Water Productivity Assessments With Landsat 8 Images in the Nilo Coelho Irrigation Scheme

Abstract

Water productivity assessments with Landsat 8 images in the Nilo Coelho irrigation scheme ANTÔNIO HERIBERTO DE CASTRO TEIXEIRA1; JANICE FREITAS LEIVAS1; RICARDO GUIMARÃES ANDRADE1 E FERNANDO BRAZ TANGERINO HERNANDEZ2 ¹Pesquisador doutor, grupo de Geociências, Embrapa Monitoramento por Satélite, CNPM, heriberto.teixeira@embrapa.br, janice.leivas@embrapa.br, ricardo.andrade@embrapa.br²Professor doutor, Laboratório de Hidráulica, Universidade Estadual Paulista, UNESP, fbthtang@agr.feis.unesp.br 1 Abstract The Nilo Coelho (NC) irrigation scheme, located in the Brazilian semi-arid region, is an important irrigated agricultural area. Land use change effects on actual evapotranspiration (ET), biomass production (BIO) and water productivity (WP) were quantified with Landsat 8 images and weather data in this scheme covering different thermohydrological conditions. The SAFER algorithm was used for ET acquirements while the Monteith’s radiation model was applied to retrieve BIO. For classifying irrigated crops and natural vegetation, the SUREAL model was used with a satellite image representing the driest period of the year. The average values for ET, BIO and WP in irrigated crops, ranged, respectively, from 1.6 ± 1.9 to 4.2 ± 1.9 mm day-1; 59 ± 86 to 146 ± 91 kg ha-1 day-1;and 2.0 ± 1.5 to 3.0 ± 1.2 kg m-3. The corresponding ranges for natural vegetation (“Caatinga”) were from 1.2 ± 1.8 to 2.6 ± 1.8 mm day-1; 43 ± 78 to 76 ± 78 kg ha-1 day-1; and 1.6 ± 1.4 to 2.7 ± 1.1 kg m-3. The incremental values, which represent the effects of the replacement of natural vegetation by irrigated crops, were 40, 54 e 23%, for ET, BIO e WP, respectively. Keywords: evapotranspiration, biomass production, land use change TEIXEIRA, A.H. de C.; LEIVAS, J.F.; ANDRADE, R.G.; HERNANDEZ, F.B.T.Análises da produtividade da água com imagens Landsat 8 no perímetro de irrigação Nilo Coelho 2 resumo O perímetro de irrigação Nilo Coelho (NC), localizado na região semiárida do Brasil, é uma importante área de agricultura irrigada. Os efeitos da mudança de uso da terra na evapotranspiração atual (ET), na produção de biomassa (BIO) e na produtividade da água (PA) foram quantificados com imagens Landsat 8 e dados climáticos neste perímetro cobrindo diferentes condições termo hidrológicas. O algoritmo SAFER foi usado para a obtenção da ET enquanto que o modelo da radiação de Monteith foi aplicado para a estnimativa da BIO. Para classificação em culturas irrigadas e vegetação natural o modelo SUREAL foi usado na imagem representativa do período mais seco do ano. Os valores médios da ET, BIO e PA nas culturas irrigadas variaram respectivamente de 1,6 ± 1,9 a 4,2 ± 1,9 mm dia-1; 59 ± 86 a 146 ± 91 kg ha-1 dia-1;e 2,0 ± 1,5 a 3,0 ± 1.2 kg m-3. Os valores correspondentes para vegetação natural (“Caatinga”) foram de 1,2 ± 1,8 a 2,6 ± 1,8 mm dia-1; 43 ± 78 a 76 ± 78 kg ha-1 dia-1; e 1,6 ± 1,4 a 2,7 ± 1,1 kg m-3. Os valores incrementais, representativos dos efeitos da substituição da vegetação natural por culturas irrigadas foram de 40, 54 e 23%, para respectivamente ET, BIO e PA. Palavras-chave: Evapotranspiração, produção de biomassa, mudança de uso da terra.

Large-Scale Spatial Modeling of Crop Coefficient and Biomass Production in Agroecosystems in Southeast Brazil

“…All the regression coefficients of the parameters in Figure 3 and equations below were determined in different areas of Brazil with digital images from different satellites, like Landsat [6,7,13,14,[23][24][25], RapidEye [26], and MODIS [9,27], with field measurements for calibration involving strong contrasting agroecosystems, and under different thermohydrological conditions throughout several years as semiarid areas [9,13,25], wetlands [27], tropical [23], and subtropical areas [6,7,14]. Most of the regressions performed from Landsat-8 were used in this work due to their similarity to the radiometric data on the visible (RGB) and near infrared (NIR) range of the Sentinel-2 satellite [22,28].…”

“…sr −1. µm −1 ) was obtained by Slob's equation [23,37] in Equation (4), which was derived by Teixeira et al [34], considering four energy balance field experiments involving different thermohydrological conditions in Brazil:…”

“…where R G is the solar radiation, R N is the net radiation, T A is the average air temperature, ε A and ε S are the atmospheric and surface emissivities, respectively, and σ is the Stefan-Boltzmann constant (5.67 × 10 −8 Wm −2 K −4 ). The denominator of the fraction of Equation (6) is a model of the long-wave atmospheric radiation [23]. We reduced the equation by applying Equation (4) in Equation (6), resulting in Equation (7), which depends only on the second term of Equation (4), without an uncertainty increase:…”

“…The HI depends on whether the property is mechanized or not, and economic and topographical factors [9]. ET r and BIO modeling, besides comparing different land uses as made in this paper, can compare different pasture managements [68], the effect of irrigation on crops [9,14,23], and the impact of drought on large areas [69]. ET r and BIO at a 10-m resolution are suitable for precision agriculture applications [70,71].…”

“…The availability of freely moderate-to-high spatial resolution satellite imagery stimulated the use of remote sensing solutions in spatial modeling, especially after the launch of the Landsat-8 satellite in 2013 [22]. While Landsat-8 imagery (at 30 m spatial resolution) has been widely used for ET mapping [6,7,[23][24][25], other remote sensing imagery, like RapidEye [26] and MODIS [27], with higher and lower spatial resolution than the Landsat-8, respectively, began to be used successfully. A new option is the Sentinel-2 satellite, launched in June 2015, which provides multi-spectral images in 13 bands at different spatial resolutions, including three visible (RGB) and one near infrared (NIR) bands at 10 m spatial resolution, six red-edge and shortwave infrared (SWIR) bands at 20 m, and three atmospheric correction bands at 60 m [28] acquired at a swath width of 290 km and a five-day temporal resolution.…”