Actual evapotranspiration by machine learning and remote sensing without the thermal spectrum.

The objectives of this study were to use machine learning algorithms to establish a model for estimating the evapotranspiration fraction (ETf) using two data input scenarios from the spectral information of the Sentinel-2 constellation, and to analyze the temporal and spatial applicability of the models to estimate the actual evapotranspiration (ETr) in agricultural crops irrigated by center pivots. The spectral bands of Sentinel 2A and 2B satellite and vegetation indices formed the first scenario. The second scenario was formed by performing the normalized ratio procedure between bands (NRPB) and joining the variables applied in the first scenario. The models were generated to predict the ETf using six regression algorithms and then compared with ETf calculated by the Simple Algorithm For Evapotranspiration Retrieving (SAFER) algorithm, was considered as the standard. The results possible to select the best model, which in both scenarios was Cubist. Subsequently, ETf was estimated only for the center pivots present in the study area and the classification of land use and cover was accessed through the MapBiomas product. Land use was necessary to enable the calculation of ETr in each scenario, in the center pivots with sugarcane and soybean crops. ETr was estimated using two ETo approaches (EToBrazil and Hargreaves-Samani). It was found that the Hargreaves-Samani equation overestimated ETr with higher errors mainly for center pivots with sugarcane, where systematic error (MBE) ranged from 0.89 to 2.02 mm d-1. The EToBrazil product, on the other hand, presented statistical errors with MBE values ranging from 0.00 to 1.26 mm d-1 for both agricultural crops. Based on the results obtained, it is observed that the ETr can be monitored spatially and temporally without the use of the thermal band, which causes the estimation of this parameter to be performed with greater temporal frequency.

Proposition of irrigation system for wetting the clay surface of tennis courts.

The key to maintaining a clay court with quality and lastingly is through water applications, carried out periodically and through systems with high distribution uniformity, developed specifically for this purpose. The objective in this study was to evaluate the performance of a sprinkler irrigation system with hose and shower, traditionally used in clay tennis court, and propose another low-cost system that is operational and technically feasible, which is the irrigating bar. For each irrigation system, three evaluations were performed. At the beginning of each test, the pressures and flow rates of the emitters were measured, and the water distribution profile method was used to determine the distribution uniformity of the systems. Distribution efficiency was obtained through the Christiansen's (UC), distribution (UD), absolute (UA), statistical (US) and Hart's (UH) uniformity coefficients, HSPA standard efficiency (UHSPA) and, coefficient of variation (CV). Subsequently, the application and irrigation efficiencies were calculated. It was found that the irrigation bar required lower operating pressure, as well as greater stability of pressure and flow in relation to the hose system. Water losses in the hose/shower system (22.0%) were higher than in the irrigation bar (0.6%). Regardless of the evaluated system, UC (68.4% and 86.5%) and UH (66.4% and 87.5%) values were similar and higher than those of the other coefficients (~51.8% and ~81.2%). The collected depths, applied by the hose/shower irrigation system, showed high spatial variability and, consequently, low values of uniformity, being classified as poor or unacceptable. The irrigating bar promoted higher values of uniformity coefficients, being classified as good. Irrigation efficiencies were 53.97 and 85.97% for hose/shower and irrigation bar systems, respectively. The hose/shower system has low performance in the irrigation of clay tennis courts. The irrigation bar system, for providing technical, operational, and economic benefits, and has the potential to be used in the irrigation of clay tennis courts.

Impact of soil water regimes and partial root-zone drying in field-grown papaya in semi-arid conditions.

This study aimed to evaluate in the papaya Tainung genotype, the effects of partial root-zone drying (PRD) technique on soil water regimes by using different frequencies of shifting irrigation-side of plant row and the effects of PRD technique on (1) crop agronomic performance, (2) titratable fruit acidity (TA), (3) total soluble solids (TSS), and TSS/TA ratio. Also, we analyze the spatial dynamic of papaya condition using normalized difference vegetation index (NDVI) from different satellite images. The study was conducted in the semi-arid region of Bahia (BA) and Minas Gerais (MG), Brazil. The combination of 100% (Full irrigation-FU), 50%, and 35% in the irrigation depth (WID) and frequencies of shifting plant-row side irrigation of 0 (Fixed Irrigation-FX), 7, 14, and 21 days were applied. Nine treatments were studied in BA and five in MG. The water available in the soil was reduced to 44% for frequencies of shifting plant-row side irrigation of 7 days, 50% for 14 days, and 85% for 21 days, compared to the soil water availability at field capacity. Partial water deficit in the soil through the PRD technique did not significantly reduce the total root length, effective root depth, and root effective horizontal distance of the papaya Tainung genotype. However, PRD treatments showed leaf abscission, which resulted in reduced leaf area and NDVI values, especially in the MG experiment. Papaya yield and fruit quality were not affected. However, except for PRD 21 35%, irrigation water depth reduced to 50 and 35% under PRD increased crop water productivity (CWP) in papaya plants. Thus, the PRD technique may save 35% of WID using the alternation of lateral shift irrigation of crop row every 7 days under water scarcity in semi-arid regions. The NDVI index was important to compare the papaya canopy vigor between the experimental areas studied. We also confirmed the potential of NDVI to monitor the vigor of papaya canopy, since we could notice the sensibility of NDVI to identify water stress in papaya in higher vapor pressure deficit (VPD) conditions occurred in October 2016 and January 2017 in Bom Jesus da Lapa-BA. Therefore, the PRD strategy can be a useful tool to save water in papaya cultivation under semi-arid conditions.

Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing.

Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the number of weather stations is insufficient. Thus, free products of remote sensing with evapotranspiration information must be used for this purpose. In this context, the objective of this study was to estimate monthly ETo from potential evapotranspiration (PET) made available by MOD16 product. In this study, the monthly ETo estimated by Penman-Monteith method was considered as the standard. For this, data from 265 weather station of the National Institute of Meteorology (INMET), spread all over the Brazilian territory, were acquired for the period from 2000 to 2014 (15 years). For these months, monthly PET values from MOD16 product for all Brazil were also downloaded. By using machine learning algorithms and information from WorldClim as covariates, ETo was estimated through images from the MOD16 product. To perform the modeling of ETo, eight regression algorithms were tested: multiple linear regression; random forest; cubist; partial least squares; principal components regression; adaptive forward-backward greedy; generalized boosted regression and generalized linear model by likelihood-based boosting. Data from 2000 to 2012 (13 years) were used for training and data of 2013 and 2014 (2 years) were used to test the models. The PET made available by the MOD16 product showed higher values than those of ETo for different periods and climatic regions of Brazil. However, the MOD16 product showed good correlation with ETo, indicating that it can be used in ETo estimation. All models of machine learning were effective in improving the performance of the metrics evaluated. Cubist was the model that presented the best metrics for r2 (0.91), NSE (0.90) and nRMSE (8.54%) and should be preferred for ETo prediction. MOD16 product is recommended to be used to predict monthly ETo, which opens possibilities for its use in several other studies.

Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = -0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d-¹ for 12 fields analyzed and NSE values 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and -0.0013, respectively. SAFER performed well for ET estimation after calibration, with r² and NSE values equal to 0.91 and RMSD = 0.469 mm d-¹. SAFER also showed good performance (r² = 0.86) after validation, with the lowest RMSD (0.58 mm d-¹) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.

Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = -0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d-¹ for 12 fields analyzed and NSE values 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and -0.0013, respectively. SAFER performed well for ET estimation after calibration, with r² and NSE values equal to 0.91 and RMSD = 0.469 mm d-¹. SAFER also showed good performance (r² = 0.86) after validation, with the lowest RMSD (0.58 mm d-¹) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.(AU)

Spatio-temporal variability of biophysical parameters of irrigated maize using orbital remote sensing / Variabilidade espaço-temporal de parâmetros biofisícos do milho irrigado utilizando sensoriamento remoto orbital

This study proposes to estimate the actual crop evapotranspiration, using the SAFER model, as well as calculate the crop coefficient (Kc) as a function of the normalized difference vegetation index (NDVI) and determine the biomass of an irrigated maize crop using images from the Operational Land Imager (OLI) and Thermal Infrared (TIRS) sensors of the Landsat-8 satellite. Pivots 21 to 26 of a commercial farm located in the municipalities of Bom Jesus da Lapa and Serra do Ramalho, west of Bahia State, Brazil, were selected. Sowing dates for each pivot were arranged as North and South or East and West, with cultivation starting firstly in one of the orientations and subsequently in the other. The relationship between NDVI and the Kc values obtained in the FAO-56 report (KcFAO) revealed a high coefficient of determination (R2 = 0.7921), showing that the variance of KcFAO can be explained by NDVI in the maize crop. Considering the center pivots with different planting dates, the crop evapotranspiration (ETc ) pixel values ranged from 0.0 to 6.0 mm d-1 during the phenological cycle. The highest values were found at 199 days of the year (DOY), corresponding to around 100 days after sowing (DAS). The lowest BIO values occur at 135 DOY, at around 20 DAS. There is a relationship between ETc and BIO, where the DOY with the highest BIO are equivalent to the days with the highest ETc values. In addition to this relationship, BIO is strongly influenced by soil water availability.(AU)

