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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-256
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-256
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 01 Aug 2019

Submitted as: research article | 01 Aug 2019

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Crops' sensitivity and adaptive capacity to drought occurrence

Catarina Alonso1, Célia Gouveia1,2, Ana Russo1, and Patrícia Páscoa1 Catarina Alonso et al.
  • 1Instituto Dom Luíz, Faculdade de Ciências da Universidade de Lisboa, Campo Grande
  • 2Instituto Português do Mar e da Atmosfera, Lisboa, Portugal

Abstract. In the context of sustainable agricultural management, drought monitoring plays a crucial role 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 of frequency of these extreme events are expected in a very near future. Therefore, the quantitative assessment of the natural ecosystems 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 Adaptative 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 indexes and soil characterization variables. A comparison between the PCA-based method and a subjective non-automatic categorical 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 on certain vulnerability class. However, the PCA method has some advantages over the categorical method, namely the ability to identify the sign of the indicators, not having to use the indicator-component subjective relationship, nor calculating weights. Furthermore, the PCA method is fully statistical and presents results according to a prior knowledge of the region and the data used.

Catarina Alonso et al.
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Short summary
A vulnerability assessment method is proposed to identify the most vulnerable regions over Portugal. Two methods were compared, namely a subjective categorical method and an automatic method, based on drought indicators, vegetation indexes and soil variables. Both methods present similar results, and both identify Minho (Alentejo) as having low (extreme) vulnerability. The automatic method has advantages as it is fully statistical and presents results without prior knowledge of the region.
A vulnerability assessment method is proposed to identify the most vulnerable regions over...
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