Assessing impacts of high flow events on fish population: Evaluation of risk-based performance measures

Ali Naghibi and Barbara Lence

Ecological Modelling, 2012, vol. 240, issue C, 16-28

Abstract: Water management decisions in regulated rivers are associated with uncertainty and complexity. For example, quantitative approaches for estimating immediate and long-term impacts of high flow events on fish populations have not sufficiently been addressed in the literature despite the institutional motivation for doing so. In this paper, a probabilistic model for estimating the long-term fish population recovery, given flood induced fish and egg losses, is developed. A framework that incorporates this model for estimating flood impacts in the form of risk-based performance measures of fish population is also presented. The performance measures are operational indicators that account for uncertainty in fish population response to high flow events. They include vulnerability, engineering resilience, and ecological resilience, as well as a modification of these measures introduced herein, which is equivalent to vulnerability multiplied by expected recovery time. Such measures characterize both short- and long-term fisheries impacts of water management decisions, and may be useful in planning, design, and real-time operation of reservoirs, and in participatory water use planning projects, along with other risk measures (e.g., life safety and economical risks). Applicability of the fish population recovery model and the estimated risk-based performance measures is explored for the case study of the Lower Campbell River in British Columbia, Canada.

Keywords: Environmental impacts; Floods; Vulnerability; Resilience; Fish population; Fish loss; Egg loss; Individual-based modeling; Probabilistic simulation; Fish habitat; Reservoir operation (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:240:y:2012:i:c:p:16-28

DOI: 10.1016/j.ecolmodel.2012.04.024

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