Digital Repository

Forecasting weekly fish production of Siyambalangamuwa reservoir in

Show simple item record

dc.contributor.author S.S. Wimalasena en_US
dc.contributor.author U.S. Amarasinghe en_US
dc.contributor.author M.G. Kularatne en_US
dc.contributor.author U. K. Jayasinghe en_US
dc.contributor.author Mudalige en_US
dc.date.accessioned 2014-12-23T08:31:06Z
dc.date.available 2014-12-23T08:31:06Z
dc.date.issued 2014
dc.identifier.citation Annual Research Symposium,Faculty of Graduate Studies, University of Kelaniya, Sri Lanka; 2014 :93p en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/4912
dc.description.abstract Provision of accurate and timely information is vital for sustainable fisheries management. The forecasts on fish stocks obtained through econometric models estimated precisely using time-series data are, therefore, of paramount importance to all stakeholders, including policy planners and other key players in the food value chain for fisheries. In the present study, an attempt was made to forecast the weekly fish production in Siyambalangamuwa reservoir (788 ha) in the North Western Province of Sri Lanka, where the fishery is dominated by exotic cichlid species of Orechromis mossambicus and O. niloticus (accounting for over 80% of the landings) with a view to investigating the possible impacts of its key intended function of releasing water for irrigation on fish production as the secondary use, and in turn, to determine the correct timing for stocking fish fingerlings into the reservoir. A series of Autoregressive Integrated Moving Average (ARIMA) models were specified to the fish production data collected from ?log-book records? maintained by the Fishermen�s Cooperative Society covering the period of 53 weeks (i.e. from 01st June 2013 to 01st June 2014). Autocorrelation and Partial Autocorrelation functions of respective time series; Anderson-Darling test; Mean Square (MS) analysis, and Autocorrelation Plots drawn for residuals obtained through the Minitab (version 15) Statistical Software were used to select the best-fitted model, i.e. the ARIMA (2.1.1). The forecasted fish production from 54th to 59th week, respectively, are: 257.3, 435.8, 423.3, 343.1, 356.9, and 392.1 Kg showing a ?decrease? in fish production during the 54th week of study period followed by an ?increase? during the 55th and 56th weeks, and a ?decrease? in production during the 57th week followed by an ?increase? during the 58th and 59th weeks. The possible reasons for this fluctuation of fish production overtime and its implications for inland fisheries management in Siyambalangamuwa reservoir are under in-depth investigation. en_US
dc.publisher Book of Abstracts, Annual Research Symposium 2014 en_US
dc.title Forecasting weekly fish production of Siyambalangamuwa reservoir in
dc.type Article en_US
dc.identifier.department Zoology and Environmental Management en_US


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search Digital Repository


Browse

My Account