Importância dos modelos de simulação de culturas diante os impactos das alterações climáticas sobre a produção agrícola - Revisão

O efeito climático é o principal responsável pelas oscilações no rendimento produtivo. Logo, é esperado que as mudanças do clima promovam alterações na agricultura, comprometam a sustentabilidade e a segurança alimentar, especialmente, em áreas semiáridas. O entendimento da amplitude desses fatores e suas consequências no rendimento agrícola mediante os diferentes cenários climáticos, regionais e tecnológicos são fundamentais nas tomadas de decisões. Para as análises desses diversos cenários, os modelos de simulação de culturas se caracterizam como ferramentas funcionais e com eficientes performances na estimativa dos níveis de produtividades, desde que devidamente calibrados e validados com dados consistentes e representativos. Dentre os modelos de simulação podemos destacar: AquaCrop - FAO, ZAE - FAO, CROPGRO e Apsim como aqueles de maiores aplicabilidades nas culturas agrícolas, sendo utilizados de maneira recorrente em diversos estudos para fins do conhecimento das lacunas de produtividade agrícola, ou “Yield Gap”. Esta revisão analisou os impactos das alterações climáticas na agricultura e o levantamento de informações dos principais modelos de simulação de culturas. Mediante síntese das informações levantadas, pode-se evidenciar o eminente impacto das alterações climáticas sobre o cenário agrícola futuro, proporcionando maior vulnerabilidade agrícola. Logo, destaca-se a importância do uso de modelos de simulação de culturas para conhecimento das lacunas de produtividade e potencial produtivo. Contudo, é evidente a necessidade de pesquisas mais detalhadas sobre a aplicabilidade dos modelos em cenários agrícolas diversos e situações climáticas amplas.Palavras-chave: modelos de simulação; sazonalidade climática; práticas resilientes; “yield gap”. Importance of crop simulation models in view of the impacts of climate change on agricultural production – Review A B S T R A C TThe climatic effect is the main responsible for the fluctuations in the productive yield. Therefore, it is expected that climate change will promote changes in agriculture, compromise sustainability and food security, especially in semi-arid areas. Understanding the breadth of these factors and their consequences on agricultural income through different climatic, regional and technological scenarios are fundamental in decision-making. For the analysis of these different scenarios, the crop simulation models are characterized as functional tools and with efficient performances in the estimation of the productivity levels, as long as they are properly calibrated and validated with consistent and representative data. Among the simulation models we can highlight: AquaCrop - FAO, ZAE - FAO, CROPGRO and Apsim as those with the greatest applicability in agricultural crops, being used in a recurring manner in several studies for the purpose of understanding agricultural productivity gaps, or “Yield Gap”. This review analyzed the impacts of climate change on agriculture and the gathering of information on the main crop simulation models. By synthesizing the information collected, it is possible to highlight the imminent impact of climate change on the future agricultural scenario, providing greater agricultural vulnerability. Therefore, the importance of using crop simulation models to understand the gaps in productivity and productive potential is highlighted. However, there is a clear need for more detailed research on the applicability of models in diverse agricultural scenarios and broad climatic situations.Keywords: simulation models; climatic seasonality; resilient practices; yield gap.

An Agent-Based Model-Driven Decision Support System for Assessment of Agricultural Vulnerability of Sugarcane Facing Climatic Change

In recent years, there have been significant changes in weather patterns, mainly caused by sharp increases in temperature, increases in carbon dioxide, and fluctuations in precipitation levels, negatively impacting agricultural production. Agricultural systems are characterized by being vulnerable to the variation of biophysical and socioeconomic factors involved in the development of agricultural activities. Agent-based models (ABMs) enable the study, analysis, and management of ecosystems through their ability to represent networks and their spatial nature. In this research, an ABM is developed to evaluate the behavior and determine the vulnerability in the sugarcane agricultural system; allowing the capitalization of knowledge through characteristics such as social ability and autonomy of the modeled agents through fuzzy logic and system dynamics. The methodology used includes information networks for a dynamic assessment of agricultural risk modeled by time series, system dynamics, uncertain parameters, and experience; which are developed in three stages: vulnerability indicators, crop vulnerability, and total system vulnerability. The development of ABM, a greater impact on the environmental contingency is noted due to the increase in greenhouse gas emissions and the exponential increase in extreme meteorological phenomena threatening the cultivation of sugarcane, making the agricultural sector more vulnerable and reducing the yield of the harvest.

Barren lives: drought shocks and agricultural vulnerability in the Brazilian Semi-Arid

This paper studies the effects of drought shocks in a vulnerable environment – the Brazilian Semi-Arid. We analyze the impact of drought shocks, measured as deviations from long-run historical averages, on agricultural outcomes in a region that suffers recurrently from drought. After controlling for municipality and year fixed effects, we use weather shocks to exactly identify outcomes. Our benchmark results show substantial effects on the loss of crop area and on the value of agricultural output, as well as on crop yields. As we investigate distributional effects, our results show that crops related to familiar agriculture suffer more from drought shocks. We follow our investigation by testing heterogeneity effects and show that adequate water provision and maintenance of forest cover help in reducing the impact of drought shocks.

