Vulnerability risk index of agricultural production in the Brazilian Semi-Arid

Minella Martins of the Earth System Science Center, National Institute for Space Research- CCST/INPE, Brazil, assessed the vulnerability of agricultural production in the Semi-Arid of Brazil and identified hotspots where public policies could be applied to reduce current and future risks.

Minella Martins

Minella Martins

Introduction

Weather and environmental conditions in semi-arid regions all over the world can seriously affect agricultural production. The Brazilian Semi-Arid region is considered one of the worlds’ most populated semi-arid regions. The rural population is almost 40% of the total population and depends mostly on rain-fed agriculture for its subsistence. Its vulnerability is increased by climatic variability, water deficiency, low adaptation capacity, and poverty. To understand how to increase the resilience and reduce the vulnerability of communities to agricultural production risk, it is necessary to understand what are the main components of crop production vulnerability and which regions are and will be most at risk. The purpose of this study is therefore to assess the vulnerability of agricultural production in the Semi-Arid of Brazil and identify subregions of the Brazilian Semi-Arid (e.g., hotspots), where public policies could be applied to reduce current and future risks.

Methodology

In this work we look at bean and maize crop yields, the most cultivated crops in the Brazilian Semi-Arid and we assess their vulnerability to environmental (soil, number of days with a water deficit, and precipitation) conditions. The data was provided by official Brazilian institutions such as The Brazilian Institute of Geography and Statistics (IBGE), and the Programa de Monitoramento Climático em Tempo Real da Região Nordeste, (PROCLIMA/INPE). Bivariate and panel regression statistical analyses were applied to assess the components that contribute to vulnerability and could be used as appropriate indicators for each subregion. The data time series used covers 2005 to 2012.

Results and Conclusions

It was found that the soil textural class and number of days with a water deficit (NDWD) represented the most satisfactory variables for crop production vulnerability. We identified that at least 24% of all cities were vulnerable in terms of crop production because of the effects of soil and the number of dry days. In a further analysis, we considered three different approaches to evaluating these indicators: range of crop production, decrease in crop production, and stress thresholds to crop production. The first used the difference in NDWD between highest and lowest crop yields through which we identified that 68% of cities are vulnerable in terms of crop production. In the second approach, we used only the minimum crop yield for each city and the corresponding dry days for the year with the smallest crop yield. With this approach we found that 54% of the cities are vulnerable. In the third approach, we considered only the cases in which the city had 10 dry days or more. Using this analysis we find that 77% of the cities in the Brazilian Semi-Arid are vulnerable in terms of dry days and soil textural class. Numbers of days with water deficit and the soil textural class are appropriate variables for detecting the vulnerability of agricultural production and can be used within an indicator system. All three approaches show a different answer to the specific question of crop production vulnerability. As the NDWD is essentially a random process, we also determined the risk of each subregion falling below given threshold levels of crop production and range.

Supervisors

Stefan Hochrainer-Stigler and Georg Pflug, Risk, Policy and Vulnerability, IIASA

Note

Minella Martins of the Earth System Science Center, National Institute for Space Research- CCST/INPE, Brazil, is a Brazilian citizen. She was funded by IIASA and worked in the Risk, Policy and Vulnerability (RPV) Program during the YSSP.

Please note these Proceedings have received limited or no review from supervisors and IIASA program directors, and the views and results expressed therein do not necessarily represent IIASA, its National Member Organizations, or other organizations supporting the work.


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Last edited: 30 September 2015

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