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.

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.

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.

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.

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.

The International Satellite Cloud Climatology Project (ISCCP)’s Convection Tracking (CT) database was designed to track the evolution of deep convective cloud systems throughout their life cycle. The database is produced in 3 steps. The first step determines whether a particular image pixel is cloudy and determines the cloud top temperature and optical thickness. The second step clusters up all adjacent cold IR pixels with brightness temperature (TBIR)< 245 K and stores the summary information about cloud structural and radiative properties. Such clusters are referred to as Convective Systems (CSs). A further test identifies Convective Clusters (CCs) as adjacent cloud pixels with TBIR < 220 K. The third step tracks each individual CS over time to form families and produces the CT database. Previous version of the CT data covered the period from 1983-2008 and treated one geostationary satellite at a time. Recently, we started producing a new version of CT data that are built upon the new, H-version ISCCP data (HXG). Improvements from this new CT data include: 1) globally uniform coverage, 2) higher spatial sampling/resolution (from 30 km down to 10 km), and 3) longer data record (1983-2015). This presentation will introduce the new ISCCP CT database and show some preliminary results including comparison with the old CT data and some essential global statistics of deep convective cloud systems.

How does climate change affect the production of native Grains of America? There is an impact of climate change on rain-fed crops productivity and its association with alimentary security. This study analyzes how events such as global warming, unsustainable agriculture or intense droughts caused by lack of water, affects the production of quinoa in Bolivia and maize in Mexico. Our estimates suggest that climate variability will modify agriculture yields (of maize and quinoa) per hectare depending on the agricultural season, the municipality and the ensemble model used to project climate change scenarios. The study indicates tremendous heterogeneity in areas and regionally. Based on the cobweb phenomena approach, it is suggested that the producers base their decisions for their future production on the assumption that present prices will continue. If this is not the case, rigid price expectations may produce irreversible supply conditions in the short run. These prices are set by the available supply of the grains. Their production is completely determined by the producers’ response to price, under conditions of pure competition.

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.

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.

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.

Spacecraft charge mitigation is critical for a host of space plasma measurement techniques. However, charge mitigation in tenuous space plasmas can be a difficult problem. It is especially difficult and essential during active experiments that feature ion or electron beams, as collection from the ambient plasma is often insufficient to balance the beam emission current. For electron emission experiments, the use of a plasma contactor that emits an ionized gas is the only practical option. A series of parametric chamber experiments were completed to address how spacecraft charge mitigation using a plasma contactor may scale in tenuous space plasmas. Experiments focus on how spacecraft potential scales with beam emission current, contactor current (the rate at which the contactor generates quasi-neutral plasma), and contactor expellant mass (ion mass). These experimental results are compared to scaling laws derived via Curvilinear Particle-In-Cell (CPIC) simulations for further validation and physical insights. Implications for improving space plasma measurements and enabling future active experiments such as the Connections Explorer (CONNEX) mission are discussed.

The variability of the middle atmosphere is driven by a variety of atmospheric waves covering various spatial and temporal scales. In particular, the northern winter mesosphere/ lower thermosphere at mid- and polar-latitudes shows a huge variability related to planetary waves, which can disturb the polar vortex leading to large scale coupling effects like sudden stratospheric warmings (SSWs) altering the vertical propagation conditions of tides and gravity waves. Here we are going to investigate and diagnose the short time variability of tides (several days) at the MLT using ground-based observations at mid and polar latitudes and data from NAVGEM-HA for selected periods. NAVGEM-HA provides information about the global structure of the zonal mean zonal and meridional wind and the zonal mean temperature as well as the tides. At mid- and high-latitudes the semi-diurnal tide (SW1 and SW2) is the dominating tidal wave during the winter season, which is also seen in meteor radar and lidar climatologies. Further, we analyze local meteor radar and lidar observations at Andenes (polar-latitude) and Juliusruh (mid-latitude) to diagnose the local amplitude and phase variability due to changes in the background mean winds caused by planetary waves and SSWs. We will show that the tidal phase (in UT) can drift significantly within several days and weeks. These local measurements are also compared to NAVGEM-HA applying the same diagnostic as to the observations. In addition to the winter time observations, we will also show results for the phase propagation of tides from summer periods.

