### Abstract

Based on a comprehensive literature review, a dynamic model was developed to simulate impacts of industrial water use on fish populations. The computer simulation model predicts the magnitude of fish losses such as impingement and enhanced mortality rates due to natural as well as man-induced perturbations. This simulator is not based on a time series analysis, biomass conversion balance, or other strictly empirical approaches. In the modelling framework, fish losses are envisioned as sinks to the ecosystem. A fish population model that was developed to make such an approach feasible, simulates the inherent dynamic fluctuations of an existing ecosystem. This multi-species simulator is age-structured like a Leslie matrix (LM), and predicts oscillatory behavior like the classical Lotka-Volterra (L-V) equations. The LM and L-V methods were unified by determination of the Leslie survival probabilities, P, for each age class as a function of various factors including: predator/prey interaction, toxicity and temperature effects, hydrodynamic conditions and others. The only data required to initialize parameters of the population model was two or three years of inexpensively sampled far-field data, such as rotenone data. In a power plant case study, for example, using the population model, temperature data and a simple hydrodynamic submodel, the impingement dynamics at cooling water screens were shown to be a reflection of aquatic population dynamics. The actual impact incurred by the aquatic ecosystem was rated by comparison of survival probabilities of unaffected areas upstream in the run-of-the-river reservoir to survival probabilities in the area surrounding the plant. The computer simulation model can be used as a predictive tool for the evaluation of power-plant site alternatives, design improvements, and overall environmental impact of fish losses on the fishery. The model methology is flexible enough to examine various impacts on a fishery, such as ecosystem influx of hazardous industrial wastes and toxic substances, sudden severe depletions of DO levels, excessive fishing, etc. The general simulator can also be integrated into an optimization scheme for maximum harvesting of adult fish subject to economical and environmental constraints.

Original language | English (US) |
---|---|

Pages (from-to) | 363-390 |

Number of pages | 28 |

Journal | Water Science and Technology |

Volume | 13 |

Issue number | 7 |

State | Published - Jan 1 1981 |

Event | Environ Impact of Man's Use of Water, Proc of a Spec Conf - Brighton, Engl Duration: Nov 3 1980 → Nov 7 1980 |

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### All Science Journal Classification (ASJC) codes

- Environmental Engineering
- Water Science and Technology

### Cite this

*Water Science and Technology*,

*13*(7), 363-390.

}

*Water Science and Technology*, vol. 13, no. 7, pp. 363-390.

**Generalized computer simulation model for the impact assessment of industrial water use on fish populations.** / Kleinstreuer, C.; Logan, Bruce Ernest.

Research output: Contribution to journal › Conference article

TY - JOUR

T1 - Generalized computer simulation model for the impact assessment of industrial water use on fish populations

AU - Kleinstreuer, C.

AU - Logan, Bruce Ernest

PY - 1981/1/1

Y1 - 1981/1/1

N2 - Based on a comprehensive literature review, a dynamic model was developed to simulate impacts of industrial water use on fish populations. The computer simulation model predicts the magnitude of fish losses such as impingement and enhanced mortality rates due to natural as well as man-induced perturbations. This simulator is not based on a time series analysis, biomass conversion balance, or other strictly empirical approaches. In the modelling framework, fish losses are envisioned as sinks to the ecosystem. A fish population model that was developed to make such an approach feasible, simulates the inherent dynamic fluctuations of an existing ecosystem. This multi-species simulator is age-structured like a Leslie matrix (LM), and predicts oscillatory behavior like the classical Lotka-Volterra (L-V) equations. The LM and L-V methods were unified by determination of the Leslie survival probabilities, P, for each age class as a function of various factors including: predator/prey interaction, toxicity and temperature effects, hydrodynamic conditions and others. The only data required to initialize parameters of the population model was two or three years of inexpensively sampled far-field data, such as rotenone data. In a power plant case study, for example, using the population model, temperature data and a simple hydrodynamic submodel, the impingement dynamics at cooling water screens were shown to be a reflection of aquatic population dynamics. The actual impact incurred by the aquatic ecosystem was rated by comparison of survival probabilities of unaffected areas upstream in the run-of-the-river reservoir to survival probabilities in the area surrounding the plant. The computer simulation model can be used as a predictive tool for the evaluation of power-plant site alternatives, design improvements, and overall environmental impact of fish losses on the fishery. The model methology is flexible enough to examine various impacts on a fishery, such as ecosystem influx of hazardous industrial wastes and toxic substances, sudden severe depletions of DO levels, excessive fishing, etc. The general simulator can also be integrated into an optimization scheme for maximum harvesting of adult fish subject to economical and environmental constraints.

AB - Based on a comprehensive literature review, a dynamic model was developed to simulate impacts of industrial water use on fish populations. The computer simulation model predicts the magnitude of fish losses such as impingement and enhanced mortality rates due to natural as well as man-induced perturbations. This simulator is not based on a time series analysis, biomass conversion balance, or other strictly empirical approaches. In the modelling framework, fish losses are envisioned as sinks to the ecosystem. A fish population model that was developed to make such an approach feasible, simulates the inherent dynamic fluctuations of an existing ecosystem. This multi-species simulator is age-structured like a Leslie matrix (LM), and predicts oscillatory behavior like the classical Lotka-Volterra (L-V) equations. The LM and L-V methods were unified by determination of the Leslie survival probabilities, P, for each age class as a function of various factors including: predator/prey interaction, toxicity and temperature effects, hydrodynamic conditions and others. The only data required to initialize parameters of the population model was two or three years of inexpensively sampled far-field data, such as rotenone data. In a power plant case study, for example, using the population model, temperature data and a simple hydrodynamic submodel, the impingement dynamics at cooling water screens were shown to be a reflection of aquatic population dynamics. The actual impact incurred by the aquatic ecosystem was rated by comparison of survival probabilities of unaffected areas upstream in the run-of-the-river reservoir to survival probabilities in the area surrounding the plant. The computer simulation model can be used as a predictive tool for the evaluation of power-plant site alternatives, design improvements, and overall environmental impact of fish losses on the fishery. The model methology is flexible enough to examine various impacts on a fishery, such as ecosystem influx of hazardous industrial wastes and toxic substances, sudden severe depletions of DO levels, excessive fishing, etc. The general simulator can also be integrated into an optimization scheme for maximum harvesting of adult fish subject to economical and environmental constraints.

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M3 - Conference article

AN - SCOPUS:0019858849

VL - 13

SP - 363

EP - 390

JO - Water Science and Technology

JF - Water Science and Technology

SN - 0273-1223

IS - 7

ER -