Academic literature on the topic 'Urban runoff Australia Mathematical models'

Abstract The Runoff assessment is a crucial parameter in understanding the urban flooding scenario. This estimation becomes the deciding factor because of the uneven distribution of rainfall. Physics-based models for simulation of Runoff from catchments are composite models based on learning algorithms. The application of models to water resource problems is complex due to the incredible spatial variability of the characteristics of watershed and precipitation forms — the pattern-learning algorithms. Fuzzy-based algorithms, Artificial Neural Networks (ANNs), etc., have gained wide recognition in simulating the Rainfall-Runoff (RR), producing a comparable accuracy. In the present study, RR modeling is carried out targeting the application and estimation of Runoff using mathematical modeling. The investigations were carried out for the Malkajgiri catchment adopting 16 years of daily data from 2005 to 2021. The statistical learning theory-based pattern-learning algorithm is further utilized to evaluate the value of Runoff for the year 2021. The results were found to have fair accordance with the analytical outcomes.

In this paper we present a benchmarking methodology, which aims at comparing urban runoff quality models, based on the Bayesian theory. After choosing the different configurations of models to be tested, this methodology uses the Metropolis algorithm, a general MCMC sampling method, to estimate the posterior distributions of the models' parameters. The analysis of these posterior distributions allows a quantitative assessment of the parameters' uncertainties and their interaction structure, and provides information about the sensitivity of the probability distribution of the model output to parameters. The effectiveness and efficiency of this methodology are illustrated in the context of 4 configurations of pollutants' accumulation/erosion models, tested on 4 street subcatchments. Calibration results demonstrate that the Metropolis algorithm produces reliable inferences of parameters thus, helping on the improvement of the mathematical concept of model equations.

Abstract The purpose of mathematical modelling of sewer networks is mainly to assess the hydraulic capacity and monitor its behaviour under different conditions to predict the future state. Sewerage network models are also part of the design process. Their advantage is the possibility of simulating the future state of the network and the precipitation and runoff process in the context of climate change. With the help of simulations, it is possible to anticipate future conditions in urban catchments and thus effectively design new networks. The aim of this paper is to summarize mathematical simulation models that are used to model sewer networks.

This article discusses the use of green roofs as rainfall water storage in its soil matrix. The methodology is analytical based on mathematical models, where runoff produced in an urban area is compared with current conditions of ordinary roofs with ceramic or bituminous materials as the original scenario, against another where green roofs are used. The study area is located in the Palavecino municipality of Lara state in Venezuela, in the flood zone of Quebrada Tabure. In this research, a quantitative comparison of the direct runoff hydrographs of the proposed scenarios was used, obtaining as a main result the reduction of runoff between 60% and 80% according to the period of return. An interesting point of this research was the incorporation of the routing of hydrographs on the roofs, reducing even more the peak flow over 90%, and delaying the peak time of the generated hydrographs between 10 and 12 minutes while the total duration of the hydrographs increase more than three times.

There is increasing awareness about uncertainties in the modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here, a modified Monte-Carlo based method is presented that reduces the subjectivity inherent in typical uncertainty approaches (e.g. cut-off thresholds), while using tangible concepts and providing practical outcomes for practitioners. The method compares the model's uncertainty bands to the uncertainty inherent in each measured/observed datapoint; an issue that is commonly overlooked in the uncertainty analysis of urban drainage models. This comparison allows the user to intuitively estimate the optimum number of simulations required to conduct uncertainty analyses. The output of the method includes parameter probability distributions (often used for sensitivity analyses) and prediction intervals. To demonstrate the new method, it is applied to a conceptual rainfall-runoff model (MOPUS) using a dataset collected from Melbourne, Australia.