Tides are critical to coastal and oceanic processes. While tidal data are available readily, they are often corrupted by various sources of error. An automated, fast MATLAB toolbox is developed to clean-up tidal timeseries data from estuarine and oceanic locations corrupted by errors. This toolbox will immensely speed up delivery of quality-controlled tidal data. It will also reduce errors in quality control, which typically involves several manual tasks. The toolbox corrects poorly interpolated and noisy data, erroneous outliers, and instrumentation bias such as spurious jumps, drifts, spikes, and modulations in the true signal. Signal clean-up involves multiple stages. First, thresholds are imposed on higher order temporal derivatives of the signal to remove gross interpolations and noise saturated signal chunks, followed by a moving median threshold to remove outliers. Then the surviving signal is filtered into tidal, subtidal and long-period components, and the long-period component is subject to a maximal overlap discrete wavelet transformation, in which the transform coefficients corresponding to multi-scale edge features are removed. Subsequently, local information in the subtidal and tidal components is compared relative to the whole signal to correct spurious amplitude modulations and sudden biases. Consequently, these components are added to recover the uncorrupted signal, and large data gaps are filled with short term harmonic reconstruction. For estuarine locations, the correlation in the spectrogram between two nearby stations is initially used to quantify and remove river influence in the signal. Applications to datasets at multiple global locations demonstrate the value of the toolbox.

The aim of this study is two-fold: (1) measure solid Earth diurnal and semi-diurnal tidal constituents using non-parametric signal analysis, and (2) calculate the time delay of the Earth’s solid tidal response between two land-based geographic locations. For these goals, high-precision tidal signals were collected from borehole strainmeters at Plate Boundary Observatory (PBO) stations in Yellowstone, WY, USA and Sequim, WA, USA. Signals from synchronized microstrain time series sampled at 10 minute intervals from 1 January 2011 to 31 December 2015 were evaluated with power spectra and harmonic analysis with statistical F-testing. The phasing of the Earth’s tidal response for the two stations was also estimated with a solid Earth tidal model. Differences between the observed and modeled phases are investigated.

Propagation of electromagnetic (EM) waves from radar and communication devices at sea can be significantly affected by the low-altitude atmospheric refractive conditions. Characterizing the spatial and temporal variability of refractivity is thus crucial to many important Navy and civilian applications. Surface layer models based on Monin-Obukhov Similarity Theory (MOST), such as the Navy Atmospheric Vertical Surface Layer Model (NAVSLaM), can be used to estimate the vertical refractive structure of the evaporation duct (ED) from measured or forecasted environmental parameters, assuming a horizontally-homogeneous stratified atmosphere. As air and sea surface temperature are two critical inputs to NAVSLaM, the rapid variation in sea surface temperature (SST) and air-sea temperature difference in the Gulf Stream region provides a relatively controlled environment for investigating the utility of NAVSLaM under inhomogeneous ducting conditions. In this paper, EM propagation in the ED over the Gulf Stream is investigated using measured data from the Coupled Air-Sea Processes and Electromagnetic-ducting Research (CASPER) East Coast experiment conducted off the coast of Duck, NC, during October-November of 2015. Measurements of the one-way propagation loss between a transmitter and receiving array as a function of the range were performed during ship crossings of the Gulf Stream. Concurrent and co-located meteorological and oceanographic measurements were also collected within the marine atmospheric boundary layer (MABL), including air temperature, SST, relative humidity, air pressure and wind speed to be used as inputs to NAVSLaM. The environmental conditions in the region of the Gulf Stream are used to model the low-altitude refractivity profiles as a function of height and range, which are input into the Advanced Propagation Model (APM) for predicting the EM propagation. Of particular focus is the effect of the rapid change in SST across the boundary between the warmer Gulf Stream and the colder surrounding ocean. EM measurements are compared with the simulated propagation loss based on the range-dependent refractivity profile predicted from NAVSLaM, as well as a best-fit Paulus-Jeske ED model. Both stable and unstable conditions encountered during the CASPER East experiment are investigated.

