Determining large scale actual evapotranspiration using agro-meteorological and remote sensing data in the northwest of Sao Paulo State, Brazil

The best irrigation management depends on accurate estimation of reference evapotranspiration (ET0) and then selection of the appropriate crop coefficient for each phenological stage. However, the evaluation of water productivity on a large scale can be done by using actual evapotranspiration (ETa), determined by coupling agrometeorological and remote sensing data. This paper describes methodologies used for estimating ETa for 20 centerpivots using three different approaches: the traditional FAO crop coefficient (K-c) method and two remote sensing algorithms, one called SEBAL and other named TEIXEIRA. The methods were applied to one Landsat 5 Thematic Mapper image acquired in July 2010 over the Northwest portion of the Sao Paulo State, Brazil. The corn, bean and sugar cane crops are grown under center pivot sprinkler irrigation. ET0 was calculated by the Penman-Monteith method with data from one automated weather station close to the study site. The results showed that for the crops at effective full cover, SEBAL and TEIXEIRA's methods agreed well comparing with the traditional method. However, both remote sensing methods overestimated ETa according to the degree of exposed soil, with the TEIXEIRA method presenting closer ETa values with those resulted from the traditional FAO K-c method. This study showed that remote sensing algorithms can be useful tools for monitoring and establishing realistic K-c values to further determine ETa on a large scale. However, several images during the growing seasons must be used to establish the necessary adjustments to the traditional FAO crop coefficient method.

Determination of total accumulated rainfall, global radiation, evapotranspiration and degree-days originated from the ECMWF model to sugar cane crop

The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

Modelos agrometeorológicos estatísticos de previsão de produtividade e qualidade para cana-de-açúcar

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Adjust of regression models to estimate the rectal temperature of broilers for the first 14 days of life

The broiler rectal temperature (t rectal) is one of the most important physiological responses to classify the animal thermal comfort. Therefore, the aim of this study was to adjust regression models in order to predict the rectal temperature (t rectal) of broiler chickens under different thermal conditions based on age (A) and a meteorological variable (air temperature - t air) or a thermal comfort index (temperature and humidity index -THI or black globe humidity index - BGHI) or a physical quantity enthalpy (H). In addition, through the inversion of these models and the expected t rectal intervals for each age, the comfort limits of t air, THI, BGHI and H for the chicks in the heating phase were determined, aiding in the validation of the equations and the preliminary limits for H. The experimental data used to adjust the mathematical models were collected in two commercial poultry farms, with Cobb chicks, from 1 to 14 days of age. It was possible to predict the t rectal of conditions from the expected t rectal and determine the lower and superior comfort thresholds of broilers satisfactorily by applying the four models adjusted; as well as to invert the models for prediction of the environmental H for the chicks first 14 days of life.

Análise de fauna e flutuação populacional de Carabidae e Staphylinidae (Coleoptera) em sistemas de plantio direto e convencional

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application of landsat images for quantifying the energy balance under conditions of land use changes in the semi-arid region of Brazil

In the Nilo Coelho irrigation scheme, Brazil, the natural vegetation has been replaced by irrigated agriculture, bringing importance for the quantification of the effects on the energy exchanges between the mixed vegetated surfaces and the lower atmosphere. Landsat satellite images and agro-meteorological stations from 1992 to 2011 were used together, for modelling these exchanges. Surface albedo (α0), NDVI and surface temperature (T0) were the basic remote sensing retrieving parameters necessary to calculate the latent heat flux (λE) and the surface resistance to evapotranspiration (rs) on a large scale. The daily net radiation (Rn) was obtained from α0, air temperature (Ta) and short-wave transmissivity (τsw) throughout the slob equation, allowing the quantification of the daily sensible heat flux (H) by residual in the energy balance equation. With a threshold value for rs, it was possible to separate the energy fluxes from crops and natural vegetation. The averaged fractions of Rn partitioned as H and λE, were in average 39 and 67%, respectively. It was observed an increase of the energy used for the evapotranspiration process inside irrigated areas from 51% in 1992 to 80% in 2011, with the ratio λE/Rn presenting an increase of 3 % per year. The tools and models applied in the current research, can subsidize the monitoring of the coupled climate and land use changes effects in irrigation perimeters, being valuable when aiming the sustainability of the irrigated agriculture in the future, avoiding conflicts among different water users. © 2012 SPIE.