The article considers one of the important directions of innovative technologies in the urban economy, application of digital terrain models in the design, development and operation of utility networks. The author considers the five tasks of using the digital model sequentially: ) development of a digital terrain model, 2) allocation of watersheds and facies, 3) plotting contours (ridges) for all facies, 4) two-level modeling of surface runoff and storm sewer, 5) solving practical problems of determining silting zones and optimizing snow removal. The original principle proposed in the article is a multi-funnel model of surface runoff, in which each facies (local catchment) is replaced by an equivalent inclined funnel. This greatly simplifies the calculations, and also allows you to combine mathematical modeling with physical modeling.

Many runoff models are currently in use to predict both the quantity and quality of storm water runoff. In most models, the quality algorithms need further development to gain the confidence of model users. The writers have attempted to disaggregate the accumulation process and to develop improved algorithms for pollutant buildup. The factors and processes that affect buildup include atmospheric dustfall due to plumes of dust-laden air, wind effects, vehicles, intentional removals (e.g., street cleaning), special activities (such as construction and demolition), biological decomposition, and population-related activities (e.g., vegetation density, insecticides, herbicides, fertilizers, and lawn cutting). Mathematical expressions for each of these mechanisms are presented and utilized to develop algorithms in the RUNOFF module of the SWMM3 package.A separate multiregression model is used to generate atmospheric dustfall from meteorological information; this is input to the new program (NEWBLD) to calculate pollutant accumulation on individual subcatchments. NEWBLD is interfaced with the RUNOFF block of SWMM3. A sensitivity analysis is carried out using data for the Chedoke Creek catchment in Hamilton, Ontario. The modified version of the SWMM3 RUNOFF block developed herein by incorporating the new water quality algorithms is called CHGQUAL. It is applied to an urban catchment in Hamilton, Ontario. Key words: storm water models, dust and dirt buildup, storm water pollution, urban hydrology, air pollution.

Quantifying hydrological losses in a catchment is crucial for developing an effective flood forecasting system and estimating design floods. This can be a complicated and challenging task when the catchment is urbanised as the interaction of pervious and impervious (both directly connected and indirectly connected) areas makes responses to rainfall hard to predict. This paper presents the challenges faced in estimating initial losses (IL) and proportional losses (PL) of the partly urbanised Brownhill Creek catchment in South Australia. The loss components were calculated for 57 runoff generating rainfall events using the non-parametric IL-PL method and parametric method based on two runoff routing models, Runoff Routing Burroughs (RORB) and Rainfall-Runoff Routing (RRR). The analysis showed that the RORB model provided the most representative median IL and PL for the rural portion of the study area as 9 mm and 0.81, respectively. However, none of the methods can provide a reliable loss value for the urban portion because there is no runoff contribution from unconnected areas for each event. However, the estimated non-parametric IL of 1.37 mm can be considered as IL of EIA of the urban portion. Several challenges were identified in the loss estimation process, mainly when selecting appropriate storm events, collecting data with the available temporal resolution, extracting baseflow, and determining the main-stream transmission losses, which reduced the urban flow by 5.7%. The effect of hydrograph shape in non-parametric loss estimation and how combined runoff from the effective impervious area and unconnected (combined indirectly connected impervious and pervious) areas affects the loss estimation process using the RORB and RRR models are further discussed. We also demonstrate the importance of identifying the catchment specific conditions appropriately when quantifying baseflow and runoff of selected events for loss estimation.

Runoff is one of the main sources of diffuse pollution of surface water. Suspended solids are the most typical contaminants of runoff. Suspended solids have a great influence on water quality and ecological status of water bodies. The content of suspended solids in water bodies is determined not only by their receipt from external sources, but also by the ability to transport sediments by flow. There is a permanent exchange of suspended solids between water bodies and bottom deposits. This fact stimulates specific requirements for modeling the transfer of suspended solids. For the most cases, models which describe the transfer of suspensions in a turbulent flow are based on the three-dimensional equation of turbulent diffusion or its two-dimensional simplification, which allows to take into account the spatial distribution of substances or it’s distribution to the width of stream. The use of such models requires a significant amount of initial data to determine the parameters of the models and is associated with a significant amount of calculations. At the same time, one-dimensional interpretation of processes is common and practically sufficient for shallow watercourses. It is more important to take into account the dynamics of the exchange of suspended solids between water mass and bottom deposits. The article is devoted to the development of a mathematical model for estimating the influence of non - point sources of pollution on the content of suspended solids in narrow watercourses. The model is based on the principle of mass balance of substances entering the flow section and takes into account the processes of sedimentation and resedimentation of suspended solids. A mathematical model in the form of a differential equation for the case of normal and overloaded flow is developed. Analytical solutions of equations for both cases are obtained. The influence of hydraulic size of the suspension on the content of suspended solids in watercourses and its distribution along the flow length is analyzed. The developed model was used for estimation of the impact of runoff from the urban area of Kharkiv city (Ukraine) on the river Lopan. The model demonstrated satisfactory compliance with field data.

