November 2020 Project Updates
New Video Update
Unpacking the DRFEWS Land Use Allocation Model
Our Land Use Allocation model involves multiple data sources to predict trajectories for land use allocations: Farm survey responses, historical data, global price information, pre-existing economic models. See how it all comes together in this 8.5-minute update video.
More Project Updates
Regional Advisory Committee Meeting Forecast
As with many of you, COVID-19 has disrupted our project’s work, but we have been busy and are making great strides on the DRFEWS modeling and simulations. That said, we have encountered many unforeseen challenges in integrating our models into a dynamic system. We will delay our next meeting with the full Regional Advisory Committee (RAC) until we have initial model simulation results to share and discuss. At this point, we are planning to be ready by Spring 2021.
Regional Spatial Economic Model
Diving into Regional Sectors and Variability
Our economic team has spent significant time developing our Regional Spatial Economic model (or Computable General Equilibrium (CGE) Model). This newer addition to our economic modeling framework examines dynamics taking place within the regional economy. It captures variations in land quality, market access, urban influence, and policies on various key economic sectors, pulling data from estimated land use, global commodity and energy prices, environmental and trade policies, and other conditions found to be relevant in our farmer survey. In May, we presented our spatial general equilibrium model to a small group of advisory stakeholders. We are incorporating feedback from this group to further refine the models, developing key details of the agricultural and energy sectors.
Real-time Applications of our Modeling Systems
COVID-19 Study We have extended our Dynamic Regional Economic model to study the impact of COVID-19 on Ohio’s economy. We added a sector to our Dynamic Regional Model which represents the health system, projecting numbers of infected patients and its interaction with other sectors. We collected related data and are developing the code and calibrating our model to match historical data. This was not part of our original DRFEWS project but is an excellent opportunity to apply our modeling work to timely issues and extend the usefulness of our work. The project is funded by a special Ohio State Office of Research grant.
Soil and Water Assessment Tool (SWAT)
Teaching an old model new tricks
Our Watershed Modeling team is engaged in innovative work which will allow the complexities of SWAT to respond to changes predicted by our other submodels. Our talented graduate students are applying computer learning techniques to train our current SWAT model to be more responsive to a dynamic system like ours. We are testing this new “surrogate SWAT model” using our Maumee watershed data.
Deglobalization Scenario Update
Translating broad scenarios into model inputs
Based on your feedback, we have identified the five scenarios (one baseline and four alternatives) that we plan to run using our integrated DRFEWS models. Our team is hard at work transforming these scenarios from broad ideas and trends into time series datasets that will represent different future conditions within the various DRFEWS submodels. We are working carefully, with the understanding that one size rarely fits all. For example, some land use changes can be modeled well within DRFEWS, responding to scenario triggers; while others (e.g., forests) are better set as a boundary condition. We’re working to integrate historical state-level data on agriculture and energy along with projections from the U.S. Department of Energy, and many other data sources. Abstracts on the scenarios have been accepted for presentation in two conferences in December, both of which are virtual this year—the Integrated Assessment Modeling Consortium and the American Geophysical Union.
Expanding the borders of sustainability assessment theory
Our team has gathered data on natural, manufactured, and human capital, including the values of several ecosystem services, to estimate an inclusive wealth index for the state of Ohio. We will use this data to begin testing methods to be extended to the entire region. We continue to combine ideas from weak and strong sustainability theory to create an assessment model that values overall welfare, but also sets viability levels for truly critical resources like water quality or carbon sequestration. But globalization has a definite impact on how we set critical levels and sustainability goals. For example, even though a region’s carbon emissions may be non-sustainable, that region could maintain welfare by trading emission offsets from other regions. In contrast, water quality problems are experienced and managed at the watershed level, which constrains, but does not eliminate, opportunities for offsets outside of the region. Since our scenarios are examining varied levels of globalization, this is an important concept to address within our model. One answer: Our sustainability team has incorporated a Social Accounting Matrix to more fully measure sustainability impacts from a product’s entire life cycle, examining different scales (equipment, value chain, economy) and multiple regions (local, state, national, and beyond).
Learn more about weak and strong sustainability indicators in this 30-minute presentation by DRFEWS project leader Elena Irwin. Watch here. (30 minutes May 2020)
Questions? Comments? Input?
Team Contact Information can be found at https://drfews.osu.edu/events/people.