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|Title:||Development of Analytical Stochastic Models for Hydrologic Design of Stormwater Control Measures|
|Other Titles:||ANALYTICAL STOCHASTIC MODELS FOR STORMWATER MANAGEMENT|
|Abstract:||Urbanization has great impacts on hydrologic processes and can result in increased flooding, water quality deterioration, and the hazards of erosion. To deal with the challenges caused by urbanization, stormwater control measures (SCMs) have been widely advocated and utilized. SCMs consist of conventional centralized end-of-pipe control facilities and distributed source control or low-impact development practices (LIDs). Combined sewer overflow (CSO) tanks, detention ponds, wetlands are examples of end-of-pipe control facilities while representative LIDs include infiltration trenches, green roofs, permeable pavements, and rain gardens. Methods used in the design and analysis of SCMs are generally classified into three categories: single-event design storm simulation models, continuous simulation models, and probability-based analytical models. Among them, probability-based analytical models consist of previously developed analytical probabilistic models (APMs) and recently proposed analytical stochastic models (ASMs). Probability-based analytical models have the advantages of being in the form of closed-form analytical equations and requiring no numerical solutions. APMs and ASMs can be used as the surrogate of continuous simulation models for design and analysis. APMs have the shortcoming of requiring simplifying assumptions of antecedent storage or soil moisture conditions. Single-event design storm simulation models have limitations of relying on the assumption that the frequency of occurrence of some of the runoff hydrograph characteristics is always equal to that of some of the input rainfall hyetograph characteristics. Continuous simulation models are time-consuming to run and require large amounts of input. ASMs can overcome many of the drawbacks of other three types of models. ASMs for stormwater management purposes treat rainfall inputs at a location of interest as a marked Poisson process and describe the temporal evolution of the probability distribution of the relative water level or the degree of soil saturation of a SCM by the Chapman-Kolmogorov equation. Both rainfall event depth and inter-arrival time are assumed to be exponentially distributed in ASMs. The concept of effective storage capacity was proposed to properly consider the effects of the instantaneous rainfall pulses represented by the Poisson process. The steady-state probability distributions of the water content or the degree of soil saturation were analytically derived and form the basis of ASMs. Relevant SCM performance statistics of interest were derived based on these probability distributions. This thesis aims to develop a suite of ASMs for the design and analysis of SCMs which can significantly reduce the impact of some of the simplifying assumptions required in previously developed APMs and ASMs, while the newly developed ASMs are still in analytically tractable forms which simplify the calculation tasks required in engineering design. In Chapter 2, an ASM is developed for evaluating the performance of CSO tanks. In Chapter 3, instead of using constant outflow functions as in previous ASM studies, more realistic orifice outflow functions are considered in the development of ASMs for stormwater detention ponds. In Chapter 4, considering different possible operating conditions rather than simply assuming a constant bottom infiltration rate, different ASMs are proposed for different types of infiltration facilities. In Chapter 5, as an example application of the ASMs, the developed ASMs are applied for the sizing of infiltration trenches following local design standards and procedures. Throughout the thesis, the developed ASMs were verified by comparing their analytical results with results obtained from continuous simulations considering various factors of climate conditions, land use conditions, soil conditions, and facility dimensions. The usefulness of ASMs were demonstrated through cases studies at different test locations. The developed ASMs are recommended as an efficient alternative of, or used together with, continuous simulation models in the planning, design, and analysis of SCMs.|
|Appears in Collections:||Open Access Dissertations and Theses|
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