Urbanization increases imperviousness and reduces infiltration, retention, and evapotranspiration, frequently aggravating urban flooding due to greater runoff and higher and faster discharge peaks. Effective strategies to mitigate flood risks require a better understanding of the watershed dynamics and space to reverse the negative impacts. However, often cities do not have proper data sets to feed mathematical models that would be helpful in mapping water dynamics. Attempts to reduce flood risks have been made for decades by means of structural interventions but were frequently designed within the logic of a local scale, using limited available spaces and often merely shifting flooding downstream. Therefore, assessing urban floods requires a modeling approach capable of reflecting the watershed scale, considering interactions between hydraulic structures and urban landscape, where best practices and non-structural measures aim to improve community flood resilience through the reduction of social and financial costs in the long run. This paper proposes an integrated approach to analyze low impact development (LID) practices complemented by non-structural measures in a case study in southern Italy, supported by mathematical modeling in a strategy to overcome a context of almost no available data and limited urban open spaces.

The U.S. Geological Survey and the City of Tucson, Arizona, have been collecting rainfall and runoff data on several watersheds in the Tucson area for several years. Among the purposes of this project is to use the data to test rainfall-runoff models in an effort to find one to successfully simulate flood flows in Tucson. One such model, the Distributed Routing Rainfall-Runoff Model (DR3M), was tested using data collected on Rob Wash in Tucson. It was found DR3M performs about as well as it does in other parts of the United States, although it tends to underestimate flood flows for large storms and overestimate flows for smaller storms. Unique features with regard to the hydrology of urban Tucson require special attention when using DR3M; these features are associated with the nature of dry washes and summer rainfall in Tucson. Experience indicates DR3M is not truly a deterministic model.

Green Stormwater Infrastructure (GSI) has become a popular method for flood mitigation as it can prevent runoff from entering streams during heavy precipitation. In this study, a recently developed neighborhood in Gresham, Oregon hosts a comparison of various GSI projects on runoff dynamics. The study site includes dispersed GSI (rain gardens, retention chambers, green streets) and centralized GSI (bioswales, detention ponds, detention pipes). For the 2017-2018 water year, hourly rainfall and observed discharge data is used to calibrate the EPA's Stormwater Management Model to simulate rainfall-runoff dynamics, achieving a Nash-Sutcliffe efficiency of 0.75 and Probability Bias statistic of 3.3%. A synthetic scenario analysis quantifies the impact of the study site GSI and compares dispersed and centralized arrangements. Each test was performed under four precipitation scenarios (of differing intensity and duration) for four metrics: runoff ratio, peak discharge, lag time, and flashiness. Design structure has significant impacts, reducing runoff ratio 10 to 20%, reducing peak discharge 26 to 68%, and reducing flashiness index 56 to 70%. There was a reverse impact on lag time, increasing it to 50 to 80%. Distributed GSI outperform centralized structures for all metrics, reducing runoff ratio 22 to 32%, reducing peak discharge 67 to 69%, increasing lag time 133 to 500%, and reducing flashiness index between 32 and 62%. This research serves as a basis for researchers and stormwater managers to understand potential impact of GSI on reducing runoff and downstream flooding in small urban watersheds with frequent rain.

