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(1 - 8 of 8)
- Title
- A Holistic Analysis of the Long-Term Challenges (&) Potential Benefits of the Green Roof, Solar PV Roofing, and GRIPV Roofing Markets in Orlando, Florida.
- Creator
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Kelly, Carolina, Tatari, Omer, Oloufa, Amr, Mayo, Talea, Zheng, Qipeng, University of Central Florida
- Abstract / Description
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Green roofs and roof-mounted solar PV arrays have a wide range of environmental and economic benefits, including significantly longer roof lifetimes, reductions in urban runoff, mitigation of the urban heat island (UHI) effect, reduced electricity demand and energy dependence, and/or reduced emissions of greenhouse gases (GHGs) and other harmful pollutants from the electricity generation sector. Consequently, green roofs and solar panels have both become increasingly popular worldwide, and...
Show moreGreen roofs and roof-mounted solar PV arrays have a wide range of environmental and economic benefits, including significantly longer roof lifetimes, reductions in urban runoff, mitigation of the urban heat island (UHI) effect, reduced electricity demand and energy dependence, and/or reduced emissions of greenhouse gases (GHGs) and other harmful pollutants from the electricity generation sector. Consequently, green roofs and solar panels have both become increasingly popular worldwide, and promising new research has emerged for their potential combination in Green Roof Integrated Photovoltaic (GRIPV) roofing applications. However, due to policy resistance, these alternatives still have marginal market shares in the U.S., while GRIPV research and development is still severely limited today. As a result, these options are not yet sufficiently widespread in the United States as to realize their full potential, particularly due to a variety of policy resistance effects with respect to each specific alternative. The steps in the System Dynamics (SD) methodology to be used in this study are summarized as follows. First, based on a comprehensive review of relevant literature, a causal loop diagram (CLD) will be drawn to provide a conceptual illustration of the modeled system. Second, based on the feedback relationships observed in this CLD, a stock-flow diagram (SFD) will be developed to form a quantitative model. Third, the modeled SFD will be tested thoroughly to ensure its structural and behavioral validity with respect to the modeled system in reality using whatever real world data is available. Fourth, different policy scenarios will be simulated within the model to evaluate their long-term effectiveness. Fifth, uncertainty analyses will be performed to evaluate the inherent uncertainties associated with the analyses in this study. Finally, the results observed for the analyses in this study and possible future research steps will be discussed and compared as appropriate.
Show less - Date Issued
- 2018
- Identifier
- CFE0007406, ucf:52741
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007406
- Title
- Streamflow prediction in ungauged basins located within data-scarce regions.
- Creator
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Alipour, Mohammadhossein, Kibler, Kelly, Wang, Dingbao, Mayo, Talea, Emrich, Christopher, University of Central Florida
- Abstract / Description
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Preservation and or restoration of riverine ecosystem requires quantification of alterations inflicted by water resources development projects. Long records of streamflow data are the first piece of information required in order to enable this analysis. Ungauged catchments located within data-scarce regions lack long records of streamflow data. In this dissertation, a multi-objective framework named Streamflow Prediction under Extreme Data-scarcity (SPED) is proposed for streamflow prediction...
Show morePreservation and or restoration of riverine ecosystem requires quantification of alterations inflicted by water resources development projects. Long records of streamflow data are the first piece of information required in order to enable this analysis. Ungauged catchments located within data-scarce regions lack long records of streamflow data. In this dissertation, a multi-objective framework named Streamflow Prediction under Extreme Data-scarcity (SPED) is proposed for streamflow prediction in ungauged catchments located within large-scale regions of minimal hydrometeorologic observation. Multi-objective nature of SPED allows for balancing runoff efficiency with selection of parameter values that resemble catchment physical characteristics. Uncertain and low-resolution information are incorporated in SPED as soft data along with sparse observations. SPED application in two catchments in southwestern China indicates high runoff efficiency for predictions and good estimation of soil moisture capacity in the catchments. SPED is then slightly modified and tested more comprehensively by application to six catchments with diverse hydroclimatic conditions. SPED performance proves satisfactory where traditional flow prediction approaches fail. SPED also proves comparable or even better than data-intensive approaches. Utility of SPED versus a simpler catchment similarity model for the study of flow regime alteration is pursued next by streamflow prediction in 32 rivers in southwestern China. The results indicate that diversion adversely alters the flow regime of the rivers while direction and pattern of change remain the same regardless of the flow prediction method of choice. However, the results based on SPED consistently indicate more substantial alterations to the flow regime of the rivers after diversion. Finally, the value added by a limited number of streamflow observations to improvement of predictions in an ungauged catchment located within a data-scarce region is studied. The large number of test scenarios indicate that there may be very few near-universal schemes to improve flow predictions in such catchments.
