No description available.

No description available.

The water quality of stormwater runoff from various road surfaces in Durban, KwaZulu- Natal was characterised by monitoring programmes established at four study areas. The investigation focussed on obtaining representative stormwater samples in order to quantitatively identify pollutant constituents transported within stormwater runoff from road surfaces during rainfall events. Stormwater runoff is a leading cause of degradation in the water quality of receiving water bodies. A review of sampling methods and equipment, informed by the objectives and resources of this investigation, resulted in the development of a stormwater runoff sampler. An economical flow weighted composite sampler was designed, developed and tested. The sampler produces one representative composite event mean concentration sample. Controlled laboratory experiments, computer simulations and field tests were conducted in order to test and calibrate the sampler. The product of the event mean concentration and total runoff volume estimated provide an estimation of the total pollutant loading from a particular drainage area. Twenty stormwater runoff event mean concentration (EMC) and atmospheric deposition samples were collected over an eighteen month period. The characterisation of stormwater runoff for this investigation included heavy metals, oxygen demanding substances, sediments and physico-chemical analysis for pH, conductivity and water hardness. Chemical analysis indicates that the pollutant levels of constituents sometimes exceeded EMCs reported internationally. The majority of contaminant EMCs exceeded the South African wastewater discharge general and special limits. The results also indicate a 60% reduction in lead (Pb) levels since the introduction of lead-free fuel in South Africa in January 2006. The findings from this investigation will provide decision-makers with an improved local data base for estimating the impacts of road transportation systems on water quality. A comparison between the four study areas also provides guidance concerning the variability of stormwater quality from different road surfaces and usage patterns. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.

Prior observations by Koch (2005) suggest the presence of soil water mixed with current rainfall in runoff samples at the Kendall subwatershed of the USDA-Agricultural Research Service Walnut Gulch Experimental Watershed (WGEW). However, previous observations elsewhere in the WGEW have shown runoff to consist mainly of current precipitation (Goodrich et al., 2004). The disparity between the two studies demonstrates a need for continued research; therefore, this study uses isotope and solute geochemical tracers to determine the sources contributing to runoff at the Lucky Hills subwatershed of the WGEW during the 2015 monsoon season. A comparison of the stable isotopes of water (2H and 18O) in runoff to those in precipitation and soil water, shows that runoff and precipitation are distinct (p < 0.05), while soil water cannot be differentiated from runoff (p > 0.05). However, graphical representations of chloride and sulfate concentrations in the three water sources (precipitation, soil water and runoff), conclusively reveal that there is negligible soil water present in the runoff at Lucky Hills. Therefore, it is likely that there is no soil water mixing into the runoff at the Lucky Hills subwatershed, but more research is necessary to confirm these results. Because no runoff or soil water data was generated at the Kendall subwatershed during the 2015 monsoon season, continued research is necessary to draw conclusions about the sources contributing to runoff in the Kendall subwatershed, and in other portions of the Walnut Gulch Experimental Watershed.

No description available.

No description available.

Digitized by Kansas Correctional Industries

One challenge that faces hydrologists in water resources planning is to predict the catchment???s response to a given rainfall. Estimation of parameter uncertainty (and model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference, with computations carried out via Markov Chain Monte Carlo (MCMC) methods, offers an attractive approach to model specification, allowing for the combination of any pre-existing knowledge about individual models and their respective parameters with the available catchment data to assess both parameter and model uncertainty. This thesis develops and applies Bayesian statistical tools for parameter estimation, comparison of model performance and hierarchical model aggregation. The work presented has three main sections. The first area of research compares four MCMC algorithms for simplicity, ease of use, efficiency and speed of implementation in the context of conceptual rainfall-runoff modelling. Included is an adaptive Metropolis algorithm that has characteristics that are well suited to hydrological applications. The utility of the proposed adaptive algorithm is further expanded by the second area of research in which a probabilistic regime for comparing selected models is developed and applied. The final area of research introduces a methodology for hydrologic model aggregation that is flexible and dynamic. Rigidity in the model structure limits representation of the variability in the flow generation mechanism, which becomes a limitation when the flow processes are not clearly understood. The proposed Hierarchical Mixtures of Experts (HME) model architecture is designed to do away with this limitation by selecting individual models probabilistically based on predefined catchment indicators. In addition, the approach allows a more flexible specification of the model error to better assess the risk of likely outcomes based on the model simulations. Application of the approach to lumped and distributed rainfall runoff models for a variety of catchments shows that by assessing different catchment predictors the method can be a useful tool for prediction of catchment response.

<p> As highway runoff is one major source of non-point pollution in urban areas, removal of contaminants in runoff should be of great concern. In this paper, the necessity of highway runoff treatment in Shanghai was approved, systemic comparisons between runoff treatments were listed, detailed discussions on treatment approach selection were given based upon the availability of land. Three design models for highway runoff treatment were proposed; one focused on the urban highway, one focused on the suburb highway, and the third focused on the urban-suburb area. A survey among scientists studying runoff in China showed that the use of constructed wetlands was a remedy that was highly approved. They also supported the establishment of an urban runoff database. This paper will assist in the development of suitable treatment strategies for highway runoff in urban areas in China.</p>

As highway runoff is one major source of non-point pollution in urban areas, removal of contaminants in runoff should be of great concern. In this paper, the necessity of highway runoff treatment in Shanghai was approved, systemic comparisons between runoff treatments were listed, detailed discussions on treatment approach selection were given based upon the availability of land. Three design models for highway runoff treatment were proposed; one focused on the urban highway, one focused on the suburb highway, and the third focused on the urban-suburb area. A survey among scientists studying runoff in China showed that the use of constructed wetlands was a remedy that was highly approved. They also supported the establishment of an urban runoff database. This paper will assist in the development of suitable treatment strategies for highway runoff in urban areas in China.