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Water resource management has immense importance in the modern world. A large amount of water is wasted due to inefficient management of rivers, lakes and other water bodies associated with them. In order to achieve improved management of water resources, control and decision support systems can be employed. To design control systems for a river, a river model is required. Traditionally, the Saint Venant equations have been used for modelling purposes. The equations describe river flows accurately, however, they are complex, non-linear and require many unknown parameters. It is therefore difficult to use them for control design purposes. On the other hand, data-based models have proven to be very useful in control design for rivers. In this thesis, different data-based modelling methods are explored, and they are applied to the data from the upper part of Murray River in Australia. For each method, the thesis analyses the ease with which available prior knowledge can be incorporated in the modelling procedure and the ability of the obtained models to describe the river well. For efficient river control, forecasts of future water demands and flows in the unregulated tributaries are required to be taken into account. A Stochastic Model Predictive Control (S-MPC) or a randomised version of it can not only accommodate such forecasts, but it can also handle physical and environmental constraints well. However, due to uncertainties in the forecasts, the feasibility of optimisation problems cannot always be guaranteed in the presence of constraints. This thesis proposes an S-MPC based river control schemes, that not only incorporate the forecasts, but also ensure feasibility of the optimisation problems. The schemes are successfully applied in simulations to the past data from the upper part of Murray River. Another important aspect of river management is to mitigate flood risks. An ideal strategy is to reduce the risk of severe floods, and at the same time not being overl

River restoration practices aiming to sustain wild salmonid populations have received considerable attention in the Unites States and abroad, as cumulative anthropogenic impacts have caused fish population declines. An accurate representation of local depth and velocity in designs of spatially complex riffle-pool units is paramount for evaluating such practices, because these two variables constitute key instream habitat requirements and they can be used to predict channel stability. In this study, three models for predicting channel hydraulics-1D analytical, 1D numerical and 2D numerical-were compared for two theoretical spawning habitat rehabilitation (SHR) designs at two discharges to constrain the utility of these models for use in river restoration design evaluation. Hydraulic predictions from each method were used in the same physical habitat quality and sediment transport regime equations to determine how deviations propagated through those highly nonlinear functions to influence site assessments. The results showed that riffle-pool hydraulics, sediment transport regime and physical habitat quality were very poorly estimated using the 1D analytical method. The 1D and 2D numerical models did capture characteristic longitudinal profiles in cross-sectionally averaged variables. The deviation of both 1D approaches from the spatially distributed 2D model was found to be greatest at the low discharge for an oblique riffle crest with converging cross-stream flow vectors. As decision making for river rehabilitation is dependent on methods used to evaluate designs, this analysis provides managers with an awareness of the limitations used in developing designs and recommendations using the tested methods. © 2008 John Wiley & Sons, Ltd.

The deterministic Riverstrahler model of river functioning is applied for the first time to sub-arctic catchments. Seasonal nutrient (N, P, Si) deliveries to the coastal zone are simulated, and nutrient annual fluxes are established for the nearly pristine river Kalix (hereafter called Kalixalven) and the heavily dammed river Lule, (hereafter called Lulealven) both located in Northern Sweden and draining into the Bothnian Bay, Baltic Sea. For Kalixalven simulations are performed with a runoff calculated from precipitation, evapo-transpiration and temperature data for the period 1990-1999, using a hydrological model calibrated on observed monthly discharges at the river outlet. The same hydrological parameters are used to calculate specific runoff for the Lulealven basin in absence of dam regulation. Reservoir filling and emptying are simulated using a simplified representation of their management rules. Diffuse sources of nutrient are evaluated according to land cover of the catchment. The simulated seasonal trends are within the range of the observed data, in particular for discharge, dissolved silica, total phosphorus, inorganic nitrogen and total organic carbon. Specific runoff is 50% higher in the Lulealven than in the Kalixalven watershed due to higher altitudes and precipitations. Average silica, nitrate and phosphorus concentrations are much lower in Lulealven than in Kalixalven. Comparison of model results for the Lulealven with and without dams shows a reduction of respectively 25% and 30% in silica and phosphorus fluxes delivered at the outlet, while nitrogen delivery is increased by 10% in the dammed vs. undammed river system. The model allows assessing the respective role of reservoir trapping of nutrient in the reservoir through algal uptake and sedimentation, and of changes in the vegetation induced by flooding the valley formerly covered by forests and wetlands.