Current Search: Medeiros, Stephen (x)
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- Title
- Analysis of Hydrodynamic and Bathymetric gradients in Canaveral National Seashore following Living shoreline and oyster restorations.
- Creator
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Spiering, David, Kibler, Kelly, Medeiros, Stephen, Singh, Arvind, University of Central Florida
- Abstract / Description
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Coastal vulnerability has been gaining recognition as a critical issue, especially with the increasing predictions of sea level rise. Susceptibility to extreme events, eutrophication, and shoreline modification has left many coastal regions in a degraded state. Shoreline protection has traditionally taken the form of seawalls and offshore breakwaters which can be detrimental to both the local ecosystems and adjoining shorelines. The objective of this thesis is to analyze the hydrodynamic and...
Show moreCoastal vulnerability has been gaining recognition as a critical issue, especially with the increasing predictions of sea level rise. Susceptibility to extreme events, eutrophication, and shoreline modification has left many coastal regions in a degraded state. Shoreline protection has traditionally taken the form of seawalls and offshore breakwaters which can be detrimental to both the local ecosystems and adjoining shorelines. The objective of this thesis is to analyze the hydrodynamic and bathymetric variation that occurs within Mosquito Lagoon, Florida following living shoreline and oyster reef restorations. The shoreline sites were sampled using a Before-After-Control-Impact (BACI) design and data were analyzed to ascertain the hydrodynamic and bathymetric variations that occurred resulting from plantings of emergent vegetation and deployment of biogenic wave break structures. Turbulent statistics were calculated to determine the effects of nearshore emergent vegetation on the incoming currents and waves. The vegetative growth in conjunction with the wave break structure was shown to reduce the onshore velocities to 46% of those observed at the reference site. Surveys among restored and degraded shorelines and oyster reefs exhibit average crest heights 10-20 cm lower in the restored sites. Nearshore slopes at the hard armored TM Seawall site were over 161% steeper than the restored sites comprised of emergent vegetation and wave break structures implying that scour was present at the toe of the structure from potentially reflected wave energies and increased swash velocities. Quantifying the hydrodynamic and geomorphic processes at work within restored shorelines and reefs may aide managers in best practices both in selection of viable restoration sites and with proper implementation of restoration techniques.
Show less - Date Issued
- 2019
- Identifier
- CFE0007535, ucf:52601
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007535
- 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
- Tidal hydrodynamic response to sea level rise and coastal geomorphology in the Northern Gulf of Mexico.
- Creator
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Passeri, Davina, Hagen, Scott, Medeiros, Stephen, Wang, Dingbao, Weishampel, John, University of Central Florida
- Abstract / Description
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Sea level rise (SLR) has the potential to affect coastal environments in a multitude of ways, including submergence, increased flooding, and increased shoreline erosion. Low-lying coastal environments such as the Northern Gulf of Mexico (NGOM) are particularly vulnerable to the effects of SLR, which may have serious consequences for coastal communities as well as ecologically and economically significant estuaries. Evaluating potential changes in tidal hydrodynamics under SLR is essential for...
Show moreSea level rise (SLR) has the potential to affect coastal environments in a multitude of ways, including submergence, increased flooding, and increased shoreline erosion. Low-lying coastal environments such as the Northern Gulf of Mexico (NGOM) are particularly vulnerable to the effects of SLR, which may have serious consequences for coastal communities as well as ecologically and economically significant estuaries. Evaluating potential changes in tidal hydrodynamics under SLR is essential for understanding impacts to navigation, ecological habitats, infrastructure and the morphologic evolution of the coastline. The intent of this research is to evaluate the dynamic effects of SLR and coastal geomorphology on tidal hydrodynamics along the NGOM and within three National Estuarine Research Reserves (NERRs), namely Grand Bay, MS, Weeks Bay, AL, and Apalachicola, FL. An extensive literature review examined the integrated dynamic effects of SLR on low gradient coastal landscapes, primarily in the context of hydrodynamics, coastal morphology, and marsh ecology. Despite knowledge of the dynamic nature of coastal systems, many studies have neglected to consider the nonlinear effects of SLR and employed a simplistic (")bathtub(") approach in SLR assessments. More recent efforts have begun to consider the dynamic effects of SLR (e.g., the nonlinear response of hydrodynamics under SLR); however, little research has considered the integrated feedback mechanisms and co-evolution of multiple interdependent systems (e.g., the nonlinear responses and interactions of hydrodynamics and coastal morphology under SLR). Synergetic approaches that integrate the dynamic interactions between physical and ecological environments will allow for more comprehensive evaluations of the impacts of SLR on coastal systems.Projecting future morphology is a challenging task; various conceptual models and statistical methods have been employed to project future shoreline positions. Projected shoreline change rates from a conceptual model were compared with historic shoreline change rates from two databases along sandy shorelines of the. South Atlantic Bight and NGOM coasts. The intent was not to regard one method as superior to another, but rather to explore similarities and differences between the methods and offer suggestions for projecting shoreline changes in SLR assessments.The influence of incorporating future shoreline changes into hydrodynamic modeling assessments of SLR was evaluated for the NGOM coast. Astronomic tides and hurricane storm surge were simulated under present conditions, the projected 2050 sea level with present-day shorelines, and the projected 2050 sea level with projected 2050 shorelines. Results