Modeling for Integrated Assessment System

The agricultural community and decision makers require tools to reliably predict crop yield, to assess optimal management practices and economic impacts. UVMRP is currently developing the Climate-Agroecosystem-UV Interactions and Economic (CAIE) system with collaborators from the University of Maryland and Colorado State University. CAIE system that will couple an advanced regional climate model with models of crops and ecosystems and economics, integrating the data from the monitoring network, the results of the effects studies, and satellite observations. This system will allow studies on how climate and crop production interact and how the interaction impacts economics and management practices.

CAIE is an integrated assessment system that simulates climate, UV radiation, crop growth, and economics. It will be able to predict how crop yield and quality will respond to changes in environmental including temperature, moisture (drought), nutrients, UV-B radiation, CO2 concentration, aerosols and other air pollutants. It will be capable of simulating agriculturally important crops (such as cotton, corn, soybean, wheat, and rice), forests, and rangelands. CAIE will include an economic assessment model that predicts economic growth of crop agriculture (total factor productivity change) based on climate. The system will have the ability analyze policy, land use, and management practices. Ultimately, the system will provide the science support for U.S. policy makers to not only establish necessary incentives and safety nets for producers, but also to assess potential risks, determine optimal practices, design effective policies, and identify mitigation and adaptation strategies to achieve sustainable development of agriculture.

CAIE structure

CAIE has the following components:

  • CWRF (Climate-Weather Research and Forecasting model) is a state of the art model that comprehensively simulates the processes behind regional climate and weather. CWRF runs on horizontal grids at U.S. nationwide scale and is capable of simulating terrestrial hydrology, precipitation, and radiation, all of which are critical for crop growth.
  • CSSP (Conjunctive Surface-Subsurface Process model) simulates canopy effects, soil temperature/moisture distributions, terrestrial hydrology variations, and land-atmosphere exchanges of water, heat, and moment fluxes.
  • LDAS (NASA Land Data Assimilation System) assimilates best available observations to produce spatially and temporally consistent land-surface model datasets, intended to reduce the errors in key variables of climate and weather models.
  • DSSAT (Decision Support System for Agrotechnology Transfer) is a crop model capable of simulating many species individually, based on the genetic characteristics of each species.
  • GOSSYM (a shortened scientific name for the genus of cotton, Gossypium) is a mechanistic model developed by USDA to simulate cotton growth given soil, weather, and management practices.
  • DayCent-UV (Daily version of Century model with UV module) is a modified version of a widely used terrestrial ecosystem biogeochemistry model DayCent, which simulates photosynthesis, plant production, carbon allocation, autotrophic and heterotrophic respiration, decomposition, evaporation, transpiration, phenology, disturbances such as fire and grazing, and management practices such as fertilizer use and irrigation.
  • TUV (Tropospheric Ultraviolet and Visible radiation model), is a well-tested radiation transfer model developed by National Center for Atmospheric Research.
  • UV-Canopy (3-D Canopy UV radiation transfer model) is a canopy level radiation transfer model that predicts UV-B within and below a canopy.
  • FASOMGHG (Forest and Agricultural Sector Optimization Model – GreenHouse Gasses version) is an economic model used by EPA that simulates land allocation and the economic impacts of changing land allocation and production practices.

For more information on ongoing research, select an interest below.