Large 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.

No description available.

<p> Strain evolution and stress evolution following the 4 April 2010 M7.2 El Mayor-Cucapah earthquake are modeled using an adaptation of the strain transient detection tool developed by <i>Holt and Shcherbenko</i> 2013. The evolution of stress is calculated from postseismic strains, which are modeled from continuous GPS horizontal displacements. Strain fields are modeled in 2 ways; the total strain field based on total observed cGPS displacements, and the residual strain field, which subtracts a reference field from the total model. The residual shows anomalous strains resulting from the postseismic relaxation of the 2010 event. Anomalous and total strains are modeled in 0.1 year epochs for 2.4 years following the event. Both total and anomalous strains are converted into stress changes over time, assuming elastic incompressible behavior. Following the El Mayor event, the GPS constrained strain evolution shows the following: (1) The Southern San Andreas experiences a reduced rate of right-lateral strike slip strain accumulation between 3 July 2010 and 7 August 2012 (Figure 16a-d). (2) The San Jacinto Fault has normal rate of right-lateral strike-slip strain accumulation during this time. (3) Before the Brawley swarm of 26 August 2012, the state of strain evolves to enable unclamping of a left-lateral fault zone in the Brawley Seismic Zone (Figure 16a-d). (4) Large shear strains accumulate on the Laguna Salada Fault (northernmost segment)/southern Elsinore FZ (Figure 16a-d). We converted the strain changes into Coulomb stress changes on existing faults (both right-lateral and left-lateral). Several regions show increased Coulomb stress changes throughout the postseismic process. Furthermore, the Coulomb stress changes on the faults in the region progressively increase toward failure up to the time of the Brawley swarm.</p>

<p> Dambos are seasonally saturated grassy valleys mainly found on the central African plateau. They are usually sub-divided into three catenary units - gleyed and frequently inundated bottoms, flat and rarely inundated floors, and sloping sandy margins - fringed at the interfluve by the well-drained uplands. Since dambos constitute &sim;11% of Africa's arable land, soil information is required to guide sustainable use of the land. Further, it is important to determine the extent of the wetland environment in these landscapes so as to avoid miss-use of the land, which could arise because of varying definitions of the wetland in these landscapes. In addition, lack of knowledge about the true nature of dambo wetlands limits our understanding of their greenhouse gas (GHG) source and sinks strengths, which prevents projection of future GHG scenarios accompanying dambo use. This study was conducted so as to address these inadequacies, and is guided by the following specific objectives: (i) delineate dambo soil-landscape elements using aerial gamma-ray and terrain data; (ii) characterize a dambo wetland; and (iii) determine CH₄ and CO₂ sources and sinks in a dambo landscape.</p><p> The area Hansen et al. (2009) studied was revisited. For objective 1, their model training and validation data were used. For objectives 2 and 3, data (e.g., soil, water table and gas samples) were collected from experimental plots in the four landscape positions, geographically constrained around dambo bottom pixels. Data used were collected during the main (March to July 2008) and short rainfall (October and November 2009) seasons in the area.</p><p> An ANOVA analysis showed landscape position to have a proportionate influence on the variability of eU (46%), K% (28%) and eTh (27%); owing to the differences in soil properties along dambo cross-profiles. The results based on random forests (RF) and multinomial-ISODATA modeling, where gamma-ray and derivatives of a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) were used to classify dambo catenary units, were accurate, but only slightly better than the method which made no use of gamma-ray (e.g., conditional inference tree) . It was concluded that dambo landscape elements can be mapped by using these two data sources; although terrain data provides more information. Based upon a combination of hydrology and soil properties, dambo bottoms were the only element shown to constitute the dambo wetland. This zone is inundated for at least three-quarters of the main rainfall season and soils are hydric. Using the landscape map created by Hansen et al. (2009), the wetland was found to constitute only &sim;15% of the dambo. This is smaller than what was mapped by FAO-Africover and the Department of Survey and Mapping, Uganda (DSM). The wetland was also found to be the main source of CH₄ and sink of CO₂, with additional strengths attributed to the neighboring floor. Given that these constitute less than 20% of the landscape, dambo net contribution to the regional CH₄ budget is insignificant because 80% of the landscape is a sink. The worry, though, is the ongoing degradation, with the impact this has on the release of CO₂.</p>

