Excess sediment is one of the main agents of water pollution, affects the aquatic ecosystem and causes siltation problems in reservoirs and rivers. Bottom sediments are coarse and easily deposited, being the major responsible for morphological alterations in rivers. Therefore, is important to estimate the amount of sediment transported in other to establish mitigation strategies and recovery of affected areas. There are several methodologies for estimating bedload transport: equations, numerical modeling, direct physical sampling, and indirect method measuring dune tracking. Most studies measure bedload transport using the equipment Helley-Smith, generally taken as reference value for other methods. However, Helley-Smith causes changes in the flow field, often resulting in overestimates in sand bed rivers. Those overestimates were not yet described and quantified in detail. This article tries to solve this gap by observing the Helley-Smith sampler at the time of sampling. For this, we used a video camera recording processed by Particle Image Velocimetry (PIV) technique to qualitatively evaluate changes that the intrusive sampler causes in the displacement of bottom sediments in a sand bed river. When the sampler was properly allocated to the bottom, PIV resulting velocity maps of bedload particle transport identified the acceleration of the bottom particles as they approached the mouth of the sampler. We also noticed areas of convergence and vorticity of the sediments towards the sampler’s mouth, which may overestimate sampling. When the sampler’s mouth was disconnected from the bed due to the morphology of the bottom, we find regions of divergence in the displacement of the sediments creating unrealistic results for bedload transport analysis. In addition, the presence of organic matter can be underestimated, which causes difficulties in analyzing the quality of the collections because it is not possible to guarantee an equity in the positioning of the equipment at the bottom of the channel. We thus recommend complementation Helley-Smith measurements with surrogate methods, for example such as using ADCPs or optical methods, as the one described here.

Inlet change along the Virginia barrier islands has been studied on an individual inlet basis. This study evaluated the ten inlets both individually and as a group. Evaluating the inlets as a group allows the discovery of inlet change patterns among the inlets. Inlet width was measured from satellite and aerial images. Width is the straight-line distance from the northernmost fast land to southernmost fast land. Measurements spanned from July 1999 to April 2018 with a frequency of four to eight width measurements per year. Total width change to 2018 was 2 percent to 357 percent. The largest change was to Great Machipongo Inlet. The inlet widened from approximately 800 meters wide in 1999 to 3645 meters wide in 2018. This widening effectively splits the remaining nine inlets into two groups. Inlet widening patterns of the two groups are high rates for the first three or four inlets and a very low rate for the final inlet of the group. Wind direction change also plays a significant role in net inlet widening. Inlet widening has not abated and wider inlets will allow larger waves to affect environmentally and commercially important areas to the west of the barrier island/inlet system.

Along sandy coasts, the seaward expansion of dunes starts with the development of embryonic dunes. Vegetation is crucial for their initiation and the subsequent increase in dune height and volume when sediment supply is sufficient. During severe storms, the plants’ tolerance to and recovery from hydrodynamic disturbances, such as exposure to saline water during high water levels and their (partial) removal during storms, is vital to the long-term (months to years) resilience of the dune building process. Accordingly, areas with high embryo dune abundance have been correlated to wider beaches, attributed both to increased wind-driven sediment supply and increased wave attenuation during storms. Recent observations have shown that alongshore variations in subtidal sandbar morphology may also lead to variations in wave attenuation and foredune erosion, following a series of extreme storms. With our research we aim to determine whether subtidal bar characteristics play a role in long-term (months to years) embryo dune development. We first analysed a data set of 112 annual bathymetric profiles (spaced 250 m alongshore) and topographic (airborne Lidar) measurements in addition to observations of embryo dune presence derived from aerial photographs, spanning 50 km along the Dutch coast from 2010 to 2016. Embryo dune area extraction was done by supervised classification of vegetation pixels on the beach. Using a linear regression model, we found that profiles with a more seaward vegetation extent significantly correlated to shallower subtidal bars, in particular during stormy years. Second, to study the timing and alongshore variability of individual erosion events in more detail, we analysed 10 years (2005-2015) of half-hourly images of a 4-km stretch of the same coast, near Egmond aan Zee, in addition to the annual data. These images provide unique observations of the entire bar-beach-dune system, allowing for the concurrent analysis of bar morphology, embryo dune areas and, crucially, embryo dune exposure to saline water and wave action during storm events. At the conference, we will further explain the observed spatial and temporal (storm-driven) variability in embryo dune development.