[Truncated abstract]This thesis investigates aspects of urban stormwater modeling and uses a small urban catchment (NE38) located in the suburb of Nedlands in Perth, Western Australia to do so. The MUSIC (Model for Urban Stormwater Improvement Conceptualisation) model was used to calibrate catchment NE38 using measured stormwater flows and rainfall data from within the catchment. MUSIC is a conceptual model designed to model stormwater flows within urban environments and uses a rainfall-runoff model adapted to generate results at six minute time steps. Various catchment scenarios, including the use of porous asphalt as an alternative road surface, were applied to the calibrated model to identify effective working stormwater disposal systems that differ from the current system. Calibrating catchment NE38 using the MUSIC model was attempted and this involved matching modeled stormwater flows to stormwater flows measured at the catchment drainage point. This was achieved by measuring runoff contributing areas (roads) together with rainfall data measured from within the catchment and altering the seepage constant parameter for all roadside infiltration sumps. ... The MUSIC model generated future scenario outcomes for alternative stormwater disposal systems that displayed similar or improved levels of performance with respect to the current system. The following scenarios listed in increasing order of effectiveness outline future stormwater disposal systems that may be considered in future urban design. 1. 35% porous asphalt application with no sumps in 2036 2. 35% porous asphalt application with no sumps in 2064 3. 68% porous asphalt application with no sumps in 2036 4. 68% porous asphalt application with no sumps in 2064. Future scenarios using the current stormwater disposal system (with roadside infiltration sumps) with porous asphalt were also run. These scenarios reduced stormwater runoff and contaminant loading on the catchment drainage point however the inclusion of a roadside infiltration sump system may not appeal to urban designers due to the costs involved with this scenario. Climate change will affect the design of future stormwater disposal systems and thus, the design of these systems must consider a rainfall reducing future. Based on the findings of this thesis, current stormwater runoff volumes entering catchment drainage points can be reduced together with contaminant loads in urban environments that incorporate porous asphalt with a stormwater disposal design system that is exclusive of roadside infiltration sumps.

[Formulae and special characters can only be approximated here. Please see the pdf version of the abstract for an accurate reproduction.] This thesis reviews, extends and applies to urban traffic analysis the entropy concept of Shannon and Luce's mathematical psychology in a fairly complex and mathematically demanding model of human decision making, if it is solved as a deeply nested structure of logit calculus. Recognising consumers' different preferences and the universal propensity to seek the best choice when going to some desired goal (k), a transparent mathematical program (MP) is developed: the equivalent of a nested multinomial logit model without its inherent computational difficulty. The MP model makes a statistical assessment of individual decisions based on a randomised (measurable) utility within a given choice structure: some path through a diagram (Rk, Dk), designed a priori, of a finite number of sequential choices. The Equivalence Theorem (ET) formalises the process and states a non-linear MP with linear constraints that maximises collective satisfaction: utility plus weighted entropy, where the weight (1/θn) is a behavioural parameter to be calibrated in each case, eg for the Perth CBD. An optimisation subject to feasible routes through the (Rk, Dk) network thus captures the rational behaviour of consumers on their individually different best-choice decision paths towards their respective goals (k). This theory has been applied to urban traffic assignment before: a Stochastic User Equi-librium (SUE). What sets this thesis apart is its focus on MP models that can be solved with standard Operations Research software (eg MINOS), models for which the ET is a conditio sine qua non. A brief list of SUE examples in the literature includes Fisk's logit SUE model in (impractically many) route flows. Dial's STOCH algorithm obviates path enumeration, yet is a logit multi-path assignment procedure, not an MP model; it is nei-ther destination oriented nor an optimisation towards a SUE. A revision of Dial's method is provided, named STOCH[k], that computes primal variables (node and link flows) and Lagrangian duals (the satisfaction difference n→k). Sheffi & Powell presented an unconstrained optimisation problem, but favoured a probit SUE, defying closed formulae and standard OR software. Their model corresponds to the (constrained) dual model here, yet the specifics of our primary MP model and its dual are possible only if one restricts himself to logit SUE models, including the ET, which is logit-specific. A real world application needs decomposition, and the Perth CBD example is iteratively solved by Partial Linearisation, switching from (measured) disutility minimisation to Sheffi & Powell's Method of Successive Averages near the optimum. The methodology is demonstrated on the Perth Central Business District (CBD). To that end, parameter Θ is calibrated on Main Roads' traffic count data over the years 1997/98 and 1998/99. The method is a revision of Liu & Fricker's simultaneous estimation of not only Θ but an appropriate trip matrix also. Our method handles the more difficult variable costs (congestion), incomplete data (missing observations) and observation errors (wrong data). Finally, again based on Main Roads' data (a sub-area trip matrix), a Perth CBD traffic assignment is computed, (a) as a logit SUE and - for comparison - (b) as a DUE (using the PARTAN method of Florian, Guélat and Spiess). The results are only superficially similar. In conclusion, the methodology has the potential to replace current DUE models and to deepen transport policy analysis, taking into account individual behaviour and a money-metric utility that quantifies 'social benefits', for instance in a cost-benefit-analysis.

