Although design decisions that are made in the preliminary design stages of a building are more cost sensitive than those that are made at later stages, previous research suggests that they result in only a slight improvement in the accuracy of building price forecasts as the design develops. However, established conventional forecasting methods lack measures of their own performance, which has inhibited the development of simpler early-stage techniques. One early-stage price forecasting model, the Storey Enclosure Method, which was developed by James in 1954, uses the basic physical measurements of buildings to estimate building prices. Although James' Storey Enclosure Model (JSEM) is not widely used in practice, it has been proved empirically, if rather crudely, to be a better model than other commonly used models. This research aims firstly to advance JSEM by using regression techniques and secondly to develop an objective approach for the assessment of model performance. To accomplish the first research aim, this research uses data from 148 completed Hong Kong projects for four types of building: offices, private housing, nursing homes, and primary and secondary schools. Sophisticated features of the modelling exercise include the use of leave-one-out cross validation to simulate the way in which forecasts are produced in practice and a dual stepwise selection strategy that enhances the chance of identifying the best model. Two types ofregressed models from different candidate sets, the Regressed Model for James' Storey Enclosure Method (RJSEM) and Regressed Model for Advanced Storey Enclosure Method (RASEM), are developed accordingly. In considering the RJSEM, RASEM, and the most commonly used alternative early stage floor area and cube models, all of the models except JSEM are found to be unbiased. The RJSEM and RASEM models are also examined for their consistency using a structured approach that involves the use of both parametric and non-parametric inference tests. This shows that although the RASEMs for different building types are generally more consistent, they are not significantly better than the other models. Finally, the combination of the forecasts that are generated from different models to capture the different aspects of information from the models is suggested as an alternative strategy for improving forecasting performance.

This thesis details the hydrodynamic research conducted at Delta Marsh as part of the Restoring the Tradition marsh rehabilitation project. Research has indicated that the hydraulic and hydrologic controls on the marsh can have considerable impacts on its ecological function, but the impacts of these controls had not previously been studied. Field hydrography and two-dimensional numerical modelling (using MIKE 21) provided insight into many aspects of the physical behaviour of Delta Marsh. Eighty five percent of the inflow to Delta Marsh from Lake Manitoba passes through Clandeboye Channel, and these discharge signals propagate as far west as Cadham Bay. Inflow to the marsh disperses quickly, and accounts for a small fraction of the water that exits the marsh during subsequent outflow. Thus, Portage Diversion water that enters the marsh through the lake can remain there even if there is a net loss in marsh volume over the season. Wind friction across Lake Manitoba has the greatest impact on short-term fluctuations in marsh volume and on the composition of marsh water, followed by the Portage Diversion and the natural inflows to Lake Manitoba. Expansions to flood diversion infrastructure will considerably impact the composition of Delta Marsh waters. Three methods of wetland discharge estimation were developed and tested. The most promising method was the regressed slope Manning method (RSMM), which estimates two-directional channel discharge as a function of the water surface elevations at both ends of a channel. When used in conjunction with the velocity index method, the RSMM can multiply the amount of reliable discharge data collected per research dollar. Thanks to its simple formulation, the RSMM is likely applicable outside of wetland settings, as well. / February 2016