Show less - Date Issued
- 2019
- Identifier
- CFE0007426, ucf:52713
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007426
- Title
- A Comprehensive Assessment of Vehicle-to-Grid Systems and Their Impact to the Sustainability of Current Energy and Water Nexus.
- Creator
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Zhao, Yang, Tatari, Omer, Oloufa, Amr, Mayo, Talea, Zheng, Qipeng, University of Central Florida
- Abstract / Description
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This dissertation aims to explore the feasibility of incorporating electric vehicles into the electric power grid and develop a comprehensive assessment framework to predict and evaluate the life cycle environmental, economic and social impact of the integration of Vehicle-to-Grid systems and the transportation-water-energy nexus. Based on the fact that electric vehicles of different classes have been widely adopted by both fleet operators and individual car owners, the following questions...
Show moreThis dissertation aims to explore the feasibility of incorporating electric vehicles into the electric power grid and develop a comprehensive assessment framework to predict and evaluate the life cycle environmental, economic and social impact of the integration of Vehicle-to-Grid systems and the transportation-water-energy nexus. Based on the fact that electric vehicles of different classes have been widely adopted by both fleet operators and individual car owners, the following questions are investigated: 1. Will the life cycle environmental impacts due to vehicle operation be reduced? 2. Will the implementation of Vehicle-to-Grid systems bring environmental and economic benefits? 3. Will there be any form of air emission impact if large amounts of electric vehicles are adopted in a short time? 4. What is the role of the Vehicle-to-Grid system in the transportation-water-energy nexus? To answer these questions: First, the life cycle environmental impacts of medium-duty trucks in commercial delivery fleets are analyzed. Second, the operation mechanism of Vehicle-to-Grid technologies in association with charging and discharging of electric vehicles is researched. Third, the feasible Vehicle-to-Grid system is further studied taking into consideration the spatial and temporal variance as well as other uncertainties within the system. Then, a comparison of greenhouse gas emission mitigation of the Vehicle-to-Grid system and the additional emissions caused by electric vehicle charging through marginal electricity is analyzed. Finally, the impact of the Vehicle-to-Grid system in the transportation-water-energy nexus, and the underlying environmental, economic and social relationships are simulated through system dynamic modeling. The results provide holistic evaluations and spatial and temporal projections of electric vehicles, Vehicle-to-Grid systems, wind power integration, and the transportation-water-energy nexus.
Show less - Date Issued
- 2017
- Identifier
- CFE0007300, ucf:52153
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007300
- Title
- Biomass density based adjustment of LiDAR-derived digital elevation models: a machine learning approach.
- Creator
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Abdelwahab, Khalid, Medeiros, Stephen, Mayo, Talea, Wahl, Thomas, University of Central Florida
- Abstract / Description
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Salt marshes are valued for providing protective and non-protective ecosystem services. Accurate digital elevation models (DEMs) in salt marshes are crucial for modeling storm surges and determining the initial DEM elevations for modelling marsh evolution. Due to high biomass density, lidar DEMs in coastal wetlands are seldom reliable. In an aim to reduce lidar-derived DEM error, several multilinear regression and random forest models were developed and tested to estimate biomass density in...
Show moreSalt marshes are valued for providing protective and non-protective ecosystem services. Accurate digital elevation models (DEMs) in salt marshes are crucial for modeling storm surges and determining the initial DEM elevations for modelling marsh evolution. Due to high biomass density, lidar DEMs in coastal wetlands are seldom reliable. In an aim to reduce lidar-derived DEM error, several multilinear regression and random forest models were developed and tested to estimate biomass density in the salt marshes near Saint Marks Lighthouse in Crawfordville, Florida. Between summer of 2017 and spring of 2018, two field trips were conducted to acquire true elevation and biomass density measures. Lidar point cloud data were combined with vegetation monitoring imagery acquired from Sentinel-2 and Landsat Thematic Mapper (LTM) satellites, and 64 field biomass density samples were used as target variables for developing the models. Biomass density classes were assigned to each biomass sample using a quartile approach. Moreover, 346 in-situ elevation measures were used to calculate the lidar DEM errors. The best model was then used to estimate biomass densities at all 346 locations. Finally, an adjusted DEM was produced by deducting the quartile-based adjustment values from the original lidar DEM. A random forest regression model achieved the highest pseudo R2 value of 0.94 for predicting biomass density in g/m2. The adjusted DEM based on the estimated biomass densities reduced the root mean squared error of the original DEM from 0.38 m to 0.18 m while decreasing the raw mean error from 0.33 m to 0.14 m, improving both measures by 54% and 58%, respectively.
Show less - Date Issued
- 2019
- Identifier
- CFE0007594, ucf:52535
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007594
- Title
- Ichetucknee Springs: Measuring the Effects of Visitors on Water Quality Parameters through Continuous Monitoring.