The variably saturated flow model Unsat 2 was used for three case study simulations of dry well recharge in the Tucson Basin, Arizona. Dry well design, and rainfall/runoff and vadose zone conditions representative of the locality were assumed in the simulations to address travel time to the regional aquifer, rates and extent of radial flow, and relative degree of solute attenuation by sorption and dilution with regional groundwater. Soil specific surface was used to estimate relative degree of sorption among the three cases. One case of uniform soil composition and two cases of layered soil composition were simulated. Clay content had the greatest influence on specific surface. Hydraulic conductivity had the greatest influence on soil water velocities and degree of radial flow. The presence of layered subsurface conditions that included strata of low hydraulic conductivity enhanced the degree of subsurface solute attenuation by sorption and dilution.

The efficacy of sedimentation ponds as a means of sediment and heavy metal remediation is investigated, with particular regard to the physical and chemical conditions that may lead to remobilisation of metals from the sediments
Thesis (M.Eng.Sc.) -- University of Adelaide, Dept. of Civil and Environmental Engineering, 2001

Superelevation transition is often used to help balance the centrifugal forces on vehicles through curved roadway sections. Such transitions have regions with near-zero cross-slope as the pavement cross-section rotates from a negative to positive grade. For drainage of roadway surfaces, regions with near-zero slope constitute 'irregular topography'. This condition promotes extended stormwater runoff drainage path lengths and may result in excessive splash from vehicles and hydroplaning. A critical concern is the effect of longitudinal slope on stormwater drainage through superelevation transition. The overall goal of this study is to provide design guidance on longitudinal slope at superelevation transitions through application of a numerical simulation model of highway drainage. Sheet flow on urban pavement surfaces is very shallow, typically measuring a depth less than one centimeter. For modeling of such flow conditions, any small discontinuity or over-simplification of the surface geometry may result in failure in the flow computation. The kinematic wave approximation to the full Saint-Venant equations is often used in many surface and subsurface water models due to its simplicity in application. However, this model fails when backwater effects, ponding, or flow on reverse slope occurs in the local scale. Furthermore, due to the complexity in the surface geometry and the existence of drainage systems, the kinematic wave model is not sufficient for modeling urban stormwater runoff. On the other hand, the full dynamic wave (DW) model usually requires more computational effort. The long computation time of DW model often compromises the accuracy of the model, making the model practically inefficient. In this study, an algorithm was developed to properly represent the irregularly shaped roadway surfaces near superelevation transition areas with unevenly spaced curvilinear grids based on the geometry profile provided by a roadway design software package such as MicroStation CAD. With this accurately defined geometric representation, a nonlinear hydrodynamic diffusion wave model for hydraulic analysis developed in this research estimates the flow depth and runoff volume on the pavement surfaces. The model computes the flow responses for rising hydrographs using a preconditioned general Conjugate Gradient method. Kinematic boundary conditions developed for the open boundaries at the upstream and downstream boundaries compute the boundary values explicitly at each time step. The result of a numerical experiment shows that the spread and concentration of sheet flow is closely related to the transition in cross slope, longitudinal slope, rainfall intensity, and the width of the road. The characteristics of the sheet flow on superelevation transition areas are analyzed to find the optimal longitudinal slope. It is found that the longitudinal slope in the range of 0.3%-0.4% is the optimal slope at superelevation transition areas which minimizes the depth of stormwater runoff. An example application of the model on a rural highway in Texas is also presented. It is found that a significant amount of stormwater may exist on traffic lanes at the superelevation transitions tested. The predicted ponding depth exceeds the minimum value for potential hydroplaning, and the pattern of the flow concentration may cause differential drag forces on traffic vehicles.
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Urbanisation is one of the key factors that contributes to urban flooding, which has caused major destruction to the environment and the human race. In particular, the increase in population and building density influence the change in hydrological characteristics in urban areas. Conversion of pervious areas into impervious areas increases the stormwater runoff quantity dramatically. One way of minimising urban flooding is to convey stormwater to receiving waters through stormwater drainage systems, which has been practised in the past. This practice is currently changing and the current stormwater management deals with the holistic management of the urban water cycle, which includes stormwater drainage, improvement of stormwater quality and use of stormwater as an alternative supply source (to meet increasing urban water demand). The most practical and economical way of designing the urban stormwater drainage systems is by the application of computer based mathematical software tools. These tools can be used to identify flood prone areas by modelling the catchment. Currently, there are several software tools available to develop urban drainage models, and to design and analyse stormwater drainage systems in urban areas. The widely used tools in Australia are