Simulating Agriculture in the Community Land Model Version 5

Abstract

Agricultural expansion and management have greatly increased global food production and altered Earth's climate by changing physical and biogeochemical properties of terrestrial ecosystems. Few Earth system models represent agricultural management practices due to the complexity of the interactions between human decisions and biological processes on global scales. We describe the new capabilities of representing crop distributions and management in the Community Land Model (CLM) Version 5, which includes time‐varying spatial distributions of major crop types and their management through fertilization and irrigation, and temperature‐based phenological triggers. Including active crop management increases peak growing season gross primary productivity (GPP), increases the amplitude of Northern Hemisphere net ecosystem exchange, and changes seasonal and annual patterns of latent and sensible heat fluxes. The CLM5 crop model simulates the global observed historical trend of crop yields with relative fidelity from 1850 to 1990. Cropland expansion was important for increasing crop production, especially during the first century of the simulations, while fertilization and irrigation were important for increasing yields from 1950 onward. From 1990 to present day, observed crop production continued to increase while CLM5 production levels off, likely because intensification practices are not represented in the model. Specifically, CLM does not currently include increasing planting density, crop breeding and genetic modification, representations of tillage, or other management practices that may also affect crop‐climate and crop‐carbon cycle interactions and alter trends in yields. These results highlight the importance of including crop management in Earth system models, particularly as global data sets for parameterization and evaluation become more readily available.

Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0

“…Despite recent development efforts, the representation of these management practices has not yet been included in CLM5. Furthermore, in a previous study by Lu et al (2017) the default representation of winter cereals performed poorly in simulating the phenology of winter wheat.…”

“…In this study, we evaluate and enhance the performance of the crop module of CLM5 focusing on the representation of seasonal and inter-annual variations in crop growth, planting and harvesting cycles, crop yields, and energy and carbon fluxes. Firstly, we transferred the modified vernalization and cold-tolerance routine by Lu et al (2017) to the CLM5 code to simulate winter cereal in a more meaningful way. Secondly, new crop-specific parameter sets for winter wheat, sugar beet, and potatoes that were gathered from the literature and from observation data were added to the default parameter scheme.…”

An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)

“…The amount of suspended solids in slurry is measured by the dry matter (DM) content (g DM g −1 slurry), which can vary due to different management practices from < 5 % up to about 20 %. Manure with a higher DM content can normally be handled as a solid (Lorimor et al, 2001). Several studies (Sommer and Olesen, 1991;Vandre et al, 1997;Misselbrook et al, 2005b) have shown a positive correlation between the DM content and NH 3 volatilization.…”

An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen, version 2 (FANv2)

“…Besides the additional process-level detail, FANv2 has an improved representation of agricultural practices. Similar to FANv1, the model is integrated to the Community Land Model (CLM), which forms the land surface component of CESM, but unlike FANv1, FANv2 makes use of the interactive crop model included in CLM (Lawrence et al, 2019;Lombardozzi et al, 2019) to determine the timing and amounts of fertilization appropriate to each crop. FANv2 also incorporates a parameterization (Gyldenkaerne et al, 2005) for evaluating volatilization losses from manure in animal housings or during storage.…”