• Energy Research

Pour réduire les risques du changement climatique, les gouvernements ont convenu dans l'Accord de Paris de limiter l'augmentation de la température mondiale à moins de 2,0 °C par rapport aux niveaux préindustriels, avec l'ambition de maintenir le réchauffement à 1,5 °C. La cartographie des réponses d'atténuation appropriées nécessite des informations sur les coûts d'atténuation par rapport aux dommages associés pour les deux niveaux de réchauffement. Dans cette évaluation, une considération critique est l'impact sur les rendements des cultures et la variabilité des rendements dans les régions actuellement confrontées à l'insécurité alimentaire. La présente étude a évalué les impacts de 1,5 °C par rapport à 2,0 °C sur les rendements du maïs, du millet perlé et du sorgho dans la savane soudanaise d'Afrique de l'Ouest en utilisant deux modèles de culture qui ont été calibrés avec des variétés communes issues d'expériences dans la région, la gestion reflétant une gamme de fenêtres de semis typiques. Comme l'intensification durable est encouragée dans la région pour améliorer la sécurité alimentaire, des simulations ont été menées à la fois pour l'utilisation actuelle d'engrais et pour un cas d'intensification (fertilité non limitative). Avec l'utilisation actuelle d'engrais, les résultats ont indiqué des pertes plus élevées de 2 % pour le maïs et le sorgho avec 2,0 °C par rapport au réchauffement de 1,5 °C, sans changement dans les rendements en mil pour aucun des scénarios. Dans le cas de l'intensification, les pertes de rendement dues au changement climatique étaient plus importantes qu'avec les niveaux actuels d'engrais. Cependant, malgré les pertes plus importantes, les rendements ont toujours été deux à trois fois plus élevés avec l'intensification, quel que soit le scénario de réchauffement. Bien que la variabilité du rendement ait augmenté avec l'intensification, il n'y avait aucune interaction avec le scénario de réchauffement. Une analyse des risques et du marché est nécessaire pour étendre ces résultats afin de comprendre les implications pour la sécurité alimentaire. Para reducir los riesgos del cambio climático, los gobiernos acordaron en el Acuerdo de París limitar el aumento de la temperatura global a menos de 2,0 °C por encima de los niveles preindustriales, con la ambición de mantener el calentamiento a 1,5 °C. El trazado de las respuestas de mitigación apropiadas requiere información sobre los costos de la mitigación frente a los daños asociados para los dos niveles de calentamiento. En esta evaluación, una consideración crítica es el impacto en los rendimientos de los cultivos y la variabilidad del rendimiento en las regiones actualmente desafiadas por la inseguridad alimentaria. El estudio actual evaluó los impactos de 1,5 °C frente a 2,0 °C en los rendimientos de maíz, mijo perla y sorgo en la sabana de Sudán de África Occidental utilizando dos modelos de cultivo que se calibraron con variedades comunes de experimentos en la región con un manejo que refleja una gama de ventanas de siembra típicas. A medida que se promueve la intensificación sostenible en la región para mejorar la seguridad alimentaria, se realizaron simulaciones tanto para el uso actual de fertilizantes como para un caso de intensificación (fertilidad no limitante). Con el uso actual de fertilizantes, los resultados indicaron pérdidas un 2% mayores para el maíz y el sorgo con 2,0 °C en comparación con el calentamiento de 1,5 °C, sin cambios en los rendimientos de mijo para ninguno de los dos escenarios. En el caso de la intensificación, las pérdidas de rendimiento debido al cambio climático fueron mayores que con los niveles actuales de fertilizantes. Sin embargo, a pesar de las mayores pérdidas, los rendimientos siempre fueron de dos a tres veces más altos con la intensificación, independientemente del escenario de calentamiento. Aunque la variabilidad del rendimiento aumentó con la intensificación, no hubo interacción con el escenario de calentamiento. Se necesitan análisis de riesgos y de mercado para ampliar estos resultados y comprender las implicaciones para la seguridad alimentaria. To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security. للحد من مخاطر تغير المناخ، اتفقت الحكومات في اتفاقية باريس على الحد من ارتفاع درجة الحرارة العالمية إلى أقل من 2.0 درجة مئوية فوق مستويات ما قبل الصناعة، مع طموح للحفاظ على ارتفاع درجة الحرارة إلى 1.5 درجة مئوية. يتطلب رسم استجابات التخفيف المناسبة معلومات عن تكاليف التخفيف مقابل الأضرار المرتبطة بمستويي الاحترار. في هذا التقييم، يتمثل أحد الاعتبارات الهامة في التأثير على غلة المحاصيل وتقلب الغلة في المناطق التي تواجه حاليًا انعدام الأمن الغذائي. قيمت الدراسة الحالية تأثيرات 1.5 درجة مئوية مقابل 2.0 درجة مئوية على غلة الذرة والدخن اللؤلؤي والذرة الرفيعة في سافانا غرب إفريقيا باستخدام نموذجين للمحاصيل تمت معايرتهما بأصناف شائعة من التجارب في المنطقة مع الإدارة التي تعكس مجموعة من نوافذ البذر النموذجية. ومع تعزيز التكثيف المستدام في المنطقة لتحسين الأمن الغذائي، أجريت عمليات محاكاة لكل من الاستخدام الحالي للأسمدة وحالة التكثيف (الخصوبة غير محدودة). مع استخدام الأسمدة الحالي، أشارت النتائج إلى خسائر أعلى بنسبة 2 ٪ للذرة والذرة الرفيعة مع 2.0 درجة مئوية مقارنة بالاحترار 1.5 درجة مئوية، مع عدم وجود تغيير في غلة الدخن لأي من السيناريوهين. في حالة التكثيف، كانت خسائر الغلة بسبب تغير المناخ أكبر من مستويات الأسمدة الحالية. ومع ذلك، على الرغم من الخسائر الأكبر، كانت الغلة دائمًا أعلى مرتين إلى ثلاث مرات مع التكثيف، بغض النظر عن سيناريو الاحترار. على الرغم من زيادة تقلب المحصول مع التكثيف، لم يكن هناك تفاعل مع سيناريو الاحترار. هناك حاجة إلى تحليل المخاطر والسوق لتوسيع نطاق هذه النتائج لفهم الآثار المترتبة على الأمن الغذائي.

