Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 116-124). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 142-155).

Submitted in fulfillment of the requirements of the Degree of Master of Technology: Civil Engineering, Durban University of Technology, 2014. / Streamflow modelling remains crucial to decision-making especially when it concerns planning and management of water resources systems in water-stressed regions. This study proposes a suitable method for streamflow modelling irrespective of the limited availability of historical datasets. Two data-driven modelling techniques were applied comparatively so as to achieve this aim. Genetic programming (GP), an evolutionary algorithm approach and a differential evolution (DE)-trained artificial neural network (ANN) were used for streamflow prediction in the upper Mkomazi River, South Africa. Historical records of streamflow and meteorological variables for a 19-year period (1994- 2012) were used for model development and also in the selection of predictor variables into the input vector space of the models. In both approaches, individual monthly predictive models were developed for each month of the year using a 1-year lead time. Two case studies were considered in development of the ANN models. Case study 1 involved the use of correlation analysis in selecting input variables as employed during GP model development, while the DE algorithm was used for training and optimizing the model parameters. However in case study 2, genetic programming was incorporated as a screening tool for determining the dimensionality of the ANN models, while the learning process was further fine-tuned by subjecting the DE algorithm to sensitivity analysis. Altogether, the performance of the three sets of predictive models were evaluated comparatively using three statistical measures namely, Mean Absolute Percent Error (MAPE), Root Mean-Squared Error (RMSE) and coefficient of determination (R2). Results showed better predictive performance by the GP models both during the training and validation phases when compared with the ANNs. Although the ANN models developed in case study 1 gave satisfactory results during the training phase, they were unable to extensively replicate those results during the validation phase. It was found that results from case study 1 were considerably influenced by the problems of overfitting and memorization, which are typical of ANNs when subjected to small amount of datasets. However, results from case study 2 showed great improvement across the three evaluation criteria, as the overfitting and memorization problems were significantly minimized, thus leading to improved accuracy in the predictions of the ANN models. It was concluded that the conjunctive use of the two evolutionary computation methods (GP and DE) can be used to improve the performance of artificial neural networks models, especially when availability of datasets is limited. In addition, the GP models can be deployed as predictive tools for the purpose of planning and management of water resources within the Mkomazi region and KwaZulu-Natal province as a whole.

The purpose of this study is to develop a method for predicting monthly flow duration curves for ungaged basins that are suitable for estimating average annual flow, and installed capacity and average annual energy generation at potential sites for hydropower development. The procedures were tested by developing monthly rainfall duration curves for five sample watersheds and then developing flow duration curves from the rainfall data. The methods were evaluated by comparing the predicted monthly flow duration curves to daily and monthly flow duration curves based on field data from the selected sites because a plant's potential energy output can be computed directly from a flow duration curve. The methods tested fit duration curves based on field data reasonably well and are suitable for preliminary evaluation of hydropower developments in ungaged basins.

No description available.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 42-46). Also available on the World Wide Web.

This study examines the relationship between the developing landscape and the water flowing through it. The study area was an 86 sq. mi. watershed located in the coastal plains in Harris County, Texas. Daily streamflow data for 52 years was obtained from USGS and coincident precipitation data was obtained from NOAA. Georeferenced parcel-level data was obtained from the Harris County Appraisal District with sufficient detail to determine year of development, parcel area, and impervious cover. Watershed boundaries were obtained from the Harris County Flood Control District. After controlling for daily precipitation, streamflow exhibited significant increases at all levels over time. Increasing streamflow was not associated with climate change. FRAGSTATS was used to quantify spatial patterns in the developed landscape on an annual basis. Regression analysis was used to determine the relationship between spatial and non-spatial measures of development and streamflow. It was found that models based on the spatial configuration of the developed landscape predict streamflow better than non-spatial measures such as total impervious cover. Several metrics were identified for their potential use as guidelines for urban planning.

The hydrological model WATFLOOD and a volume-area scaling relationship are applied to estimate glacier wastage and seasonal Melt contribution to the headwaters of the North and South Saskatchewan Rivers on the eastern slopes of the Canadian Rocky Mountains from 1975-1998. Wastage is defined as the annual volume of glacier ice melt that exceeds the annual volume of snow accumulation into the glacier system, causing an annual net loss of glacier volume. Melt is defined as the annual volume of glacier ice melt that is equal to, or less than, the annual volume of snow that does not melt from the glacier and instead accumulates into the glacier system. It is proposed that the distinction between these two components of glacier runoff is important in studies of the impact of glacier variations on flow. A comparison of similar glacierised and non-glacierised basin hydrographs shows that glacierised basins have greater specific streamflow in the late summer months of otherwise low flow, and the presence of glaciers in a basin results in a lower coefficient of variation of the July to September and annual streamflow as a result of the natural regulating impact of glaciers on streamflow. Glacier wastage and Melt are estimated from a hydrological-hypsometric comparison of glacierised and non-glacierised basins, mass balance data from Peyto Glacier and the published work of other researchers. The similarity of these results to those from the volume-area scaling approach indicates that this is a suitable method for estimating glacier wastage on a regional scale. Whilst the WATFLOOD results were similar to those from the hydrological-hypsometric approach regionally, there were considerable differences between the estimates of combined glacier wastage and Melt from different methods in the small, highly glacierised Peyto Glacier basin. The WATFLOOD results, and thus the estimates of Melt, are therefore treated with caution and it is proposed that glacier runoff data is collected with which to improve the model calibration, verify results and make uncertainty estimations, currently prevented by the severe lack of data on glaciers in the North and South Saskatchewan River basins.<p> The results show that glacier wastage was smaller than Melt and varied between glaciers, though contributed over 10% to streamflow in a number of basins in the July to September period 1975-1998. Melt was positively correlated with basin glacier cover and contributed over 25% to streamflow from basins with glacier cover as little as 1% in the July to September period. The significance of Melt is manifest in its timing since it is equal to the annual volume of snow that accumulates into the glacier system, the volume of which melts as ice instead of snow thus entering the stream in the later summer months after snowmelt. Future glacier decline is therefore expected to result in an advancement of peak flow towards a snowmelt regime hydrograph, assuming that post glacial basin conditions do not similarly delay snowmelt runoff. The resulting reduced late summer flow, compounded by decreasing wastage contributions, is a concern for agricultural and industrial streamflow users, such as hydropower plants, and threatens ecological habitats. Downstream at Edmonton and Calgary, glacier wastage contributed approximately 3% of streamflow 1975-1998; however, Melt supplied over double this volume of flow thus the concern here is whether reservoir capacities are large enough to store a sufficient volume of the spring peak flow to meet supply needs in the late summer months of decreasing flows.

