A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Now showing 1 - 8 of 8
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    Pluvial Flood Risk Estimation Procedure for Small Urban Watersheds
    (2012) Cone, John Trevor; McCuen, Richard H; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Pluvial flooding, when runoff causes flooding before it reaches a body of water, is a type of flooding that often is overlooked in flood risk studies. This study outlines a general procedure that can be used to model urban pluvial flood scenarios, estimate damages, and quantify pluvial flood risk for microwatersheds (watersheds of a few square miles or less). The model development was accomplished using EPA's SWMM in combination with GIS datasets and analyses. Sensitivity analyses were performed on many model inputs including runoff surface slope, imperviousness, infiltration parameters, and pipe roughness. The overall procedure was tested on a 215-acre sewershed in Washington, DC. The results indicate that pluvial flooding can have serious consequences, even in areas that are not close to existing bodies of water and are at relatively high elevations. The 10-, 100-, and 200-yr rainfall events modeled produced damage estimates of approximately $430,000, $904,000, and $1,093,000, respectively.
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    Response of hydrologic calibration to replacing gauge-based with NEXRAD-based precipitation data in the USEPA Chesapeake Bay Watershed model
    (2012) Kim, Sunghee; Brubaker, Kaye L; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This study investigated the response of hydrologic calibration to replacing gauge-based with radar-based precipitation data in the USEPA Chesapeake Bay Program (CBP) Watershed (CBW) model over the Potomac River Basin. Specific objectives were to (1) compare gauge-based and NEXRAD radar-based (Multisensor Precipitation Estimator, MPE) data at the (a) point-pixel and (b) spatially aggregated level; (2) evaluate the model's calibration accuracy using the different precipitation data sets; and (3) examine the response of model hydrology. Hourly gauge-point and MPE-pixel data were compared at 80 locations. The CBP's interpolated and aggregated precipitation data at the model unit (county) level were compared with MPE data aggregated to the same 114 county-based spatial segments. The model calibration followed the CBP's automated approach, using observed streamflow at 37 gauge stations. Model performance was evaluated using calibration and hydrologic statistics, and GIS-aided spatial information. Calibrated parameters and model hydrologic fluxes were compared. The average annual gauge-point and MPE-pixel values (excluding hours when either was missing) agreed well. Differences in average annual values between the spatially aggregated data sets were, however, significant in parts of the study area. When parameter constraints were relaxed to allow calibration to adjust to the smaller volume of precipitation, the model using MPE outperformed the model calibrated to CBP precipitation data at 65% of the 37calibration sites. The model response was controlled largely by the seasonal difference in precipitation inputs: (1) calibration process could not compensate for large differences in seasonal flow bias caused by the seasonal volume of precipitation; (2) seasonal flow bias affected the lower zone nominal soil moisture storage parameter (LZSN), mainly affecting interflow and groundwater flow. The surface flow component was generally the same for the different precipitation inputs. The two precipitation data types can be used interchangeably to simulate surface-flow dominated processes, but care must be taken in simulations where subsurface pathways and residence times are important. MPE is a strong alternative to gauge-based precipitation data because of its spatiotemporal coverage and rare missing records. Using MPE in hydrologic modeling is appealing because of the improved calibration accuracy of the CBW model demonstrated in this study.
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    Calibrating Shenandoah Watershed SWAT Model Using A Nonlinear Groundwater Algorithm
    (2011) Wang, Yan; Brubaker, Kaye L.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This study contributes to a project with the Interstate Commission on the Potomac River Basin to build a model of the Potomac watershed using the Soil Water Assessment Tool (SWAT). The 2,937 mi2 Shenandoah watershed represents about 40% of the Potomac Basin by area. The model subdivides the Shenandoah watershed into 28 subwatersheds and 489 hydrologic response units. SWAT's linear-reservoir groundwater algorithm is modified into a new non-linear method. Modeled flows are compared to observations (dating from 1996 to 2006) at 15 USGS stream gages. The model is auto-calibrated using the Parameter Estimation Software (PEST), experimenting with options to improve model performance. The best model results are obtained by applying ordinal weights to the observation groups, decreasing from headwaters to outlet, and pre-calibrating the roughness coefficients using empirical equations. The calibrated model will contribute to understanding hydrological processes and predicting the effects of land use and climate change in the watershed.