Objetivou-se com o presente estudo estimar a evapotranspiração real da cultura por meio do modelo SAFER, calcular o Kc em função do NDVI e a biomassa da cultura do milho irrigado, utilizando para isso imagens dos sensores Operacional Land Imager (OLI) e Thermal Infrared Sensor (TIRS) do satélite Landsat-8. Foram selecionados os pivôs 21 ao 26 de uma fazenda comercial localizada nos municípios de Bom Jesus da Lapa e Serra do Ramalho, situadas no oeste do estado da Bahia, Brasil. As épocas de semeadura dentro dos pivôs são ordenadas em Norte e Sul ou Leste e Oeste, iniciando o cultivo primeiro em uma das orientações e posteriormente na outra. Verifica-se com base na relação entre NDVI e KcFAO, um alto valor do coeficiente de determinação (R2=0,7921), evidenciando que a variância do KcFAO pode ser explicada pelo NDVI na cultura do milho. Considerando-se os pivôs centrais com diferentes datas de plantio, os valores dos pixels da ETc variaram de 0,0 a 6,0 mm d-1 durante o ciclo fenológico. Os maiores valores foram encontrados para o DOY 199, correspondendo ao DAS em torno de 100 dias. Os valores mais baixos da BIO ocorrem aos 135 DOY em torno de 20 DAS. É observado que existe uma relação entre a ETc e BIO, os DOY mais elevados da BIO são equivalentes com os maiores valores de ETc . Além desta relação, a BIO é fortemente influenciada pela disponibilidade hídrica no solo.(AU)

Impact of drought associated with high temperatures on Coffea canephora plantations: a case study in Espírito Santo State, Brazil.

Droughts are major natural disasters that affect many parts of the world all years and recently affected one of the major conilon coffee-producing regions of the world in state of Espírito Santo, which caused a huge crisis in the sector. Therefore, the objective of this study was to conduct an analysis with technical-scientific basis of the real impact of drought associated with high temperatures and irradiances on the conilon coffee (Coffea canephora Pierre ex Froehner) plantations located in the north, northwest, and northeast regions of the state of Espírito Santo, Brazil. Data from 2010 to 2016 of rainfall, air temperature, production, yield, planted area and surface remote sensing were obtained from different sources, statistically analyzed, and correlated. The 2015/2016 season was the most affected by the drought and high temperatures (mean annual above 26 °C) because, in addition to the adverse weather conditions, coffee plants were already damaged by the climatic conditions of the previous season. The increase in air temperature has higher impact (negative) on production than the decrease in annual precipitation. The average annual air temperatures in the two harvest seasons that stood out for the lowest yields (i.e. 2012/2013 and 2015/2016) were approximately 1 °C higher than in the previous seasons. In addition, in the 2015/2016 season, the average annual air temperature was the highest in the entire series. The spatial and temporal distribution of Enhanced Vegetation Index values enabled the detection and perception of droughts in the conilon coffee-producing regions of Espírito Santo. The rainfall volume accumulated in the periods from September to December and from April to August are the ones that most affect coffee yield. The conilon coffee plantations in these regions are susceptible to new climate extremes, as they continue to be managed under irrigation and full sun. The adoption of agroforestry systems and construction of small reservoirs can be useful to alleviate these climate effects, reducing the risk of coffee production losses and contributing to the sustainability of crops in Espírito Santo.

Mapping within­field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application.

Accurate information about the spatiotemporal variability of actual crop evapotranspiration (ETa), crop coefficient (Kc) and water productivity (WP) is crucial for water efficient management in the agriculture. The Earth Engine Evapotranspiration Flux (EEFlux) application has become a popular approach for providing spatiotemporal information on ETa and Kc worldwide. The aim of this study was to quantify the variability of water consumption (ETa) and the Kc for an irrigated commercial planting of soybeans based on the EEFlux application in the western region of the state of Bahia, Brazil. The water productivity (WP) for the fields was also obtained. Six cloud-free images from Landsat 7 and 8 satellites, acquired during the 2016/17 soybean growing season were used and processed on the EEFlux platform. The ETa from EEFlux was compared to that of the modified FAO (MFAO) approach using the following statistical metrics: Willmot's index of agreement (d-index), root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The Kc from EEFlux was compared to the Kc used in the soybean field (Kc FAO-based) and to the Kc values obtained in different scientific studies using the d-index. A similar procedure was performed for WP. Our results reveal that EEFlux is able to provide accurate information about the variability of ETa and the Kc of soybean fields. The comparison between ETa EEFlux and ETa MFAO showed good agreement based on the d-index, with values of 0.85, 0.83 and 0.89 for central pivots 1, 2 and 3, respectively. However, EEFlux tends to slightly underestimate ETa. The Kc EEFlux showed good accordance with the Kc values considered in this study, except in phase II, where a larger difference was observed; the average WP of the three fields (1.14 kg m-3) was higher than that in the majority of the previous studies, which is a strong indicator of the efficient use of water in the studied soybean fields. The study showed that EEFlux, an innovative and free tool for access spatiotemporal variability of ETa and Kc at global scale is very efficient to estimate the ETa and Kc on different growth stages of soybean crop.

