Hydraulics And Performance Evaluations Of Fish Passages Based On Computational Fluid Dynamics And Individual Based Methods

Hydraulics and Performance Evaluations of Fish Passages Based on Computational Fluid Dynamics and Individual-based Methods

Fish passages have been used as an important tool to restore the connectivity of rivers segmented by dams and weirs. However, due to the complexity of rivers, structures, and fish biology, numerous existing fishways only achieved very limited success at considerable cost (Silva et al., 2018a). Reasons for the failures or inefficiencies results often ascribe the poor understandings of fishway hydraulics and fish response to these flow characteristics. Consequentially, oversimplified design methods and build-and-test paradigms are used in practice. To improve the fishway design methodology, this thesis developed numerical models and practical tools. Because of its popularity in fishway community, the first part of this thesis investigated hydraulics condition of Nature-like fish passage (NLFP), which is made of a series of rock weirs. Typical engineering design of rock weirs relies on simplified, one-dimensional equations dependent on empirical coefficients. However, most simplified methods fail to accurately predict the hydraulics through rock weirs because they do not consider flow through interstitial spaces between rocks and the way interstitial flow alters the head-discharge relationship. To improve the design methodology and to better capture the complex hydraulics past rock weirs, a three-dimensional, high-resolution computational fluid dynamics (CFD) model was utilized to study the problem. The simulation results demonstrate that the flow phenomena and head-discharge relationship are significantly different between broad-crest weirs and rock weirs. The interstitial spaces between rocks not only drain a portion of total discharge, but also accelerate the weir overflow. Based on the results, a flow decomposition approach is proposed to quantify the discharge through a rock weir. The decomposition includes contributing flows from (1) weir flow over the individual rocks and (2) interstitial flow between rocks. The applicability of the proposed decomposition was demonstrated with an independent case. For practical use of the proposed flow decomposition method, a Python-based design tool was developed. The second part of this thesis developed a fish behavior model to predict fish migrating movement for various applications. When designing fish passage for migrating fish, two important questions need to be answered: (1) whether they can swim through the fish passage and (2) whether fish can find the entrance of fish passage. This thesis work developed a new open-source, three-dimensional fish behavior model and demonstrated the capability of this fish model by answering the two questions in Chapter 3 and Chapter 4, respectively. Chapter 3 reports the implementation and application of an Eulerian-Lagrangian Agent Model (ELAM) on the popular computational physics platform OpenFOAM, called ELAM-OF. ELAM models use the Eulerian framework for the flow field simulation and the Lagrangian framework to model individual fish's sensory region and track its movement, which is based on a set of rules for fish behaviors. The fish behavior model and rules are adapted from the Eulerian-Lagrangian Agent Model in Goodwin et al. (2006) and Goodwin et al. (2014), which has shown success in engineering applications. The advantage of ELAM-OF is that it provides a framework for using unstructured meshes to model complex domains such as fish passage and natural rivers. The modualized design of ELAM-OF makes it easy to "plug-and-play" different components such as flow solvers, fish behavior rules, stimuli, and both migrating directions. Chapter 3 shows the calibration, validation, and application of upstream migration through a vertical slot fishway. The analysis uncovered fish passing routes, patterns, failures, and efficacy, which demonstrates the capability of the proposed ELAM-OF model to evaluate fish response before fishway construction. To investigate if fish can find the entrance, Chapter 4 introduces a workflow and toolset to solve the problem in a wider domain with a longer time horizon. The workflow converts the flow results in popular 2D hydraulics models such as SRH-2D and HEC-RAS 2D into the format of the fish behavior and tracking model ELAM-OF. The conversion involves both mesh and flow results. The converted hydraulic model data are then used by the ELAM-OF model to track the movement of individual fish particles. A real-world case was simulated for the York Haven Dam on the Susquehanna River where data from a fish tagging and monitoring study were used for calibration. The case shows that the tools developed in this work can successfully complete the workflow and the simulated fish movement results qualitatively compare well with field data. The simulated results were then further analyzed to explain the low efficacy of the existing fish ladder and confirm the feasibility of the location of a new fish passage. In conclusion, this ELAM-OF model provides an effective and efficient way to evaluate the location and efficacy of the planned fish passage before construction, which help prevent the expensive and inefficient build-and-test paradigm in current practice.

Fish and Wildlife Implementation Plan

Cognitive Movement Ecology

At least since Darwin argued that the difference in cognitive abilities between animals and humans is one of degree and not of kind, the study of animal cognition has been an active and dynamic subfield of behavioral sciences. It has, however, been based almost entirely on experimental studies of animals in captivity and belongs - as a field - more snugly in the realm of Psychology (or Ethology), with relatively little application to understanding the behavior of animals in the wild. Movement Ecology, in contrast, is a more recent branch of Ecology devoted almost entirely to the analysis of animal movements in the wild. Technological developments allow for animals to be tracked in the wild in ever-increasing numbers, precision, and duration. Movement ecology has, to some extent, “chased the data”, reflecting the practical need to analyze and interpret those data. Much of the most important developments of recent decades are devoted to dealing with the trickier aspects of the statistical analysis of movement data - which in their multidimensionality, autocorrelation, gappiness and measurement error, and behavioral complexity pose no shortage of hairy statistical problems.