<p> The amplitude and spectral shape of shortwave radiation are used to retrieve aerosol and cloud properties from airborne and ground based measurements. By interacting with clouds and aerosols in the Earth's atmosphere, the wavelength-dependent radiation emitted by the sun is modified. This thesis presents the change in radiation due to absorption and scattering by clouds and aerosols, which result in distinct spectral signatures in shortwave radiation spectra. </p><p> The spectral signature in shortwave radiation due to aerosols is quantified by airborne measurements of irradiance above and below aerosol layers. This radiative effect is quantified by the relative forcing efficiency, which is used to compare the impact of aerosols from different air masses, locations, and time of day. The relative forcing efficiency is the net irradiance change due to the presence of aerosols normalized by aerosol optical thickness and incident irradiance. It is shown to vary by less than 20% per unit of midvisible aerosol optical thickness for aerosols sampled during 4 different experiments, except for highly absorbing aerosols near Mexico City. The similarity in relative forcing efficiency for these experiments, not expected a priori, suggests that this quantity is constrained for various types of aerosols with differing scattering and absorption characteristics even when surface albedo differs. To estimate the radiative effect of aerosols sampled in the Los Angeles basin during one of the experiments, where no concurrent measurements of optical thickness with spectral irradiance were available, a new iterative technique was devised to use aerosol optical thickness measurements from another airborne platform. </p><p> Cloud-transmitted zenith radiance spectra were measured from the ground in Boulder, Colorado. In these measurements, spectral signatures of cloud optical and microphysical properties were uncovered. The spectral signatures are the result of radiation that is transmitted through clouds, where ice or liquid water cloud particles modulate the radiation by absorbing and scattering incident light in a wavelength-dependent manner. Typically, the magnitudes of radiance at 2 wavelengths have been used to retrieve cloud properties, but by using wavelength-dependent features more sensitivity to cloud microphysical properties is obtained. This thesis presents a method to analyze wavelength-dependent signal, where spectral features such as slopes, curvatures, and shifts in locations of maxima and minima are parameterized. These spectral features found in normalized radiance are quantified by introducing 15 parameters. These 15 parameters form the basis of a new generalized retrieval obtaining cloud optical thickness (&tau;), effective radius (<i>r_e</i>), and thermodynamic phase (&phis;). When applied to a liquid water cloud case, this retrieval matched a measured transmittance spectrum with a smaller root mean square difference over the entire spectrum (3.1%) than two other methods (up to 6.4%). To quantify the retrieval over all possible combinations of &tau;, <i> r_e</i>, and &phis;, simulated measurements were used in conjunction with realistic measurement and model error characteristics. By combining these error characteristics within the GEneralized Nonlinear Retrieval Analysis (GENRA) a solution probability distributions can be built. The information of cloud properties contained within cloud-transmitted radiance is greater on average for liquid water clouds than for ice clouds. For all possible combinations of cloud properties, radiance transmitted through clouds with &tau;&lt;20 contain the most information on cloud properties, indicating that the 15 parameters have greatest sensitivity to cloud properties of optically thin clouds (&tau;&lt;20). Of the 15 parameters, only 10 are required to retrieve accurately &tau;, <i> r_e</i>, and &phis; for any cloud except for ice clouds with &tau;>25 and <i>r_e</i>>30 &mu;m. Using this retrieval, the correct thermodynamic phase is determined from transmittance with a probability greater than 99.4% for horizontally homogeneous clouds that contain either ice or liquid water cloud particles.</p>

