A Systems Engineering Methodology for Structuring and Calibrating Lake Ecosystem Models

A methodology is presented which makes use of both theory-based and data-based information to structure and calibrate low-order dynamic models for lake ecosystem analysis. A brief historical review explores the inductive and deductive aspects of past modeling efforts and describes the motivation for this research. A methodology, summarized in a flowchart, is discussed in terms of data analysis, conceptualization, development of a mathematical model, calibration, and three feedback stages for validity checks. This approach has been applied to the study of nutrient cycling in the south basin of Lake George, NY. The results of several iterations of the methodology are given and discussed in terms of statistical validity and agreement with biological theory. The final model is a set of difference equations containing two state variables and three external variables, and shows a good fit to the existing data. This is one of the first lake ecosystem studies to make extensive use of data in order to develop model relationships and estimate parameters.

[1]  J. P. Killus,et al.  SIMPLE: A simplified ecosystem model for Lake George, New York , 1978, WSC '78.

[2]  C. K. Minns,et al.  Prediction of Egg Development Times of Freshwater Copepods , 1978 .

[3]  R. Jones,et al.  Water Report: Eutrophication of water bodies: Insights for an age old problem. , 1978 .

[4]  M. Hutchins,et al.  Input/Output Models as Decisions Criteria for Lake Restoration , 1978 .

[5]  Carolyne M. Gowdy.  Input signals for sampling and identification of ecological systems , 1978, ICASSP.

[6]  R. T. Oglesby,et al.  Phosphorus loadings to lakes and some of their responses. Part 1. A new calculation of phosphorus loading and its application to 13 New York lake 1 , 1978 .

[7]  R. T. Oglesby,et al.  Phosphorus loadings to lakes and some of their responses. Part 2. Regression models of summer phytoplankton standing crops, winter total P, and transparency of New York lakes with known phosphorus loadings 1 , 1978 .

[8]  S. Chatterjee,et al.  Regression Analysis by Example , 1979 .

[9]  O. Loucks,et al.  SIMULATIONS OF SEVERAL RUNOFF MANAGEMENT OPTIONS FOR A SMALL URBAN LAKE , 1977 .

[10]  Charles F. Cooper.  Ecosystem models and environmental policy , 1976 .

[11]  R. Poole.  Stochastic difference equation predictors of population fluctuations. , 1976, Theoretical population biology.

[12]  L. J. Bledsoe,et al.  10 – Linear and Nonlinear Approaches for Ecosystem Dynamic Modeling , 1976 .

[13]  R. Mulholland,et al.  14 – Control Theory and the Regulation of Ecosystems , 1976 .

[14]  R. Poole.  Empirical multivariate autoregressive equation predictors of the fluctuations of interacting species , 1976 .

[15]  Bernard C. Patten,et al.  Ecosystem Linearization: An Evolutionary Design Problem , 1975, The American Naturalist.

[16]  Bernard C. Patten,et al.  10 – Total Ecosystem Model for a Cove in Lake Texoma* , 1975 .

[17]  Richard A. Park,et al.  A generalized model for simulating lake ecosystems , 1974 .

[18]  R. Mulholland,et al.  Analysis of linear compartment models for ecosystems. , 1974, Journal of theoretical biology.

[19]  Donald J. O'Connor,et al.  A Dynamic Model of the Phytoplankton Population in the Sacramento—San Joaquin Delta , 1971 .

[20]  Richard B. Williams.  10 – Computer Simulation of Energy Flow in Cedar Bog Lake, Minnesota Based on the Classical Studies of Lindeman* , 1971 .

[21]  Carl W. Chen.  Concepts and Utilities of Ecologic Model , 1970 .

[22]  R. Mansueti.  Fundamental of Ecology.Eugene P. Odum , 1960 .

[23]  D. Cochrane,et al.  Application of Least Squares Regression to Relationships Containing Auto-Correlated Error Terms , 1949 .

[24]  V. Volterra.  Variations and Fluctuations of the Number of Individuals in Animal Species living together , 1928 .