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Development of an early warning system for agricultural production anomalies in the Chaco region in Argentina

  • 31 August, 2023
  • Wageningen University, Water Systems and Global Change
  • dr. R.W.A. Hutjes
  • dr.ir. I. Supit

Throughout history, climate variability has been present in the Chaco Region, yet due to agricultural expansion in the last 50 years, the negative effects of this variability for yields have become more visible. As one of the major grain producers in the world, export of grains is a very substantial part of GDP in Argentina. Having good and reliable early-season predictions for crop yields enables decision-makers and farmers to better react on shortages posed by inter-seasonal climatic variability (i.e. The El-Niño Southern Oscillation (ENSO)) and climate change. This periodic oscillation has a profound effect on climate in Chaco Region and ENSO´s rainfall is believed to change even more with predicted higher temperatures in the Chaco Region for the coming decades. Recently, The World Meteorological Organization (WMO) has developed a framework for an Early Warnings for All initiative.
This study will mainly focus on pillars 1,2 and provide considerable inputs for a regional/national platform as described in pillar 3. Once completed this study, it will be a valuable tool to adjust policy-making and tailor on- and off-field production management according to seasonal and future predictions.
In Argentina the hydro-meteorological station network is operated by several governmental entities, making data collection rather scattered and public access very restricted. Throughout Argentina hydro-meteorological data is scarce, duration of data series is short with many missing values, especially outside the Pampa region. Due to this data scarcity, the use of remote sensing to estimate variables such as LAI and gridded rainfall datasets (e.g. CHIRPS) in combination with our own observational data network becomes interesting for model input.
A reliable tool capable to simulate near and far future yields will facilitate integrated decision making in planning public policies and improve management strategies at field and regional for anomalous weather conditions. Agronomic- and soil hydraulic parameters, forecasts, real time weather, and remote sensing data will be combined into a decision support system to develop useful indicators of future expected soil water balance, crop growth and yields. A calibrated reliable yield prediction model would be of great interest to government agencies and farmers to provide a seasonal decision-support system that can be used to manage soil and water resources and on-farm decisions in a more efficient way in this semiarid region with little available data. In order to reach out to farmers and other actors and to strengthen INTA´s ability to transfer knowledge towards the agricultural sector, the outcomes of this research can be used to co-create through a bottom-up participatory process and together with all stakeholders a digital support platform for the automated prediction and early warning of water resource availability and crop yields, where seasonal, evaluation of scenario effects and management strategies come together in one decision-making platform operated through a website or mobile application.

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Howard van Meer

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