Browsing by Subject "Remote Sensing"
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Item Estimating Canopy Fuel Parameters with In-Situ and Remote Sensing Data(2012-02-14) Mutlu, MugeCrown fires, the fastest spreading of all forest fires, can occur in any forest type throughout the United States and the world. The occurrence of crown fires has become increasingly frequent and severe in recent years. The overall aim of this study is to estimate the forest canopy fuel parameters including crown base height (CBH) and crown bulk density (CBD), and to investigate the potential of using airborne lidar data in east Texas. The specific objectives are to: (1) propose allometric estimators of CBD and CBH and compare the results of using those estimators to those produced by the CrownMass/FMAPlus software at tree and stand levels for 50 loblolly pine plots in eastern Texas, (2) develop a methodology for using airborne light detection and ranging (lidar) to estimate CBD and CBH canopy fuel parameters and to simulate fire behavior using estimated forest canopy parameters as FARSITE inputs, and (3) investigate the use of spaceborne ICEsat /GLAS (Ice, Cloud, and Land Elevation Satellite/Geoscience Laser Altimeter System) lidar for estimating canopy fuel parameters. According to our results from the first study, the calculated average CBD values, across all 50 plots, were 0.18 kg/m? and 0.07 kg/m?, respectively, for the allometric equation proposed herein and the CrownMass program. Lorey?s mean height approach was used in this study to calculate CBH at plot level. The average height values of CBH obtained from Lorey?s height approach was 10.6 m and from the CrownMass program was 9.1 m. The results obtained for the two methods are relatively close to each other; with the estimate of CBH being 1.16 times larger than the CrownMass value. According to the results from the second study, the CBD and CBH were successfully predicted using airborne lidar data with R? values of 0.748 and 0.976, respectively. The third study demonstrated that canopy fuel parameters can be successfully estimated using GLAS waveform data; an R? value of 0.84 was obtained. With these approaches, we are providing practical methods for quantifying these parameters and making them directly available to fire managers. The accuracy of these parameters is very important for realistic predictions of wildfire initiation and growth.Item Estimating potential evapotranspiration over the Edwards Aquifer, utilizing the Priestley-Taylor equation(2011-12) Edwards, Carl Alexander; Groat, Charles G.; Kreitler, Charles W.; Quiñonez-Piñón, Rebeca; Scanlon, BridgetEstimating recharge is a critical aspect of groundwater management, when aquifer resources are constrained by multiple users. The Edwards Aquifer, an artesian aquifer underlying Austin and San Antonio, Texas, sustains municipalities, farmers and fragile habitats at discharge locations. Rising municipal demand for Edwards water supports the need for effective conservation over time to maintain the well-being of all users. Predicting recharge is a valuable tool for determining future available resources. Evapotranspiration (ET) accounts for a majority of water loss following precipitation, significantly affecting recharge. Developing a method for accurate regional estimates of ET is complicated by aquifer characteristics, expensive instrumentation, and a variable climate. This study investigates a specific method for estimating regional potential ET (ETp), by combining the Priestley-Taylor equation with data primarily retrieved from the Moderate-Resolution Imaging Spectroradiometer. Improved resolution and timing of satellite measurements provides greater regional specificity for variables related to ET calculations. ETp is then estimated for 2004 and 2005, utilizing data from MODIS, aboard NASA’s Aqua and Terra satellites. Land surface temperature, leaf area index and albedo retrieved from MODIS replace in situ measurements, which are often nonexistent in a regional context. Incoming radiation, a direct input in the Priestley-Taylor equation, is retrieved from the National Center for Environmental Prediction’s North American Regional Reanalysis Model (NARR). Results show methods overestimate ET between 400% to over 1000% when compared to actual ET (ETa) at two locations in the northeast portion of the aquifer. Correlation is improved when ETp is treated as an instantaneous rate rather than daily. During months of above average precipitation, which are more representative of potential conditions, instantaneous ETp exceeded ETa by an average of 81%, with a root mean squared error of 1.15 mm/30min and an average positive bias of 2.84 mm/30min. Considering the soil moisture limited conditions throughout Central Texas, a positive bias is not surprising. Incorporating a calibrated Priestly-Taylor could improve accuracy, but estimating regional ETp remains restricted by available daily data necessary for calculations and comparison.Item Fractional Snow-Cover Mapping Through Artificial Neural Network Analysis of MODIS Surface Reflectance.