|A water budget model for pond aquaculture
Shree S. Nath, Department of Biological and Agricultural Engineering, University of Georgia, Athens, GA 30602
John P. Bolte, Department of Bioresource Engineering, Oregon State University, Corvallis, OR 97331
15 October 1998, CRSP Research Report 98-126
Abstract A water budget simulation model that can be used for forecasting water requirements for aquaculture ponds has been developed. Water sources considered in the model include regulated inflow, precipitation and runoff, whereas water losses include evaporation, seepage, effluent discharge, and overflow. The model has been validated for ponds located at the Asian Institute of Technology (AIT), Thailand and at El Carao, Honduras which are, respectively, located in the humid and dry tropics. Simulation results indicate that precipitation accounted for 69.8% of the total water gains for the AIT and 43.2% for El Carao. Regulated inflow provided 27% of the gains for AIT and 52.8% for El Carao. Runoff gains were minimal at both locations due to small watershed areas. Evaporation accounted for 54.9 and 40.1% of the overall water loss predicted for the AIT and El Carao locations, with seepage accounting for the remaining loss. Predicted water requirements at AIT over a 5-month period exceeded actual amouts by 14.9%, apparently because seepage loss was over-estimated. For El Carao, however, predicted water requirements were only 78.2% of the amount actually added, apparently due to poor estimates of evaporative water loss which averaged 0.32 cm day-1 compared to pan evaporative measurements of 0.43 cm day-1. In contrast, the predicted evaporative water loss for the AIT pond (0.47 cm day-1) closely matched pan evaporation measurements (0.45 cm day-1). The availability of relative humidity and cloud cover data for AIT explain the higher accuracy in evaporative water loss estimates, and therefore water requirements, compared to El Carao. If comprehensive weather datasets are available, the water budget model developed herein is a useful tool for estimating pond water requirements at individual facilities located in different geographical regions.
This abstract was excerpted from the original paper, which was published in Aquacultural Engineering, 18(1998):175-188.
José Aguilar-Manjarrez, Faculty of Marine Sciences, Autonomous University of Baja California, Ensenada, Mexico
Shree S. Nath, Department of Bioresource Engineering, Oregon State University, Corvallis, Oregon USA
15 October 1998, CRSP Research Report 98-127
Abstract The present study is an update of an earlier assessment of warm-water fish farming potential in Africa, by Kapetsky (1994). The objective of this study was to assess locations and areal expanses that have potential for warm-water and temperate-water fish farming in continental Africa.
The study was based on previous estimates for Africa by the above author, and on estimates of potential for warm-water and temperate-water fish farming in Latin America by Kapetsky and Nath (1997). However, a number of refinements have been made. The most important refinement was that new data allowed a sevenfold increase in resolution over that used in the previous Africa study, and a twofold increase over that of Latin America (i.e. to 3 arc minutes, equivalent to 5 km x 5 km grids at the equator), making the present results more usable in order to assess fish farming potential at the national level.
A geographical information system (GIS) was used to evaluate each grid cell on the basis of several land-quality factors important for fish-farm development and operation regardless of the fish species used. Protected areas, large inland water bodies and major cities were identified as constraint areas, and were excluded from any fish farming development altogether. Small-scale fish farming potential was assessed on the basis of four factors: water requirement from ponds due to evaporation and seepage, soil and terrain suitability for pond construction based on a variety of soil attributes and slopes, availability of livestock wastes and agriculture by-products as feed inputs based on manure and crop potential, and farm-gate sales as a function of population density. For commercial farming, an urban market potential criterion was added based on population size of urban centres and travel time proximity. Both small-scale and commercial models were developed by weighting the above factors using a multi-criteria decision-making procedure.
A bioenergetics model was incorporated into the GIS to predict, for the first time, fish yields across Africa. A gridded water temperature data set was used as input to a bioenergetics model to predict number of crops per year for the following three species: Nile tilapia (Oreochromis niloticus), African catfish (Clarias gariepinus) and Common carp (Cyprinus carpio). Similar analytical approaches to those by Kapetsky and Nath (1997) were followed in the yield estimation. However, different specifications were used for small-scale and commercial farming scenarios in order to reflect the types of culture practices found in Africa. Moreover, the fish growth simulation model, documented in Kapetsky and Nath (1997), was refined to enable consideration of feed quality and high fish biomass in ponds.
The small-scale and commercial models derived from the land-quality evaluation were combined with the yield potential of each grid cell for each of the three fish species to show the coincidence of each land-quality suitability class with a range of yield potentials. Finally, the land quality-fish yield potential combinations were put together to show where the fish farming potential coincided for the three fish species.
The results are generally positive. Estimates of the quality of land show that about 23% of continental Africa scored very suitable for both small-scale and commercial fish farming. For the three fish species, 50-76% of Africa's land has the highest yield range potential, and the spatial distribution of this yield is quite similar among the species and farming systems. However, the spatial distribution of carp culture potential was greater than for Nile tilapia and African catfish. Combining the two farming system models with the favourable yields of the three fish species suggest that over 15% of the continent has land areas with high suitability for pond aquaculture.
The final fish farming potential estimates for the three species together show that about 37% of the African surface contains areas with at least some potential for small-scale farming, and 43% for commercial farming. Moreover, 15% of the same areas have the highest suitability score, and suggest that for small-scale fish farming, from 1.3 to 1.7 crops/y of Nile tilapia, 1.9 to 2.4 crops/y of Africa catfish and 1.6 to 2.2 crops/y of Common carp can be achieved in these areas.
Estimates for commercial farming range from 1.6 to 2.0 crops/y of Nile tilapia, 1.3 to 1.7 crops/y of Africa catfish and 1.2 to 1.5 crops/y of Common carp. From a country viewpoint, the results are also generally positive. For small-scale farming of the three species, 11 countries scored very suitable in 50% or more of their national area. The corresponding results for commercial farming were that 16 countries scored very suitable in 50% or more of their national area.
