Water Quality Management in Aquacultural Production using Aquasmat
Keywords:
Fish, Feed, Water quality, AQUASMAT, Applications
Abstract
This paper introduces a newly developed model, AQUASMAT, and its potential applications, especially in the tropical environment. AQUASMAT can help identify and quantify the cause, effect and relationships between water quality parameters, the physical environment and aquatic ecosystem. It is well suited for production ponds and other water bodies, as well as for predicting general pond dynamics. AQUASMAT is a valuable tool for water quality modeling and aquacultural management. In this overview, the model is shown to have the following capabilities: (1) a graphical user interphase and management data capability; (2) identification and quantification of cause and effect relationships of feed with respect to chemical water quality parameters, the physical environment, and aquatic ecosystem; (3) analysis of complex relationships in impaired production ecosystems and suggestion of cause and management of the various causes of impairment; (4) prediction of feed wastage and economic viability of the production system; (5) presentation of the effect of different management operations on fish yield; (6) tracking of more than 40 parameters which are not easily obtainable from conventional measurement procedures. The model can thus help to fill the knowledge gap and also explore cost-effective and appropriate management measures for ailing aquacultural production systems.References
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Diana J.S. (1993). Conservation and utilization of fish genetic resources in capture and culture fisheries. In “Cohen J.I.; Potter C.S. (Eds). Case Studies of Genetic Resource Conservation in Natural Habitats. American Association for the Advancement of Science (AAS) Publication. 89–103.
FAO (2005). Yearbook of Fishery Statistics. Vol.100/2. Rome
Hargreaves, J.A. and Tomasso, J.R. (2004). Environmental Biology. In “Tucker, C.S. & Hargreaves, J.A. (Eds). Biology and Culture of Channel Catfish”. Developments in Aquaculture and Fisheries Science. Elsevier, Netherlands. 34, 36-68.
Hargreaves, J.A. and Tucker, C.S., (2003). Defining loading limits of static ponds for catfish aquaculture. Aquacultural Engineering, 28, pp.47-63.
Hargreaves, J.A. (1997). A simulation model of ammonia dynamics in commercial catfish ponds in the southeastern United States. Aquacultural Engineering 16, 27 – 43.
Harris, G.P. (1986). Phytoplankton Ecology: Structure, Function and Fluctuation. Chapman and Hall, London, 384 pp.
Le Cren, E.P., and Lowe-McConnell, R.H. (1980). The Functioning of Freshwater Ecosystems. Cambridge University Press, Cambridge, UK. 588 pp.
Mwegoha, W. J. S.; Kaseva, M. E. and Sabai, S. M. M. (2010). Mathematical modeling of dissolved oxygen in fish ponds. African Journal of Environmental Science and Technology Vol. 4(9), pp. 625-638. Available online at http://www.academicjournals.org/AJEST
Park, R.A. and Clough, J.S. (2009). AQUATOX (Release 3) Modeling Environmental Fate and Ecological Effects in Aquatic Ecosystems. Volume 2: Technical Documentation U.S. Environmental Protection Agency Washington DC.
Tucker, C.S. (1985). Organic matter, nitrogen, and phosphorus content of sediments from channel catfish ponds. Mississippi Agricultural and Forestry Experiment Station Research Report 10-7, Mississippi State University, Mississippi, USA. 3p.
Wang, Y.H.; Turton, R.; Semmens, K. and Borisova, T. (2008). Raceway design and simulation system (RDSS): An event-based program to simulate the day-to-day operations of multiple-tank raceways. Aquacultural Engineering, 39, 59–71.
Welcomme, R.L. (1996). Aquaculture and world aquatic resources. In: Baird, D.J.; Beveridge, M.C.M.; Kelly, L.A.; Muir, J.F. (Eds.), Aquaculture and Water Resource Management. Blackwell Sciences, Oxford, pp. 1_/18.
