remoto, balanço de radiação, Landsat. LOCAL AND REGIONAL VARIABILITY OF EVAPOTRANSPIRATION ESTIMATED BY SEBAL ALGORITHMABSTRACT: In the context of water resources scarcity, the rational use of water for irrigation is necessary, implying precise estimations of the actual evapotranspiration (ET). With the recent progresses of remote-sensed technologies, regional algorithms estimating evapotranspiration from satellite observations were developed. This work aimed at applying the SEBAL algorithm (Surface Energy Balance Algorithms for Land) at three Landsat-5 images during the second semester of 2006. These images cover irrigated areas, dense native forest areas and caatinga areas in three regions of the state of Ceará (Baixo Acaraú, Chapada do Apodi and Chapada do Araripe). The SEBAL algorithm calculates the hourly evapotranspiration from the latent heat flux, estimated from the surface energy balance. The hourly evapotranspiration values obtained were greater than 0.60 mm h -1 in irrigated or dense native vegetation areas, from 0.35 to 0.60 mm h -1 in sparse vegetation areas and almost null in degradated areas. The analysis of hourly evapotranspiration means by Tukey test at 5% probability level showed not only a significant variability locally but also at a regional scale in the state of Ceará.KEYWORDS: remote sensing, radiation balance, Landsat. INTRODUÇÃOA crescente demanda hídrica e, por outro lado, a deterioração dos recursos naturais e sua escassez em algumas regiões tornam o gerenciamento integrado dos recursos hídricos cada vez mais imprescindível (SCHMIDT et al., 2004). Sabe-se que o setor agrícola é o maior consumidor de água, alcançando cerca de 69% de toda a água derivada de rios, lagos e aquíferos subterrâneos. Os
Soil salinization due to irrigation affects agricultural productivity in the semi-arid region of Brazil. In this study, the performance of four computational models to estimate electrical conductivity (EC) (soil salinization) was evaluated using laboratory reflectance spectroscopy. To investigate the influence of bandwidth and band positioning on the EC estimates, we simulated the spectral resolution of two hyperspectral sensors (airborne ProSpecTIR-VS and orbital Hyperspectral Infrared Imager (HyspIRI)) and three multispectral instruments (RapidEye/REIS, High Resolution Geometric (HRG)/SPOT-5, and Operational Land Imager (OLI)/Landsat-8)). Principal component analysis (PCA) and the first-order derivative analysis were applied to the data to generate metrics associated with soil brightness and spectral features, respectively. The three sets of data (reflectance, PCA, and derivative) were tested as input variable for Extreme Learning Machine (ELM), Ordinary Least Square regression (OLS), Partial Least Squares Regression (PLSR), and Multilayer Perceptron (MLP). Finally, the laboratory models were inverted to a ProSpecTIR-VS image (400-2500 nm) acquired with 1-m spatial resolution in the northeast of Brazil. The objective was to estimate EC over exposed soils detected using the Normalized Difference Vegetation Index (NDVI). The results showed that the predictive ability of the linear models and ELM was better than that of the MLP, as indicated by higher values of the coefficient of determination (R 2 ) and ratio of the performance to deviation (RPD), and lower values of the root mean square error (RMSE). Metrics associated with soil brightness (reflectance and PCA scores) were more efficient in detecting changes in the EC produced by soil salinization than metrics related to spectral features (derivative). When applied to the image, the PLSR model with reflectance had an RMSE of 1.22 dS·m −1 and an RPD of 2.21, and was more suitable for detecting salinization (10-20 dS·m −1 ) in exposed soils (NDVI < 0.30) than the other models. For all computational models, lower values of RMSE and higher values of RPD were observed for the narrowband-simulated sensors compared to the broadband-simulated instruments. The soil EC estimates improved from the RapidEye to the HRG and OLI spectral resolutions, showing the importance of shortwave intervals (SWIR-1 and SWIR-2) in detecting soil salinization when the reflectance of selected bands is used in data modelling.
Resumo -O objetivo deste trabalho foi avaliar os impactos das mudanças climáticas na demanda de água para irrigação de culturas perenes, na Bacia do Jaguaribe, no Estado do Ceará. Foi empregado o sistema integrado de modelagem regional PRECIS ("Providing Regional Climates for Impact Studies"), e aplicado o método de redução de escala de bacia hidrográfi ca, com as condições de contorno do modelo climático regional (HadRM3P). Foi utilizado um conjunto de climatologia de base do modelo de 1961 a 1990 e de projeções climáticas futuras. As coordenadas geográfi cas da região em estudo foram consideradas para interpolação num sistema de informação geográfi ca. A evapotranspiração de referência foi estimada por meio de dados da temperatura média mensal. As mudanças climáticas projetadas aumentaram a demanda projetada de água para irrigação, porque a evapotranspiração foi estimada para aumentos de 3,1 a 2,2% e a precipitação pluvial foi estimada para diminuições de 30,9 a 37,3%. O aumento da necessidade hídrica foi estimada em 32,9% a 43,9%, para o ano de 2040, conforme o cenário analisado.Termos para indexação: evapotranspiração, irrigação, SIG. Climate change and impacts on water requirement of permanent crops in the Jaguaribe Basin, Ceará, BrazilAbstract -The aim of this study was to estimate climate change impacts on irrigation water demand for permanent crops. The PRECIS (Providing Regional Climates for Impact Studies) system was applied, and downscaling techniques were used at the river basin level, with the boundary conditions of the regional climate model (HadRM3P). A climate data set was generated for 1961 to 1990 (baseline) and for future climate projections. The regional geographical coordinates were considered for interpolation in a georeferenced coordinated system. The reference evapotranspiration was estimated through data of monthly average temperature. Projected climate change increased projected irrigation water demand, because evapotranspiration was estimated to increase by 3.1 to 2.2% and rainfall was estimated to decrease by 30.9 to 37.3%. The 2040 water need was estimated to increase by 32.9% to 43.9%, according to the analyzed scenario.
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