Farm location data from Zimbabwe, Kenya, Uganda and Malawi were used to verify the GIS-based predictions of fish farming potential, from the standpoint of the farming system models combined with fish yields. This verification procedure indicated that the models used in the study are in general fairly accurate for strategic planning of aquaculture development.
This abstract was excerpted from the original paper, which was published in CIFA Technical Paper No. 32(1998), FAO, 170 pp.The full version of this publication is available here.
Yang Yi, Agricultural and Aquatic Systems Program, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120 Thailand
15 October 1998, CRSP Research Report 98-128
Abstract A bioenergetics growth model for Nile tilapia in fertilized ponds, which linked Nile tilapia growth with limiting nutrients in pond water, was developed. The model incorporated six key variables affecting Nile tilapia growth in fertilized ponds: body size, water temperature, photoperiod, dissolved oxygen, unionized ammonia and food availability. In the model, food availability was estimated by a relative feeding level parameter, which was a function of potential net primary productivity based on limiting nutrients, and standing crop of Nile tilapia. The model was validated using growth data of Nile tilapia in 30 fertilized ponds, and successfully detected growth variations among ponds receiving the same nitrogen and phosphorus inputs. The model described 76% of the variance in growth in these ponds, and the relationship between predicted and observed growth rates had a slope of 0.93 and an intercept of 11.51, not significantly different from 1 and 0, respectively. The model indicated that the growth variations were caused by carbon limiting primary production during 55-99% of the culture period. Sensitivity analysis indicated that the parameters related to net energy from feeding were more sensitive than those related to fasting catabolism, and that the growth was most sensitive to photoperiod and then food availability when DO was above its critical limit (1.0 mg l-1), but was most sensitive to DO when it was below the critical limit. Tilapia growth was more sensitive to DO than UIA. Initial tilapia size was the least sensitive variable when UIA was above the critical limit in the model. Compared with previous models, this study provides a more reasonable and accurate way to estimate relative feeding level (f) based on fish standing crop and potential net primary productivity derived by a limiting nutrient.
This abstract was excerpted from the original paper, which was published in Aquacultural Engineering, 18(3):157-173.
Karen L. Veverica, Department of Fisheries and Allied Aquaculture, Auburn University, Alabama, USA
Nathanael Hishamunda and Pélagie Nyirahabimana, Department of Agricultural Economics and Rural Sociology, Auburn University, Alabama, USA
15 April 1999, CRSP Research Report 99-129
Abstract This report discusses the first phase of the National Fish Culture Project in Rwanda that extended from 1983 through 1988. The project focused solely on fish culture and endeavored to improve fish production in existing ponds through a dynamic extension service. Physical, social, and economic constraints to fish culture in Rwanda are presented in addition to background on the project's extension strategy and a description of the extension agent training. Fifty-five extension agents were trained, and upon completion of the project, approximately 3,000 ponds had been covered through the project's extension efforts. Over the four-year duration of the project, average pond productivity increased from 3.4 to 14.5 kg are-1 yr-1. A 41% internal rate of return was calculated for fish culture as a farm enterprise. The increased cost to maintain the extension program in comparison with the increase in fish production resulted in a 27% internal rate of return to the government of Rwanda. Finally, recommendations for future fish culture projects are discussed in addition to a five-phase aquaculture development plan.
This abstract was excerpted from the original article which was published as CRSP Research Report 99-129 by the Information Management and Networking Component of the Pond Dynamics/Aquaculture Collaborative Research Support Program (PD/A CRSP).
Claude E. Boyd and Bartholomew W. Green, Department of Fisheries and Allied Aquacultures, Alabama Agricultural Experiment Station, Auburn University, Alabama 36849 USA
15 April 1999, CRSP Research Report 99-130
Abstract This study was conducted to determine the dry matter and elemental composition of two species of tilapia, Oreochromis aureus and O. niloticus. Thirty-two O. aureus (total length, 85-223 mm; live weight, 10.2-210 g) and 34 O. niloticus (total length, 61-282 mm; live weight, 13.7-282 g) were dried, cooled, and weighed to the nearest 0.01 g to calculate the percentage dry weight. From these samples, carbon and nitrogen analyses were made and ash content was determined. To calculate the concentrations of phosphorus, calcium, magnesium, sodium, potassium, iron, manganese, zinc, and copper, five ml of a 2 N acid solution were added to the ash. The mixture was dried and the remaining residue was diluted to volume with the 2 N acid solution in a 100 ml volumetric flask and filtered through acid-washed filter paper. Element concentrations of the two species of tilapia were calculated. Though fish samples represented a wide range in total length and total weight, regression analyses of concentrations of dry matter, ash, and individual elements (Y) on total length (X) did not reveal an influence of fish size on composition. Minor elements such as iron showed greater variation whereas major elements, ash, and dry matter showed less variation. Tilapia are comprised of approximately 25% dry matter--which consists of approximately 20% inorganic matter (ash), 80% organic matter, and 44% carbon--and 75% water. The average nitrogen concentration for both species combined was 8.7% and the protein content of the whole fish was approximately 56.6%. A correlation matrix was developed from simple linear regressions conducted between all combinations of individual elements in each species. Significant correlations among the elements were found, indicating that fish probably have a fairly consistent proportion of the different elements contained in their bodies. Two examples are provided illustrating how the data compiled in this study were used to compute efficiencies of nutrient utilization and potential nutrient loading in aquaculture ponds.
This abstract was excerpted from the original paper, which was published in Journal of the World Aquaculture Society, 29(1):125-128.
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