Vertical electrical sounding (VES) surveys were performed on the Chukchi Sea ice near Utqiagvik (ne’ Barrow), AK in March, 2018, using a capacitively coupled resistivity array. The purpose of this study was to determine the effectiveness of the VES method in determining the thickness of the sea ice and potentially the depth to the sea floor. The array was deployed in an atypical set-up, with the transmitter and a single receiver being moved incrementally further from a central point. The results of three trials from 2018 are presented, along with the re-analysis of data from two trials from March, 2016. The VES data were analyzed using “cumulative resistivity” plots, from which ice thicknesses were determined. Ice depths were measured by drilling through the ice at the central point of the array. The VES and drill thicknesses agree to within a few percent for the ≲1m-thick ice. The VES plots may also indicate differences in ice composition as it transitions from the solid uppermost ice down to seawater.

This study investigates how marine resource users are impacted by the offshore Block Island Wind Farm (BIWF). In the summer and fall of 2017, we conducted semi-structured interviews with recreational and commercial fishermen that use the area around the BIWF. We asked fishermen about their perceptions of changes in the ecology of the area during and after the offshore wind turbines were constructed, and how their behavior and use of the area changed in response to the construction and post-construction of the wind farm. We interviewed over 20 fishermen, mainly based out of Block Island or Point Judith, Narragansett. Analysis of the interview data suggests that some fishermen view the wind farm as a positive development for fishing in the area, while others have mixed feelings or dislike the project. Perceptions of changes in the BIWF area seem to vary within and among commercial and recreational fishermen. In addition, comparison of interview data with ecological data on fish and lobster in the BIWF area before, during and post-construction highlights areas of agreement and disagreement between perceived and observed changes. These results provide important information on how offshore wind farms in the Northeast are impacting marine resource users in terms of perceived and observed impacts. Open Access Paper: https://www.frontiersin.org/articles/10.3389/fmars.2018.00439/full

Spanning a period of more than 15 years, the Landsat Legacy Project Team researched, complied and published, in late 2017, Landsat's Enduring Legacy that describes the myriad of factors that surround the nearly half-century of monitoring the Earth's surface with Landsat. Born of technologies that evolved from the World War II, Landsat not only pioneered global land monitoring but, in the process, drove innovation in digital imaging technologies and encouraged development of global imagery archives. Access to this imagery led to early breakthroughs in natural resources assessments, particularly for agriculture, forestry, and geology. The technical and political aspects of the remote sensing revolution led by Landsat were not simple or straightforward. Early conflicts between civilian and defense satellite remote sensing users gave way to disagreements over whether the Landsat system should be a public service or a private enterprise. Only the combined engagement of civilian and defense organizations ultimately saved this pioneer satellite land monitoring program from termination. With the emergence of 21st century Earth system science research, coupled with greatly enhanced data computing, storage and transfer capabilities, the full value of the Landsat concept and its continuous, calibrated nearly half-century global archive has been recognized and embraced. The attempts to privatize Landsat had dramatic negative impacts on the collection, availability, and use of the data. These impacts should inform deliberations on the future of the Landsat program moving toward a Sustained Land Imaging program following Landsat 9. Discussion of Landsat's future continues, but its heritage will not be forgotten.

