Article ID Journal Published Year Pages File Type
4376409 Ecological Modelling 2012 13 Pages PDF
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.

► Fish population recovery model developed to estimate long-term impacts of floods. ► Model inputs are immediate impact estimates of high flow events on fish and eggs. ► Uncertainty is addressed by utilizing different risk-based performance measures. ► The risk-based performance measures address both short- and long-term impacts. ► These estimates may be used in water resources decision-making processes.

Related Topics
Life Sciences Agricultural and Biological Sciences Ecology, Evolution, Behavior and Systematics
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