Methodological approach to quantify the effect of changing climate patterns on bean crop yield in the State of Durango

Esquivel-Arriaga, Gerardo; Sánchez-Cohen, Ignacio; López-Santos, Armando; Velásquez-Valle, Miguel Agustín; Bueno-Hurtado, Palmira

doi:10.5154/r.rchsza.2015.08.011

ISSN e: 2007-4018 / ISSN print: 2007-3828

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Vol. XV, issue 1 January - June 2016

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Methodological approach to quantify the effect of changing climate patterns on bean crop yield in the State of Durango

Enfoque metodológico para cuantificar el efecto del cambio en patrones de clima sobre el rendimiento del cultivo de frijol en el estado de Durango

Gerardo Esquivel-Arriaga; Ignacio Sánchez-Cohen; Armando López-Santos; Miguel Agustín Velásquez-Valle; Palmira Bueno-Hurtado

Keywords: mitigation, downscaling, climatic variability, vulnerability

10.5154/r.rchsza.2015.08.011

Received: 2015-08-25
Accepted: 2016-04-28
Available online: 2016-06-15
Pages:17-28

Abstract Highlights

A method to analyze climate variability and quantify its impact on bean yield under regionalized climate change scenarios is proposed. The algorithm consists of four steps: a) identification of agricultural land sown with bean, b) obtaining of climate parameters that define the region and use of a stochastic generator (LARS-WG) to obtain regionalized climate change scenarios; c) the matrices that define the climate conditions at the site are embedded into a crop model (EPIC) to assess the impact on crop yield and d) a spatial distribution of the information is performed. The results indicate that under future climate change scenarios (A2 and A1B), yield increases in the range of 0.1 t·ha-1 are expected in some areas, along with decreases of 0.2 t·ha-1 in others. Increases in maximum and minimum temperature, as well as increases and decreases in rainfall, are also foreseen for some areas of the state. Based on the proposed method and the expected future changes in climate patterns, it would be advisable to perform simulation runs considering adjustments in management practices to compute the reduction in climate risk to agricultural areas.

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