The ice sheet-ocean modeling community is making large strides toward developing coupled models capable of examining the interactions and feedbacks between ice shelves and ocean along the Antarctic margin. We present preliminary results and address some of the challenges that have arisen during the development of a coupled ice sheet-ocean model. The ice sheet model is icepack, a shallow-shelf finite element model written in Python. The ocean model is the Regional Ocean Modelling System (ROMS), a terrain-following vertical (sigma) coordinate model that has been modified to interface with a moving ice shelf. These two models are coupled in an online configuration using the Framework for Ice Sheet Ocean Coupling (FISOC). The use of a model with sigma coordinates for the ocean component introduces a simplification and a complication to modeling a moving ice draft. The sigma coordinate system retains the same number of vertical layers at any depth, eliminating the need to convert grid cells between ice and water, when using a fixed grounding line configuration. However, as the ice shelf draft evolves in time, topographic configurations develop that induce pressure gradient errors in ROMS. We quantify these errors in an idealized set-up with an artificially changing ice draft following the ISOMIP+ geometry. We compare results between an ice draft that is smoothed to meet standard ROMS smoothing criteria (rx0, rx1) and a non-smoothed ice draft. Finally, we present a simple parameterization in a buffer zone near the grounding line that uses interpolated melt rates from the ocean model, allowing us to maintain a steep ice topography in the ice model without inducing pressure gradient errors in the short water column in the ocean model. This model configuration will be applied to Pine Island Glacier and used to examine present and possible future states of the ice sheet-ocean system.

Current General Circulation Models (GCMs) are struggling to capture the observed diurnal cycle of precipitation. One major problem is that GCMs usually have difficulties to simulate nocturnal deep convections. Nocturnal deep convections are usually decoupled with the land surface and are controlled by other factors aloft, which have not been fully understood. The Plains Elevated Convection at Night (PECAN) is a multi-institutional collaborated field experiment conducted at the central Great Plains during summertime (1 June to 15 July) 2015 on the purpose of improving the understanding and simulation of the processes that initial and maintain deep convections at night. During the 45-day PECAN period there are 31 intensive operational periods (IOP) of nighttime deep convections, each last for one night. The unique part of PECAN experiment is the use of 6 fixed and 4 mobile PECAN Integrated Sounding Arrays (PISA) to take detailed measurements for each IOP. These detailed measurements of thermodynamics, wind and water vapor profiles in high temporal resolution (typically 90-min) allow the observation of the evolution of boundary layer and propagating features. We will report results from the analysis of these PISAs using a constrained variational analysis method to understand the large-scale environment that control the nighttime deep convections at the central Great Plains.

The use of stable isotopic tracer methods is becoming a popular approach for in situ evapotranspiration (ET) partitioning studies at the ecosystem scale. Ecosystem evapotranspiration is usually partitioned based on different isotopic composition among the aggregated ET flux (δET) and its two components: physical evaporation process (δE) and biological transpiration process (δT). Uncertainties in calculating these three isotopic compositions, especially δET, are usually not negligible and could propagated to large uncertainty in the ET partitioning outcomes. In this study, we present a new ET partitioning approach utilizing dual isotope-based evapotranspiration partitioning based on d-excess (d-excess = δ2H - 8 × δ18O) . A field deployable laser absorption spectrometer was used for in situ measurements of isotopic composition (δ2H and δ18O) of atmospheric water vapor at different heights within the turbulently mixing ecosystem boundary layer for tallgrass prairie. This study incorporated a new refinement to the Craig-Gordon model to describe δE. During non-growing season, estimates of δET—based on Keeling plot and flux-gradient approaches—were compared against δE values derived by the Craig-Gordon model, under the assumption of no transpiration and thus the equality between δET and δE. During the growing season, coupled with isotopic sampling in plant and soils, we partitioned ET into transpiration and evaporation. This refined dual isotope-based approach of ET partitioning shows promise in reducing the uncertainties of the fractional contributions of evaporation and transpiration, thus enhance our understanding on the mechanisms underlying plant water use efficiency and the role of vegetation ecophysiological processes in eco-hydrologic processes under the changing environment.