Crops' exposure, sensitivity and adaptive capacity to drought occurrence

Author:

Alonso Catarina,Gouveia Celia M.ORCID,Russo AnaORCID,Páscoa Patrícia

Abstract

Abstract. In the context of sustainable agricultural management, drought monitoring plays a crucial role in assessing the vulnerability of agriculture to drought occurrence. Drought events are very frequent in the Iberian Peninsula (and in Portugal in particular), and an increase in frequency of these extreme events are expected in a very near future. Therefore, the quantitative assessment of the natural-ecosystem vulnerability to drought is still very challenging, mainly due to the difficulties of having a common definition of vulnerability. Consequently, several methods have been proposed to assess agricultural vulnerability. In this work, a principal component analysis (PCA) was performed based on the components which characterize the exposure, sensitivity and adaptive capacity of the agricultural system to drought events with the aim of generating maps of vulnerability of agriculture to drought in Portugal. Several datasets were used to describe these components, namely drought indicators, vegetation indices and soil characterization variables. A comparison between the PCA-based method and a variance method using the same indicators was performed. Results show that both methods identify Minho and Alentejo as regions of low and extreme vulnerability, respectively. The results are very similar between the two methods, with small differences in certain vulnerability classes. However, the PCA method has some advantages over the variance method, namely the ability to identify the sign of the indicators, not having to use the indicator–component subjective relationship, and not needing to calculate weights. Furthermore, the PCA method is fully statistical and presents results according to prior knowledge of the region and the data used.

Funder

Fundação para a Ciência e a Tecnologia

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

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