Alan Massaru Nakai

Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones

Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.

Assessments and How an Increase in Temperature may Have an Impact on Agriculture in Brazil and Mapping of the Current and Future Situation

Tthe possible impacts of climate change in the vulnerability of agricultural production will be analysed considering a increase in temperature of 3 °C or more until the end of the century. In order to analyse agricultural production it is important to remember that the study of the effects of the increase in temperature, should also be done together with other factors like for instance, water availability and the increase of CO2concentration. The potential risks imposed by climate change to Brazilian agriculture justify investments in farming research, particularly in the genetic modification of crops. In addition, studies to quantify the nature of extreme events, for periods between 2050 and 2011 have to be conducted. Technological advances in the management of crops and the adoption of good farming practices may also minimise impacts expected. The importance of developing crops tolerant to higher temperatures and water deficit is emphasized. With temperature increasing over 4 °C, impacts suffered will be strong at magnitudes not yet known by science. The main conclusion is that in terms of food supply, temperature rises above 4 °C place Brazil in a very vulnerable situation, compromising its current role of the future’s main player in relation to providing food to the world.

Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults

Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times.

NatData: A Platform to Integrate Geospatial Data from Natural Resources of the Brazilian Biomes

There are numerous challenges for sustainable agriculture. One of them is to provide an inventory of natural resources, to allow their evaluation for a sustainable use in production systems for food, fiber, essences and energy. The generation and maintenance of this inventory requires efforts of strategic innovation management in order to reduce errors, inconsistencies and unpredictability, replacing them with precise diagnosis, monitoring, early exploration of problems, needs and requirements. Then, it should act as a guide for investment in organization of knowledge and generation of technology flows. This requires an easier access to organized and integrated data about natural resources of different biomes. however, this access is often hampered by a number of reasons, mainly due to their volume and heterogeneity. This paper describes the NatData platform, which is under development at the Brazilian Agricultural Research Corporation (Embrapa). It intends to overcome the challenges, aiming to integrate data from Brazilian natural resources, preserving their semantic and allowing different users to access the data.