Assessment of Potential Yields Using Climate Change Scenarios for Agricultural Crops in Mexico

Submitted by Antonio Arce | published 22nd Apr 2022 | last updated 22nd Jul 2022
A map showing impacts across Mexico

A map showing climate change impacts in agriculture across Mexico

Introduction

This report summarises the findings of the consultancy project "Estimación de rendimientos potenciales con escenarios de cambio climático para diversos cultivos agrícolas en México", funded by the government of Canada under the UNDP-INECC partnership. The project aimed at understanding the impacts of climate change on yields of agricultural crops of importance for Mexico. 

Climate change poses significant threats to food security in Mexico. A large part of domestic food production is performed under rainfed conditions. This project modeled the impact of changes in temperature and precipitation on agricultural yields of the six most important crops in Mexico: corn, beans, wheat, soy, sorghum, and barley. Four individual adaptation measures were also modeled:

  • Changing the sowing date to match the shift of the rain season.
  • Applying organic mulches to retain moisture.
  • Simulating the response of a phenological variety adapted to drier conditions and 
  • The use of irrigation to compensate for a water deficit. 

The use of a biophysical crop model (Aquacrop-FAO) combined with historical climate data and agricultural-specific parameters allowed for the validation of crop models in different case studies. The previous step enabled the use of future climate change scenarios, simulating the potential impacts of climate change on crop yields. 

Results point towards a loss of yield for most of the crops validated across case studies. This is particularly true for basic cereals such as corn, beans, and wheat. The case studies on sorghum and barley resulted in yield increases or decreases; while only soybeans projected gains in some areas.

The adaptation measures showed an improvement compared to the lack of them. Out of the four adaptation measures modeled, changing sowing dates to account for weather variability and using organic mulches were the most promising adaptation measures. Changing sowing dates is a relatively simple measure to account for the weather variability under future climate change conditions. The use of organic mulches allows for maximising the retention of moisture and the use of water.  

This weADAPT article is an abridged version of the original text, which can be downloaded from the right-hand column. Please access the original text for more detail, research purposes, full references, or to quote text.

Methodology

The objective of this consultancy was to "Develop and apply a methodology to estimate
future yields considering climate change scenarios for some agricultural crops in Mexico (corn, beans, wheat, and soy), through the use of recent and specialized software, as well as the compilation of databases to estimate the impact of climate change on the yield of these crops". Additionally, four adaptation measures were modeled. 

The general methodology was based on the application of a biophysical crop model (Aquacrop, by FAO) combined with climate change scenario data. The climate change scenario data considered five global coupled climate models (CNRM, GFDL, HADGEM, MPI and REA ensemble), two representative concentration pathways (4.5 and 8.5 W/m2) and three time horizons (2015-2039, 2045-2069 and 2075-2099).  

Six crops were considered in this study: maize, beans, soybeans, sorghum, barley and wheat. For each of those crops, at least two case studies were developed. A case study consisted of the combination of climate and agricultural data for past and future yields for a specific location. Several model iterations were implemented to calibrate the baseline model. Once the baseline showed agreement with the observed historical yield data, future climate scenario data replaced historical data to simulate the impact of climate change with no changes from the baseline agricultural practices. Furthermore, four adaptation options were simulated: the change of sowing date, the use of organic mulches, the inclusion of new varieties and the use of irrigation. 

Results

The calibration of crop models using historical observed yield and climatic data was satisfactory, meaning observed and modelled yield data differed in no more than 15% in most case studies. Regarding future climatic scenarios, precipitation is expected to decrease while its intra-annual distribution is expected to shift for the majority of case studies. Water productivity will decrease, requiring more water quantities already from a near time horizon (2015-2039). Water stress was found to be a major factor explaining biomass loss, particularly during the initial growth phase of crops. Case studies located in cold areas might experience a longer growing season leading to an increased biomass production, although water availability is set to limit the potential. A similar effect occurs with carbon dioxide concentration. An increase in global carbon dioxide concentration could lead to higher productivity in theory but more water will be needed in order to materialise this possibility. 

Some case studies present conditions of low yield already in the current time horizon, implying that climate change will have a magnifying effect. Looking at future climate change scenarios, yield loss was found in most of the crop case studies. Yield of staple cereals would be particularly affected already from a short term horizon: maize (-30%), beans (-15%), and wheat (-30%). Sorghum and barley present cases where the yield increases or decreases, although their decreasing trend is more prominent in distant time horizons. Only soybean projected gains in high rainfall areas (one out of two case studies). 

The adaptation measures projected different results across crops and case studies. The use of additional water yielded the best results in the dry zones located in the north of the country. However, various studies show deficits in water availability and overexploitation of aquifers in that area. The best second and third measures were the change in planting date and the change in the phenological characteristics of the varieties. The application of organic mulches and the change in phenological characteristics projected the best results for temperate zones. In warm areas with high rainfall, the main limitation is soil fertility; hence the application of organic mulches had good results. The change in planting date turned out to be a measure that allowed recovering between 5% and 20% of the yield impacted by climate change, considering all the case studies.

Takeaways and Lessons Learned

  • Changes in future precipitation will have a major impact on crop yields. Reduced precipitation in combination with increased temperatures will impact the water available for crop development, compromising the overall yield output.  
  • Climate change is likely to have major impacts on crop yields in Mexico if no adaptation actions are taken. Potential yield loss was found for almost all crops and case studies, with some exceptions for soybean. 
  • Implementating adaptation measures can greatly mitigate the impacts of climate change. Simple actions such as adjusting the sowing time can mitigate yield loses by 20%. Using organic mulches and introducing new varieties yield good results, but they also require investments and capacity building.
  • The use of crop models proved to be a simple and easy to implement tool to assist in the design of adaptation measures.  

Further resources