SWMM, MOUSE, DRAINS and XP-UDD. The accuracy of these models depends on the correct selection of model parameter values. Some of these parameters can be physically measured, whereas the other parameters are impossible or difficult to measure. Therefore, these parameter values, which are impossible or difficult to measure physically, have to be estimated through model calibration. Model calibration is done through an iterative process by comparing model predictions with observations, until the two sets match with each other within a reasonable accuracy. There are several methods available to calibrate mathematical models ranging from trial and error to optimisation methods. Traditionally, model calibration is done through trial and error. With this method, the experienced modellers estimate the model parameter values starting with educated guesses and refining these guesses by comparing observations and predictions (due to these parameter values). However, this method is subjective, time consuming and can also miss the optimum parameter set. On the other hand, computer based automatic optimisation methods have proven to be robust and efficient. In this project, one of the most popular automatic calibration optimisation method known as genetic algorithms (GAs) are used to calibrate the urban drainage models. Recently, GAs have proven to be successful and efficient in identifying the optimal solution for water resource modelling applications. These applications include rainfallrunoff modelling, river water quality modelling, pipe system optimisation and reservoir optimisation. However, in order to produce efficient and robust solutions, proper selection of GAs operators is necessary for the application, before conducting the optimisation. These GA operators include population size, number of simulations, selection method, and crossover and mutation rates. There are some general guidelines available to choose GAs operators for standard GAs optimisation applications. However, there are no specific guidelines available for selecting GAs operators for urban drainage model parameter optimisation. Therefore, the sensitivity of these operators were analysed in this study through numerical experiments by repetitive simulation considering one GAs operator at a time, by integrating GAs and urban drainage modelling software tools. This produced appropriate GAs operators for use in urban drainage model parameter optimisation. XP-UDD urban stormwater drainage software and GENESIS GAs software tools were used in this study to model the urban drainage catchment(s) and model parameter optimisation. These two software tools were linked through their input and output files to conduct the model parameter optimisation. Two typical urban catchments in Victoria (Australia) were used in selecting the appropriate GAs operators. For each catchment, two design storm events (i.e. small and large) were considered. The small storm considered runoff only from the impervious areas, while the large storm produced runoff from both impervious and pervious areas. Seven parameters were identified in the urban drainage model (which required calibration), two related to impervious area and the other five related to pervious area. Typical parameter values were assumed and used in XP-UDD models of the study catchments to produce the hydrographs corresponding to these two design storms and these hydrographs were then considered in the integrated GENESIS/XP-UDD as observed hydrographs in optimising GAs operators. Numerical experiments produced consistent and robust GAs operators for parameter optimisation of urban drainage models. Although there is no mathematical basis for optimising parameter values through repetitive simulation, this is an acceptable practice for complex systems. Model calibration was carried out only for one of the two study catchments used for GAs operator study, because of the time constraints. Furthermore, one catchment was considered sufficient, since the purpose of this part of the study was to investigate and demonstrate the use of GAs for optimising parameter values of urban drainage models. Observed rainfall/runoff data were available for this catchment only for small storms, which produced runoff only from impervious areas. Therefore, only the impervious area parameter values were estimated. The results obtained from GAs optimisation were compared with previous studies and found to be satisfactory. The soil infiltration parameters, which represent a sub-set of pervious area parameters, were determined through soil infiitrometer tests, which were conducted at several sites in the study catchment, which was used for model calibration. Soil infiltration tests were conducted, because the soil infiltration parameter values could not be estimated through model calibration, due to unavailability of observed data related to large storms. A standard double-ring infiltrometer was used to estimate these parameter values through field measurements and these measurements were taken over a period of six hours. Rainfall was measured for five days prior to the field test using a pluviometer, to determine the antecedent rainfall depths at the study sites. Soil infiltration parameter values were estimated by fitting soil infiitrometer test data to Horton's infiltration equation, since the Horton's infiltration equation is built into XP-UDD and is widely used in urban drainage modelling applications in Australia. Soil samples were also tested and analysed to determine the soil particle size distribution of each site to determine the soil type. In order to understand different soil types and to determine the soil infiltration rates in different urban catchments, these soil infiltrometer tests were conducted at another nineteen sites of seven urban drainage catchments in four city councils in Victoria. The infiltration parameter values found in this study were in general significantly different to the values given in DRAINS and XP-UDD software user manuals.