(2010-07-14) Dobreva, Iliyana D.Accurate areal measurements of snow-cover extent are important for hydrological and climate modeling. The traditional method of mapping snow cover is binary where a pixel is approximated to either snow-covered or snow-free. Fractional snow cover (FSC) mapping achieves a more precise estimate of areal snow-cover extent by determining the fraction of a pixel that is snow-covered. The two most common FSC methods using Moderate Resolution Imaging Spectroradiometer (MODIS) images are linear spectral unmixing and the empirical Normalized Difference Snow Index (NDSI) method. Machine learning is an alternative to these approaches for estimating FSC, as Artificial Neural Networks (ANNs) have been used for estimating the subpixel abundances of other surfaces. The advantages of ANNs over the other approaches are that they can easily incorporate auxiliary information such as land-cover type and are capable of learning nonlinear relationships between surface reflectance and snow fraction. ANNs are especially applicable to mapping snow-cover extent in forested areas where spatial mixing of surface components is nonlinear. This study developed an ANN approach to snow-fraction mapping. A feed-forward ANN was trained with backpropagation to estimate FSC from MODIS surface reflectance, NDSI, Normalized Difference Vegetation Index (NDVI) and land cover as inputs. The ANN was trained and validated with high spatial-resolution FSC derived from Landsat Enhanced Thematic Mapper Plus (ETM+) binary snow-cover maps. ANN achieved best result in terms of extent of snow-covered area over evergreen forests, where the extent of snow cover was slightly overestimated. Scatter plot graphs of the ANN and reference FSC showed that the neural network tended to underestimate snow fraction in high FSC and overestimate it in low FSC. The developed ANN compared favorably to the standard MODIS FSC product with the two methods estimating the same amount of total snow-covered area in the test scenes.Item Ground Truthing Sargassum in Satellite Imagery: Assessment of Its Effectiveness as an Early Warning System(2012-02-14) Tabone, WendyLarge aggregations of Sargassum, when at sea, provide important habitat for numerous marine species of vertebrates and invertebrates. It is especially important for the young of several species of sea turtles. However, when large aggregations of Sargassum come ashore on beaches frequented by tourist it is often viewed as a nuisance or even a health hazard. It then becomes a burden to beach management and has to be physically removed as quickly as possible. Many Gulf coast beaches suffer from Sargassum accumulation on a regular basis. Timely information on the size and location of the Sargassum habitat is important to developing coastal management plans. Yet, little is known about the spatial and temporal distribution of Sargassum in the Gulf of Mexico. There is no systematic program to assess the distribution of the macroalgae, therefore practical management plans are difficult to execute. In 2008, Gower and King of the Canadian Institute of Ocean Sciences along with Hu of the University of South Florida, using satellite imagery, identified extensive areas of Sargassum in the western Gulf of Mexico. These were not confirmed with ground truthing data. To date ground truthing observations have not been directly compared with the corresponding satellite images to confirm that it was in fact Sargassum, as the satellite images suggested. y building on the information and research methods of Gower and King, current ground truthing data taken from Texas Parks and Wildlife Gulf trawl sampling surveys was analyzed. In addition, shoreline information and imagery was used to substantiate the data derived from current Moderate-resolution Imaging Spectroradiometer (MODIS) Enhanced Floating Algae Index (EFAI) images. As part of the NASA sponsored research project Mapping and Forecasting of Pelagic Sargassum Drift Habitat in the Gulf of Mexico and South Atlantic Bight for Decision Support, NASA satellite MODIS EFAI images provided by Dr. Hu were used to identify and substantiate corresponding floating Sargassum patches in the Gulf of Mexico. Using the most recent advances in technology and NASA satellite remote sensing, knowledge can be obtained that will aid future decision making for addressing Sargassum in the Gulf of Mexico by substantiating the data provided by satellite imagery. Findings from this research may be useful in developing an early warning system that will allow beach managers to respond in a timely manner to Sargassum events.Item Human Appropriation of Net Primary Productivity (HANPP) in Texas: A Statewide Analysis of Sustainability in the Agricultural and Timber Sectors(2010-07-14) Graff, Christopher P.The sustainability of the Texas agricultural and timber sectors is measured using the ratio of human appropriation of net primary productivity (HANPP) to available net primary productivity (NPP) on a county-by-county basis for the entire state. By combining NPP and HANPP, a measure of ecologic sustainability in terms of carbon dynamics is achieved. This is based on a six-year average from 2000 to 2005 obtained from the NASA MODIS sensor, as well as the calculated NPP harvested from agricultural and timber activities reported by USDA Agricultural and Texas Forest Department timber statistics covering the same years. The spatial pattern of NPP in Texas is strongly influenced by moisture availability and is naturally highest in the Gulf Coastal Plains, and parts of east Texas. Areas of artificially-high NPP can often rival or surpass naturally occurring NPP and occur primarily due to irrigation, such