Development of Predictive Relationships for Sub-Grid Scale Flow Variability Within 2D Hydraulic Models for Improved Fisheries Habitat Quantification
Can sub-grid scale flow variability be predicted from 2D hydraulic model grid scale variables to improve predictions of fish habitat availability?
Although 2D hydraulic models are widely used in fisheries management, calibration and validation data is frequently collected such that a disparity exists in sampling volume and the mesh element domain. The mismatch in sampling volumes prohibits estimation of the velocity variability that exists within a mesh element. The proposed study addresses the need to collect validation data at spatial scales consistent with mesh elements and quantify velocity variability in model outputs. The probability distributions of velocities collected within regions concurrent with individual mesh elements will be related to local grid scale variables. The proportion of mesh element containing suitable velocity for juvenile salmonid habitat can be determined after sub-grid scale flow variability is related to grid scale variables.
Need and Benefit
Traditional methods for estimating salmonid habitat rely on labor intensive field measurements of water depth and velocity. 2D hydraulic models are now commonly used as an inexpensive means to estimate depth and velocity and therefore predict habitat quantity and quality. Thus 2D models are an indispensable tool for fisheries management on regulated rivers.
These models are used as an inexpensive means to quantify existing habitat and explore potential habitat gains that may result from management actions such as flow releases and mechanical channel reconfiguration. The ability of these models to predict habitat gains offers the potential to more effectively utilize resources and better manage fisheries. However, typical velocity validation measurements for 2D hydraulic models precludes determination of velocity variability within mesh elements.
While 2D velocity models are currently an integral part of fisheries management, empirical data is needed to quantify sub-grid scale flow variability to enable full utilization of model outputs. Once flow variability within model grid cells is quantified, fisheries managers can confidently rely on 2D hydraulic models and better estimate the quantity of suitable juvenile salmonid habitat.
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