demonstrated that incorporating shoreline changes had variable impacts on the hydrodynamics; storm surge was more sensitive to the shoreline changes than astronomic tides. It was concluded that estimates of shoreline change should be included in hydrodynamic assessments of SLR along the NGOM. Evaluating how hydrodynamics have been altered historically under a changing landscape in conjunction with SLR can provide insight to future changes. The Grand Bay estuary has undergone significant landscape changes historically. Tidal hydrodynamics were simulated for present and historic conditions (dating back to 1848) using a hydrodynamic model modified with unique sea levels, bathymetry, topography, and shorelines representative of each time period. Changes in tidal amplitudes varied across the domain. Harmonic constituent phases sped up from historic conditions. Tidal velocities in the estuary were stronger historically, and reversed from being flood dominant in 1848 to ebb dominant in 2005. To project how tidal hydrodynamics may be altered under future scenarios along the NGOM and within the three NERRs, a hydrodynamic model was used to simulate present (circa 2005) and future (circa 2050 and 2100) astronomic tides. The model was modified with projections of future sea levels as well as shoreline positions and dune elevations obtained from a Bayesian network (BN) model. Tidal amplitudes within some of the embayments increased under the higher SLR scenarios; there was a high correlation between the change in the inlet cross-sectional area under SLR and the change in the tidal amplitude within each bay. Changes in harmonic constituent phases indicated faster tidal propagation in the future scenarios within most of the bays. Tidal velocities increased in all of the NERRs which altered flood and ebb current strengths.The work presented herein improves the understanding of the response of tidal hydrodynamics to morphology and SLR. This is beneficial not only to the scientific community, but also to the management and policy community. These findings will have synergistic effects with a variety of coastal studies including storm surge and biological assessments of SLR. In addition, findings can benefit monitoring and restoration activities in the NERRs. Ultimately, outcomes will allow coastal managers and policy makers to make more informed decisions that address specific needs and vulnerabilities of each particular estuary, the NGOM coastal system, and estuaries elsewhere with similar conditions.
Show less - Date Issued
- 2015
- Identifier
- CFE0006049, ucf:50962
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006049
- Title
- Development of an Automated Method for Identification of Wet and Dry Channel Segments Using LiDAR Data and Fuzzy Logic Cluster Analysis.
- Creator
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Rowney, Chris, Wang, Dingbao, Medeiros, Stephen, Kibler, Kelly, University of Central Florida
- Abstract / Description
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Research into the use of LiDAR data for purposes other than simple topographic elevation determination, such as urban land cover classification and the identification of forest biomass, has become prominent in recent years. In many cases, alternative analysis methodologies conducted using airborne LiDAR data are possible because the raw data collected during a survey can include information other than the classically used elevation and coordinate points, the X, Y, and Z of the plane. In...
Show moreResearch into the use of LiDAR data for purposes other than simple topographic elevation determination, such as urban land cover classification and the identification of forest biomass, has become prominent in recent years. In many cases, alternative analysis methodologies conducted using airborne LiDAR data are possible because the raw data collected during a survey can include information other than the classically used elevation and coordinate points, the X, Y, and Z of the plane. In particular, intensity return values for each point in a LiDAR grid have been found to provide a useful data set for wet and dry channel classification. LiDAR intensity return data are, in essence, a numeric representation of the characteristic light reflectivity of the object being scanned; the more reflective the object is, the higher the intensity return will be. Intensity data points are collected along the course of the channel network and within the perceived banks of the channel. Intensity data do not crisply reflect a perfectly wet or dry condition, but instead vary over a range such that each location can be viewed as partially wet and partially dry. It is advantageous to assess problems of this type using the methods of fuzzy logic. Specifically, the variance in LiDAR intensity return data is such that the use of fuzzy logic to identify intensity cluster centers, and thereby assign wet and dry condition identifiers based on fuzzy memberships, is a possibility. Membership within a fuzzy data set is characterized by a value representing the degree of membership. Typically, membership values range from 0 (representing non-membership) through 1 (representing full membership), with many observations found to be not at either extreme but instead at some intermediate value representing partial membership. The ultimate goal of this research was to design and develop an automated algorithm to identify wet and dry channel sections, given a previously identified channel network based on topographic elevation, using a combination of intensity return values from LiDAR data and fuzzy logic clustering methods, and to implement that algorithm in such a way as to produce reliable multi-class channel segments in ArcGIS. To enable control of calculations, limiting parameters were defined, specifically including the maximum allowable bank slope, and a filtering percentage to more accurately accommodate the study area.Alteration of the maximum allowable bank slope has been shown to affect the comparative quantity of high and low intensity centroids, but only in extreme bank slope conditions are the centroids changed enough to hamper results. However, interference from thick vegetation has been shown to lower intensity values in dry channel sections into the range of a wet channel. The addition of a filtering algorithm alleviates some of the interference, but not all. Overall results of the tool show an effective methodology where basic channel conditions are identified, but refinement of the tool could produce more accurate results.