as in the Panhandle and lower Rio Grande Valley. Human appropriation of this carbon is greatest in the Panhandle and lower Rio Grande Valley where, in many counties, >45% of all carbon produced is appropriated. HANPP values throughout the rest of the state are moderate (10-24%) corresponding well with global and national HANPP literature. These results support two conflicting findings: increased HANPP indicates decreased ecological sustainability, but is also a measure of increased agricultural efficiency.Item Investigating impacts of natural and human-induced environmental changes on hydrological processes and flood hazards using a GIS-based hydrological/hydraulic model and remote sensing data(2009-06-02) Wang, LeiNatural and human-induced environmental changes have been altering the earth's surface and hydrological processes, and thus directly contribute to the severity of flood hazards. To understand these changes and their impacts, this research developed a GISbased hydrological and hydraulic modeling system, which incorporates state-of-the-art remote sensing data to simulate flood under various scenarios. The conceptual framework and technical issues of incorporating multi-scale remote sensing data have been addressed. This research develops an object-oriented hydrological modeling framework. Compared with traditional lumped or cell-based distributed hydrological modeling frameworks, the object-oriented framework allows basic spatial hydrologic units to have various size and irregular shape. This framework is capable of assimilating various GIS and remotely-sensed data with different spatial resolutions. It ensures the computational efficiency, while preserving sufficient spatial details of input data and model outputs. Sensitivity analysis and comparison of high resolution LIDAR DEM with traditional USGS 30m resolution DEM suggests that the use of LIDAR DEMs can greatly reduce uncertainty in calibration of flow parameters in the hydrologic model and hence increase the reliability of modeling results. In addition, subtle topographic features and hydrologic objects like surface depressions and detention basins can be extracted from the high resolution LiDAR DEMs. An innovative algorithm has been developed to efficiently delineate surface depressions and detention basins from LiDAR DEMs. Using a time series of Landsat images, a retrospective analysis of surface imperviousness has been conducted to assess the hydrologic impact of urbanization. The analysis reveals that with rapid urbanization the impervious surface has been increased from 10.1% to 38.4% for the case study area during 1974 - 2002. As a result, the peak flow for a 100-year flood event has increased by 20% and the floodplain extent has expanded by about 21.6%. The quantitative analysis suggests that the large regional detentions basins have effectively offset the adverse effect of increased impervious surface during the urbanization process. Based on the simulation and scenario analyses of land subsidence and potential climate changes, some planning measures and policy implications have been derived for guiding smart urban growth and sustainable resource development and management to minimize flood hazards.Item Investigation of coastal dynamics of the Antarctic Ice Sheet using sequential Radarsat SAR images(2009-05-15) Tang, Sheng-JungIncreasing human activities have brought about a global warming trend, and cause global sea level rise. Investigations of variations in coastal margins of Antarctica and in the glacial dynamics of the Antarctic Ice Sheet provide useful diagnostic information for understanding and predicting sea level changes. This research investigates the coastal dynamics of the Antarctic Ice Sheet in terms of changes in the coastal margin and ice flow velocities. The primary methods used in this research include image segmentation based coastline extraction and image matching based velocity derivation. The image segmentation based coastline extraction method uses a modified adaptive thresholding algorithm to derive a high-resolution, complete coastline of Antarctica from 2000 orthorectified SAR images at the continental scale. This new coastline is compared with the 1997 coastline also derived from orthorectified Radarsat SAR images, and the 1963 coastline derived from Argon Declassified Intelligence Satellite Photographs for change detection analysis of the ice margins. The analysis results indicate, in the past four decades, the Antarctic ice sheet experienced net retreat and its areal extent has been reduced significantly. Especially, the ice shelves and glaciers on the Antarctic Peninsula reveal a sustained retreating trend. In addition, the advance, retreat, and net change rates have been measured and inventoried for 200 ice shelves and glaciers. A multi-scale image matching algorithm is developed to track ice motion and to measure ice velocity for a number of sectors of the Antarctic coast based on 1997 and 2000 SAR image pairs. The results demonstrate that a multi-scale image matching algorithm is much more efficient and accurate compared with the conventional algorithm. The velocity measurements from the image matching method have been compared with those derived from InSAR techniques and those observed from conventional ground surveys during 1970-1971. The comparison reveals that the ice velocity in the front part of the Amery