Chemical assumptions in input designation and parameter determination in the DayCent-Chem Model
St Brice L. 2007. Chemical assumptions in input designation and parameter determination in the DayCent-Chem Model. Bates College
From the abstract: "Ecosystem scientists use computer models to predict the effects of atmospheric deposition on terrestrial and aquatic ecosystems. Models require a set of unique input variables which are used to predict outputs, and the relationship between the two is characterized by various parameters. Many ecological models represent heterogeneous ecosystems as homogeneous entities and so require that simplifying assumptions be made about the ecosystem being studied. Additionally, assumptions are made in determining the parameters which define the relationships between these inputs and outputs. The assumptions made about inputs and parameters affect the degree to which model predictions vary from observed values for variables in the field. Sensitivity analysis seeks to identify and quantify the effects that changes in input variables and model parameters have on model output. In this study, DayCent-Chem (a coupled, non-spatial biogeochemical model) was initialized for Hadlock Brook Watershed in Acadia National Park. Sensitivity analysis was used to explore the relationship between chemical assumptions made, both in the representation of model processes (through parameter determination) and in the designation of the model inputs, on the model's predictive capability. The model was found to be sensitive to the five categories of manipulations carried out, being most sensitive to cation exchange capacity manipulations followed by mineral denudation, texture, partial pressure of CO2 and reaction database manipulations, in that order."
- Type
- Academic
- Authors
- St Brice, Lois
- Date of Issue
- 2007-04-09
- Publisher
- Bates College
- Units
- ACAD , GRSM , ROMO
- Keywords
- Alkalinity, Aluminum (Al), Carbon dioxide (CO2), Cations, Chemistry, Discharge, Herbicides, Integrated pest management (IPM), Invasive plants, Invasive species, Minerals, Modeling, Nitrates (NO3), Organic compounds, pH, Silica (SiO2), Soil, Soil chemistry, thesis, Watersheds