Student Number : 9700136A - PhD thesis - School of Civil and Environmental Engineering - Faculty of Engineering and the Built Environment / A sediment budget model in which each steady discharge scours sediment along a trajectory towards ultimate target storage or deposits sediment towards the same ultimate target storage has been conceptualized and developed. The method is aimed at routing sediment in morphologically diverse bedrock-controlled channels in which sediment transport and storage is not a continuous process in space and time and mostly occurs in response to discrete discharges. The relative value of the ultimate stable scour depth (Huss) for each steady discharge with respect to the current scour depth after adding sediment supply determines the potential to scour or store sediment. Scour depths measured at discrete locations along the longitudinal profile of a laboratory pool at discrete times until changes in scour were not discernible for each steady discharge and sediment size have been integrated to provide the Huss and storage depletion curve. The experimentally established dependence of scour depth on critical flow depth, settling velocity and sediment supply formed the basis of generating dimensionless Huss and storage depletion curve from these parameters using the Buckingham π theorem. The optimization of experimental results to generate the storage depletion curve gave the exponent of time (φ) and the exponential decay factor (k) as 0.5 and 0.0040207 respectively. Regression fit of dimensionless Huss and critical flow intensity gave a linear relationship with a gradient of 0.90214, y-intercept of –1.4766 and R2 of 96%. The suitability of the model for budgeting sediment dynamics in a series of connected storage units, the validity of using the relative values of Huss and the current scour depth after adding sediment supply to determine scour potential and the existence of active storage associated with sediment supply for each steady discharge have been confirmed experimentally. Modelling with equivalent steady discharges computed from unit stream power principles on the rising and the falling limbs of the hydrograph resulted in scour on the rising limb of magnitude dependent on the magnitude and sequence of the flood event, and less or no scour on recession. The modelling concepts and approach have thus been validated and the potential to reasonably simulate sediment storage changes in bedrock-controlled rivers demonstrated.

Efficient storage and retrieval of data is critical in today's computing environments and storage systems need to keep up with the pace of evolution of other system components like CPU, memory etc., for building an overall efficient system. With virtualization becoming pervasive in enterprise and cloud-based infrastructures, it becomes vital to build I/O systems that better account for the changes in scenario in virtualized systems. However, the evolution of storage systems have been limited significantly due to adherence to legacy interface standards between the operating system and storage subsystem. Even though storage systems have become more powerful in the recent times hosting large processors and memory, thin interface to file system leads to wastage of vital information contained in the storage system from being used by higher layers. Virtualization compounds this problem with addition of new indirection layers that makes underlying storage systems even more opaque to the operating system. This dissertation addresses the problem of inefficient use of disk information by identifying storage-level opportunities and developing pro-active techniques to storage management. We present a new class of storage systems called pro-active storage systems (PaSS), which in addition to being compatible with existing I/O interface, exerts a limit degree of control over the file system policies by leveraging it's internal information. In this dissertation, we present our PaSS framework that includes two new I/O interfaces called push and pull, both in the context of traditional systems and virtualized systems. We demonstrate the usefulness of our PaSS framework by a series of case studies that exploit the information available in underlying storage system layer, for overall improvement in IO performance. We also built a framework to evaluate performance and energy of modern storage systems by implementing a novel I/O trace replay tool and an analytical model for measuring performance and energy of complex storage systems. We believe that our PaSS framework and the suite of evaluation tools helps in better understanding of modern storage system behavior and thereby implement efficient policies in the higher layers for better performance, data reliability and energy efficiency by making use of the new interfaces in our framework.

Damaging changes and interventions in the water cycle in our landscape caused mainly in the last century together with uncertainties from climate change are the cause of more frequent occurrences of hydrological extremes. In Hydrology, the most urgent problem is that the values of the long-term mean flows are decreasing in rivers as well as the yield of groundwater sources, but on the other hand, we cannot forget to the problem of extreme floods. In these consequences developing methods and tools to uncertainty analysis of the reservoir yield and of the reservoir flood protection is very important, useful and desired. The main aim was to determine the functional volumes of the reservoir considering input data measurement uncertainties and to quantify them and was explained how uncertainty took into account in results. The active storage capacity was determined from the historical series of monthly flows that were affected by uncertainties, next were applied on water evaporation, seepage losses of the dam and morphological volume-area curves. The simulation-optimization reservoir model was developed and temporal reliability as reservoir yield performance measures was applied. This model will extend the existing UNCE_RESERVOIR software. The flood capacity was determined from random flood wave variations were obtained by repeatedly generating uncertainty on the flood hydrograph. Software was developed based on the modified Klemes method, which was able to transform flood waves. The measurement uncertainties of data inputs were created using Monte Carlo method in both softwares. By connecting two softwares, the functional volumes of the reservoir under conditions of measurement uncertainties were complexly determined. The case study was applied to the real water reservoir, in the Morava River Basin. The result will be whether the dam is resistant to the current conditions, or the optimal design of the functional volumes of reservoir under conditions uncertainties.