Human-mediated climate change over the past century has made significant impacts on global ecosystems and biodiversity including accelerating redistribution of the geographic ranges of species. In mountainous regions, the transition zone from continuous closed-canopy subalpine forests to treeless alpine tundra areas at higher elevations is commonly referred to as ‘Alpine Treeline Ecotone’ (ATE). Globally, warming climate is expected to drive the ATE upslope, which could lead to negative impacts on local biodiversity and modify ecosystem function. However, existing studies rely primarily on field-based data which are difficult and time consuming to collect. In this research, we define three critical characteristics of the ATE including 1) an abrupt spatial shift in vegetative activity as elevation varies, 2) reduction in vegetative activity as elevation increases, and 3) vegetative activity is at an intermediate level. Using the geospatial tools provided by Google Earth Engine, we construct an index (ATEI) to identify areas with the three ATE features based on the image gradients of vegetative activity and elevation datasets. Based on the ATEI and Google Earth imagery in 115 Landsat pixels, we establish a Logistic regression model to estimate the probability of whether or not a sampled pixel is located within the ATE. The prediction accuracy is approximately 80%. Furthermore, the ATEI-estimated ATE elevation is strongly correlated (r = 0.96) with a set of field-based data at 20 sampling sites from across the region. Based on the average annual ATEIs from 2009 to 2011, we estimate the average ATE elevation for each mountain range in the western U.S. The result varies from 1,183 m to 3,584 m. The detection metric developed in this study facilitates monitoring the geographic location and potential shifts of ATEs as well as the general impact of climate change in mountainous regions during recent decades. We also expect this approach to be useful in monitoring other ecosystem boundaries.

A system capable of reliably detecting catastrophic landslides and centimeter movement in land mass could save lives and offers landowners valuable information about gradual changes in soil displacement on their land. With precise acceleration and relative positioning data collected from an accelerometer and a set of GPS receivers, a system can be designed to detect subtle changes in sensor position due to land movement. With the rapid production of new microprocessors and greater memory storage capabilities the limits of microcontroller systems are continually expanding. The Slide Sentinel project offers landowners a low-cost alternative to commercial equipment consisting of a network of remote low power sensors that detect fast linear slides and eventually lower soil movements such as creep. Long range low-power (LoRa) radio connections on these sensor nodes wirelessly transmit three-dimensional acceleration, Real Time Kinematic (RTK) GPS coordinates, and sudden shift alerts to a common base station where they are exported to an online spreadsheet to be processed remotely.

Index Terms: 1622: Earth system modeling; 1630: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1996 Web Services; 4305: Space weather; 6334: Regional Planning This work addresses a key objective of SERVIR-Mekong Project related to integrating geospatial information in government decision-making, planning, and communication for societal good. The SERVIR-Mekong is a partnership between the U.S. Agency for International Development (USAID) and the U.S. National Aeronautics and Space Agency (NASA) formed to help regional organizations in the Lower Mekong Region to use information provided by Earth observing satellites and geospatial technologies in managing climate risks. Our work integrated multiple satellite-based earth observation systems, in-situ station data and spatial data with the Soil & Water Assessment Tool (SWAT) hydrologic model employed in the Mekong River Basin region to develop a Lower Mekong River Basin region’s hydrological decision support system. Simulated hydrological fluxes of streamflow, soil moisture, and evapotranspiration at the Lower Mekong River Basin were presented utilizing our developed hydrological decision support system. Our work results have been presented via multiple Tethys platforms, Tethys is an easily customizable platform that hosts web applications, that facilitate accessing NASA satellite-based earth observation systems as well as the Lower Mekong River Basin region’s hydrological decision support system. Earth observations data has provided solutions to assist people in the Lower Mekong River Basin to overcome various obstacles experienced in enhancing hydrological decisions that are related to difficult access and incompleteness, inconsistency, scarcity, as well as poor spatial representation of in situ data products.

