No abstract

This study was aimed at establishing a detailed understanding on the prevailing constituent loads and concentrations in the Gin river flow at Baddegama, and to reveal how they are related to the river flow. Concentrations and constituent loads in the Gin river at Baddegama (6°11'23" N, 80°11'53" E) during 2001-2009 were modelled in the study using load-discharge rating curve for estimating constituent loads in rivers. Constituents considered in the study included chloride, total alkalinity, total residue, total hardness, calcium and total iron. For each constituent, the samples tested generally at monthly frequency during 2001-2009 at Baddegama were used in conjunction with the observed daily stream flow data to develop and calibrate a multiple regression model. The regression models developed for all constituent loads showed higher coefficients of determination values reflecting a strong relationship between the estimated rating curve and measured constituent loads. The estimated constituent loads had substantial temporal variation and generally peaked in May and October, coinciding with high flows. Load estimates of chloride, total alkalinity, total hardness, and calcium indicated statistically significant downward temporal trends. For the total residue, a statistically significant upward trend was indicated. Concentrations of chloride, total alkalinity, total residue, total hardness, and calcium were well below the highest desirable levels of specifications cited in the Sri Lanka Standards for potable water. However the concentration of total iron, which ranged between 0.8 mg/L and 4.8 mg/L significantly exceeded the highest desirable limit for potable water and the maximum permissible limit for inland waters of Sri Lanka.

Abstract:Modelling approach is a useful tool which provides information on spatial distribution of basin hydrologic components. In that context distributed hydrological models play a vital role in efficient planning and managing water resources systems. But their applications are partly limited due to the requirement of large amount of data which are not always available and difficulties in obtaining such data due to bureaucratic constraints. Global public domain data sets have become increasingly available on the internet and it is appropriate to make use of such data which can often be supplemented for ground-based data. The objective of this study is to investigate the applicability of the distributed hydrological model, YHyM/BTOPMC to simulate the major hydrological characteristics in Gin ganga watershed utilizing the global data sets readily available in public domain along with the local available rainfall and discharge data. Gin ganga is a river which is one of the main sources of water supply to the southern region of Sri Lanka. It's catchment entirely lies within the wet zone of the country and frequently subjected to flooding during the rainy seasons. Hence, it is vital to comprehend the hydrology of the watershed in order to gain knowledge on current and future hydrological conditions. In the study, YHyM/BTOPMC model performance was evaluated by the Nash-Sutcliffe Efficiency (E) and the volume ratio of simulated discharge to observed discharge (Vr). The results show that the overall hydrological behaviour of the Gin ganga watershed is adequately simulated by the model. Further the results are discussed in the context of how the model simulation results replicate the temporal variation of basin hydrological characteristics such as ground water saturation deficit, soil moisture states, base flow etc.

This study investigates the applicability of global public domain data versus local detailed data for distributed hydrological modelling using a case study approach. Major hydrological characteristics in Gin river basin are simulated in the study by applying the distributed hydrological model, YHyM/BTOPMC (University of Yamanashi Distributed Hydrological Model with Blockwise use of TOPMODEL and Muskingum-Cunge method) utilizing the global public domain data sets (Case 1) and local detailed data sets (Case 2). Evaluation of the model outputs for Case 1 and Case 2 shows that the overall hydrological behavior of the Gin river basin is adequately simulated by the model for both Case 1 and Case 2. The simulated average annual discharge volumes in Case 1 and Case 2 at Agaliya during 2002-2006, vary from the observed average annual discharge volume by ?4.25 and ?1.31 %, respectively. In general, simulated daily discharge in Case 1 shows slightly higher value than that of Case 2 resulting a difference of 0.9 m 3 /s during 2002-2006, on average. The relative differences between the simulated daily discharges in Case 1 and Case 2 become higher during the recession limbs of the flow hydrographs at Agaliya. Reasons for these variations are being discussed in the study. The results of the study give motivation towards the use of global public domain data for hydrologic simulations in data-poor (limited availability of local data) basins.

Human induced impacts on the river systems result in decrease in water quality, which is generally reflected by an increase of particulate matter in rivers. Turbidity and suspended solids are part of physical and aesthetic parameters and good indicators of other pollutants that are carried as sediment in suspension. Study objectives were to define the relation between turbidity and total suspended solid (TSS) concentration in Gin river at Baddegama (6°11'23" N, 80°11'53" E) in developing an estimation technique for TSS load, and to reveal how turbidity and TSS load vary with the streamflow. Linear regression model developed between turbidity and TSS concentration showed strong positive correlation (R 2 = 0.98). Results strongly suggest turbidity is a suitable monitoring parameter for TSS, where TSS evaluation is crucial when logistical and financial constraints make TSS sampling impractical. Mean daily TSS loads in the Gin river at Baddegama during 2000-2009 were modeled in the study using load-discharge rating curve for estimating constituent loads in rivers. Relatively strong relationship (R 2 = 0.85) was observed between the rating curve estimated and observed TSS loads. Estimated TSS loads were having substantial temporal variation and generally peaked in May and October, coinciding with the high flows. Turbidity which ranged between 2.3 NTU (Nephelometric Turbidity Units) and 195 NTU significantly exceeded the maximum permissible limits of the water quality standards set for the potable water as well the inland waters of Sri Lanka. Since there was no specific water quality standards developed for TSS in Sri Lanka to compare with the present values, TSS concentrations were compared with the permissible total solid levels. TSS concentrations which ranged between 2.4 mg/l and 204 mg/l were well below the maximum permissible total solid level cited in the Sri Lanka standards for potable water. Understanding on this turbidity and TSS characteristics in Gin river flow might be useful for water managers and planners to adjust operations accordingly at water treatment plants.