Two independent hydrologic research projects, the development of (1) a research watershed system and (2) a streamflow prediction model, were carried out. The first project was primarily a field instrumentation task involving both design and implementation of a system of research watersheds. Two small (50 acre) research watersheds which may become either representative or experimental in nature were initiated within the University of British Columbia Research Forest. A larger research watershed system was described which could include the Alouette River Watershed. This system of watersheds when subjected to more rigorous experimental procedures should yield valuable, management and conservation design criteria for Pacific Coast forested regions. The second project was primarily analytic in nature, employing the use of multiple regression and a digital computer. A computer program was developed which models the snowmelt streamflow of large watersheds in a manner which makes short term prediction of the streamflow possible. The prediction variables were temperature recorded at a single centrally located station, time and streamflow recorded at the outlet from the watershed. The model predicted flood flow one to five days in advance of measured streamflow for the Fraser River Watershed (78,000 square miles in area) during the spring runoff period of 1955 and 1964. This model required calibration at the beginning of each spring runoff period. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

The aim of this research project was to estimate parameters for the distribution of annual maximum flood levels for the Zambezi River at Katima Mulilo. The estimation of parameters was done by using the maximum likelihood method. The study aimed to explore data of the Zambezi's annual maximum flood heights at Katima Mulilo by means of fitting the Gumbel, Weibull and the generalized extreme value distributions and evaluated their goodness of fit.

published_or_final_version / abstract / toc / Mechanical Engineering / Master / Master of Philosophy

The aim of this research project was to estimate parameters for the distribution of annual maximum flood levels for the Zambezi River at Katima Mulilo. The estimation of parameters was done by using the maximum likelihood method. The study aimed to explore data of the Zambezi's annual maximum flood heights at Katima Mulilo by means of fitting the Gumbel, Weibull and the generalized extreme value distributions and evaluated their goodness of fit.

Forecast models are investigated and developed for use in local water management to aid in determining short term water requirements and availability. The forecast models include precipitation occurrence and depth using a Markov chain model, temperature and solar radiation with a multivariate autoregressive model, and streamflow with autoregressive-moving average models. The precipitation, temperature, and solar radiation forecasts are used with a soil moisture model to determine water demands. A state space approach to the Muskingum-Cunge streamflow routing technique is developed. The forecast water demands and streamflow forecasts are used as inputs to this routing model. Forecast model errors and propagation of these errors from one model into the next are investigated.

Department of Civil, Surveying and Environmental Engineering. Bibliography: leaves 246-255

The National Water Act (Act 36 of 1998) provides for an ecological Reserve as the quantity (flow) and quality of water needed to protect aquatic ecosystems. While there are methods available to quantify the ecological Reserve in terms of flow, methods of linking flow to water quality are lacking. Therefore, the research presented in this thesis investigated various modelling techniques to estimate the effect of flow on water quality. The aims of the research presented in this thesis were: Aim 1: Can the relationship between flow and water quality be accurately represented by simple statistical models? Aim 2: Can relatively simple models accurately represent the relationship between flow and water quality? Aim 3: Can the effect of diffuse sources be omitted from a water quality model and still obtain realistic simulations, and if so under what conditions? Aim 4: Can models that solely use historical monitoring data, accurately represent the relationships between flow and water quality? In Chapter 3, simple Q-C regressions of flow and water quality were investigated using Department of Water Affairs (DWA) historical monitoring data. It was found that while flow versus salinity regressions gave good regression fits in many cases, the Q-C regression approach is limited. A mechanistic/statistical model that attempted to estimate the point and diffuse signatures of nutrients in response to flow was developed in Chapter 4 using DWA historical monitoring data. The model was verified as accurate in certain case studies using observed point loading information. In Chapter 5, statistical models that link land cover information to diffuse nutrient signatures in response to flow using DWA historical data were developed. While the model estimations are uncertain due to a lack of data, they do provide an estimation of the diffuse signature within catchments where there is flow and land cover information available. Chapter 6 investigates the extension of an existing mass-balance salinity model to estimate the effect of saline irrigation return flow on in-stream salinity. The model gave accurate salinity estimates for a low order stream with little or no irrigation within its catchment, and for a permanently flowing river within a catchment used extensively for irrigation. Chapter 7 investigated a modelling method to estimate the reaction coefficients involved in nitrification using only DWA historical monitoring data. Here, the model used flow information to estimate the residence time of nutrients within the studied river reaches. While the model obtained good estimations of nitrification for the data it was applied to, very few DWA data sets were suitable for the model. Chapter 8 investigated the ability of the in-stream model QUAL2K to estimate nutrient concentrations downstream of point and diffuse inputs of nutrients. It was found that the QUAL2K model can give accurate results in cases where point sources dominate the total nutrient inputs into a river. However, the QUAL2K simulations are too uncertain in cases where there are large diffuse source inputs of nutrients as the load of the diffuse inputs is difficult to measure in the field. This research highlights the problem of data scarcity in terms of temporal resolution as well as the range of constituents measured within DWA historical monitoring data for water quality. This thesis in addition argues that the approach of applying a number of models is preferable to applying one model to investigate the research aims, as particular models would be suited to particular circumstances, and the development of new models allowed the research aims of this thesis to be explored more thoroughly. It is also argued that simpler models that simulate a few key processes that explain the variation in observed data, are more suitable for implementing Integrated Water Resource Management (IWRM) than large comprehensive water quality models. From this research, it is clear that simple statistical models are not adequate for modelling the relationship between flow and water quality, however, relatively simple mechanistic models that simulate a limited number of processes and water quality variables, can provide accurate representations of this relationship. Under conditions where diffuse sources are not a major factor within a catchment, models that omit diffuse sources can obtain realistic simulations of the relationship between flow and water quality. Most of the models investigated in this thesis demonstrate that accurate simulations of the relationships between flow and water quality can be obtained using solely historical monitoring data.