Show less - Date Issued
- 2015
- Identifier
- CFE0006053, ucf:50975
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006053
- Title
- A Continuous Hydrologic Model Structure for Applications at Multiple Time Scales.
- Creator
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Griffen, Jonathan, Wang, Dingbao, O'Reilly, Andrew, Medeiros, Stephen, University of Central Florida
- Abstract / Description
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There are many different controlling factors on the partitioning of rainfall into runoff. However, the influence of each of these controls varies across different temporal scales. Consequently, numerous water balance models have been developed in the literature for application across various time scales. These models are usually developed for a particular time scale so that the controls with the greatest influence on rainfall partitioning are captured. For example, the SCS curve number method...
Show moreThere are many different controlling factors on the partitioning of rainfall into runoff. However, the influence of each of these controls varies across different temporal scales. Consequently, numerous water balance models have been developed in the literature for application across various time scales. These models are usually developed for a particular time scale so that the controls with the greatest influence on rainfall partitioning are captured. For example, the SCS curve number method was developed to simulate direct runoff at the event scale; the (")abcd(") model was developed as a monthly water balance model; and the Budyko model was developed for long-term water balance. More recently, the proportionality hypothesis, which traces its origins from the SCS curve number method, has been identified as the commonality between these three hydrologic models, suggesting that this hypothesis may be the unifying principle of hydrologic models across various time scales.The objective of this thesis is to develop a conceptual hydrologic model structure for continuous simulations for multiple time scales. The developed model is applicable to daily, monthly, and annual time scales.Direct runoff is computed by a proportionality relationship in the SCS curve number method. In the (")abcd(") model, evapotranspiration and storage at the end of each time period are computed by a proportionality relationship, however evapotranspiration is computed based on an exponential relationship of storage and potential evapotranspiration while base flow is computed based on a linear reservoir model. In the Budyko model, runoff and evapotranspiration are computed by a proportionality relationship.The primary difference with the proposed model in this thesis in comparison with the other three water balance models is the application of the proportionality hypothesis to the partitioning of surface runoff and continuing abstraction as well as the partitioning of continuing evapotranspiration and subsurface flow.The proposed model structure is implemented in Matlab. The developed model includes six parameters, which are estimated for 71 case study catchments in the United States using a genetic algorithm. The model performances at the daily, monthly and annual time scales are evaluated during calibration and validation periods, and compared with the (")abcd(") model and a Budyko-type model developed for multiple time scales.Evaluation of the models shows that the proposed model performs better or comparable to the other models at all time scales.
Show less - Date Issued
- 2014
- Identifier
- CFE0005173, ucf:50672
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005173
- Title
- Response of Streamflow and Sediment Loading in the Apalachicola River, Florida to Climate and Land Use Land Cover Change.
- Creator
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Hovenga, Paige, Medeiros, Stephen, Wang, Dingbao, Kibler, Kelly, University of Central Florida
- Abstract / Description
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Located in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay in the Northern Gulf of Mexico, directly influencing the ecology of the region, in particular seagrass and oyster production. The objective of this study is to evaluate the response of runoff and sediment loading in the Apalachicola River under projected climate change scenarios and land use / land cover ...
Show moreLocated in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay in the Northern Gulf of Mexico, directly influencing the ecology of the region, in particular seagrass and oyster production. The objective of this study is to evaluate the response of runoff and sediment loading in the Apalachicola River under projected climate change scenarios and land use / land cover (LULC) change. A hydrologic model using the Soil Water Assessment Tool (SWAT) was developed for the Apalachicola region to simulate daily discharge and sediment load under present (circa 2000) and future conditions (circa 2100) to understand how the system responds over seasonal and event time frames to changes in climate, LULC, and coupled climate / LULC. These physically-based models incorporate a digital elevation model (DEM), LULC, soil maps, climate data, and management controls. Long Ashton Research Station-Weather Generator (LARS-WG) was used to create downscaled stochastic temperature and precipitation inputs from three Global Climate Models (GCM), each under Intergovernmental Panel on Climate Change (IPCC) carbon emission scenarios for A1B, A2, and B1. Projected 2100 LULC data provided by the United States Geological Survey (USGS) EROS Center was incorporated for each corresponding IPCC scenario. Results indicate climate change may induce seasonal shifts to both runoff and sediment loading, acting to extend periods of high flow and minimum sediment loadings or altering the time at which these events occur completely. Changes in LULC showed minimal effects on flow while more sediment loading was associated with increased agriculture and urban areas and decreased forested regions. A nonlinear response for both streamflow and sediment loading was observed by coupling climate and LULC change into the hydrologic model, indicating changes in one may exacerbate or dampen the effects of the other. Peak discharge and sediment loading associated with extreme events showed both increases and decreases in the future, with variability dependent on the GCM used. Similar behavior was observed in the total discharge resulting from extreme events and increased total sediment load was frequently predicted for the A2 and A1B scenarios for simulations involving changes in climate only, LULC only, and both climate and LULC. Output from the individual GCMs predicted differing responses of streamflow and sediment loading to changes in climate on both the seasonal and event scale. Additional region-specific research is needed to better optimize the GCM ensemble and eliminate those that provide erroneous output. In addition, future assessment of the downscaling approach to capture extreme events is required. Findings from this study can be used to further understand climate and LULC implications to the Apalachicola Bay and surrounding region as well as similar fluvial estuaries while providing tools to better guide management and mitigation practices.
