DECODING 3-D MOVEMENT PATTERNS OF FISH IN RESPONSE TO HYDRODYNAMICS AND WATER QUALITY FOR FORECAST SIMULATION

Abstract

A theoreticallyand computationally-robust mathematical approach for decoding movement patterns of individual fish responding to biotic and physicochemical stimuli is described. The modeling approach, coupled Eulerian-Lagrangian agent individual-based modeling (CEL Agent IBM), is intuitive and based on well-established principles in computer science, fluid and water quality dynamics, computational fluid dynamics (CFD) modeling, neuroscience, and game and foraging theories. A CEL Agent IBM couples a 3-D Lagrangian particle-tracker supplemented with behavioral rules to a Eulerian CFD model. Mathematical structure of the behavioral rules is derived from an agent-based, event-driven foraging model. Stimuli are queried from information provided by a CFD or water quality model or a priori field data. Back-casting simulation analysis results in a mechanistic mathematical formulation of behavior amenable to forecast simulation. In this paper, we describe the theoretical concepts of a CEL Agent IBM used to decode observed 3-D movement and passage patterns of downstream migrating juvenile salmon (migrants) at Lower Granite Dam on the Snake River, Washington, USA. The prototype CEL Agent IBM (the Numerical Fish Surrogate) is presently used by the US Army Corps of Engineers to quantitatively forecast and assess the response of migrants to virtual designs of alternative bypass systems at federal hydropower dams. As this specific example illustrates, CEL Agent IBMs are applicable to many aquatic systems and provide the theoretical and computational facility for improving existing individual-based modeling and water resource decision-support.