Remote sensing as a tool to determine biophysical parameters of irrigated seed corn crop / Sensoriamento remoto como ferramenta para determinação de parâmetros biofísicos da cultura do milho semente irrigado

In recent years, many studies have been conducted combining orbital remote sensing data and crop growth models for vegetation monitoring, evapotranspiration estimation and quantification of biophysical parameters, e.g., NDVI, surface temperature, albedo, and biomass. The aim of the present study was to estimate evapotranspiration (ETr), biomass (BIO), and water productivity (WP) for irrigated seed corn crop using the SAFER algorithm and Landsat 8 satellite images. For this, eight cloud-free images were acquired at different phenological stages over the interest area on the United States Geological Survey website and meteorological data. ETr was estimated by the SAFER algorithm, BIO by the Monteith model, and WP by the BIO/ETr ratio. ETr values ranged from 0 to 6 mm d-1, with the highest values coinciding with the period of high vegetative crop vigor, while the lowest values were found at the sowing season. The highest biomass values were observed from images at 46 and 62 days after sowing (DAS), corresponding to 286 and 289 kg ha-1 d-1, respectively. The highest mean of water productivity was observed at 62 DAS, with 6.9 kg m-3 of water, corresponding to the period of maximum vegetative crop vigor. The application of the SAFER model together with Landsat 8 satellite images was an alternative to identifying the spatial and temporal variation of biophysical parameters of the corn crop. It could assist in the management of water in irrigated agriculture and decision making in large-sized farms.(AU)

Nos últimos anos, tem sido realizado muitos estudos que associam dados de sensoriamento remoto orbital e modelos de crescimento de cultura para fins de monitoramento da vegetação, estimativa de evapotranspiração e quantificação de parâmetros biofísicos, por exemplo o NDVI, temperatura da superfície, albedo, biomassa. O objetivo do presente estudo foi estimar a evapotranspiração (ETr), a biomassa (BIO) e a produtividade de água (PA) para a cultura do milho semente irrigado utilizando-se o algoritmo SAFER e imagens do satélite Landsat 8. Para tal, foram adquiridas oito imagens, em diferentes fases fenológica, livre de nuvem sobre a área de interesse no site United States Geological Survey e dados meteorológicos. A ETr foi estimada por meio do algoritmo SAFER, a BIO pelo modelo de Monteith e a PA pela razão BIO/ETr. A ETr apresentou valores variando entre 0 e 6 mm d-1, sendo os maiores valores coincidentes com o período de maior vigor vegetativo da cultura e os menores com a época de semeadura. Os maiores valores de biomassa são notados nas imagens aos 46 e 62 dias após a semeadura (DAS), correspondendo a 286 e 289 kg ha-1 d-1, respectivamente. A maior média da produtividade da água é observado aos 62 DAS, com 6,9 kg m-3 de água, correspondente ao período de máximo vigor vegetativo da cultura. A aplicação do modelo SAFER juntamente com imagens do Satélite Landsat 8 mostrou-se uma alternativa na identificação da variação espacial e temporal dos parâmetros biofísicos da cultura do milho, podendo auxiliar no manejo da água na agricultura irrigada e na tomada de decisão em propriedades agrícolas de grande porte.(AU)

Irrigation frequency and vermiculite proportion in substrate for Eucalyptus grandis seedling / Frequências de irrigação e proporção de vermiculita em mudas de Eucalyptus grandis

This study aimed to determine the best irrigation frequency and vermiculite proportion in substrate for Eucalyptus grandis seedling production in poorly technified nurseries. The experiment was carried out in Chapadão do Sul - MS (Brazil) from April 8 to July 23, 2013 (106 days). The experimental design was in randomized blocks arranged in a split-plots, with four irrigation frequencies (plots) and five vermiculite proportions (subplots) and six replications. Irrigation depth was estimated by the reference evapotranspiration (Penman-Monteith) multiplied by a crop coefficient (Kc) of 2. Average daily irrigation depth was 5.5 mm during the experimental period. The results showed that two daily irrigations (at 11:00 a.m. and 7:00 p.m.) and filling tubes with 80% vermiculite and 20% soil were most suitable for eucalyptus seedling production under these experimental conditions.(AU)