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    A DECISION SUPPORT SYSTEM FOR THE SPATIAL CONTROL OF INVASIVE BIOAGENTS
    (2010) Hebou, Luc; Montas, Hubert J; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    A Decision Support System (DSS) is developed and applied to the spatial control of invasive bioagents, exemplified in this study by the resident Canada goose species (Branta Canadensis) in the Anacostia River system of the District of Columbia. The DSS incorporates a model of goose movement that responds to resource distribution; a twocompartment Expert System (ES) that identifies the causes of goose congregation in hotspots (Diagnosis ES) and prescribes strategies for goose population control (Prescription ES); and a Geographic Information System (GIS) that stores, analyzes, and displays geographic data. The DSS runs on an HP xw8600 64-bit Workstation running Window XP Operating System. The mathematical model developed in this study simulates goose-resource dynamics using partial differential equations - solved numerically using the Finite Element Method (FEM). MATLAB software (v. 7.1) performed all simulations. ArcGIS software (v. 9.3) produced by Environmental Systems Research Institute (ESRI) was used to store and manipulate georeferenced data for mapping, image processing, data management, and hotspot analysis. The rule-based Expert Systems (ES) were implemented within the GIS via ModelBuilder, a modular and intuitive Graphical User Interface (GUI) of ArcGIS software. The Diagnosis ES was developed in three steps. The first step was to acquire knowledge about goose biology through a literature search and discussions with human experts. The second step was to formalize the knowledge acquired in step 1 in the form of logical sentences (IF-THEN statements) representing the goose invasion diagnosis rules. Finally, in the third step, the rules were translated into decision trees. The Prescription ES was developed by following the same steps as in the development of the Diagnosis ES, the major difference being that, in this case, knowledge was acquired relative to goose control strategies rather than overpopulation causes; and additionally, knowledge was formalized based on the Diagnosis and on other local factors. Results of the DSS application indicate that high accessibility to food and water resources is the most likely cause of the congregation of geese in the critical areas identified by the model. Other causes include high accessibility to breeding and nesting habitats, and supplementary, artificial food provided by people in urban areas. The DSS prescribed the application of chemical repellents at feeding sites as a goose control strategy (GCS) to reduce the quality of the food resources consumed by resident Canada geese, and therefore the densities of geese in the infested locations. Two other prescribed GCSs are egg destruction and harvest of breeding adult geese, both of which have direct impacts on the goose populations by reducing their densities at hotspots or slowing down their increase. Enclosing small wetlands with fencing and banning the feeding of geese in urban areas are other GCSs recommended by the ES. Model simulations predicted that these strategies would reduce goose densities at hotspots by over 90%. It is suggested that further research is needed to investigate the use of similar systems for the management of other invasive bioagents in ecologically similar environments.
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    Evaluation of Nitrogen Nonpoint-source Loadings using High Resolution Land Use Data in a GIS: A Multiple Watershed Study for the State of Maryland.
    (2008-08-14) Ahmed, Sarah Naveed; Moglen, Glenn E; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The performance of three monitoring perspectives, for the detection of watershed compliance with water quality standards, was evaluated. In order to compare performances 35 watershed nonpoint-source nitrogen loading cases were calculated within a GIS. Calculations showed that the probability of loads exceeding a criterion at the watershed outlet is more representative of upstream conditions than a nominal mean load comparison at the watershed outlet. Combined outlet compliance interpretations were found to isolate loading conditions that on average did not exceed the criterion; however, variations within loading distributions were large such that compliant conditions were threatened. The whole watershed perspective mapped the relationship between stream network structure, land cover/land use, and loadings. Comparisons between the perspectives suggested that both outlet perspectives usually are consistent with whole watershed conditions. Semivariograms were demonstrated to characterize spatial variability in loadings and predict the accuracy with which monitoring sites represent loads at upstream locations.
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    Development and Application of a Stream Flashiness Index based on Imperviousness and Climate using GIS
    (2007-07-26) Ravirajan, Karthik; Moglen, Glenn E; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This work examines the relationship between imperviousness, climate, and the Richards-Baker (R-B) index, a measure of ow variability. Regression equations to predict the R-B index are developed for annual, cool, and warm seasons. The re- gression equations developed, are calibrated using stream ow data from 1970-2000 for 29 USGS streamgages throughout Maryland. Regression equations for the R-B ashiness index are developed as a function of imperviousness, precipitation char- acteristics, and drainage area. The relationship is used to estimate stream quality conditions throughout Maryland for present and future land use and climate. The regression equations are used to calculate the future stream ow variability by pro- jecting the R-B index predictors to re ect the following conditions: (1) Increasing imperviousness only, (2) Climate change only, and (3) Jointly changing impervious- ness and climate. Finally, the relationship between R-B index and stream quality is studied.
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    Sensitivity of Peak Discharge Calculation to GIS-Derived Hydrologic Routing Parameters in the TR-20 Rainfall-Runoff Model
    (2006-08-15) Stack, Ian Malone; Moglen, Glenn; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Hydrologic routing of runoff from upstream locations is a central element in rainfall-runoff modeling. Channel cross-section geometry is used to develop routing parameters for this process. The sensitivity of the routed peak discharge to cross-section location along the routing reach is examined using two methods in this thesis. First, an enumeration method was used to analyze the sensitivity of overall peak discharge to the channel routing process by executing the TR-20 model for all possible cross-section locations evaluated within the GIS. Second, a regression equation as a function of the modified att-kin method routing coefficient, reach length, and channel slope shows promise as a planning and decision making tool when implementing the rainfall-runoff model. Finally, case study analyses support the usefulness that a possible future expert system would provide for guidance on developing routing reach cross-section characteristics to engineers and other professionals that use GIS to perform hydrologic rainfall-runoff modeling.
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    MODELING WATER QUANTITY AND WATER QUALITY WITH THE SWMM CONTINUOUS STREAMFLOW MODEL UNDER NON-STATIONARY LAND-USE CONDITION USING GIS
    (2004-05-04) Medina, William; Moglen, Glenn E.; Civil Engineering
    GIS data widely available today can be used to better estimate watershed parameters for the SWMM model. An interface was developed to create SWMM input files from spatial data. The interface delineates watersheds and allows update of land-use parameters. SWMM performs continuous simulation but it assumes a time-invariant land use. A "hot-start" technique was developed that uses end values from one year's simulation to initialize state variables for the next year. This technique allows for dynamically changing the land use model parameters to reflect changes in time. Based on the simulation results, three regression models were developed to adjust constant land-use model results to account for land use changes in peak discharges, baseflow, and total phosphorus loads. These adjustments use imperviousness as an index of land use changes. The regression equations adjust streamflow and water quality results from a constant land use SWMM simulation to conditions with time-varying land use.