Ice Shelf has increased by about 50-200 m/a. The rates of ice calving and temporal variation of ice flow pattern have been also analyzed by integrating the ice margin change measurement with the ice flow velocity at the terminus of the outlet glacier.Item Investigation of Glacial Dynamics in the Lambert Glacier-Amery Ice Shelf System (LAS) Using Remote Sensing(2012-12-10) Chi, Zhaohui 1982-Numerous recent studies have documented dynamic changes in the behaviors of large marine-terminating outlet glaciers and ice streams in Greenland, the Antarctic Peninsula, and West Antarctica. However, fewer observations of outlet glaciers and ice shelves exist for the East Antarctic Ice Sheet. In addition, most recent surface velocity mappings of the Lambert Glacier-Amery Ice Shelf system (LAS) are derived for the time period of 1997-2000. From this research, surface velocity measurements provide a more extended view of the behavior and stability of the LAS over the past two decades than can be gleaned from a single observational period. This study uses remote sensing to investigate whether significant changes in velocities have occurred from the late 1980?s through the late 2010?s and assesses the magnitude of mass balance changes observed at the grounding line. To accomplish this goal, surface velocities of the LAS from late 1980?s to late 2010?s for three separate time periods are measured. The observed surface velocities of the LAS ranged from 0 to 1300 m yr^-1 during 1988-1990. A slight slowing down is detected in the central Amery Ice Shelf front by analyzing the surface velocity measurements made along the centerlines. The mass balance is the difference between snow accumulation and the outflux of the grounded LAS and is calculated for individual sub-basin during the three time intervals of 1988-1990, 1999-2004, and 2007-2011 to illustrate the mass balance variation under sub-basin level. The flux gates of the Lambert Glacial sub-basin combined with the Mellor Glacial and the Fisher Glacial sub-basin appear to be the largest outlet of the grounded ice of the LAS. The ice mass transported from the interior region through the three flux gates in total is 43.58 Gt yr^-1, 36.72 Gt yr^-1, and 38.61 Gt yr^-1 respectively for the three time intervals above. The sub-basins in the eastern side appear differently than the western side. The outfluxes of the eastern sub-basins vary from 15.85 to 18.64 Gt yr^-1, while the western outfluxes vary from 15.85 to 18.64 Gt yr^-1. The grounded LAS has discharged ice from 84.55 to 81.60 Gt yr^-1 and to 79.20 Gt yr^-1 during 1980s-1990s and 1990s-2000s. Assuming the snow accumulation distribution is stable, the grounded LAS mass lose has increased 2.95 Gt yr^-1 from 1980s to 1990s and 2.40 Gt yr^-1 from 1990s to 2000s. These results indicate insight into the stability of the Amery Ice Shelf over the last few decades.Item Modeling Endemic Bark Beetle Populations in Southwestern Ponderosa Pine Forests(2015-02-20) Garza, ChristopherBark beetle populations phase between epidemic, outbreak levels, and low population density, endemic levels. The majority of scientific research is focused on outbreak populations because of the associated economic, ecological, and social impacts. Endemic populations are rarely studied but could provide information about the triggers that cause outbreaks. The goal of this thesis was to gain a better understanding of how endemic populations persist in a landscape through time by looking at the spatial distribution and susceptibility of host trees in southwestern US forested landscapes. To do this, I (1) analyzed 21 years of field data to examine the population dynamics of bark beetles and the factors that affect them, (2) created a statistical model for predicting the absolute risk of individual trees to bark beetle-cause mortality using tree, stand, and beetle pressure variables, and (3) simulated a forest landscape to develop a framework for applying tree-level risk assessments. In 1995, forty-five sites were established throughout the southwestern US to measure bark beetle activity and associated tree and stand characteristics. The plots were periodically revisited through 2012 resulting in over twenty years of bark beetle data with highly variable population densities over time and space. Site maximum dbh and the number of ponderosa pines per acre were significant (P <.029) for predicting the probability a rise in the population density of bark beetles. Tree, stand, and beetle pressure were significant (P < .001) in predicting the probability of beetle caused tree mortality per year. Using GIS, remote sensing, and ground truth data, a ponderosa pine forest was simulated with information about the size and configuration of trees in the landscape. This simulated landscape was used to develop a framework for tree-level risk assessments. The results are discussed further in the context of bark beetle management and further research opportunities. In 1995, forty-five sites were established throughout the southwestern US to measure bark beetle activity and associated tree and stand characteristics. The plots were periodically revisited through 2012 resulting in over twenty years of bark beetle data with highly variable population densities over time and space. Site maximum dbh and the number of ponderosa pines per acre were significant (P <.029) for predicting the probability a rise