Show less - Date Issued
- 2015
- Identifier
- CFE0006326, ucf:51543
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006326
- Title
- Effects of climate change and anthropogenic activities on the Everglades landscape.
- Creator
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Sandhu, Daljit, Singh, Arvind, Wang, Dingbao, Medeiros, Stephen, University of Central Florida
- Abstract / Description
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The Everglades has been experiencing major changes, both climatic and anthropogenic, such that the landscape is experiencing additional stresses and forcings leading it away from its natural equilibrium. The land within and surrounding the Everglades has undergone severe modifications that may have detrimental effects on wildlife and natural features, such as rivers and landscape connectivity. Here in this study, the main focus is on understanding and quantifying hydrologic and geomorphic...
Show moreThe Everglades has been experiencing major changes, both climatic and anthropogenic, such that the landscape is experiencing additional stresses and forcings leading it away from its natural equilibrium. The land within and surrounding the Everglades has undergone severe modifications that may have detrimental effects on wildlife and natural features, such as rivers and landscape connectivity. Here in this study, the main focus is on understanding and quantifying hydrologic and geomorphic signatures of climatic and anthropogenic changes on the Everglades landscape. For this, in particular, available data on natural hydrological processes was used, such as rainfall, groundwater elevation, streamflow as well as surface elevations and satellite images for three different regions. These regions are categorized as forested, urban (nearby Everglades regions) and transition (in between forested and urban regions). The results show distinct differences in the statistics of observed hydrologic variables for the three different regions. For example, the probability distribution functions (PDFs) of groundwater elevation for the case of urban region show a shift in mean as well as lower asymmetry as compared to forested regions. In addition, a significant difference in the slopes between smaller and larger scales of the power spectral densities (PSDs) is observed when transitioning from forested to urban. For the case of the streamflow PDFs and PSDs, the opposite trends are observed. Basin properties extracted from digital elevation models (DEMs) of the Everglades reveal that drainage densities increase when moving from the urban to the forested sub-regions, highlighting the topographic and land use/land cover changes that the Everglades has been subjected to in recent years. Finally, computing the interarrival times of extreme ((>)95th percentile) events that suggest power-law behavior, the changes in power-law exponents of the hydrologic processes further highlights how these processes differ spatially and how the landscape has to respond to these changes. Quantifying these observed changes will help develop a better understanding of the Everglades and other wetlands ecosystems for management to future changes and restoration.
Show less - Date Issued
- 2016
- Identifier
- CFE0006495, ucf:51395
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006495
- 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
- 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
- Title
- Hydrologic controls on the natural drainage networks extracted from high-resolution topographic data.
- Creator
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Hooshyar, Milad, Wang, Dingbao, Medeiros, Stephen, Singh, Arvind, Kibler, Kelly, Weishampel, John, University of Central Florida
- Abstract / Description
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Drainage networks are important geomorphologic and hydrologic features which significantly control runoff generation. Drainage networks are composed of unchannelized valleys and channels. At valley heads, flow changes from unconfined sheet flow on the hillslope to confined flow in valley. Localized confined flow dominates in valleys as a result of convergent topography with positive curvature. Channels initiate at some distance down from the valley head, and the transition from unchannelized...
Show moreDrainage networks are important geomorphologic and hydrologic features which significantly control runoff generation. Drainage networks are composed of unchannelized valleys and channels. At valley heads, flow changes from unconfined sheet flow on the hillslope to confined flow in valley. Localized confined flow dominates in valleys as a result of convergent topography with positive curvature. Channels initiate at some distance down from the valley head, and the transition from unchannelized valley to channel is referred to as the channel head. Channel heads occur at a point where fluvial transport dominates over diffusive transport.From the hydrologic perspective, channels are categorized as perennial, intermittent, and ephemeral streams based on the flow durations. Perennial streams flow for the most of the time during normal years and are maintained by groundwater discharge. Intermittent (i.e. seasonal) streams flow during certain times of the year receiving water from surface sources such as melting snow or from groundwater. Lastly, ephemeral streams flow only in direct response to precipitation without continuous surface flow. In this dissertation, the hydrologic controls on the drainage networks extracted from high resolution Digital Elevation Models (DEMs) based on Light Detection and Ranging (LiDAR) are investigated. A method for automatic extraction of valley and channel networks from high-resolution DEMs is presented. This method utilizes both positive (i.e., convergent topography) and negative (i.e., divergent topography) curvature to delineate the valley network. The valley and ridge skeletons are extracted using the pixels' curvature and the local terrain conditions. The valley network is generated by checking the terrain for the existence of at least one ridge between two intersecting valleys. The transition from unchannelized to channelized sections (i.e., channel head) in each 1st-order valley tributary is identified independently by categorizing the corresponding contours using an unsupervised approach based on K-means clustering. The method does not require a spatially constant channel initiation threshold (e.g., curvature or contributing area). Moreover, instead of a point attribute (e.g., curvature), the proposed clustering method utilizes the shape of contours, which reflects the entire cross-sectional profile including possible banks. The method was applied to three catchments: Indian Creek and Mid Bailey Run in Ohio, and Feather River in California. The accuracy of channel head extraction from the proposed method is comparable to state-of-the-art channel extraction methods. Valleys extracted from DEMs may be wet (flowing) or dry at any given time depending on the hydrologic conditions. The temporal dynamics of flowing streams are vitally important for understanding hydrologic processes including surface water and groundwater interaction and hydrograph recession. However, observations of wet channel networks are limited, especially in headwater catchments. Near infrared LiDAR data provide an opportunity to map wet channel networks owing to the fine spatial resolution and strong absorption of light energy by water surfaces. A systematic method is developed to map wet channel networks by integrating