Civil Engineering - Theses
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ItemNo Preview AvailableEffect of land surface heterogeneity on satellite near-surface soil moisture observations(University of Melbourne, 2009)This thesis develops a technique to reduce the error in near-surface soil moisture estimates from spacebome passive microwave sensors, by accounting for the heterogeneity of land surface conditions within the sensor field of view. Using experimental data collected in the course of this research, it is demonstrated that this technique will significantly reduce the error in satellite near-surface soil moisture retrieval. The technique has been developed specifically for the first dedicated passive microwave soil moisture satellite, the European Soil Moisture and Ocean Salinity Mission (SMOS), which will use L-band (1.4GHz) measurements to map nearsurface soil moisture globally at a near-daily time scale. The main steps taken to develop these techniques are the first evaluation of the core radiative transfer model of the SMOS soil moisture retrieval algorithm for the Australian conditions using airborne data, and an analysis of the land surface controls on near-surface soil moisture distribution at the satellite footprint scale. These initial steps provided the tools in order to test the accuracy of the soil moisture retrieval approach proposed for SMOS at the satellite footprint scale in the presence of spatial variability of the land surface, and to develop a new retrieval approach for SMOS which overcomes the shortfalls identified in the SMOS proposed approach.
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ItemAddressing uncertainties associated with water accounting(University of Melbourne, 2009)Water accounts provide information to a range of stakeholders who make decisions related to water. There are significant challenges in quantifying all of the information elements included in water accounts. Some information elements are measured while others are estimated. There is uncertainty associated with the information presented in water accounts, either due to measurement uncertainty or the assumptions made during the estimation process. The presence of uncertainties in water accounts poses two problems. Firstly, the decisions made based on information presented in the accounts may change if the associated uncertainties were disclosed. Secondly, due to the uncertainties associated with each element, the accounts rarely balance. At present the uncertainty in water accounts is not well understood and it is not systematically captured and reported in the accounts. This thesis identifies and quantifies the major sources of uncertainty in water accounts. Established techniques to quantify the uncertainties are only available for a few of the elements. A number of new techniques are developed to quantify the uncertainty associated with elements that include unmetered water use, net evaporation from storages, reservoir volumes and impacts of farm dams. A general framework to quantify uncertainties is developed and applied to a case study, the Werribee River basin (Victoria, Australia). The largest uncertainties in this catchment are associated with estimating rainfall runoff and surface water -groundwater interactions. A new method to constrain the uncertainty associated with each component of the water accounts and to create a balanced set of accounts, based on numerical data reconciliation, is presented. If the uncertainty surrounding each element is known, it is possible to improve the estimates and reduce the uncertainties by removing combinations of inflows and outflows that do not create a balanced set of accounts. Existing analytical techniques to perform the required calculations for data reconciliation are not suitable in water accounting because they assume that all uncertainties can be described using a Gaussian distribution. In order to incorporate other types of probability distributions, a numerical technique is developed. Overall, this thesis presents three new contributions: an identification of information elements which are useful to decision makers; a quantification of uncertainties associated with the elements reported in water accounts and methods are presented to quantify these uncertainties; a new numerical method, data reconciliation, to minimise the uncertainties by considering the joint probability of all inflows and outflows that create a balanced set of accounts.
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ItemA hybrid microsimulation model of freight transport demand(University of Melbourne, 2009)
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ItemA study of aerodynamic wind loads on tall buildings using wind tunnel tests and numerical simulations(University of Melbourne, 2009)
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ItemPricing carbon in power sector investment : a stochastic decision tree analysis(University of Melbourne, 2007)
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ItemIntersectoral water allocation : valuing water and the case for water property rights(University of Melbourne, 2006)