California Cropland Carbon Monitoring and Modeling Framework
Creators
Description
Proposal to the California Air Resources Board for the California Cropland Monitoring and Modeling Framework.
About
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.
Files
CCMMF_Proposal_Technical Portion.pdf
Files
(2.1 MB)
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Additional details
Funding
Dates
- Accepted
-
2024-04-08Notice of Intent to Award Contract
- Submitted
-
2024-03-22Proposal submission date
Software
- Repository URL
- https://github.com/ccmmf