Objetivou-se determinar as melhores frequências de irrigação e proporção de vermiculita em substrato para produção de mudas de Eucalyptus grandis em viveiros menos tecnificados. O experimento foi realizado entre 08/04/2013 e 23/07/2013 (106 dias) e conduzido em Chapadão do Sul-MS, Brasil. O delineamento experimental foi em blocos casualizados, em parcelas subdivididas, tendo nas parcelas quatro frequências de irrigação e nas subparcelas cinco proporções de vermiculita, com seis repetições. A lâmina de irrigação foi estimada pela evapotranspiração de referência (Penman-Monteith) multiplicada pelo coeficiente de cultivo (Kc) = 2. A lâmina média diária de irrigação no período experimental foi de 5,5 mm. Constatou-se que o manejo com duas irrigações diárias (11:00h e 19:00h) e preenchimento de tubetes com 80% de vermiculita e 20% de solo de barranco é mais indicado para a produção de mudas de eucalipto nessas condições.(AU)

Mapping of corn phenological stages using NDVI from OLI and MODIS sensors / Mapeamento dos estádios fenológicos da cultura do milho utilizando o NDVI derivado dos sensores OLI e MODIS

Crop phenology knowledge is relevant to a series of actions related to its management and can be accessed through vegetation indexes. Thus, this study aimed to evaluate the use of the Normalized Difference Vegetation Index (NDVI), from images of OLI and MODIS sensors, to obtain phenological information from corn crops. To this end, we evaluated two corn cropping areas, irrigated by a central pivot, and located western Bahia state, Brazil. These areas were managed with high technology and had no record of biotic and abiotic stresses. NDVI showed a well-defined temporal pattern throughout the corn cycle, with a rapid increase at the beginning, stabilization at intermediate stages, and decreases at the end of the cycle. Excellent fits for polynomial equations were obtained to estimate NDVI as a function of days after sowing (DAS), with R² values of 0.96 and 0.95 for images of OLI and MODIS sensors, respectively. This demonstrates that both sensors could characterize corn canopy changes over time. NDVI ranges were correlated with the main phenological stages (PE), using the direct relationship between both variables (NDVI and PE) with days after sowing (DAS). For the beginning and end of each phenological stage, NDVI ranges were validated through model identity testing. NDVI proved to be a suitable parameter to assess corn phenology accurately and remotely. Finally, NDVI was also an important tool for detecting biotic and abiotic stresses throughout the crop cycle, and hence for decision making based on corn phenology.(AU)

O conhecimento da fenologia das culturas é relevante para uma série de ações relacionadas ao seu manejo e pode ser acessada por meio de índices de vegetação. Portanto, objetivou-se com este trabalho avaliar o potencial do uso do Índice de Vegetação por Diferença Normalizada (NDVI), calculado a partir de imagens dos sensores OLI e MODIS para obter informações fenológicas da cultura do milho. Para tanto, foram utilizadas duas áreas de cultivo de milho irrigadas por sistema de pivô central na região oeste do estado da Bahia, Brasil. Estas áreas foram manejadas com alta tecnologia e sem registro de ocorrência de estresses bióticos e abióticos. O NDVI apresentou um padrão temporal bem definido ao longo do ciclo de desenvolvimento, com rápido incremento no início do desenvolvimento, estabilização nos estádios intermediários, e decréscimos na parte final do ciclo. Excelentes ajustes para as equações polinomiais foram obtidos para estimar o NDVI em função dos dias após a semeadura (DAS), com R² de 0,96 e 0,95 para as imagens do sensor OLI e MODIS, respectivamente, demonstrando que os sensores são capazes de caracterizar temporalmente as modificações do dossel da cultura do milho ao longo do ciclo. Intervalos de valores de NDVI foram correlacionados com os principais estádios fenológicos (EF) da cultura do milho, utilizando a relação direta de ambas as variáveis (NDVI e EF) com os dias após a semeadura (DAS). Os intervalos de valores de NDVI para o início e final de cada estádio fenológico foram validados através do teste de identidade do modelo, tornando o NDVI uma variável adequada para ser utilizada no acesso a fenologia do milho com precisão de maneira remota. Por fim, esses valores também são uma importante ferramenta para detecção de problemas bióticos e abióticos ao longo do ciclo de cultivo e para tomadas de decisão baseadas na fenologia da cultura.(AU)

Alternative low-cost precipitation kit for assessing irrigation systems / Kit de precipitação alternativo de baixo custo para avaliação de sistemas de irrigação