<p> This dissertation reports on the methods and results of a three-phased investigation to estimate the annual volume of ephemeral-channel-focused groundwater recharge attributable to urbanization (urban-enhanced groundwater recharge) in the Sierra Vista subwatershed of southeastern Arizona, USA. Results were used to assess a prior estimate. </p><p> The first research phase focused on establishment of a study area, installation of a distributed network of runoff gages, gaging for stage, and transforming 2008 stage data into time series of volumetric discharge, using the continuous slope-area method. Stage data were collected for water years 2008 - 2011. </p><p> The second research phase used 2008 distributed runoff data with NWS DOPPLER RADAR data to optimize a rainfall-runoff computational model, with the aim of identifying optimal site-specific distributed hydraulic conductivity values and model-predicted infiltration. </p><p> The third research phase used the period-of-record runoff stage data to identify study-area ephemeral flow characteristics and to estimate channel-bed infiltration of flow events. Design-storm modeling was used to identify study-area predevelopment ephemeral flow characteristics, given the same storm event. The difference between infiltration volumes calculated for the two cases was attributed to urbanization. Estimated evapotranspiration was abstracted and the final result was equated with study-area-scale urban-enhanced groundwater recharge. These results were scaled up to the Sierra Vista subwatershed: the urban-enhanced contribution to groundwater recharge is estimated to range between 3270 and 3635 cubic decameters (between 2650 and 2945 acre-feet) per year for the period of study. Evapotranspirational losses were developed from estimates made elsewhere in the subwatershed. This, and other sources of uncertainty in the estimates, are discussed and quantified if possible.</p>

The potential of remote sensing in upland soil erosion studies has been examined on Glaisdale Moor, North Yorkshire Moors. The study considers four different remote sensing sources, viz. sequential air photographs, ground radiometry, Landsat Thematic Mapper (TM) and SPOT simulation. Sequential air photographs have been interpreted in order to elucidate the land use/land cover changes and the drainage development and associated erosion problems in the region. A series of statistical analyses were employed in an effort to establish the relationships between the different spectral variables and the soil/ground variables. Attempts have also been made to evaluate the spectral separability performance of the Ground radiometer, the Landsat TM and the SPOT simulation wave bands. The Landsat TM and the SPOT simulation imagery have been further analysed in order to gather information about the best band and band combinations that would be required to optimize the discrimination of moorland surface types including eroded areas. Digital image processing of the Landsat TM and the SPOT simulation subscene for Glaisdale Moor was performed using the DIAD image processing system. The land use/land cover classification information derived from the air photographs, the Landsat TM and the SPOT simulation, has been used as an input into a soil loss prediction model (USLE) to predict the soil erosion rate of the study area. Of the various remote sensing systems used, air photographs and TM data proved the most useful in this area.

<p> This thesis investigated the science behind polarimetric road ice detection systems. Laboratory Mueller matrix measurements of a simulated road under differing surface conditions were collected searching for a discriminatory polarization property. These Mueller matrices were decomposed into depolarization, diattenuation, and retardance. Individual sample surface polarization properties were then calculated from these three unique matrices and compared. Specular and off-specular reflection responses of each sample were collected. Four polarization properties stood out for having high separation between dry and iced measurements: Depolarization Index, Linear Diattenuation, Linear Polarizance, and Linear Retardance. </p><p> Through our investigation polarimetric ice detection is possible. Continued research of the polarization properties of road ice can result in the development of a road ice detection system. Proposed deployment methods of such a system have been outlined following the analysis of the data collected in this experiment. </p>