elevation and signal intensity of ground returns. The signal intensity thresholds for identifying wet pixels are extracted from frequency distributions of intensity return within the convergent topography extent using a Gaussian mixture model. Moreover, the concept of edge in digital image processing, defined based on the intensity gradient, is utilized to enhance detection of small wet channels. The developed method was applied to the Lake Tahoe area based on eight LiDAR acquisitions during recession periods in five watersheds. A power-law relationship between streamflow and wetted channel length during recession periods was derived, and the scaling exponent (L?Q^0.38) is within the range of reported values from fieldwork in other regions.Several studies in the past focused on the relationship between drainage density (i.e., drainage length divided by drainage area) and long-term climate and reported a U-shape pattern. In this dissertation, this relationship was re-visited and the effect of drainage area on drainage density was investigated. Long-term climate was quantified by climate aridity indices which is the ratio between long-term potential evaporation and precipitation. 120 study sites across the United States with minimal human disturbance and a wide range of climate aridity index were selected based on the availability of LiDAR data. The drainage networks were delineated from LiDAR-based 1 m DEMs using the proposed curvature-based method. Despite the U-shaped relationship in the literature, our result shows a significant decreasing trend in the drainage density versus climate aridity index in arid regions; whereas no trend is observed in humid watersheds. This observation and its discrepancy with the reported pattern in the literature are justified considering the dynamics of the runoff erosive force and the resistance of vegetation and the climate controls on them. Our findings suggest that natural drainage networks in arid regions are more sensitive to the change in long-term climate conditions compared with drainage networks in humid climate. It was also found that drainage density has a decreasing trend with drainage area in arid regions; however, no trend was observed in humid regions. In a broader sense, the findings influence our understanding of the formation of drainage networks and the response of hydrologic systems to climate change. The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to movement of water. The branching angles, i.e., the angle between two adjoining channels, in drainage networks are important features related to the network topology and contain valuable information about the forming mechanisms of the landscape. Based on channel networks extracted from 1 m Digital Elevation Models of 120 catchments with minimal human impacts across the United States, we showed that the junction angles have two distinct modes with ?1 ? 49.5(&)deg; and ?2 ? 75.0(&)deg;. The observed angles are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphologic signature of hydrologic processes on drainage networks and develop more refined landscape evolution models.
Show less - Date Issued
- 2017
- Identifier
- CFE0006604, ucf:51278
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006604
- Title
- Base Flow Recession Analysis for Streamflow and Spring Flow.
- Creator
-
Ghosh, Debapi, Wang, Dingbao, Chopra, Manoj, Singh, Arvind, Medeiros, Stephen, Bohlen, Patrick, University of Central Florida
- Abstract / Description
-
Base flow recession curve during a dry period is a distinct hydrologic signature of a watershed. The base flow recession analysis for both streamflow and spring flow has been extensively studied in the literature. Studies have shown that the recession behaviors during the early stage and the late stage are different in many watersheds. However, research on the transition from early stage to late stage is limited and the hydrologic control on the transition is not completely understood. In...
Show moreBase flow recession curve during a dry period is a distinct hydrologic signature of a watershed. The base flow recession analysis for both streamflow and spring flow has been extensively studied in the literature. Studies have shown that the recession behaviors during the early stage and the late stage are different in many watersheds. However, research on the transition from early stage to late stage is limited and the hydrologic control on the transition is not completely understood. In this dissertation, a novel cumulative regression analysis method is developed to identify the transition flow objectively for individual recession events in the well-studied Panola Mountain Research Watershed in Georgia, USA. The streamflow at the watershed outlet is identified when the streamflow at the perennial stream head approaches zero, i.e., flowing streams contract to perennial streams. The identified transition flows are then compared with observed flows when the flowing stream contracts to the perennial stream head. As evidenced by a correlation coefficient of 0.90, these two characteristics of streamflow are found to be highly correlated, suggesting a fundamental linkage between the transition of base flow recession from early to late stages and the drying up of ephemeral streams. At the early stage, the contraction of ephemeral streams mostly controls the recession behavior. At the late stage, perennial streams dominate the flowing streams and groundwater hydraulics governs the recession behavior. The ephemeral stream densities vary from arid regions to humid regions. Therefore, the characteristics of transition flow across the climate gradients are also tested in 40 watersheds. It is found that climate, which is represented by climate aridity index, is the dominant controlling factor on transition flows from early to late recession stages. Transition flows and long-term average base flows are highly correlated with a correlation coefficient of 0.82. Long-term average base flow and the transition flow of recession are base flow characteristics at two temporal scales, i.e., the long-term scale and the event scale during a recession period. This is a signature of the co-evolution of climate, vegetation, soil, and topography at the watershed scale. The characteristics of early and late recession are applied for quantifying human impacts on streamflow in agricultural watersheds with extensive groundwater pumping for irrigation. A recession model is developed to incorporate the impacts of human activities (such as groundwater pumping) and climate variability (such as evapotranspiration) on base flow recession. Groundwater pumping is estimated based on the change of observed base flow recession in watersheds in the High Plains Aquifer. The estimated groundwater pumping rate is found consistent compared with the observed data of groundwater uses for irrigation. Besides streamflow recession analysis, this dissertation also presents a novel spring recession model for Silver Springs in Florida by incorporating groundwater head, spring pool altitude, and net recharge into the existing Torricelli model. The results show that the effective springshed area has continuously declined since 1988. The net recharge has declined since the 1970s with a significant drop in 2002. Subsequent to 2002, the net recharge increased modestly but not to the levels prior to the 1990s. The decreases in effective springshed area and net recharge caused by changes in hydroclimatic conditions including rainfall and temperature, along with groundwater withdrawals, contribute to the declined spring flow.