Irrigation systems must be assessed periodically to verify equipment quality and the need for adjustments. For this, precipitation test kits are necessary. However, commercially available kits have as their main disadvantage the high cost. Therefore, this study aimed to develop an alternative low-cost precipitation kit and verify its efficiency compared to an available commercial brand. The validation test was carried out at the Laboratory of Hydraulics of the Federal University of Viçosa (UFV) using a conventional sprinkler system organized in a quadrangular arrangement. Water collections were carried out within two hours using a grid of plastic collectors spaced at 3 × 3 m and installed at 0.7 m above the ground. The coefficient of determination (R2 ), uniformity coefficients, application efficiency, and thematic maps of the spatial variability of the applied irrigation depth were compared between kits and used for the validation of measurements. The results showed a high agreement between the developed (GESAI) and a commercial kit (Trademark) (R2 = 0.9849), and a high spatial agreement between the collected water depths. Therefore, the GESAI kit is a low-cost alternative for the assessment of irrigation systems.(AU)

Os sistemas de irrigação devem ser avaliados periodicamente para a verificação da qualidade do equipamento e a necessidade de ajustes. Para isso, kits de ensaios de precipitação são necessários, entretanto, os kits comercialmente disponíveis apresentam como principal desvantagem o elevado custo. Assim, o presente trabalho teve como objetivo elaborar um kit de precipitação alternativo de baixo custo e averiguar a sua eficiência frente a marca comercial disponível. O ensaio de validação foi realizado no Laboratório de Hidráulica da Universidade Federal de Viçosa (UFV), utilizando um sistema de aspersão convencional, disposto em um arranjo quadrangular. As coletas de água foram realizadas no período de duas horas, com auxílio de uma malha de coletores plásticos espaçados em 3 x 3 m e instalados a 0,7 m acima do solo. Para comparação e validação das medições foram utilizados o coeficiente de determinação (R²), coeficientes de uniformidade, eficiência de aplicação e mapas temáticos da variabilidade espacial da lâmina aplicada entre os kits. Os resultados mostraram que houve elevada concordância entre o kit desenvolvido (GESAI) e o kit comercial (Trademark) (R² = 0,9849) e uma concordância espacial elevada entre as lâminas coletadas. Portanto, recomenda-se o uso do kit GESAI como uma alternativa de baixo custo para a avaliação de sistemas de irrigação.(AU)

Remote sensing as a tool to determine biophysical parameters of irrigated seed corn crop / Sensoriamento remoto como ferramenta para determinação de parâmetros biofísicos da cultura do milho semente irrigado

In recent years, many studies have been conducted combining orbital remote sensing data and crop growth models for vegetation monitoring, evapotranspiration estimation and quantification of biophysical parameters, e.g., NDVI, surface temperature, albedo, and biomass. The aim of the present study was to estimate evapotranspiration (ETr), biomass (BIO), and water productivity (WP) for irrigated seed corn crop using the SAFER algorithm and Landsat 8 satellite images. For this, eight cloud-free images were acquired at different phenological stages over the interest area on the United States Geological Survey website and meteorological data. ETr was estimated by the SAFER algorithm, BIO by the Monteith model, and WP by the BIO/ETr ratio. ETr values ranged from 0 to 6 mm d-1, with the highest values coinciding with the period of high vegetative crop vigor, while the lowest values were found at the sowing season. The highest biomass values were observed from images at 46 and 62 days after sowing (DAS), corresponding to 286 and 289 kg ha-1 d-1, respectively. The highest mean of water productivity was observed at 62 DAS, with 6.9 kg m-3 of water, corresponding to the period of maximum vegetative crop vigor. The application of the SAFER model together with Landsat 8 satellite images was an alternative to identifying the spatial and temporal variation of biophysical parameters of the corn crop. It could assist in the management of water in irrigated agriculture and decision making in large-sized farms.

Nos últimos anos, tem sido realizado muitos estudos que associam dados de sensoriamento remoto orbital e modelos de crescimento de cultura para fins de monitoramento da vegetação, estimativa de evapotranspiração e quantificação de parâmetros biofísicos, por exemplo o NDVI, temperatura da superfície, albedo, biomassa. O objetivo do presente estudo foi estimar a evapotranspiração (ETr), a biomassa (BIO) e a produtividade de água (PA) para a cultura do milho semente irrigado utilizando-se o algoritmo SAFER e imagens do satélite Landsat 8. Para tal, foram adquiridas oito imagens, em diferentes fases fenológica, livre de nuvem sobre a área de interesse no site United States Geological Survey e dados meteorológicos. A ETr foi estimada por meio do algoritmo SAFER, a BIO pelo modelo de Monteith e a PA pela razão BIO/ETr. A ETr apresentou valores variando entre 0 e 6 mm d-1, sendo os maiores valores coincidentes com o período de maior vigor vegetativo da cultura e os menores com a época de semeadura. Os maiores valores de biomassa são notados nas imagens aos 46 e 62 dias após a semeadura (DAS), correspondendo a 286 e 289 kg ha-1 d-1, respectivamente. A maior média da produtividade da água é observado aos 62 DAS, com 6,9 kg m-3 de água, correspondente ao período de máximo vigor vegetativo da cultura. A aplicação do modelo SAFER juntamente com imagens do Satélite Landsat 8 mostrou-se uma alternativa na identificação da variação espacial e temporal dos parâmetros biofísicos da cultura do milho, podendo auxiliar no manejo da água na agricultura irrigada e na tomada de decisão em propriedades agrícolas de grande porte.