Water productivity assessment by using MODIS images and agrometeorological data in the Petrolina municipality, Brazil

The municipality of Petrolina, located in the semi-arid region of Brazil, is highlighted as an important agricultural growing region, however the irrigated areas have cleared natural vegetation inducing a loss of biodiversity. To analyze the contrast between these two ecosystems the large scale values of biomass production (BIO), evapotranspiration (ET) and water productivity (WP) were quantified. Monteithś equation was applied for estimating the absorbed photosynthetically active radiation (APAR), while the new SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The water productivity (WP) was analysed by the ratio of BIO by ET at monthly time scale with four bands of MODIS satellite images together with agrometeorological data for the year of 2011. The period with the highest water productivity values were from March to April in the rainy period for both irrigated and not irrigated conditions. However the largest ET rates were in November for irrigated crops and April for natural vegetation. More uniformity of the vegetation and water variables occurs in natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops, due to the different crop stages, cultural and irrigation managements. The models applied with MODIS satellite images on a large scale are considered to be suitable for water productivity assessments and for quantifying the effects of increasing irrigated areas over natural vegetation on regional water consumption in situations of quick changing land use pattern. © 2012 SPIE.

Avaliação de sistema silvipastoril através do desempenho produtivo de búfalos manejados nas condições climáticas de Belém, Pará

Foi conduzido um trabalho para estudar as relações entre variáveis produtivas, fisiológicas e de conforto animal de búfalos e fatores do ambiente físico, em sistema silvipastoril, envolvendo mogno africano (Kaya ivorensis) e nim indiano (Azadirachta indica) e pastejo rotacionado intensivo de Cynodon nlemfuensis, no período de maio de 2003 a novembro de 2004, na Unidade de Pesquisa Animal “Senador Álvaro Adolpho”, Embrapa Amazônia Oriental, Belém, Pará, no tipo climático Afi, com época mais chuvosa de dezembro a maio e menos chuvosa, de junho a novembro. A área de pastagem experimental, de 5,4 ha, está dividida em seis piquetes, com permanência animal de cinco dias e 25 dias de descanso. Foram utilizados 26 bubalinos Murrah, inteiros, com idade entre 231 e 303 dias. Efetuou-se análise descritiva dos dados experimentais, para obtenção de médias, desvio padrão, valores mínimos e máximos, correlações e variâncias, considerando-se ganho de peso, disponibilidade e composição química da forrageira, variáveis fisiológicas dos animais, variáveis climáticas, desenvolvimento das essências florestais, Índices de Conforto (IC) e de Temperatura – Umidade (ITU). Observou-se excelente desempenho ponderal dos animais experimentais, com ganhos médios de 0,911 kg/dia e peso vivo final de 510 kg. Nos períodos mais e menos chuvosos, a disponibilidade, os níveis de proteína bruta do caule, folha e planta inteira e a digestibilidade “in vitro” da matéria seca e da orgânica da forrageira foram satisfatórios, atendendo as necessidades mínimas para manutenção e destacado desempenho produtivo. Houve interferências das variáveis meteorológicas nos batimentos cardíacos, freqüência respiratória, temperatura retal e movimento ruminal dos animais. O IC ultrapassou o nível crítico, principalmente no período menos chuvoso, bem como os níveis de ITU foram elevados, suplantando o considerado de emergência, indicando a necessidade de práticas de manipulação do ambiente físico para elevar o desempenho animal. O desenvolvimento das essências florestais já fornece melhor ambiência aos animais, em função do sombreamento, o que contribui para a redução do estresse térmico e promove melhor performance produtiva dos búfalos.

Large-Scale Water Productivity Assessments with MODIS Images in a Changing Semi-Arid Environment: A Brazilian Case Study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

ERA-interim reanalysis debiased at FLUXNET sites

(preliminary) Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10% to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27% to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the Wind Speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.