Show less - Date Issued
- 2015
- Identifier
- CFE0005951, ucf:50814
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005951
- Title
- Understanding Hydroclimatic Controls on Stream Network Dynamics using LiDAR Data.
- Creator
-
Kim, Seoyoung, Wang, Dingbao, Medeiros, Stephen, Nam, Boo Hyun, Singh, Arvind, Sumner, David, University of Central Florida
- Abstract / Description
-
This dissertation investigates the hydroclimatic controls on drainage network dynamics and characterizes the variation of drainage density in various climate regions. The methods were developed to extract the valley and wet channel networks based on Light Detection and Ranging (LiDAR) data including the elevation and intensity of laser returns. The study watersheds were selected based on the availability of streamflow observations and LiDAR data. Climate aridity index was used as a...
Show moreThis dissertation investigates the hydroclimatic controls on drainage network dynamics and characterizes the variation of drainage density in various climate regions. The methods were developed to extract the valley and wet channel networks based on Light Detection and Ranging (LiDAR) data including the elevation and intensity of laser returns. The study watersheds were selected based on the availability of streamflow observations and LiDAR data. Climate aridity index was used as a quantitative indicator for climate. The climate controls on drainage density were re-visited using watersheds with minimal anthropogenic interferences and compared with the U-shape relationship reported in the previous studies. A curvature-based method was developed to extract a valley network from 1-m LiDAR-based Digital Elevation Models. The relationship between drainage density and climate aridity index showed a monotonic increasing trend and the discrepancy was explained by human interventions and underestimated drainage density due to the coarse spatial resolution (30-meter) of the topographic maps used in previous research. Observations of wet channel networks are limited, especially in headwater catchments in comparison with the importance of stream network expansion and contraction. A systematic method was developed to extract wet channel networks based on the signal intensities of LiDAR ground returns, which are lower on water surfaces than on dry surfaces. The frequency distributions of intensities associated with wet surface and dry surface returns were constructed. With the aid of LiDAR-based ground elevations, signal intensity thresholds were identified for extracting wet channels. The developed method was applied to Lake Tahoe area during recession periods in five watersheds. A power-law relationship between streamflow and wet channel length was obtained and the scaling exponent was consistent with the reported findings from field work in other regions.Perennial streams flow for the most of the time during normal years and are usually defined based on a flow duration threshold. The streamflow characteristics of perennial streams in this research were assessed using the relationship between streamflow exceedance probability and wet channel ratio based on wet channel networks extracted from LiDAR data. Non-dimensional analysis based on the relationship between streamflow exceedance probability and wet channel ratio showed that results were consistent with previous research about perennial stream definition, and provided the possibility to use wet channel ratio to define perennial streams. Wetlands are important natural resources and need to be monitored regularly in order to understand their inundation dynamics, function and health. Wetland mapping is a key part of monitoring programs. A framework for detecting wetland was developed based on LiDAR elevation and intensity information. After masking out densely vegetated areas, wet areas were identified based on signal intensity of ground returns for barrier islands in East-Central Florida. The intensity threshold of wet surface was identified by decomposing composite probability distribution functions using a Gamma mixture model and the Expectation-Maximization algorithm. This method showed good potential for wetland mapping.The methodology developed in this dissertation demonstrated that incorporating LiDAR data into the drainage networks, stream network dynamics and wetlands results in enhanced understanding of hydroclimatic controls on stream network dynamics. LiDAR data provide a rich information source including elevation and intensity, and are of great benefit to hydrologic research community.
Show less - Date Issued
- 2016
- Identifier
- CFE0006532, ucf:51372
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006532
- Title
- An Integrated Hydrodynamic-Marsh Model with Applications in Fluvial, Marine, and Mixed Estuarine Systems.