- Creator
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Faraji, Sarah, Singh, Arvind, Wang, Dingbao, Mayo, Talea, University of Central Florida
- Abstract / Description
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Ichetucknee Springs System is in north central Florida, under the jurisdiction of the Suwannee River Water Management District (SRWMD). The Ichetucknee River is one of the most pristine spring-fed rivers in Florida and became a state park in 1970. Over 400,000 people visited the Ichetucknee Springs State Park in 2016. From that total, over 130,000 people came during the tubing season alone (Memorial Day to Labor Day). During the tubing season, only 750 visitors per day are allowed to launch...
Show moreIchetucknee Springs System is in north central Florida, under the jurisdiction of the Suwannee River Water Management District (SRWMD). The Ichetucknee River is one of the most pristine spring-fed rivers in Florida and became a state park in 1970. Over 400,000 people visited the Ichetucknee Springs State Park in 2016. From that total, over 130,000 people came during the tubing season alone (Memorial Day to Labor Day). During the tubing season, only 750 visitors per day are allowed to launch from the North Launch, near the Ichetucknee Head Spring. The park enforces visitor usage of the river during these time frames to protect the integrity of the aquatic vegetation and aquatic organisms in the northern portion of the River. The objective of this study is to evaluate the response of water quality from the Head Spring to the seasonal changes in visitor numbers to the Park. Water quality parameters were continuously monitored and recorded by a SRWMD station using a YSI EXO2 and SUNA nitrate sensor: temperature, turbidity, pH, specific conductivity, dissolved oxygen content, and nitrates (NO2+NO3). Water quality data from April 2015 to September 2017 was reviewed and processed into max daily values that were compared to daily visitor counts. Results from the statistical analysis indicate there is a significant difference in turbidity from the Head Spring during the tubing season and outside the tubing season (Kruskal-Wallis, p(<)0.001), which results from higher visitor counts during the weekends of the tubing season. However, due to inconsistency of water quality readings and equipment damage, some data were lost or outside the range of monitoring capabilities; which may have resulted in decreased correlation between water quality and daily visitor counts. Continued evaluation of water quality by continuous monitoring is warranted as it can assist the SRWMD and Ichetucknee Springs State Park Staff better monitor and evaluate the health of the Ichetucknee Springs System.
Show less - Date Issued
- 2017
- Identifier
- CFE0006873, ucf:51748
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006873
- Title
- Remote Sensing of Coastal Wetlands: Long term vegetation stress assessment and data enhancement technique.
- Creator
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Tahsin, Subrina, Medeiros, Stephen, Singh, Arvind, Mayo, Talea, University of Central Florida
- Abstract / Description
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Apalachicola Bay in the Florida panhandle is home to a rich variety of salt water and freshwater wetlands but unfortunately is also subject to a wide range of hydrologic extreme events. Extreme hydrologic events such as hurricanes and droughts continuously threaten the area. The impact of hurricane and drought on both fresh and salt water wetlands was investigated over the time period from 2000 to 2015 in Apalachicola Bay using spatio-temporal changes in the Landsat based NDVI. Results...
Show moreApalachicola Bay in the Florida panhandle is home to a rich variety of salt water and freshwater wetlands but unfortunately is also subject to a wide range of hydrologic extreme events. Extreme hydrologic events such as hurricanes and droughts continuously threaten the area. The impact of hurricane and drought on both fresh and salt water wetlands was investigated over the time period from 2000 to 2015 in Apalachicola Bay using spatio-temporal changes in the Landsat based NDVI. Results indicate that salt water wetlands were more resilient than fresh water wetlands. Results also suggest that in response to hurricanes, the coastal wetlands took almost a year to recover while recovery following a drought period was observed after only a month. This analysis was successful and provided excellent insights into coastal wetland health. Such long term study is heavily dependent on optical sensor that is subject to data loss due to cloud coverage. Therefore, a novel method is proposed and demonstrated to recover the information contaminated by cloud. Cloud contamination is a hindrance to long-term environmental assessment using information derived from satellite imagery that retrieve data from visible and infrared spectral ranges. Normalized Difference Vegetation Index (NDVI) is a widely used index to monitor vegetation and land use change. NDVI can be retrieved from publicly available data repositories of optical sensors such as Landsat, Moderate Resolution Imaging Spectro-radiometer (MODIS) and several commercial satellites. Landsat has an ongoing high resolution NDVI record starting from 1984. Unfortunately, the time series NDVI data suffers from the cloud contamination issue. Though simple to complex computational methods for data interpolation have been applied to recover cloudy data, all the techniques are subject to many limitations. In this paper, a novel Optical Cloud Pixel Recovery (OCPR) method is proposed to repair cloudy pixels from the time-space-spectrum continuum with the aid of a machine learning tool, namely random forest (RF) trained and tested utilizing multi-parameter hydrologic data. The RF based OCPR model was compared with a simple linear regression (LR) based OCPR model to understand the potential of the model. A case study in Apalachicola Bay is presented to evaluate the performance of OCPR to repair cloudy NDVI reflectance for two specific dates. The RF based OCPR method achieves a root mean squared error of 0.0475 sr?1 between predicted and observed NDVI reflectance values. The LR based OCPR method achieves a root mean squared error of 0.1257 sr?1. Findings suggested that the RF based OCPR method is effective to repair cloudy values and provide continuous and quantitatively reliable imagery for further analysis in environmental applications.