Evapotranspiration for irrigated agriculture using orbital satellites / Evapotranspiração para áreas irrigadas utilizando satélites orbitais

Acknowledging the importance of evapotranspiration as a mediating factor for efficient irrigation management and water balance, the objective of study is to compare the Simple Algorithm forEvapotranspiration Retrieving (SAFER) to the standard method proposed by FAO-56 for real evapotranspiration, as well as prove its value as an implement in irrigation management for the Brazilian Savanna. Data used refers to 2015's harvest of seven center pivots, located in the municipality of São Desidério in western Bahia. For the SAFER algorithm, the images used were acquired by the Landsat-8 satellite during the entire maize crop cycle. The SAFER algorithm estimation demonstrates the spatial and temporal distribution of the evapotranspiration. A maximum evapotranspiration of 5.38 mm d-1 was observed during the crop's reproductive stage. In relation to the standard method, SAFER showed a mean absolute error of 0.40 mm. Thus, concluding that the algorithm can be used to estimate the actual evapotranspiration crop as an alternative to the standard method proposed by FAO-56 for water resources management.

Reconhecendo a importância da evapotranspiração como fator mediador para uma gestão de irrigação eficiente e o balanço hídrico, o objetivo desse estudo foi comparar o Simple Algorithm for Evapotranspiration Retrieving (SAFER) ao método padrão proposto no FAO-56 para estimativa de evapotranspiração real, bem como apontar sua utilidade como ferramenta de gestão de irrigação para o Cerrado brasileiro. Utilizaram-se dados referentes à safra de 2015 de sete pivôs centrais localizados no município de São Desidério, no oeste da Bahia. Para utilizar algoritmo SAFER, adotaram-se imagens adquiridas pelo satélite Landsat-8 durante o ciclo da cultura do milho. As estimativas pelo algoritmo SAFER demonstraram a variabilidade espaço-temporal da evapotranspiração. A evapotranspiração máxima de 5,38 mm d-1 foi observada durante o estágio reprodutivo da cultura. Em relação ao método padrão, o SAFER apresentou erro médio absoluto de 0,40 mm. Dessa forma, conclui-se que o algoritmo pode ser adotado para se estimar evapotranspiração atual da cultura como alternativa ao método padrão proposto no FAO-56 na gestão de recursos hídricos.

Productivity and water demand of maize estimated by the modified satellite Priestley-Taylor algorithm / Produtividade e demanda hídrica do milho estimado pelo algoritmo de Priestley-Taylor modificado para satélite

The water demand of crops, as well as the relation of this variable to productivity and other important factors related to the sustainable management of agriculture, makes it relevant to estimate parameters that help in the most assertive and efficient decision-making in the agricultural environment. In this context, the work aims to estimate the actual evapotranspiration (ETa), biomass (Bio), water productivity (WP) and crop productivity (P), using the Landsat-8 satellite, through the Modified Satellite Priestley-Taylor Algorithm (MS-PT). For this, ETa was estimated for maize culture irrigated by central pivots, using the MS-PT with six images of Landsat-8, which were free of clouds. The ETa estimate was accurate in the first 60 days after emergence (DAE) of the crop. Subsequently, the variables Bio, P, and WP were estimated using the ETa and the assumptions of the Monteith (1972) model. Therefore, we sequentially calculated the dry biomass, crop productivity and water productivity. ETa presented a high correlation with Bio from the second image (06/10/2015), due to the canopy closure of the crop and, consequently, the predominance of transpiration in the evapotranspiration phenomenon. The water productivity was constant throughout the maximum vegetative stage until the reproductive phase R4 of the crop, verifying in this interval the best efficiency in the conversion of water in biomass. From the obtained results, it is verified that the set of algorithms used in the estimation of the parameters demonstrated the potential to increase the capacity to handle agriculture in a more efficient, assertive and sustainable way.(AU)