in the population density of bark beetles. Tree, stand, and beetle pressure were significant (P < .001) in predicting the probability of beetle caused tree mortality per year. Using GIS, remote sensing, and ground truth data, a ponderosa pine forest was simulated with information about the size and configuration of trees in the landscape. This simulated landscape was used to develop a framework for tree-level risk assessments. The results are discussed further in the context of bark beetle management and further research opportunities.Item Multi-scale texture analysis of remote sensing images using gabor filter banks and wavelet transforms(2009-05-15) Ravikumar, RahulTraditional remote sensing image classification has primarily relied on image spectral information and texture information was ignored or not fully utilized. Existing remote sensing software packages have very limited functionalities with respect to texture information extraction and utilization. This research focuses on the use of multi-scale image texture analysis techniques using Gabor filter banks and Wavelet transformations. Gabor filter banks model texture as irradiance patterns in an image over a limited range of spatial frequencies and orientations. Using Gabor filters, each image texture can be differentiated with respect to its dominant spatial frequency and orientation. Wavelet transformations are useful for decomposition of an image into a set of images based on an orthonormal basis. Dyadic transformations are applied to generate a multi-scale image pyramid which can be used for texture analysis. The analysis of texture is carried out using both artificial textures and remotely sensed image corresponding to natural scenes. This research has shown that texture can be extracted and incorporated in conventional classification algorithms to improve the accuracy of classified results. The applicability of Gabor filter banks and Wavelets is explored for classifying and segmenting remote sensing imagery for geographical applications. A qualitative and quantitative comparison between statistical texture indicators and multi-scale texture indicators has been performed. Multi-scale texture indicators derived from Gabor filter banks have been found to be very effective due to the nature of their configurability to target specific textural frequencies and orientations in an image. Wavelet transformations have been found to be effective tools in image texture analysis as they help identify the ideal scale at which texture indicators need to be measured and reduce the computation time taken to derive statistical texture indicators. A robust set of software tools for texture analysis has been developed using the popular .NET and ArcObjects. ArcObjects has been chosen as the API of choice, as these tools can be seamlessly integrated into ArcGIS. This will aid further exploration of image texture analysis by the remote sensing community.Item Observing Short-Term Geomorphic Change in a Human-Modified River Using Terrestrial Repeat Photographs and Traditional Surveys: Uncompahgre River, Colorado, USA(2012-07-16) Depke, Tyler J.The Uncompahgre River in Ouray, CO, was modified in 1996 from a braided river system to a meandering river channel. Large boulders of riprap were placed along designed meanders to prevent erosion and enable the development of permanent human structures on the flood plain. Deposition of gravel bars in the modified channel occurs annually during the summer. This gravel is "mined" by the City of Ouray; however, the effects of this excavation and the original modification were never assessed. This study provides an assessment by quantifying cross-sectional area change, cumulative grain-size distributions, shear stresses, slopes, and sinuosities using traditional survey methods. In addition, volume change of a gravel bar inside the modified channel was estimated using extreme oblique photographs (>45 degrees from nadir) that were obtained from nearby cliffs. Close-range photogrammetry was used in the natural channel downstream to evaluate photogrammetric methods using different lenses, image sensors, and camera geometries. Both traditional and photogrammetric methods clearly indicated significant deposition in the modified channel, whereas erosion occurred directly downstream from the modified channel, but did not occur at a reach 1.5 km downstream. In the natural channel, no cross-sectional area change occurred, grains were poorly sorted, and the longitudinal slope was ~four times steeper than the modified channel. Shear stress ratios were used as an erosion threshold, which did not correlate with actual cross-sectional area change, but a decrease in shear stress ratios from May 2011 to September 2011 were associated with erosion. Average RMSE values for DEMs created from extremeoblique photographs of a gravel bar in May 2011 and September 2011 were 0.140 m and 0.324 m, respectively. Using a DEM of difference with a t-statistic filter revealed that 115m3 of gravel was deposited. The Uncompahgre River showed similar geomorphic characteristics to other rivers in southwest Colorado, however, the slope of the natural and modified channels were much steeper than other rivers. Extreme-oblique photography and unconventional sensors both yielded reliable results, showing that these atypical techniques can be used in terrestrial photogrammetric applications