Abstract Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assessment system can be an essential tool for end-users at different levels. This paper provides an overview of the approaches, algorithms, design, and capabilities of the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) for gridded crop modeling and yield forecasting along with risk analysis and climate impact studies. CRAFT is a flexible and adaptable software platform designed with a user-friendly interface to produce multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the pre-installed crop models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for seasonal climate forecasts. Its integrated and modular design allows for easy adaptation of the system to different regional and scientific domains. CRAFT requires gridded input data to run the crop simulations on spatial scales of 5 and 30 arc-minutes. Case studies for South Asia for two crops, including wheat and rice, shows its potential application for risk assessment and in-season yield forecasting.

Seasonal climate variability determines crop productivity in Ethiopia, where rainfed smallholder farming systems dominate in the agriculture production. Under such conditions, a functional and granular spatial yield forecasting system could provide risk management options for farmers and agricultural and policy experts, leading to greater economic and social benefits under highly variable environmental conditions. Yet, there are currently only a few forecasting systems to support early decision making for smallholder agriculture in developing countries such as Ethiopia. To address this challenge, a study was conducted to evaluate a seasonal crop yield forecast methodology implemented in the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT). CRAFT is a software platform that can run pre-installed crop models and use the Climate Predictability Tool (CPT) to produce probabilistic crop yield forecasts with various lead times. Here we present data inputs, model calibration, evaluation, and yield forecast results, as well as limitations and assumptions made during forecasting maize yield. Simulations were conducted on a 0.083° or ∼ 10 km resolution grid using spatially variable soil, weather, maize hybrids, and crop management data as inputs for the Cropping System Model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT). CRAFT combines gridded crop simulations and a multivariate statistical model to integrate the seasonal climate forecast for the crop yield forecasting. A statistical model was trained using 29 years (1991–2019) data on the Nino-3.4 Sea surface temperature anomalies (SSTA) as gridded predictors field and simulated maize yields as the predictand. After model calibration the regional aggregated hindcast simulation from 2015 to 2019 performed well (RMSE = 164 kg/ha). The yield forecasts in both the absolute and relative to the normal yield values were conducted for the 2020 season using different predictor fields and lead times from a grid cell to the national level. Yield forecast uncertainties were presented in terms of cumulative probability distributions. With reliable data and rigorous calibration, the study successfully demonstrated CRAFT’s ability and applicability in forecasting maize yield for smallholder farming systems. Future studies should re-evaluate and address the importance of the size of agricultural areas while comparing aggregated simulated yields with yield data collected from a fraction of the target area.

Adverse weather conditions, once rare anomalies, are now becoming increasingly commonplace, causing heavy losses to crops and livestock. One of the most immediate and far-reaching concerns is the potential impact on agricultural productivity and global food security. Although studies combining crop models and future climate data have been previously carried out, such research work in Central Asia is limited in the international literature. The current research aims to harness the predictive capabilities of the CRAFT (CCAFS Regional Agricultural Forecasting Toolbox) to predict and comprehend the ramifications stemming from three distinct RCPs, 2.6, 4.5, and 8.5, on wheat yield. As a result, the arid steppe zone was found to be the most sensitive to an increase in greenhouse gases in the atmosphere, since the yield difference between RCPs 2.6 and 8.5 accounted for almost 110 kg/ha (16.4%) and for 77.1 kg/ha (10.4%) between RCPs 4.5 and 8.5, followed by the small hilly zone with an average loss of 90.1 and 58.5 kg/ha for RCPs 2.6–8.5 and RCPs 4.5–8.5, respectively. The research findings indicated the loss of more than 10% of wheat in the arid steppe zone, 7.6% in the small hilly zone, 7.5% in the forest steppe zone, and 6% in the colo steppe zone due to climate change if the modeled RCP 8.5 scenario occurs without any technological modernization and genetic modification. The average wheat yield failure in the North Kazakhstan region accounted for 25.2, 59.5, and 84.7 kg/ha for RCPs 2.6–4.5, 4.5–8.5, and 2.6–8.5, respectively, which could lead to food disasters at a regional scale. Overall, the CRAFT using the DSSAT crop modeling system, combined with the climate predictions, showed great potential in assessing climate change effects on wheat yield under different climate scenarios in the North Kazakhstan region. We believe that the results obtained will be helpful during the development and zoning of modified, drought-resistant wheat varieties and the cultivation of new crops in the region.