Household’s Agricultural Vulnerability to Climate Induced Disasters: A Case on South-west Coastal Bangladesh

Climatic events have a significant impact on south-western coastal agriculture in Bangladesh. The purpose of this study was to assess household’s agricultural vulnerability to climate-induced disasters and to identify the sub-indicators of adaptive capacity that determine the agricultural vulnerability to climate-induced disasters of south-western coastal households in Bangladesh. The vulnerability has been calculated by taking the Intergovernmental Panel on Climate Change (IPCC) concept through an Agricultural Vulnerability Index (AVI). Then, the ordered logit model has been employed to identify the key sub-indicators of adaptive capacity that determine the agricultural vulnerability to climate-induced disasters. A survey of 346 household heads from the two villages (181 household’s head from Sutarkhali and 165 household’s head from Nalian) of Sutarkhali Union of Dacope Upazila under Khulna District has been used in this study. Findings reveal that the mean score of Sutarkhali is 0.703 (high) for exposure, 0.762 (high) for sensitivity, 0.397 (low) for adaptive capacity and finally, the AVI is 0.689 (high). In the same fashion, Nalian has an average score of 0.658 (high) for exposure, 0.681 (high) for sensitivity, 0.410 (low) for adaptive capacity, and finally 0.643 (high) for the AVI. Non-farm employment, ownership of livestock, access to irrigation pump, improved crop diversification/ saline tolerant High Yielding Variety (HYV) crops, and access to farm credit have been found statistically significant sub-indicators of adaptive capacity that determine the agricultural vulnerability of both study sites. Finally, it is recommended that the intervention required for coastal adaptation of agriculture should be initiated by respective authorities.

Household’s Agricultural Vulnerability to Climate Induced Disasters: A Case on South-west Coastal Bangladesh

Climatic events have a significant impact on south-western coastal agriculture in Bangladesh. The purpose of this study was to assess household’s agricultural vulnerability to climate-induced disasters and to identify the sub-indicators of adaptive capacity that determine the agricultural vulnerability to climate-induced disasters of south-western coastal households in Bangladesh. The vulnerability has been calculated by taking the Intergovernmental Panel on Climate Change (IPCC) concept through an Agricultural Vulnerability Index (AVI). Then, the ordered logit model has been employed to identify the key sub-indicators of adaptive capacity that determine the agricultural vulnerability to climate-induced disasters. A survey of 346 household heads from the two villages (181 household’s head from Sutarkhali and 165 household’s head from Nalian) of Sutarkhali Union of Dacope Upazila under Khulna District has been used in this study. Findings reveal that the mean score of Sutarkhali is 0.703 (high) for exposure, 0.762 (high) for sensitivity, 0.397 (low) for adaptive capacity and finally, the AVI is 0.689 (high). In the same fashion, Nalian has an average score of 0.658 (high) for exposure, 0.681 (high) for sensitivity, 0.410 (low) for adaptive capacity, and finally 0.643 (high) for the AVI. Non-farm employment, ownership of livestock, access to irrigation pump, improved crop diversification/ saline tolerant High Yielding Variety (HYV) crops, and access to farm credit have been found statistically significant sub-indicators of adaptive capacity that determine the agricultural vulnerability of both study sites. Finally, it is recommended that the intervention required for coastal adaptation of agriculture should be initiated by respective authorities.

Household’s Agricultural Vulnerability to Climate Induced Disasters: A Case on South-west Coastal Bangladesh

The purpose of this study was to assess household’s agricultural vulnerability to climate induced disasters and to identify the indicators of adaptive capacity that determine the vulnerability of south-western coastal household’s in Bangladesh. The vulnerability was calculated by taking the Intergovernmental Panel on Climate Change (IPCC) concept through an Agricultural Vulnerability Index (AVI). Then the ordered logit model was employed in order to identify key determinants of agricultural vulnerability to climate induced disasters. A survey of 346 household’s head from the two settlements (181 household’s head from Sutarkhali and 165 household’s head from Nalian) of Sutarkhali Union of Dacope Upazila under Khulna District was used in this study. Findings revealed that the mean score of Sutarkhali was 0.703 (high) in exposure, 0.724 (high) in sensitivity, 0.341 (low) in adaptive capacity and finally, the agricultural vulnerability index (AVI) was 0.695 (high). On the same fashion, Nalian was an average score of 0.697 (high) in exposure, 0.721 (high) in sensitivity, 0.386 (low) in adaptive capacity, and finally 0.677 (high) in agricultural vulnerability index (AVI). Annual savings, formal education, ownership of livestock, improved seeds supply, access to irrigation pump, improved crop diversification/ High Yielding Variety (HYV) crops, access to large farm size and access to farm credit were found to be statistically significant indicators of adaptive capacity that determine agricultural vulnerability of the both study sites. Finally it is recommended that the intervention required for coastal adaptation of agriculture should be initiated by respective authorities.