A demanda hídrica das culturas, assim como a relação dessa com variáveis de produtividade e outros importantes fatores relacionados ao manejo da agricultura sustentável, faz com seja relevante a estimação de parâmetros que auxiliam de modo assertivo e eficiente a tomada de decisão no ambiente agrícola. Nesse contexto, o objetivo desse trabalho foi estimar a evapotranspiração real (ETa), biomassa (Bio), produtividade da água (WP) e a produtividade da cultura (P), utilizando imagens do satélite Landsat-8, por meio do algoritmo Priestley-Taylor modificado para satélite (MS-PT). Para isso, estimou-se a ETa para a cultura do milho irrigado por pivôs central, utilizando o MS-PT com seis imagens do Landsat-8, as quais encontravam-se livre de nuvens. A estimativa da ETa foi acurada nos primeiros 60 dias após a emergência (DAE) da cultura. Posteriormente, as variáveis Bio, P, e WP foram estimadas utilizando a ETa e os pressupostos do modelo de Monteith (1972). A ETa apresentou alta correlação com a Bio a partir da segunda imagem (10/06/2015), em função do fechamento dossel da cultura e consequentemente a predominância da transpiração no fenômeno de evapotranspiração. A WP foi constante durante o máximo crescimento vegetativo até a fase reprodutiva da cultura denominada R4, sendo verificado nessa amplitude de tempo a melhor eficiência da conversão de água em biomassa. A partir dos resultados obtidos, verifica-se que esse conjunto de algoritmos utilizados para estimativa dos parâmetros relacionados a produtividade do milho mostraram o potencial de crescimento que se tem para melhorar a capacidade de como lidar com uma agricultura mais eficiente, assertiva e sustentável.(AU)

Productivity and water demand of maize estimated by the modified satellite Priestley-Taylor algorithm / Produtividade e demanda hídrica do milho estimado pelo algoritmo de Priestley-Taylor modificado para satélite

The water demand of crops, as well as the relation of this variable to productivity and other important factors related to the sustainable management of agriculture, makes it relevant to estimate parameters that help in the most assertive and efficient decision-making in the agricultural environment. In this context, the work aims to estimate the actual evapotranspiration (ETa), biomass (Bio), water productivity (WP) and crop productivity (P), using the Landsat-8 satellite, through the Modified Satellite Priestley-Taylor Algorithm (MS-PT). For this, ETa was estimated for maize culture irrigated by central pivots, using the MS-PT with six images of Landsat-8, which were free of clouds. The ETa estimate was accurate in the first 60 days after emergence (DAE) of the crop. Subsequently, the variables Bio, P, and WP were estimated using the ETa and the assumptions of the Monteith (1972) model. Therefore, we sequentially calculated the dry biomass, crop productivity and water productivity. ETa presented a high correlation with Bio from the second image (06/10/2015), due to the canopy closure of the crop and, consequently, the predominance of transpiration in the evapotranspiration phenomenon. The water productivity was constant throughout the maximum vegetative stage until the reproductive phase R4 of the crop, verifying in this interval the best efficiency in the conversion of water in biomass. From the obtained results, it is verified that the set of algorithms used in the estimation of the parameters demonstrated the potential to increase the capacity to handle agriculture in a more efficient, assertive and sustainable way.

A demanda hídrica das culturas, assim como a relação dessa com variáveis de produtividade e outros importantes fatores relacionados ao manejo da agricultura sustentável, faz com seja relevante a estimação de parâmetros que auxiliam de modo assertivo e eficiente a tomada de decisão no ambiente agrícola. Nesse contexto, o objetivo desse trabalho foi estimar a evapotranspiração real (ETa), biomassa (Bio), produtividade da água (WP) e a produtividade da cultura (P), utilizando imagens do satélite Landsat-8, por meio do algoritmo Priestley-Taylor modificado para satélite (MS-PT). Para isso, estimou-se a ETa para a cultura do milho irrigado por pivôs central, utilizando o MS-PT com seis imagens do Landsat-8, as quais encontravam-se livre de nuvens. A estimativa da ETa foi acurada nos primeiros 60 dias após a emergência (DAE) da cultura. Posteriormente, as variáveis Bio, P, e WP foram estimadas utilizando a ETa e os pressupostos do modelo de Monteith (1972). A ETa apresentou alta correlação com a Bio a partir da segunda imagem (10/06/2015), em função do fechamento dossel da cultura e consequentemente a predominância da transpiração no fenômeno de evapotranspiração. A WP foi constante durante o máximo crescimento vegetativo até a fase reprodutiva da cultura denominada R4, sendo verificado nessa amplitude de tempo a melhor eficiência da conversão de água em biomassa. A partir dos resultados obtidos, verifica-se que esse conjunto de algoritmos utilizados para estimativa dos parâmetros relacionados a produtividade do milho mostraram o potencial de crescimento que se tem para melhorar a capacidade de como lidar com uma agricultura mais eficiente, assertiva e sustentável.