Advancements in crop modeling help adapt to climate change

A Nebraska Water Center (NWC) research team is making several advancements in crop modeling – the set of mathematical equations describing how crop genetics, crop management practices, and the environment interact together to determine crop growth.

 

Development of the soil carbon and carbon dioxide respiration model

Soil carbon dioxide (CO2) respiration is a major flux in the global carbon cycle and is a measure of the CO2 naturally released from soil as a result of decomposition. The global concern over increasing CO2 levels has driven the need for accurate estimation of carbon storage in the soil, as well as CO2 respiration.

NWC post-doctoral research associates Sahila Beegum and Wenguang Sun are making advancements in modeling soil carbon and carbon dioxide respiration to help decision makers compare different management strategies and the impact they have on soil carbon and carbon dioxide. The new models also provide different projected climate outcomes and the impact they may have on crop production.

Beegum and Sun worked in conjunction with USDA-ARS to publish an article titled “Incorporation of carbon dioxide production and transport module into a Soil-Plant-Atmosphere Continuum model” in Geoderma, an Elsevier Publication.

CO2 release from agricultural soils is influenced by multiple factors, including soil, plant, water, and atmospheric properties. Accurate estimation of the CO2 fluxes in the soil and soil respiration requires a process-based modeling approach, considering the complex interactions of all these factors.

“These models can help in understanding the impact of different environmental and agricultural management practices on the soil carbon dynamics and respiration,” Beegum said.

Incorporation of carbon dioxide production and transport module into a Soil-Plant-Atmosphere continuum model.

1. A carbon dioxide production and diffusion-based transport module is developed and incorporated into a process-based soil-plant-atmosphere continuum model called MAIZSIM.
2. The newly developed model can simulate carbon dioxide production from soil organic matter (microbial respiration) and roots (root respiration).
3. Microbial respiration is based on the soil microbial processes by accounting for the carbon dynamics in the organic matter pools as moderated by the soil water content, temperature, microbial synthesis, humification, and decomposition of the carbon pools. Root respiration is simulated based on root mass, age, soil water content, and temperature.
4. The model demonstrates accurate prediction of soil CO2 respiration in response to environmental, soil, and crop growth effects.

Improvements to cotton model help improve crop yields

Cotton crop simulation models predict plant growth and development as influenced by environmental conditions and crop management. Current models run once per day. However, an improvement by Beegum, Sun and the team runs simulations hourly, resulting in a more accurate model. The new update also allows for adaptation of the model to simulate the impact of climate change factors, including atmospheric carbon dioxide (CO2) and temperature.

The team again worked in conjunction with the U.S. Department of Agriculture's Agricultural Research Service (USDA-ARS) in Maryland to publish their work in Scientific Reports, a Nature Publication, titled “Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes.”

Beegum, Sun and the team are improving crop models for more than just theoretical uses.

“Improved crop models help better estimate crop growth, development, and yields under varying environmental and management conditions,” Beegum said. “This research and the newly developed model will be helpful for scientists, agricultural managers and policymakers interested in assessing the effects of soil, water, temperature, carbon dioxide dynamics, nutrient stresses, etc., on cotton crop growth and development and in making adaptation strategies.”

As crop models continue to improve, they can play a crucial role in assisting farmers to optimize irrigation water, nitrogen, and other management practices, leading to higher crop yields. Accounting for factors like seed, soil and environment, these models enable informed decisions and enhanced agricultural productivity.

Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes

• The radiation use efficiency-based photosynthesis model in GOSSYM has been replaced with a Farquhar biochemical model of photosynthesis, supplemented by the Ball-Berry leaf energy balance transpiration model.
• The simulation of below-ground processes in GOSSYM, which previously used RHIZOS, has been improved by replacing it with 2DSOIL, a mechanistic two-dimensional finite element soil process model.
• The newly developed model facilitates accurate cotton crop simulations under varying conditions of soil, water, temperature, carbon dioxide, and nutrient levels, and it can simulate all these processes at an hourly time step.

Models now available for use by growers and researchers

“Our primary focus is on enhancing crop simulation models that capture soil-plant-atmospheric interactions,” says Beegum. “These improved models are now available as a graphical user interface (GUI), simplifying their usage for farmers and researchers.”

Beegum, Sun and the team’s research expands existing tools to include more data that is relevant in a changing climate. The models allow us to see how more carbon in the atmosphere interacts with less nitrogen use or less water. By better capturing the full soil-plant-atmosphere interaction in these new models, decisions can be made that include consideration of climate change and more efficient management strategies while still reaching production goals.