Novo: Development of and Agriculture Drought Risk Model for the Iberian Peninsula Antigo: Development an Agriculture Drought Risk Model for the Iberian Peninsula: a neural network approach

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Development of an Agriculture Drought Risk model for the Iberian Peninsula

Publication . Ribeiro, Andreia Filipa Silva; Russo, Ana Cristina Machado; Gouveia, Célia Marina Pedroso

Among climate extremes, droughts are a major source of risk to agriculture and food security, which are expected to be increasingly affected considering the tendency towards a warmer climate. Within the context of climate change, the Iberian Peninsula (IP) is one of the regions recurrently highlighted as one of the areas expected to be particularly affected by drought episodes, due to the strong variations in the precipitation regime that make the region prone to drought events. In this way, this dissertation aimed the development of an agricultural drought risk model to contribute to more resilient systems in the IP. The skills of several drought indicators (SPEI, VCI, TCI and VHI) in predicting wheat and barley yields were firstly assessed based on neural networks and multiple linear regression models. Afterwards, copula-based models were designed to assess the joint probability of crop yields and droughts for a probabilistic risk assessment. The agricultural drought risk was then defined as the conditional probability of crop-loss under drought conditions and mapped at the province level of the IP. Ultimately, the additional risk associated with the occurrence of extreme temperatures during droughts was evaluated to characterize how the interaction between dry and hot conditions may exacerbate the impacts of the individual hazards in agriculture. The results showed the good performance of drought indicators in predicting the occurrence of crop failures. In general, barley exhibits greater agricultural drought risk in comparison to wheat. Overall, the risk of crop-loss increases with the severity of drought conditions, and drought-related risks increase with the interaction with extreme temperatures. Although compound dry and hot conditions lead to the larger damages in crop yield than the individual drought- or heat-stress, drought is still the dominant factor. From an operational point of view, this research intends contributing to the agricultural decision-making.

2020-10Tese de doutoramento

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Fundação para a Ciência e a Tecnologia

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OE

Número da atribuição

PD/BD/114481/2016