| research a few current interests |
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Runoff from urban surfaces and porous pavement, including solar thermal enrichment.Faculty: William James |
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Background: As urbanisation increases, there is increased contaminant loading on receiving waters from point and nonpoint sources. Stormwater runoff from pavement adds significantly to these contaminant loadings. Sources of contaminant loadings include solar radiative heat, the atmosphere, adjacent land-uses, automobile traffic and the asphalt that these vehicles use. Temperature is the number one determinant of ecosystem types downstream of urbanization. Yet temperature modeling is very inadequate in our existing models; none compute heat accumulation in blacktop paving and roof tiles, nor do any urban runoff models cover the transport of thermal energy by runoff, even though all aquatic chemical and biochemical processes are temperature-dependent. Areas such as Detroit are effectively enormous, exposed, black-body solar receptors, and rainfall/runoff is an efficient transporter of heat from hot pavement and roofs. Cold water fisheries have disappeared from creeks downstream of urban centres. Summary: Alternatives to asphalt is the thrust of this research. This study involves the installation of four test pavements in a parking lot at the University, four smaller test rigs in the laboratory, and extensive in-situ tests elsewhere in Ontario, to determine the quality of urban runoff. Water quality is being determined at the surface of the pavements as well as at the base and sub-base. Initial results show that the runoff generated from the three porous pavements have better water quality characteristics. Factors such as temperature, total and suspended solids, conductivity and other parameters from the asphalt show extreme high values, compared to the porous pavements. Having investigated performance over longer times, we are now producing appropriate stormwater management models. Publications: Abstracts of ten dissertations are available - to read them, click here. Please check my lists of publications,
grad student theses, and bibliographies. I am working on a monograph on this topic - if
you would like to help review it, or for further info please email me! |
Decision Support Systems For Urban Stormwater Management Modelling.Faculty: William James. |
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Background: Sustainability and eco-restoration factors are first and foremost computable by continuous modeling, or period-of-record modeling. Most processes relevant to ecosystem concerns seem to imply a need for continuous modeling. Long-term, continuous water quality modeling leads naturally to consideration of impacts on aquatic ecosystems. Continuous modeling for several 102 years has now become feasible, indeed desirable, especially in order to address concerns of sustainability. Such modelling in turn requires better shells and decision support code. Continuous models may become very complex, gradually integrating encyclopedic knowledge of component processes as it becomes available, applying it to vast databases as the databases build over time, examining potentially thousands of arrays of best management practices (BMPs) as they are put forward from time-to-time, re-running each array for say 102 years of hydro-meteorologic and physical topo-hydrographic data. Cost-benefit studies require many iterations. Summary: In this work, the minimum requirements of decision support systems (DSS) that favor continuous modeling are provided in a shell. Written for a drag-and-drop Windows environment, my shell is PCSWMM, which aims especially at sensitivity, calibration and error-analysis (SCEA) for design applications using large-scale, long-term, continuous modeling at high spatial and temporal resolution. So far as is known, this was (still is?) the first shell to focus especially on SCEA for design applications at this large-scale (say 103 and more elements) and this long duration (say 102 years) continuous water quality modeling at high resolutions (elements as small as say 100 ft length, 10-1 acre extent and integration intervals as small as 10-seconds). In PCSWMM, SCEA is rendered semi-automatic for several 102 differently named hydrologic parameters and a total number of parameters of the order of several 104, depending on the processes active, and the spatial resolution. Currently we are developing for continuous models rain time-series generators for long-term high-resolution synthetic rate-of-rainfall input datasets having characteristics related to a shorter-term observed rain record nearby. Publications: I am working on a monograph on this topic - if you would like to
help review it please email me! Abstracts of eight postgraduate theses are available (see
T53, 51,48,40,37,33,29,18) - to read them, click here. Please
also check my lists of publications and related grad student theses also. Email me for
further info. Rain storm models For Storm Water Management Faculty: William James. Background:Convective summer thunderstorms are dynamic: they age, have preferred trajectories and preferred directions, they are not stationary on the average, and they are multicellular. In stormwater management, there is still almost no modeling of thunderstorm dynamics, even though all surface water quality modeling is wrong if the input rain is wrong. In North America, GIS, rain and weather radar data are readily available. Weather radar units are becoming economical, compared with networks of recording rain gauges - urban runoff in sewers is now being controlled in Japan by small-scale radar. Software exists for converting radar reflectivities to rainfall intensities at a length-scale of 50 meters and in time steps of 1 to 6 minutes, approaching the resolution and averaging what we need for urban hydrology. We have used ArcInfo to convert radar reflectivities to rainfall intensities directly, and to model storm cell dynamics, as a part of the spatial data management for the SWMM program. Summary: To account for the actual variation and aging of storm cells, a three
dimensional storm model is fitted to either the observed coverage of ground-level rain
intensities or the radar images, giving an estimate of the storm spatial distribution at
reasonable time steps such as one minute. Storm cell speeds and directions are computed.
For each time step the average spatial rainfall over each of the watershed subcatchments
is computed, and rainfall time series generated for input into SWMM. Finally we are
currently generating long-term high-resolution time series of rainfall rates, having the
same expected characteristics as the shorter term observed records nearby. Time series management for modelling impacts of urban drainage systems Faculty: William James Background: Urban surface water quality modelling should be long-term and continuous, say 75 years, or three generations (3GM). Realistic models and reliable modelling techniques require a great deal of time series data. Two popular modelling programs are being integrated in this research: the Hydrologic Simulation Program - FORTRAN (HSPF), and the Stormwater Management Model (SWMM). The problem with these programs is that they incorporate their own time series data management systems, and the novice user must spend considerable time learning specific database functions. A common time series manager will improve the efficiency of modelling analyses, since database functions and other utilities will be shared between applications. Summary: TS data management systems were developed by the US Geological Survey (ANNIE) and the US Army Corps of Engineers Hydrologic Engineering Center (HEC-DSS). The focus of this research is the design of a new common DSS/ANNIE/HSPF/SWMM interface, such that design turn-around times will be decreased, learning speeds increased, and urban hydrologic models provided with a flexible means for exchanging data and accessing data sources and information systems on the information highway. Publications: Jenny (Yiwen) Wang and Mike Gregory completed their theses in 1995 and 1996 on the
above topics. An earlier student who worked on a similar topic is Ali Unal, while students
whose work involved some aspects of TS data management included: Luis Carvalho, Mark
Stirrup, Karen Dennison, Al Dunn and Mark Robinson. For links to abstracts
of the eight theses, click here. |