The aim of this dissertation was to develop a multi-criteria decision support system (MCDSS) to allow a specified manager to select with confidence one or many of these BMPs for a particular site. The principal design approach was a review of South African and international literature pertaining to stormwater management techniques, in particular BMPs. This information was formulated into a primary matrix using a rank-and-weighting method. The scores were then checked against the literature to ensure that they were reasonable, culminating in the initial MCDSS. The MCDSS was then provided with seven scenarios, described in the literature, and the output reviewed. Although, the MCDSS would select appropriately when given few criteria for selection when these were increased, inappropriate outcomes resulted. Consequently, weighting factors were assigned to each criterion. The MCDSS was further tested using all the selection criteria and the output deemed satisfactory. The MCDSS was then tested in a case study of the Town Bush stream catchment at eleven sites along the river network and the results were adequate. Taking into consideration the economic aspects of BMP implementation a need also arose for the sites to be allocated to certain authorities depending upon ownership or responsibility. The sites were prioritised depending on potential threat to property and lastly by the hydrological nature of the stream at each site. A stormwater plan for the study area was also proposed. Although the MCDSS was functioning adequately it was not without its limitations. Limitations included the use of drainage areas as a surrogate measure for peak discharge thus, not allowing the user to design a series of BMPs or treatment chain. A second limitation was that initially the BMPs were designed as offline systems where stormwater is managed before entering the channel but in this study they were used as inline systems. Hence the ultimate selection was biased towards those BMPs able to deal with large drainage areas. Recommendations for further improvement include the development of a surrogate measure for drainage area thus allowing the user to design a treatment chain of BMPs; testing the MCDSS in more diverse circumstances; developing a more comprehensive set of selection criteria; and developing a clearer priority-setting model as the one used was rather simplistic. In conclusion the MCDSS provides the user with a useful tool where the selection and implementation of BMPs no longer has to take place in an ad hoc manner.
Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2001