The California Cropland Monitoring and Modeling Framework (CCMMF) will be a biogeochemical model and data integration pipeline to generate current year inventories and future projections of soil carbon (SOC) stocks and greenhouse gas fluxes (GHG) from California’s croplands. CCMMF will leverage Bayesian techniques to combine model predictions and heterogeneous datasets into unified wall-to-wall inventories and climate and scenario-based projections. Data layers will be generated as ensemble projections to facilitate propagation of uncertainty through downstream applications.

CCMMF will produce new gridded time series of key agronomic practices including planting, harvest, irrigation, and tillage at a consistent temporal resolution. These agronomic management time series will be generated by combining remotely sensed data with agronomic statistics and biogeochemical modeling. The biogeochemistry model will be built on the SImplified PhotosyNthesis and EvapoTranspiration model (SIPNET), expanded to represent agronomic management, nitrogen cycling, and fluxes of nitrous oxide and methane. We will utilize existing and newly-derived remote sensing of annual land management and agricultural practices to drive the model will produce consistent model estimates that do not depend on obtaining records from individual farmers. The statistical workflow engine will extend the Predictive Ecosystem Analyzer (PEcAn) to support annual updates and both climate-based and management scenario-based projections.

The combination of a simplified biogeochemistry model that simulates agronomic practices from remote-sensed inputs and an open, consistent, variance-explicit data framework will allow CCMMF to achieve robust estimates of SOC and GHG inventories across lands with highly varied but coarsely measured management. All data and software that is part of CCMMF will be open, free, and deployable on state computing resources. This requirement sets a bar for transparency, and a foundation for future innovation and transferability, that is not possible with the current suite of proprietary systems.

• Chris Black, Pools and Fluxes LLC
• David LeBauer, The LeBauer Approach LLC and The University of Arizona
• Mike Dietze, Boston University
• Rob Kooper, University of Illinois and National Center for Supercomputing Applications
• Mike Longfritz
• Shawn Serbin, NASA

• National Aeronautics and Space Administration
• California Air Resources Board

This section will be developed as the project gets under way. In the mean time, feel free to reach out directly to team members or through our GitHub Discussions.

A central focus of this project is to generate open source software and open data that will enable transparency while facilitating reuse, collaboration, and derivative works. To this end, we release our works under the following licenses:

• Software: BSD 3-Clause
• Writing: CC-BY
• Data Products: Public domain (CC0).

If any CCMMF software repositories, data products, or documentation are missing a LICENSE file or if their terms of use are unclear, please let us know. For any questions about the terms of use, feel free to start a discussion or contact a team lead.