Aquaculture Systems Modeling

Introduction

The current work on aquaculture systems modeling builds on previous experience and achievements under the PD/A CRSP. Models of aquaculture ponds developed to date have been deterministic and have evolved, from the original models in which water quality was assumed to be uniform throughout a pond, through models of stratified ponds. One of the models currently under development uses stochastic weather inputs to generate probability distributions for pond water quality and fish yields. The second model is used to analyze the flow of nutrients, particularly nitrogen, in an integrated aquaculture/agriculture system. The two distinct efforts will result in models that are useful for: 1) the study of pond management practices and the evaluation of possible production targets; 2) the analysis of environmental impacts from aquaculture; and 3) the study of nutrient and resource cycling in integrated agriculture/aquaculture systems.

The models are being tested with data from various PD/A CRSP sites. The stochastic model being developed makes extensive use of the weather data included in the PD/A CRSP database. In addition, water quality and fish yield results from various PD/A CRSP treatments and sites are used to calibrate and validate the models. The models developed can be useful as components of decision support systems being developed under the PD/A CRSP. Ultimately, aquaculture system models provide improved understanding of the dynamics of aquaculture ponds, and make it possible to design more reliable and efficient production practices.

Collaborating Institutions

University of California, Davis

Raul H. Piedrahita

Daniel Jamu

Zhimin Lu

Introduction

The aquaculture pond modeling work under way at the University of California, Davis, addresses constraints to aquacultural productivity, as well as those relating to environmental effects of aquaculture. Computer modeling is a unique tool which can be used to quantify pond processes and enhance our understanding of aquacultural ponds. This enhanced knowledge will eventually translate into pond management techniques with improved nutrient utilization, reduced negative environmental impacts and more reliable and predictable pond yields.

In the work being proposed here, an initial version of a stochastic pond model will be refined, and a deterministic pond model will be integrated with an agricultural production model. The two distinct efforts will result in models that are useful for: 1) the study of pond management practices and the evaluation of possible production targets; 2) the analysis of environmental impacts from aquaculture; and 3) the study of nutrient and resource cycling in integrated agriculture/aquaculture systems. The two efforts are presented separately below.

Invesitgations to be Conducted

Relationship Between Carbon Input and Sediment Quality in Aquaculture Ponds
Stochastic Modeling of Temperature, Dissolved Oxygen and Fish Growth Rate in Aquaculture Ponds