Show less - Date Issued
- 2016
- Identifier
- CFE0006546, ucf:51331
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006546
- Title
- Coupling Infrastructure Resilience and Flood Risk Assessment for a Coastal Urban Watershed.
- Creator
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Joyce, Justin, Chang, Ni-bin, Mayo, Talea, Wanielista, Martin, University of Central Florida
- Abstract / Description
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This thesis sheds light on coupling potential flood risk and drainage infrastructure resilience of low-lying areas of a coastal urban watershed to flood hazards and subsequent multi-scale impacts of those hazards via detailed modeling frameworks. Physically based models along with statistical models are employed to highlight the complexity for characterizing flood risk while evaluating such risk under various levels of adaptive capacity from traditional flood management techniques to low...
Show moreThis thesis sheds light on coupling potential flood risk and drainage infrastructure resilience of low-lying areas of a coastal urban watershed to flood hazards and subsequent multi-scale impacts of those hazards via detailed modeling frameworks. Physically based models along with statistical models are employed to highlight the complexity for characterizing flood risk while evaluating such risk under various levels of adaptive capacity from traditional flood management techniques to low impact development (LID), as a first step to conduct resilience assessment. Findings indicate that the coupling flood risk and infrastructure resilience is achievable by the careful formulation of flood risk associated with a resilience metric, which is a function of the hazard(s) considered, vulnerability and adaptive capacity. The results also give insights into improving existing methodologies for municipalities in flood management practices such as incorporating multi-criteria flood risk evaluation that includes resilience.
Show less - Date Issued
- 2017
- Identifier
- CFE0006748, ucf:51844
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006748
- Title
- Groundwater modeling for assessing the impacts of natural hazards in east-central Florida.
- Creator
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Xiao, Han, Wang, Dingbao, Nam, Boo Hyun, Medeiros, Stephen, Mayo, Talea, Hall, Carlton, University of Central Florida
- Abstract / Description
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In coastal east-central Florida (ECF) , the low-lying coastal alluvial plains and barrier islands have a high risk of being inundated by seawater due to climate change effects such as sea-level rise, changing rainfall patterns, and intensified storm surge from hurricanes., This will produce saltwater intrusion into the coastal aquifer from infiltration of overtopping saltwater. In the inland ECF region, sinkhole occurrence is recognized as the primary geologic hazard causing massive financial...
Show moreIn coastal east-central Florida (ECF) , the low-lying coastal alluvial plains and barrier islands have a high risk of being inundated by seawater due to climate change effects such as sea-level rise, changing rainfall patterns, and intensified storm surge from hurricanes., This will produce saltwater intrusion into the coastal aquifer from infiltration of overtopping saltwater. In the inland ECF region, sinkhole occurrence is recognized as the primary geologic hazard causing massive financial losses to society in the past several decades. The objectives of this dissertation are to: (1) evaluate the impacts of sea-level rise and intensified storm surge on the extent of saltwater intrusion into the coastal ECF region; (2) assess the risk level of sinkhole occurrence in the inland ECF region. In this dissertation, numerical modeling methods are used to achieve these objectives. Several three-dimensional groundwater flow and salinity transport models, focused on the coastal ECF region, are developed and calibrated to simulate impacts of sea-level rise and storm surge based on various sea-level rise scenarios. A storm surge model is developed to quantify the future extent of saltwater intrusion. Several three-dimensional groundwater flow models, focused on the inland ECF region, are developed and calibrated to simulate the spatial variation of groundwater recharge rate for analyzing the risk level of sinkhole occurrence in the geotypical central Florida karst terrains. Results indicate that sea-level rise and storm surge play a dominant role in causing saltwater intrusion, and the risk of sinkhole occurrence increases linearly with an increase in recharge rate while the timing of sinkhole occurrence is highly related to the temporal variation of the difference of groundwater level between confined and unconfined aquifers. The outcome will contribute to ongoing research focused on forecasting the impacts of climate change on the risk level of natural hazards in ECF region.
Show less - Date Issued
- 2017
- Identifier
- CFE0007298, ucf:52160
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007298