The lunar surface consists of a regolith layer, i.e., fragmental and unconsolidated rock material of highly varied character, which covers the underlying bedrock. Understanding the structure and composition of the lunar regolith and the underlying bedrock is very important to reveal geologic features of the Moon, explore natural resources humans can exploit, and obtain valuable information regarding the history of the solar system. Electromagnetic radiations from the surface of the Moon at microwave frequencies depends on the physical, chemical, and electrical properties of the regolith layer and the bedrock. Moreover, the electromagnetic penetration depth changes with frequency which allows wideband microwave radiometers operating below 50 GHz to conveniently profile these properties versus depth to characterize the lunar regolith and bedrock with wide spatial coverage. Combining current models of depth-dependent physical and chemical properties with simple electromagnetic forward radiation models, surface emissions over the Apollo sites were simulated and compared with Chinese Chang’E-1 and Chang’E-2 multi-frequency microwave radiometer measurements. Potential sources of the differences between the simulations and measurements have been identified as the temperature dependence of the electrical properties of the regolith, bedrock type, surface and bedrock roughness, as well as density fluctuations, scattering due to inhomogeneities, and coherent interference of electromagnetic fields within the regolith. However, many of these subjects have been studied thoroughly for the remote sensing of the cryosphere; thus leveraging this experience with the rapid developments in radiometer designs, wideband microwave radiometers promise valuable scientific returns in future lunar missions.

Over 33,000 flash flood events recorded by the NOAA National Weather Service (NWS) between 2006 and 2017, after polygon warnings replaced county-wide warnings, are analyzed in terms of NEXRAD (Next Generation Weather Radar) radar coverage in two ways. Events are binned in two large categories according to whether the starting point of an event falls inside or outside the range implied by the 6 kft AGL bottom-of-the-beam altitude, accounting for beam clutter and beam obstructions. Separately, events are classified according to the percentage surface area covered under the 6 kft beam height for each NWS Weather Forecast Office (WFO) or state. Emphasis is on unwarned events associated with fatalities, injuries and property damage and their relationship to WFO-area NEXRAD coverage. Significant property damage is defined in terms of the mean damage per event of about $411k. There is parity in the ratio of events warned or unwarned inside the inside/outside distance bins except for injury-event ratios. The linear fits to the traditional metrics of warned ratio (WR), false alarm ratio (FAR) and critical success index (CSI) are statistically significant and improve with more radar coverage. A stronger sensitivity is found for the WR as a function of the total number of events. New metrics are also evaluated, such as the mean flash flood partial event warning (PEW) and the ratios of unwarned to all events per WFO have statistically significant variations with radar coverage, improving with higher coverage. This is unlike the linear fits to the ratios of unwarned fatal-to-all-fatal events, which is marginally significant. Unwarned fatal-to-all-fatal, unwarned injury-to-all events and unwarned significant damage-to-nonzero damage event ratios are both not statistically significant to the 95% level of significance. The large scatter in the data results in very low coefficients of determination, and is interpreted to mean that radar coverage alone is not necessarily the primary driver though there is sensitivity to variations in such coverage.

Land use/land cover (LULC) change could adversely affect watershed health by elevating nutrients and sediment levels and intensifying the risk of flooding. In this study, a spatially-explicit LULC change modeling framework was coupled with the Chesapeake Bay Watershed Model (CBWM) to investigate the impact of LULC change on nutrients (total nitrogen and total phosphorous), sediment and runoff volume in the watersheds surrounding Virginia’s Shenandoah National Park, U.S. Four stakeholder-informed scenarios alongside a Recent Trends LULC change scenario were studied. The stakeholder-informed LULC change scenarios, which differed in consideration of future planning and population growth, were developed through several meetings with stakeholders. To develop the Recent Trends, the historical LULC trend from 2001 to 2011 was analyzed. Using 2011 as a baseline scenario, the spatio-temporal patterns of LULC change were estimated as influenced by physiographic and socio-economic drivers 50 years in the future (2061). The projected LULCs were fed into the CBWM to predict the change in average annual loading of nutrients, sediment and runoff volume. While the changes in loads at the full study area were not substantial (< 0.9%), changes became more pronounced at finer spatial scales. Expectedly, the LULC change scenario with ad-hoc planning and high population growth resulted in the largest increase in runoff volume. However, the scenario with ad-hoc planning and low population growth showed the largest increase in the simulated pollutants. This was because while this scenario projected less development, it projected more increases in agricultural LULCs that export more nutrients and sediment than other changing LULCs. This implied that sole land use planning based on urban development is not sufficient for watershed protection and agricultural LULCs need to be incorporated in concert in our future planning. This further suggested that land use planning plays a more critical role than population growth rate in water quality management. The results have implications for the Chesapeake Bay total maximum daily load and could help well-informed future land use planning and watershed protection by incorporating the impact of future LULC change on water quality and quantity.