- Creator
-
Alizad, Karim, Hagen, Scott, Medeiros, Stephen, Wang, Dingbao, Weishampel, John, University of Central Florida
- Abstract / Description
-
Coastal wetlands experience fluctuating productivity when subjected to various stressors. One of the most impactful stressors is sea level rise (SLR) associated with global warming. Research has shown that under SLR, salt marshes may not have time to establish an equilibrium with sea level and may migrate landward or become open water. Salt marsh systems play an important role in the coastal ecosystem by providing intertidal habitats and food for birds, fish, crabs, mussels, and other animals...
Show moreCoastal wetlands experience fluctuating productivity when subjected to various stressors. One of the most impactful stressors is sea level rise (SLR) associated with global warming. Research has shown that under SLR, salt marshes may not have time to establish an equilibrium with sea level and may migrate landward or become open water. Salt marsh systems play an important role in the coastal ecosystem by providing intertidal habitats and food for birds, fish, crabs, mussels, and other animals. They also protect shorelines by dissipating flow and damping wave energy through an increase in drag forces. Due to the serious consequences of losing coastal wetlands, evaluating the potential future changes in their structure and distribution is necessary in order for coastal resource managers to make informed decisions. The objective of this study was to develop a spatially-explicit model by connecting a hydrodynamic model and a parametric marsh model and using it to assess the dynamic effects of SLR on salt marsh systems within three National Estuarine Research Reserves (NERRs) in the Northern Gulf of Mexico. Coastal salt marsh systems are an excellent example of complex interrelations between physics and biology, and the resulting benefits to humanity. In order to investigate salt marsh productivity under projected SLR scenarios, a depth integrated hydrodynamic model was coupled to a parametric marsh model to capture the dynamic feedback loop between physics and biology. The hydrodynamic model calculates mean high water (MHW) and mean low water (MLW) within the river and tidal creeks by harmonic analysis of computed tidal constituents. The responses of MHW and MLW to SLR are nonlinear due to localized changes in the salt marsh platform elevation and biomass productivity (which influences bottom friction). Spatially-varying MHW and MLW are utilized in a two-dimensional application of the parametric Marsh Equilibrium Model to capture the effects of the hydrodynamics on biomass productivity and salt marsh accretion, where accretion rates are dependent on the spatial distribution of sediment deposition in the marsh. This model accounts both organic (decomposition of in-situ biomass) and inorganic (allochthonous) marsh platform accretion and the effects of spatial and temporal biomass density changes on tidal flows. The coupled hydro-marsh model, herein referred to as HYDRO-MEM, leverages an optimized coupling time step at which the two models exchange information and update the solution to capture the system's response to projected linear and non-linear SLR rates.Including accurate marsh table elevations into the model is crucial to obtain meaningful biomass productivity projections. A lidar-derived Digital Elevation Model (DEM) was corrected by incorporating Real Time Kinematic (RTK) surveying elevation data. Additionally, salt marshes continually adapt in an effort to reach an equilibrium within the ideal range of relative SLR and depth of inundation. The inputs to the model, specifically topography and bottom roughness coefficient, are updated using the biomass productivity results at each coupling time step to capture the interaction between the marsh and hydrodynamic models.The coupled model was tested and validated in the Timucuan marsh system, located in northeastern Florida by computing projected biomass productivity and marsh platform elevation under two SLR scenarios. The HYDRO-MEM model coupling protocol was assessed using a sensitivity study of the influence of coupling time step on the biomass productivity results with a comparison to results generated using the MEM approach only. Subsequently, the dynamic effects of SLR were investigated on salt marsh productivity within the three National Estuarine Research Reserves (NERRs) (Apalachicola, FL, Grand Bay, MS, and Weeks Bay, AL) in the Northern Gulf of Mexico (NGOM). These three NERRS are fluvial, marine and mixed estuarine systems, respectively. Each NERR has its own unique characteristics that influence the salt marsh ecosystems. The HYDRO-MEM model was used to assess the effects of four projections of low (0.2 m), intermediate-low (0.5 m), intermediate-high (1.2 m) and high (2.0 m) SLR on salt marsh productivity for the year 2100 for the fluvial dominated Apalachicola estuary, the marine dominated Grand Bay estuary, and the mixed Weeks Bay estuary. The results showed increased productivity under the low SLR scenario and decreased productivity under the intermediate-low, intermediate-high, and high SLR. In the intermediate-high and high SLR scenarios, most of the salt marshes drowned (converted to open water) or migrated to higher topography. These research presented herein advanced the spatial modeling and understanding of dynamic SLR effects on coastal wetland vulnerability. This tool can be used in any estuarine system to project salt marsh productivity and accretion under sea level change scenarios to better predict possible responses to projected SLR scenarios. The findings are not only beneficial to the scientific community, but also are useful to restoration, planning, and monitoring activities in the NERRs. Finally, the research outcomes can help policy makers and coastal managers to choose suitable approaches to meet the specific needs and address the vulnerabilities of these three estuaries, as well as other wetland systems in the NGOM and marsh systems anywhere in the world.
Show less - Date Issued
- 2016
- Identifier
- CFE0006523, ucf:51360
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006523
- Title
- Incorporating Remotely Sensed Data into Coastal Hydrodynamic Models: Parameterization of Surface Roughness and Spatio-Temporal Validation of Inundation Area.