The aim of the research contained in this thesis was to develop a model of long-term upland catchment runoff that can be used for ungauged catchments. This is a problem due to the complex spatial and temporal nature of runoff and the main contributing processes, precipitation (P) and evapotranspiration (Et). It is also a problem due to the lack of suitable data on which to base and test models of these processes, particularly in remote upland areas such as the north-west of England, the study area of this research. Long-term runoff is important since it represents the maximum rate at which water is available for human use and management, for assessment of water resource yield and for prediction of extreme events that are particularly important in respect to climate change. Methods currently in use by water companies in the UK, such as North West Water Limited (NWW), are inadequate since they fail to account for the spatial and temporal nature of runoff. New more reliable methods are therefore required which will equip water managers with flexible and responsive runoff modelling tools based upon routinely available data and that are sensitive to the complex physical nature of the processes involved. A physically based distributed runoff model was developed using GIS technology and spatial data to interpolate and extrapolate available point-based hydrometeorological data. The strategy required the development of models to derive areal representations of P and Et. For the P modelling several interpolation techniques and artificial neural network models were investigated. The results were evaluated against an independent data set. The results showed that a geostatistical interpolation technique, detrended Kriging, which uses pointbased precipitation and spatial elevation data provided the most accurate estimates when compared to other methods. The models of Et involved extrapolation of point-based Et values derived from the Penman-Monteith formula (Monteith, 1965), using spatial land cover data. A point-based temperature function model (Wright and Harding, 1993) that reduces the Penman estimates of Et for upland sites was spatially implemented using spatial temperature and elevation data. No independent data were available for model evaluation but first estimates of errors were gained through comparison of errors of runoff and precipitation estimates. Overall it was found that the most accurate E, model results were derived when the temperature function model was not implemented. Evidence of whether or not a lumped or heterogeneous land cover representation provided the more accurate results was unclear. Error evaluation and sensitivity analysis of the modelled runoff was carried out using measured runoff records and the results were compared to those produced using the North West Water model. It was found that the GIS-based model provided improved estimates of long-term average annual runoff for upland catchments. The largest component of the errors of the GIS-based method were associated with the Et estimates. This was principally a result of poor quality and limited availability of data for the study area. The research highlights many wider issues related to the use of GIS and spatial data for hydrological modelling.

<p> Thermal remote sensing is a powerful tool for measuring the spatial variability of evapotranspiration due to the cooling effect of vaporization. The residual method is a popular technique which calculates evapotranspiration by subtracting sensible heat from available energy. Estimating sensible heat requires aerodynamic surface temperature which is difficult to retrieve accurately. Methods such as SEBAL/METRIC correct for this problem by calibrating the relationship between sensible heat and retrieved surface temperature. Disadvantage of these calibrations are 1) user must manually identify extremely dry and wet pixels in image 2) each calibration is only applicable over limited spatial extent. Producing larger maps is operationally limited due to time required to manually calibrate multiple spatial extents over multiple days. This dissertation develops techniques which automatically detect dry and wet pixels. LANDSAT imagery is used because it resolves dry pixels. Calibrations using 1) only dry pixels and 2) including wet pixels are developed. Snapshots of retrieved evaporative fraction and actual evapotranspiration are compared to eddy covariance measurements for five study areas in Florida: 1) Big Cypress 2) Disney Wilderness 3) Everglades 4) near Gainesville, FL. 5) Kennedy Space Center. The sensitivity of evaporative fraction to temperature, available energy, roughness length and wind speed is tested. A technique for temporally interpolating evapotranspiration by fusing LANDSAT and MODIS is developed and tested.</p><p> The automated algorithm is successful at detecting wet and dry pixels (if they exist). Including wet pixels in calibration and assuming constant atmospheric conductance significantly improved results for all but Big Cypress and Gainesville. Evaporative fraction is not very sensitive to instantaneous available energy but it is sensitive to temperature when wet pixels are included because temperature is required for estimating wet pixel evapotranspiration. Data fusion techniques only slightly outperformed linear interpolation. Eddy covariance comparison and temporal interpolation produced acceptable bias error for most cases suggesting automated calibration and interpolation could be used to predict monthly or annual ET. Maps demonstrating spatial patterns of evapotranspiration at field scale were successfully produced, but only for limited spatial extents. A framework has been established for producing larger maps by creating a mosaic of smaller individual maps.</p>