Mangrove forests, occupying tropical and subtropical coastal areas, serve as coast protector, water filter, spot of attraction and an exceptional carbon reservoir. Despite these extraordinary ecological and economic functions, our understanding of the mangroves is limited because field survey is hard to conduct in the intertidal mangrove habitats. While satellite remote sensing provides good spatial and temporal coverages globally, data availability at the tropical latitudes is limited due to frequent cloud contamination. The quickly emerging unmanned aerial vehicle (UAV) technique enables data collection under almost all weather conditions, thus provides new opportunities. By mounting light detection and ranging (LiDAR) sensors on UAVs, the 3D structure of mangroves can be accurately characterized even at individual tree level. The basic tree parameters such as tree height and crown size can be easily extracted, which then enables the estimation of biomass, carbon stock and other important ecological indices. This study uses high density (>100 pt/m2) UAV-LiDAR data collected at four consecutive years to detect the growth rate and pattern of mangroves. The change detection is done at individual tree level. The dependence of mangrove growth pattern on tree species and clumpingness are analyzed. The output will allow scientists and environment managers to know mangroves better and to manage them effectively and efficiently.

Based on a large database of Wideband Imaging Camera (WIC), which is a part of Far Ultraviolet (FUV) instrument, onboard the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite during 5 years between 2000 and 2005, we found a new morphological type of transpolar arcs (TPAs), which are identified as “nightside distorted TPAs”. The nightside ends of the dawnside (duskside) TPAs got distorted toward pre- (post-) midnight sector; These TPAs look like the shape of an alphabetical letter of “J” or “L”. We identified 17 nightside distorted TPAs from our database. The 12 events out of 17 nightside distorted TPA events were the dawnside TPA with the nightside end distorted toward the pre-midnight sector (“J”-shaped TPA), and the TPAs in the duskside, whose nightside parts got distorted toward the post-midnight sector, were found in the remnant 5 events (“L”-shaped TPA). Statistically, the nightside distorted TPAs can dominantly be found under the northward Interplanetary Magnetic Field (IMF) conditions. Furthermore, when the IMF-By component pointed to the dawnward (duskward) direction, the “J” (“L”)-shaped TPAs were dominantly observed, suggesting that the relation between the IMF-Bz and By orientations, and the locations of the nightside distorted TPAs is consistent with that between the IMF conditions and regular TPA previously reported. We also followed the time sequence of the nightside distorted TPA evolution with the IMAGE FUV-WIC imager and additional Polar UVI data. In most cases, the “J” and “L”-shaped TPAs started to grow from the nightside main auroral oval, and protruded to the dayside region with being distorted. In this presentation, we will introduce several selected cases of the nightside distorted TPA among our database, and discuss why and how the nightside end of the TPA became distorted toward pre- or post-midnight sectors based on the in-situ satellite nightside plasma sheet observations and the electron drift velocity distribution calculated utilizing a simple electromagnetic field model in magnetotail, together with the auroral imager data.

A hybrid Linear Programming (LP) and Nonlinear Programming (NLP) optimization model is developed for California’s hydropower operations. Built on top of Pyomo library, a high optimization modeling language in Python, the model can connect to several freely available, state-of-the-art solvers. In this model, fast evaluation of LP and detailed model representation of NLP are fully utilized. The hybrid model solves the same problem with linear approximation (a simplified objective function representation) and with NLP solver, where no simplification is made to objective function. Outputs from LP model are used as initial values (warmstart) for NLP model’s decision variables, which reduce number of iterations for convergence and so runtime. The model is capable of representing large network of hydropower plants that are in serial or parallel, or fixed and variable head plants. The model is used to evaluate effects of increased solar photovoltaic (PV) generation in California. California has a goal of generating electricity from renewable resources at least 33% by 2020, and 50% by 2030, and solar PV generation supplies most of renewable generation portfolio during daytime. This expanded use of solar PV changes generation pattern from one daily peak system to two daily peak system. Due to excess generation of solar PV, negative prices can occur during daytime. Therefore, evaluating effects of solar PV on hydropower operations and adapting to new conditions are essential.

Quantification of river flow is a significant component of water resource management needed to develop infrastructure, prepare for drought or flood, and ensure equitable resource use. Yet, these data have often been deficient in rural regions generally dependent on smaller river systems, especially in low- and middle- income countries, and in places where no remote gaging capabilities currently exist. A relationship between river flow and width has been previously demonstrated in attempts to record and monitor flow with only satellite-based measurements; however, those methods have focused on rivers with a width of > 30m and have shown extreme errors when compared to historical gaging records. A new technique for monitoring river flow remotely is presented here, which uses Manning’s equation for open channel flow coupled with width measurements from satellites. This technique allows for the creation of a remotely-sensed historical river flow record and uses the minimum number of ground-based measurements for the calibration of Manning’s equation. Cross-river depth profile, discharge, and slope are necessary for initial calibration. This method used four-band satellite images with 3m-resolution for width measurements, with images being adjusted for the Normalized Difference Water Index (NDWI) for better delineation of the water’s edge. Buffalo Creek, in Freeport, Pennsylvania and the Mutale River, in the Limpopo Province of South Africa, were used as study locations. An estimation of flow at each site was obtained using every available satellite image of those transects. Preliminary results indicated successful calibration of Manning’s equation for the individual river transects, and verification of this method yielded flow estimation with an average of 74% error at Buffalo Creek and 48% error at the Mutale River, when compared to historical data from gages present near the study sites. The primary challenge of using this method on smaller rivers is the determination of width from the satellite images. Automated techniques to delineate the water’s edge are presented as recommendations to increase accuracy. This method may be used as an additional tool in river flow monitoring for water resource management.

Gas hydrates have been reported to exist in marine sediments from various parts of the world ocean. The hydrates start decomposing soon after recovery of the sediments through coring operations due to changes in ambient pressure and temperature. This decomposition leads to changes in sedimentary structures, and thus complicates physical property related measurements of the sediments by conventional methods. In this study, we used a medical X-ray CT scanner to quickly scan the recovered cores, and then used raw data from the CT, and thus avoided image processing steps, to estimate porosity and density of the sediments. The raw data were in terms of CT numbers, which were obtained by drawing a circular region of interest (ROI) to cover most of the sediments visible in a cross section XCT image of the sediments. The data were weighted for relative contribution of liquid and solid in sediments before estimating porosity. On the other hand, density was estimated by using an average CT number that was automatically calculated by the Osirix software used for drawing the ROI on an XCT image, and by using a calibration equation based on a set of standards. Although some uncertainty in estimation of relative volumes of solid, liquid and gas could not be avoided, the results obtained by this new procedure were in good agreement with those obtained by conventional methods. Since porosity and density estimates by the new procedure can be made in a matter of minutes after core recovery, it can guide progress of coring operation and further processing of hydrate-bearing sediments.

Sea Level Rise is a global concern that has varying and potentially serious consequences on the local level. Although national policies and international frameworks can help to reduce the severity of sea level rise by limiting future emissions, in the current policy framework in the United States, local governments hold most of the responsibility for protecting their communities from flooding and the impacts of future sea level rise, with limited assistance from state and federal governments. Recognizing that local governments are largely driven by their community’s needs and desires, a survey of 500 persons affiliated with coastal communities across the east coast of the United States was conducted to identify public perceptions on the relative priority of sea level rise planning, components that should be included in local plans, protection priorities, funding mechanisms, methods to resolve conflict, and acceptable adaptation responses. The information from this survey was then provided to representatives from six local governments in a barrier island New Jersey to help identify its appropriateness and usefulness for local planning. In addition to discussing the key findings of the public survey, an overview of the responses from government officials will be presented, with an emphasis on comparing and contrasting the viewpoints of public officials and members of the public to help foster stronger collaborations among all members of a community (residents, businesses, utilities, governments and others) to help address local adaptation in light of this complex issue.