The hydrological model WATFLOOD and a volume-area scaling relationship are applied to estimate glacier wastage and seasonal Melt contribution to the headwaters of the North and South Saskatchewan Rivers on the eastern slopes of the Canadian Rocky Mountains from 1975-1998. Wastage is defined as the annual volume of glacier ice melt that exceeds the annual volume of snow accumulation into the glacier system, causing an annual net loss of glacier volume. Melt is defined as the annual volume of glacier ice melt that is equal to, or less than, the annual volume of snow that does not melt from the glacier and instead accumulates into the glacier system. It is proposed that the distinction between these two components of glacier runoff is important in studies of the impact of glacier variations on flow. A comparison of similar glacierised and non-glacierised basin hydrographs shows that glacierised basins have greater specific streamflow in the late summer months of otherwise low flow, and the presence of glaciers in a basin results in a lower coefficient of variation of the July to September and annual streamflow as a result of the natural regulating impact of glaciers on streamflow. Glacier wastage and Melt are estimated from a hydrological-hypsometric comparison of glacierised and non-glacierised basins, mass balance data from Peyto Glacier and the published work of other researchers. The similarity of these results to those from the volume-area scaling approach indicates that this is a suitable method for estimating glacier wastage on a regional scale. Whilst the WATFLOOD results were similar to those from the hydrological-hypsometric approach regionally, there were considerable differences between the estimates of combined glacier wastage and Melt from different methods in the small, highly glacierised Peyto Glacier basin. The WATFLOOD results, and thus the estimates of Melt, are therefore treated with caution and it is proposed that glacier runoff data is collected with which to improve the model calibration, verify results and make uncertainty estimations, currently prevented by the severe lack of data on glaciers in the North and South Saskatchewan River basins.<p> The results show that glacier wastage was smaller than Melt and varied between glaciers, though contributed over 10% to streamflow in a number of basins in the July to September period 1975-1998. Melt was positively correlated with basin glacier cover and contributed over 25% to streamflow from basins with glacier cover as little as 1% in the July to September period. The significance of Melt is manifest in its timing since it is equal to the annual volume of snow that accumulates into the glacier system, the volume of which melts as ice instead of snow thus entering the stream in the later summer months after snowmelt. Future glacier decline is therefore expected to result in an advancement of peak flow towards a snowmelt regime hydrograph, assuming that post glacial basin conditions do not similarly delay snowmelt runoff. The resulting reduced late summer flow, compounded by decreasing wastage contributions, is a concern for agricultural and industrial streamflow users, such as hydropower plants, and threatens ecological habitats. Downstream at Edmonton and Calgary, glacier wastage contributed approximately 3% of streamflow 1975-1998; however, Melt supplied over double this volume of flow thus the concern here is whether reservoir capacities are large enough to store a sufficient volume of the spring peak flow to meet supply needs in the late summer months of decreasing flows.

This study explores the spatial-temporal patterns of Section 404 permitting program under the Clean Water Act and examines its impact on mean and peak annual streamflow. The study area consists of 47 sub-basins that are delineated based on USGS streamflow gauges. These sub-basins span from the southern portion of coastal Texas to the easternmost portion of coastal Texas. Descriptive, spatial and spatial-temporal statistical methods are used to explore patterns in Section 404 permitting between 1996 and 2003. The effects of Section 404 permit types on mean and peak annual streamflow over the same 8 year period are also statistically modeled with a host of other relevant control variables. Exploratory analyses of Section 404 permits demonstrated characteristics that were indicative of suburban and, to a larger extent, exurban development. Explanatory analyses of the effects of Section 404 permitting on mean and peak streamflow showed that Section 404 permits increase both measures. These increases were minimal on a per-permit basis but have the ability to accumulate over time and result in much larger increases. Section 404 permits also displayed an ordered effect based on the permit type. Permit types that represent larger impacts had larger effects. The effects of permits of streamflow followed a descending pattern of Individual permits, Letters of Permission, Nationwide permits, and General permits. This “type of permit impact” supports the use of this measure as an indicator of wetland impact and loss and corroborates previous studies that have incorporated this measure.