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As flooding is inevitable and becoming increasingly frequent, efficient flood management strategies should be developed to manage floods, especially in developing countries. Rainfall-Runoff-Inundation (RRI) model, which is based on a diffusive wave model, was applied to Gin River Basin, Sri Lanka using daily rainfall data. The RRI model was calibrated and validated for three past flood events (2003, 2016, and 2017) based on observed discharge data and inundation maps developed from ground survey data and satellite images. The Nash–Sutcliffe efficiency (NSE) values for river discharge obtained at the downstream gauging station were greater than 0.7 during both the calibration and validation experiments. Simulated inundation data showed good agreement with the limited observational records. The Critical Success Index (CSI) value for inundated extent in large flood event (May 2017) within downstream was greater than 0.3. Incorporation of embankment information significantly improved the accuracy of the simulation of inundation extent during large flood events (May 2017). The CSI value without embankment information for large flood event (May 2017) within downstream decreased to around 0.1. On the other hand, the embankment information was less useful for smaller flood events caused by less extreme rainfall. Inclusion of embankment information for large flood events enhanced the model performance, thus ensuring the availability of accurate inundation information for efficient flood risk planning and management in the basin.

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.

Hydrologic modelling is widely used as a tool for making decisions and predictions in planning and managing water resources. Successful application of a hydrologic model depends upon careful calibration and validation using appropriate performance measures in satisfying corresponding performance evaluation criteria. Performance of MIKE 11 NAM rainfall runoff model was assessed using four calibration objectives and their different combinations, as applied to upper Gin catchment, Sri Lanka. The four calibration objectives measured different aspects of hydrograph: good water balance, good overall agreement of the shape of the hydrograph, good agreement for peak flows, and good agreement for low flows. Their numerical performance was measured using four objective functions from which fifteen calibration schemes were formed (four single objective schemes and eleven multi-objective schemes). Using aggregated distance measure, equal weights were assigned to the four objective functions. Shuffled complex evolution algorithm was used to solve the multiple calibration objective problems. Model performance was evaluated using three criteria: Nash-Sutcliffe coefficient (NSE), percent bias (PBIAS) and coefficient of determination (R 2 ). Results revealed significant trade-offs between the objective functions, highlighting that no single calibration objective was able to depict all the aspects of the hydrograph simultaneously. However, multi-objective calibration yielded more accurate and consistent simulations covering different aspects of the hydrograph, simultaneously with overall best performance shown for combination of the four objective functions satisfying all the performance evaluation criteria (NSE=0.56, R 2 = 0.56, PBIAS=17%), compared to the single-objective calibration. Instead of using R 2 alone, use of the corresponding regression slope as a weighing factor of R 2 was recommended following further analysis of simulation results.