such as, post-restoration assessments, as long as proper base-to-height ratios are achieved.Item Remote sensing studies and morphotectonic investigations in an arid rift setting, Baja California, Mexico(2009-05-15) El-Sobky, Hesham FaroukThe Gulf of California and its surrounding land areas provide a classic example of recently rifted continental lithosphere. The recent tectonic history of eastern Baja California has been dominated by oblique rifting that began at ~12 Ma. Thus, extensional tectonics, bedrock lithology, long-term climatic changes, and evolving surface processes have controlled the tectono-geomorphological evolution of the eastern part of the peninsula since that time. In this study, digital elevation data from the Shuttle Radar Topography Mission (SRTM) from Baja California were corrected and enhanced by replacing artifacts with real values that were derived using a series of geostatistical techniques. The next step was to generate accurate thematic geologic maps with high resolution (15-m) for the entire eastern coast of Baja California. The main approach that we used to clearly represent all the lithological units in the investigated area was objectoriented classification based on fuzzy logic theory. The area of study was divided into twenty-two blocks; each was classified independently on the basis of its own defined membership function. Overall accuracies were 89.6 %, indicating that this approach was highly recommended over the most conventional classification techniques. The third step of this study was to assess the factors that affected the geomorphologic development along the eastern side of Baja California, where thirty-four drainage basins were extracted from a 15-m-resolution absolute digital elevation model (DEM). Thirty morphometric parameters were extracted; these parameters were then reduced using principal component analysis (PCA). Cluster analysis classification defined four major groups of basins. We extracted stream length-gradient indices, which highlight the differential rock uplift that has occurred along fault escarpments bounding the basins. Also, steepness and concavity indices were extracted for bedrock channels within the thirty-four drainage basins. The results were highly correlated with stream length-gradient indices for each basin. Nine basins, exhibiting steepness index values greater than 0.07, indicated a strong tectonic signature and possible higher uplift rates in these basins. Further, our results indicated that drainage basins in the eastern rift province of Baja California could be classified according to the dominant geomorphologic controlling factors (i.e., faultcontrolled, lithology-controlled, or hybrid basins).Item Study of Multi-Scale Plant-Groundwater Interactions(2014-05-30) Gou, SiGroundwater serves as one of the main and reliable water sources for human-being and groundwater dependent ecosystems (GDEs). GDEs are threatened by insufficient groundwater supply, due to increasing groundwater extraction and climate change. Sustainable groundwater management should address the water needs for both human and ecosystems, which requires a better understanding of the complex interactions between GDEs and groundwater. This dissertation examines plant-groundwater interactions and their implications at a range of scales. At the plant scale (~1 m^(2)), a physically-based model was developed to explore the hydraulic mechanisms of plant groundwater use. New functions of root water uptake and hydraulic redistribution (HR) in the model were driven by the potential gradients along the groundwater-soil-plant-atmosphere continuum, and a new water stress function was based on the linear relationship between stomatal conductance and root hydraulic conductance. These functions were further incorporated into a groundwater-land surface model, ParFlow.CLM, to develop a spatial distributed ecohydrological model at the stand scale (~1000 m^(2)). The modified ParFlow.CLM was used to conduct a 8-year simulation with half hourly time step at a AmeriFlux oak savanna site in California. It performed well when simulating daily, hourly, and spatial changes of water and energy dynamics. It captured the seasonal shift of plant water source from soil water during the wet season to groundwater during the dry season. The model simulated both hydraulic lift and hydraulic descent during oak active and dormant seasons. The model suggested that HR at this site was a mechanism for oaks to compete for water with annual grasses. At the regional scale (~1000 km^(2)), a method was proposed to identify vegetative GDEs using remote sensing data and to generate a detailed GDEs map for the Edwards aquifer region in Texas. This method used Landsat ETM+ and MODIS images to track the changes of NDVI for each vegetation pixel under different precipitation conditions. The NDVI dynamics were used to identify the vegetation with high potential to use groundwater. The method produces a detailed map of potential GDEs, which represents the first step towards sustainable water management associated with these ecosystems.Item Suspended Sediment Dynamics of Texas EstuariesReisinger, Anthony ShermanItem Understanding Spatio-Temporal Variability and Associated Physical Controls of Near-Surface Soil Moisture in Different Hydro-Climates(2013-05-06) Joshi, ChampaNear-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices.