Volume 59 (2011): Issue 3 (September 2011)

The objective of this paper is to simulate flow frequency distribution curves for Amazon catchments with the aim of scaling power generation from small hydroelectric power plants. Thus, a simple nonlinear rainfall-runoff model was developed with sigmoid-variable gain factor due to the moisture status of the catchment, which depends on infiltration, and is considered a factor responsible for the nonlinearity of the rainfall-runoff process. Data for a catchment in the Amazon was used to calibrate and validate the model. The performance criteria adopted were the Nash-Sutcliffe coefficient (R²), the RMS, the Q_95% frequencyc flow percentage error, and the mean percentage errors ranging from Q_5% to Q_95%.. Calibration and validation showed that the model satisfactorily simulates the flow frequency distribution curves. In order to find the shortest period of rainfall-runoff data, which is required for applying the model, a sensitivity analysis was performed whereby rainfall and runoff data was successively reduced by 1 year until a 1.5-year model application minimum period was found. This corresponds to one hydrological year plus the 6-month long "memory". This analysis evaluates field work in the ungauged sites of the region.

This study examines two long-term time series of nitrate-nitrogen concentrations from the River Ouse and Stour situated in the Eastern England. The time series of monthly averages were decomposed into trend, seasonal and cyclical components and residuals to create a simple additive model. Residuals were then modelled by linear time series models represented by models of the ARMA (autoregressive moving average) class and nonlinear time series models with multiple regimes represented by SETAR (self-exciting threshold autoregressive) and MSW (Markov switching) models. The analysis showed that, based on the minimal value of residual sum of squares (RSS) of one-step ahead forecast in both datasets, SETAR and MSW models described the time series better than models ARMA. However, the relative improvement of SETAR models against ARMA models was low ranging between 1% and 4% with the exception of the three-regime model for the River Stour where the improvement was 48.9%. In comparison, the relative improvement of MSW models was between 44.6% and 52.5 for two-regime and from 60.4% to 75% for three-regime models. However, the visual assessment of models plotted against original datasets showed that despite a high value of RSS, some ARMA models could describe the analyzed time series better than AR (autoregressive), MA (moving average) and SETAR models with lower values of RSS. In both datasets MSW models provided a very good visual fit describing most of the extreme values. The results of this work could be used as a base for construction of other time series models used to describe or predict nitrate-nitrogen concentrations.

Flow in compound channels with overbank flows becomes more complex because of shear interactions between flows in main channel and flood plains, lateral momentum transfer and secondary flows. Compound channels have interesting applications in flood control, civil engineering and environmental management. Because it is difficult to obtain sufficiently accurate and comprehensive understandings of flow in natural compound rivers, the developed models of flow in overbank flows have many uncertainties. The main aims of this paper are to analysis and quantify the uncertainty results of quasi two dimensional flow modeling in compound channels. In this paper a quasi two dimensional depth averaged model, known as Shiono and Knight Model (SKM), in compound channel is used and uncertainty analysis of its simulation results is done based on Monte-Carlo simulations. Results indicated that although the SKM model can simulate quasi-two-dimensional flow accurately but it has many uncertainties in simulation results. The uncertainties of model results in high are greater than low flows. Also uncertainties in discharge capacity and shear stress are greater than those for velocity profiles. Overall results cleared that the SKM model, beyond from its strong physical basics, requires rigorous effort on local calibration processes, especially for high flood flows and these limit its global applicability and generalities.

The paper introduces the test of aggregation as a simple, inexpensive method of evaluating suspension quality during drinking water treatment, suitable for use in both laboratory and operation conditions. The procedure and derivation of the aggregation test is described. The method is used for a demonstration of the influence of mean velocity gradient and mixing time on floc properties formed during the aggregation in a Couette reactor. It was proved that with increasing velocity gradient, the size of the aggregates present in the suspension decreases, and the suspension is substantially more homogeneous than with use of lower gradients. Further, it was confirmed that the size of aggregates reaches the steady state after a specific mixing time, which becomes shorter with increasing value of velocity gradient.

The follow up research into the IHDS process was carried out with a Couette device. The outcome of this study provides a comprehensive understanding of the effect that both the agitation intensity and the agitation time have on the kinetics and the mechanism of the aggregation process. The results obtained confirm the very favourable influence of high agitation intensity for the formation of more compact and dense aggregates than those formed by the accustomed flocculation conditions with low agitation intensity. This research also proved that the agitation intensity and time are the inherent means profoundly influencing the properties of the resultant aggregates such as their size, shape, density and homogeneity. Further, it was confirmed that the aggregation process passes through a minimum. Furthermore, it was verified that the aggregation process takes place in four consecutive phases, namely a) the phase of formation, b) the phase of compaction, c) the phase of a steady (equilibrium) state and d) most probably the phase of inner restructuring. The pattern of the aggregates development in these phases remains the same irrespective of the magnitude of the velocity gradient applied but the time at which these phases are completed is velocity gradient dependent. Last but not least this study proved that the dimensionless product Ca = G T = const. has no general validity.

Study is focused on the numerical modeling of fly-ash transport in three sands, which was experimentally studied in the laboratory. Sands were packed in glass cylinders with diameter of 5.52 cm and height of 18 cm. Sands were also packed in plastic cylinders with diameter of 30 cm and height of 40 cm. The fly-ash and pulse infiltrations were applied on the top of all cylinders. Visually observed and gravimetrically evaluated fly-ash migration in small cylinders corresponded to fly-ash mobility in large columns detected using the SM400 Kappameter. The HYDRUS-1D code was used to simulate observed fly-ash transport. Parameters of soil hydraulic functions were either obtained using the Tempe cells and the RETC program or estimated using numerical inversion of transient water flow data measured in both types of columns using HYDRUS-1D. Parameters characterizing colloid transport in sands were then estimated from the final fly-ash distribution in sandy columns using attachment/detachment concept in HYDRUS-1D. Fly-ash mobility increased with increasing sand particle sizes, e.g. pore sizes. Particle sizes and pore water velocity influenced the attachment coefficient, which was calculated assuming filtration theory. The same longitudinal dispersivity, sticking efficiency and detachment coefficient sufficiently characterized fly-ash behavior in all sands.