Many reservoirs provide multiple benefits to people around the world, in addition to primary uses such as irrigation. Thus, reservoir management should address their multiple uses. The water quality of ten irrigation reservoirs in Sri Lanka was examined in the present study with the objective of better understanding the effects of hydrological regimes on reservoir water quality and trophic state. Basic limnological parameters pertinent to the nutrient loads to, and trophic state of, the reservoirs were collected from June 2013 to February 2016. The sampling period was arbitrarily divided into two periods of approximately similar duration (period 1 = June 2013–September 2014; period 2 = October 2014–February 2016) to investigate whether or not there was a seasonal variation in the water quality parameters. Although temporal and spatial variations were observed, most water quality parameters were within the levels acceptable for drinking water standards. The 10 reservoirs were also ordinated by principal component analysis (PCA) on the basis of the water quality parameters of the two sampling periods in a two‐dimensional score plot. Reservoirs in the first principal component (PC1) axis were represented by negative scores attributable to the dissolved oxygen concentration and pH and, to a lesser extent, by electrical conductivity and chlorophyll‐a concentration. Positive scores in PC1 were represented by reservoirs with a score loading attributable to alkalinity, nitrate concentration, Secchi depth, temperature and seston weight and, to a lesser extent, from the total phosphorus concentration. There was a significant negative correlation of PC1 scores with relative reservoir water‐level fluctuation (RRLF; the ratio of mean reservoir water‐level amplitude to mean reservoir depth). Furthermore, Carlson's trophic index also were influenced by RRLF, although not by hydraulic retention time (HRT), indicating allochthonous nutrient inputs into the irrigation reservoirs were mainly governed by RRLF, but not by HRT. Thus, the results of the present study provide useful insights into achieving desirable reservoir water quality through the manipulation of the hydrological regime.
As fisheries production in reservoirs of most countries is a secondary use, challenges for improved management of fisheries should be addressed by building partnership between fisheries and other interested groups such as agriculture concerned with water management. Attempts were therefore made to develop empirical fish yield predictive models in ten irrigation reservoirs of Sri Lanka incorporating morphological, edaphic and hydrological parameters together with fishing intensity, with a view to investigating their influence on fish yields. Reservoir fish yield was found to be significantly correlated with two formulations of morpho-edaphic index (i.e., conductivity in μS cm-1 /mean depth in m [MEIc] and alkalinity in m. equiv. l-1)/mean depth in m [MEIa]), and a relative reservoir level fluctuation index (RRLF), defined as the mean amplitude of the annual reservoir level fluctuations divided by the mean depth of the reservoir. Both MEIc and MEIa also had significant positive ln-ln relationships with RRWL, indicating that RRWL can be used as an independent variable in reservoir fish yield prediction. Reservoir fish yield was also related to fishing intensity (FI in boat-days ha-1 , yr-1) conforming to a ln-linear regression model (p<0.05). When MEIa, MEIc and RRWL were used as predctor variables together with FI, reservoir fish yield (FY) was multiply correlated as follows: Ln FY = 3.245 + 0.327 Ln MEIa + 0.023 FI (R 2 = 0.355; p< 0.01) Ln FY = 3.403 + 0.249 Ln MEIc + 0.019 FI (R 2 = 0.369; p< 0.01) Ln FY = 1.330 + 0.650 Ln RRWL + 0.016 FI (R 2 = 0.593; p< 0.001) The empirical yield predictive model based on RRWL and FI as independent variables was more robust than those based on MEIa and MEIc, and the former has significant management implications because RRWL can be manipulated by irrigation authorities whereas control of FI is under the jurisdiction of fisheries authorities. Hence, through an effective dialogue between irrigation and fisheries authorities, there is a considerable potential to optimize fish yields in irrigation reservoirs of Sri Lanka.
Management of reservoir water quality is a global challenge due to the natural process of eutrophication and anthropogenic aggravation. In Sri Lanka, irrigation reservoirs support several secondary uses such as fish production, livestock farming, and many communal uses including drinking water supply. In the present study, basic limnological parameters of ten irrigation reservoirs of Sri Lanka were investigated from June 2013 to February 2016, with a view to identifying influence of hydrological regimes on reservoir water quality. Spatio-temporal similarities of water quality parameters were studied employing the self-organizing map (SOM) routine of the artificial neural network application. The sample vectors, classified on the SOM lattice, indicated 6 clusters at 50% similarity level. When reservoir that were categorized according to hydraulic retention time (HRT) and relative reservoir level fluctuation (RRWL; defined as the ratio of the mean reservoir level amplitude to mean depth), were compared with dominant water quality parameters in SOM lattice, it was evident that some productivity-related water quality parameters were influenced HRT and RRWL. The results of the study revealed that HRT and RRWL can essentially be controlled through management of hydrological regimes in irrigation reservoirs, thus, close dialogue between irrigation authorities and other users of reservoir water resources are needed to ensure desired water quality of the reservoirs.
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