Garden with Insight v1.0 Help: Model overview

The Garden with Insight garden simulator uses a simulation model derived largely from the Erosion-Productivity Impact Calculator (EPIC) model (Williams et al., 1984). EPIC was developed to predict how water and wind erosion affects soil productivity (crop yield) as part of the 1985 Resources Conservation Act (RCA) analysis for the 1977 Soil and Water Resources Conservation Act. EPIC is used by farmers and other decision makers to decide what strategies are best to reduce soil erosion on particular lands. It is an empirical model based largely on published experiments and data. It has also been incorporated into several other models that address related hydrology issues.

EPIC puts its strongest emphasis on weather simulation, hydrology (water movement), water and wind erosion, soil temperature, and nitrogen and phosphorus cycling. Plant growth is simulated in less detail. We translated almost all of EPIC from FORTRAN to C++ (and then to Pascal for the current version) and made several adaptations to simulate the home garden. See our section on the differences between EPIC and Garden with Insight.

It is important to understand that this simulation is not very accurate at this point. Inaccuracy in the simulation arises from at least three sources:

1. We may not have translated the EPIC code correctly. The EPIC FORTRAN code is many thousands of lines long, and we have not tested every aspect of the simulation well enough to be sure no translation errors remain.
2. Our parameters may be wrong. Most of the parameters used in the simulation are from EPIC data sets, but for the submodels we added (flowering and fruiting, plant drawing, harvest) we estimated parameters from a quick reading of the plant growth literature. Some of these numbers may be wrong at this point.
3. The simulation may not go into enough detail in a particular area. Because we adapted a hydrology model to a situation for which it was not designed, there are significant gaps in what is covered by the simulation. For example, earthworms and soil microbes are very important in gardens, but they are not simulated here, at least not explicitly. And the pH and cation exchange models are very simple. In this explanation of the models we will explain these gaps and how they could be improved.

You might ask: if the simulation isn't accurate, what is it good for? Here is our answer. When you walk around outside, how do you think of the soil? Do you think of it as "dirt", inert, uncomplicated, not very interesting? Do you think of it at all? In fact, the soil is a fascinating and complicated ecosystem, with bacteria, earthworms and insects, with spongy organic matter, with sand, silt and clay, with pore spaces filled with air and water, with horizons of different colors, with a complex dance of ions in solution. And what do you think of plants? Are they boring? On close examination plants are truly elegant creatures, with modularity, hormonal communication, microscopic root hairs, transpiration, flowering signals, pollen tubes, geometry, phototropism, phyllotaxy. If you think of this simulation like a spreadsheet and expect answers to questions about your garden, you will indeed be disappointed. But if you think of the simulation as a world to explore and an invitation to learn, you will find something worthwhile.

If there is anything here you don't understand, please don't give up! Go and look it up in a book. We hope poking around in this model explanation and playing with the program will help you get started (and interested) in looking more deeply into these topics.

Quick synopsis of large model areas

Weather simulation
The weather simulation works mainly by generating patterns of temperature, radiation, and precipitation similar to the weather patterns in a climate. Long-term average values for weather variables are used along with measurements of the amount of variation to generate values from normal distributions. Also, an autocorrelation matrix whose parameters were calculated from about 30 years of data from 1000 U.S. climates modifies the simulated weather to account for similarity through time.

Hydrology
Since EPIC was designed largely as a predictor of water erosion (wind erosion was added later), this simulation has a large hydrology component. The soil area (soil patch) is modeled as a series of horizontal layers through which water and dissolved materials move and through which plant roots penetrate. The movement of water through the soil after a rainfall is simulated by calculating runoff from the soil surface, percolation through the soil layers, horizontal flow beneath the soil surface, and water table dynamics.

Nutrient cycling
Nutrient cycles are modeled for nitrogen (N), phosphorus (P), and carbon (C). The nitrogen cycle has labile (soluble) and organic portions. The phosphorus cycle has labile, organic, and mineral portions. The carbon cycle is modeled as a series of pools of decomposing organic matter, from still-standing dead plant matter to soil humus. Decomposition and mineralization of N, P and C are carried out by soil microbes, which are not explicitly simulated.

Plant growth
Plant growth is simulated with a basic heat unit system that correlates plant growth with temperature. Accumulated heat units drive potential growth, and actual growth is reduced from potential growth by considering several constraints on plant growth: temperature, solar radiation, soil moisture, soil aeration, labile nitrogen and phophorus, soil strength, and aluminum toxicity.

EPIC introduction.
Model contents