Anemômetro ultrassônico baseado em sensor de distância

In this work we propose the development of an ultrasonic anemometer using distance sensors. The wind is an important tool for studying the dynamics of the atmosphere, changes in climate and agricultural crops meteorological variable. Thus it is necessary advances in studies that provide increasingly characterizing the behavior of the wind. Currently there are several types of anemometers to measure wind speed, among which stands out due to the ultrasonic anemometer accuracy in measurements. But this device has a high cost difficult to use. Therefore, we sought to lower the cost of the ultrasonic anemometer, developing an apparatus capable of measuring wind velocity using distance sensors. In this type of anemometer wind speed is measured based on the transit time of the ultrasonic pulse, in this same distance sensors to space technique measures. Here various assemblies seeking the best configuration which could use the distance sensor to measure wind speed were made. Arrangements bulkhead and separate transducers are examples of worked assemblies that will be detailed in chapter 3. With the measures collected (with and without wind) histograms, which show the distribution of records transit time of the sound wave for each case were generated. Two of the studied configurations show favorable results regarding the use of the distance sensor as the wind speed.

Setting up a network of agrometeorological stations in East Timor

A developed and sustainable agriculture requires a permanent and reliable monitoring of climatic/ meteorological elements in (agro) meteorological stations which should be located close to agricultural, silvicultural or pastoral activities. An adequate network of meteorological stations is then a necessary condition to support innovation and development in any country. Developing countries, mainly those with a history of frequent conflicts, presents deficient number of weather stations, often poorly composed and improperly distributed within their territories, and without a regular operation that allows continuity of records for a sufficiently long period of time. The objective of this work was to build a network of meteorological and agro-meteorological stations in East Timor. To achieve this goal, the number and location of pre-existing stations, their structure and composition (number and type of sensors, communication system,… ), the administrative division of the country and the available agro-ecological zoning, the agricultural and forestry practices in the country, the existing centres for the agricultural research and the history of the weathers records were taken into account. Several troubles were found (some of the automatic stations were assembled incorrectly, others stations duplicated information regarding the same agricultural area, vast areas with relevant agro-ecological representativeness were not monitored …). It was proposed the elimination of 11 existing stations, the relocation of 7 new stations in places not covered until then, the automation of 3 manual meteorological stations. Two networks were then purposed, a major with 15 agro-meteorological stations (all automatized) and one other secondary composed by 32 weather stations (only two were manual). The set of the 47 stations corresponded to a density of 329 km2/station. The flexibility in the composition of each of the networks was safeguarded and intends to respond effectively to any substantive change in the conditions in a country in constant change. It was also discussed the national coverage by these networks under a “management concept for weather stations”.

Panicum maximum cv. Tanzânia: climate trends and regional pasture production in Brazil.

Projected change in forage production under a range of climate scenarios is important for the evaluation of the impacts of global climate change on pasture-based livestock production systems in Brazil. We evaluated the effects of regional climate trends on Panicum maximum cv. Tanzânia production, predicted by agro-meteorological model considering the sum of degree days and corrected by a water availa bility index. Data from Brazilian weather stations (1963?2009) were considered as the current climate (baseline), and future scenarios, based on contrasting scenarios interms of increased temperature and atmospheric CO2 concentrations (high and low increases), were determined for 2013?2040 (2025 scenario) and for 2043?2070 (2055 scenario). Predicted baseline scenarios indicated that there are regional and seasonal variations in P. maximum production related to variation intemperature and water availability during the year. Production was lower in the Northeast region and higher in the rainforest area. Total annual productionunder future climate scenarios was predicted toincrease by up to 20% for most of the Brazilian area, mainly due to temperature increase, according to each climate model and scenario evaluated. The highest increase in forage production is expected to be in the South, Southeast and Central-west areas of Brazil. In these regions, future climate scenarios will not lead to changes in the seasonal production, with largerincreases in productivity during the summer. Climate risk is expected to decrease, as the probability of occurrence of low forage productions will be lower. Due to the predicted increase in temperature and decrease in rainfall in the Northeast area, P. maximum production is expected to decrease, mainly when considering scenarios based on the PRECIS model for the 2055 scenario.