Multi-Model approach to study the impact of climate variability on the productivity of wheat systems
As part of the USDA NIFA-funded project 'Regional Approaches to Climate Change for Pacific Northwest Agriculture', a regional assessment of yields, water and carbon footprint for baseline and future climatic conditions is being conducted using computer models. REACCH aims at ensuring the long-term viability of cereal-based farming in the Pacific Northwest and at identifying farming practices that can help minimize impacts on productivity and reduce GHG emissions under climate change. Gridded daily weather data (4x4 km) for the period 1979 - 2010 are available for baseline simulations. For future weather, daily data projected by 14 GCMS for two representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 ppm) are being used, for a total of 28 future weather scenarios. An ensemble of 5 wheat growth models extracted from CropSyst, APSIM-Wheat, CERES-Wheat, STIC and EPIC are being coded to run under the platform of CropSyst. This platform will provide input/output operations and scenario creation capabilities (weather, soils, crop rotations, management), and will simulate hydrologic processes, including all components of the water balance, and nutrient cycling. This approach will allow the simulation of wheat yields using different wheat growth modeling approaches under a common set of environmental conditions. Growth of rotational crops other than wheat will be simulated using CropSyst crop modules. The main objective of this multi-model study is to reduce the uncertainty associated with individual wheat growth models, with the expectation that model ensembles will provide a better estimation of future outcomes as typically accepted by the climate modeling community. Preliminary evidence has shown that the use of ensembles of crop growth models can also be an effective approach to reduce uncertainty.
Mukhtar Ahmed is Assistant Professor at PMAS, Arid Agriculture University Rawalpindi Pakistan and now working as Post Doc under Regional Approaches to Climate Change for Pacific Northwest Agriculture. His research focuses on the impact of climate change on crop ecology and rainfed ecosystem management. He is involved in the use of statistical and dynamic models as risk management tools to mitigate the challenges of changing climate.He got PhD degree in Agronomy (Specialization in Crop Physiology, Simulation Modeling and Climate variability) with practical experience in teaching, field/laboratory experiments, model parameterization and simulations, soil water dynamics, modeling nutrient use efficiency, rainfall forecasting using climatic drivers, dryland management, crop production under changing climate and drought tolerant selection.
Publications and Presentations:
Ahmed, M., Karimi, T., Nelson, R., Stockle, C. Multi-Model Approach to Study the Impact of Climate Variability on the Productivity of Wheat Systems. ASA, CSSA & SSSA International Annual Meeting, Nov. 1-6, 2014, Long Beach, CA (poster).
Ahmed, M. and C. Stockle. 2017. Quantification of climate variability, adaption and mitigation for agricultural sustainability. Springer International Publishing, Switzerland.
Akhtar, M., Hassan, F., Ahmed, M., Hayat, R., Stockle, C. 2015. Is rainwater harvesting an option for designing sustainable cropping patterns for rainfed agriculture? Land Degradation and Development. 27(3): 630-640.