- Creator
-
Medeiros, Stephen, Hagen, Scott, Weishampel, John, Wang, Dingbao, Yeh, Gour-Tsyh, University of Central Florida
- Abstract / Description
-
This dissertation investigates the use of remotely sensed data in coastal tide and inundation models, specifically how these data could be more effectively integrated into model construction and performance assessment techniques. It includes a review of numerical wetting and drying algorithms, a method for constructing a seamless digital terrain model including the handling of tidal datums, an investigation into the accuracy of land use / land cover (LULC) based surface roughness...
Show moreThis dissertation investigates the use of remotely sensed data in coastal tide and inundation models, specifically how these data could be more effectively integrated into model construction and performance assessment techniques. It includes a review of numerical wetting and drying algorithms, a method for constructing a seamless digital terrain model including the handling of tidal datums, an investigation into the accuracy of land use / land cover (LULC) based surface roughness parameterization schemes, an application of a cutting edge remotely sensed inundation detection method to assess the performance of a tidal model, and a preliminary investigation into using 3-dimensional airborne laser scanning data to parameterize surface roughness.A thorough academic review of wetting and drying algorithms employed by contemporary numerical tidal models was conducted. Since nearly all population centers and valuable property are located in the overland regions of the model domain, the coastal models must adequately describe the inundation physics here. This is accomplished by techniques that generally fall into four categories: Thin film, Element removal, Depth extrapolation, and Negative depth. While nearly all wetting and drying algorithms can be classified as one of the four types, each model is distinct and unique in its actual implementation.The use of spatial elevation data is essential to accurate coastal modeling. Remotely sensed LiDAR is the standard data source for constructing topographic digital terrain models (DTM). Hydrographic soundings provide bathymetric elevation information. These data are combined to form a seamless topobathy surface that is the foundation for distributed coastal models. A three-point inverse distance weighting method was developed in order to account for the spatial variability of bathymetry data referenced to tidal datums. This method was applied to the Tampa Bay region of Florida in order to produce a seamless topobathy DTM.Remotely sensed data also contribute to the parameterization of surface roughness. It is used to develop land use / land cover (LULC) data that is in turn used to specify spatially distributed bottom friction and aerodynamic roughness parameters across the model domain. However, these parameters are continuous variables that are a function of the size, shape and density of the terrain and above-ground obstacles. By using LULC data, much of the variation specific to local areas is generalized due to the categorical nature of the data. This was tested by comparing surface roughness parameters computed based on field measurements to those assigned by LULC data at 24 sites across Florida. Using a t-test to quantify the comparison, it was proven that the parameterizations are significantly different. Taking the field measured parameters as ground truth, it is evident that parameterizing surface roughness based on LULC data is deficient.In addition to providing input parameters, remotely sensed data can also be used to assess the performance of coastal models. Traditional methods of model performance testing include harmonic resynthesis of tidal constituents, water level time series analysis, and comparison to measured high water marks. A new performance assessment that measures a model's ability to predict the extent of inundation was applied to a northern Gulf of Mexico tidal model. The new method, termed the synergetic method, is based on detecting inundation area at specific points in time using satellite imagery. This detected inundation area is compared to that predicted by a time-synchronized tidal model to assess the performance of model in this respect. It was shown that the synergetic method produces performance metrics that corroborate the results of traditional methods and is useful in assessing the performance of tidal and storm surge models. It was also shown that the subject tidal model is capable of correctly classifying pixels as wet or dry on over 85% of the sample areas.Lastly, since it has been shown that parameterizing surface roughness using LULC data is deficient, progress toward a new parameterization scheme based on 3-dimensional LiDAR point cloud data is presented. By computing statistics for the entire point cloud along with the implementation of moving window and polynomial fit approaches, empirical relationships were determined that allow the point cloud to estimate surface roughness parameters. A multi-variate regression approach was chosen to investigate the relationship(s) between the predictor variables (LiDAR statistics) and the response variables (surface roughness parameters). It was shown that the empirical fit is weak when comparing the surface roughness parameters to the LiDAR data. The fit was improved by comparing the LiDAR to the more directly measured source terms of the equations used to compute the surface roughness parameters. Future work will involve using these empirical relationships to parameterize a model in the northern Gulf of Mexico and comparing the hydrodynamic results to those of the same model parameterized using contemporary methods. In conclusion, through the work presented herein, it was demonstrated that incorporating remotely sensed data into coastal models provides many benefits including more accurate topobathy descriptions, the potential to provide more accurate surface roughness parameterizations, and more insightful performance assessments. All of these conclusions were achieved using data that is readily available to the scientific community and, with the exception of the Synthetic Aperture Radar (SAR) from the Radarsat-1 project used in the inundation detection method, are available free of charge. Airborne LiDAR data are extremely rich sources of information about the terrain that can be exploited in the context of coastal modeling. The data can be used to construct digital terrain models (DTMs), assist in the analysis of satellite remote sensing data, and describe the roughness of the landscape thereby maximizing the cost effectiveness of the data acquisition.
Show less - Date Issued
- 2012
- Identifier
- CFE0004271, ucf:49506
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004271