Skip to content

GeoEPIC Yield Calibration Tutorial

This tutorial outlines the steps to perform yield calibration for multiple sites using GeoEPIC, leveraging the setup from regional simulations. Calibration fine-tunes model parameters to better match simulated outputs (like crop yield) with observed data across a region.

  1. Set Up the Workspace: Before starting calibration, you must have a properly organized workspace containing all necessary input files (Site, Soil, Weather, Operations) for the multiple sites in your calibration region. Follow the procedures detailed in the Regional Simulation Tutorial, specifically Steps 1-3 (Set Up Environment, Prepare Input Files, Set Up Workspace). This ensures you have:

    • A configured geoEpic environment.
    • All required .SIT, .SOL, .DLY, and .OPC files for each site.
    • A well-structured workspace directory (e.g., workspace/) containing these inputs and the EPIC model executable.

  2. Perform Calibration: The core calibration process involves selecting parameters to adjust (e.g., crop parameters in .OPC or site/soil parameters), defining an objective function (how to measure the match between simulated and observed yields), and using a calibration algorithm or workflow to find optimal parameter values. For detailed, step-by-step instructions on:

    • Preparing observed yield data.
    • Selecting appropriate parameters for calibration.
    • Configuring and running a calibration workflow or tool (potentially using libraries like spotpy or custom geoEpic calibration utilities).
    • Evaluating calibration performance. Please refer to the dedicated Calibration Procedure Guide. This guide provides the specific commands, scripts, and methodologies required to execute the yield calibration.

  3. Access Calibrated Parameters: Once the calibration process (as described in the Calibration Procedure Guide) is complete, the optimized parameter values will typically be stored in output files or potentially within Python objects generated by the calibration script.

    • The specific format and location depend on the calibration tool or script used. It might be a CSV file, a JSON file, or directly printed to the console. Example conceptual access (actual implementation depends on the calibration tool): `` # Example: Assuming calibration results are saved to a file import pandas as pd

    try: # Load parameters maybe saved by the calibration tool calibrated_params = pd.read_csv('./workspace/calibration_outputs/best_parameters.csv') print("Calibrated Parameters:") print(calibrated_params)

      # Or access parameters if stored in a Python object (conceptual)
  # best_run_parameters = calibration_result.best_parameters
  # print(best_run_parameters)

    except FileNotFoundError: print("Calibration output file not found. Check calibration process outputs.") except Exception as e: print(f"Error accessing calibration results: {e}")

    `` Refer back to the Calibration Procedure Guide for specifics on where and how to retrieve the final calibrated parameter set generated by your chosen calibration method. These parameters can then be used for subsequent validated regional simulations.