River delta avulsions are a primary mechanism to distribute sediment and build coastal land. Experiments show that an avulsion can generate a new delta lobe, and subsequent avulsions yield multiple lobes that amalgamate to produce a semi-circular fan deposit. For channels that are actively building lobes, a condition of sediment transport equilibrium develops, termed alluvial grade, which is characterized by material bypassing the delta topset and dispersing to the delta foreset. Previous studies have examined alluvial grade under conditions of steady subsidence and uniform basin depth. However, on tectonically active margins, deltas are affected by punctuated subsidence and lobes prograde into basins with variable depth. Both conditions disrupt alluvial grade, which in turn affects avulsion timescales and thus delta morphology. We explore these interrelated processes using measurements of delta and basin morphology based on field surveys and remote sensing collected from the Selenga Delta, which is located along the Baikal Rift Zone. Major earthquakes, affiliated with normal faulting and possessing recurrence intervals of several millennia, lower large portions of the subaerial delta several meters below mean lake level. This results in an increased regional gradient that triggers lobe-scale avulsions. Moreover, the timescale for these events is shorter than that predicted via autogenic lobe switching. Additionally, during periods tectonic quiescence, smaller channel-scale avulsions occur every 10--90 yrs, which produces sedimentation that compensationally fills embayments located between distributary channels. This process gives rise to the delta's fan-shape morphology. Stratigraphically, tectonically driven subsidence events are expected to preserve discrete sedimentary units that represent deposition and reworking associated with short-term channel avulsions. Understanding the interplay between discrete, tectonically driven subsidence events and autogenic sediment accumulation patterns of a delta prograding into a tectonically active basin will improve interpretations of stratigraphy of ancient systems.

The upper crust in the forearc of the Cascadia subduction zone hosts a complex network of faults that accommodate trench-parallel and trench-normal shortening due to oblique subduction and northward migration of the Oregon/Washington forearc block. Outside of the Seattle area, the seismic potential of major faults, as well as how they connect in a 3-D network, is poorly known. The trench-normal Doty fault, a major, north-dipping forearc fault crosses the I-5 corridor south of the Centralia-Chehalis urban area. Its length, orientation, and hypothesized total offset are comparable to the active Seattle fault, but it is unclear if the Doty fault poses a similar modern seismic hazard. We present preliminary results from the Chehalis Basin project (fieldwork summer 2018). We seek to define the Doty fault’s length, structure, dip, and linkages with smaller, likely transpressive faults to accommodate 3-D crustal deformation. We investigate possible blind faults south of the mapped Doty fault, near the site of a proposed flood-control water retention facility, and present evidence for recent fault activity. A multi-disciplinary approach is critical for regional investigations given dense foliage and glacial cover. Thus, we apply aeromagnetic and ground magnetic data, a regional gravity grid, high-resolution gravity lines, seismicity from a local broadband network, targeted geologic mapping, provenance characterization of Quaternary to Neogene sediments, dating, Lidar interpretation and field reconnaissance of geomorphic features to our research questions. The aeromagnetic data and prior geologic mapping suggest the Doty fault connects to unnamed NNW-striking faults to the west, and our new data will confirm or refute this hypothesis. Initial mapping and aeromagnetic interpretation suggest transpressive faults exist NNE of the Doty fault, which together bound a discrete region of uplift (Lincoln Creek uplift). There is little seismicity in the region recorded by the PNSN regional seismic network, and our PASSCAL array will help confirm the existence or absence of small, local earthquakes that could indicate neotectonic activity.

Accurate photoionization rates are vital for the study and understanding of ionospheres and may account for the discrepancy in electron densities and mismatched altitude profiles of current E-region models. The underestimation of electron density profiles could be mitigated by high-resolution cross sections that preserve autoionization lines which allow solar photons to leak through to lower altitudes. We present new ionization rates calculated with high-resolution (0.001 nm) O and N2 photoionization and electron impact cross sections, and a high-resolution solar spectrum as inputs to CPI’s Atmospheric Ultraviolet Radiance Integrated Code [AURIC, Strickland et al., 1999]. The new electron impact cross sections show little structure and have minimal effect on calculations of ionization rates. Results from AURIC with updated O and N2 cross sections indicate increased production rates up to ~40% in the E-region, specifically between 100–115 km. Likewise, production rates determined using the ionospheric photoionization rate code from Meier et al. [2007] also illustrate an increase in the O and N2 production rates (typically of more than 10%) when using the newly calculated cross sections. Additionally, we find that O and N2 dominate the volume production rates above 130 km while O2 is expected to be the main contributor from 95–130 km. AURIC model results that use the default data and model results with the new O and N2 cross sections both track very well with electron density profiles determined from Arecibo ISR observations. AURIC model results using the new cross section calculations are in better agreement with Arecibo observations at higher altitudes. Our current findings indicate that O2 plays a dominant role in photoionization production rates in the E-region. Therefore it is crucial to update ab initio ionospheric models with high-resolution photoionization cross sections.

Since 2008, the rate of seismic events within the Central United States has dramatically increased, which is likely associated with wastewater injection from nearby oil and gas operations. Surface deformation measurements derived from spaceborne interferometric synthetic aperture radar (InSAR) data can be used to quantify the magnitude and spatial extent of the injection-related stress perturbation, which are critical for understanding the complex interaction between the injected fluid and the earth’s subsurface. In this study, we processed Sentinel-1 InSAR data over Central and West Texas using a recently developed processing framework that performs topography/geometry phase corrections prior to the interferogram formation (Zebker 2017). We streamlined the creation of upsampled digital elevation maps (DEMs) from NASA Shuttle Radar Topographic Mission (SRTM) data, as well as the collection of Sentinel-1 precise orbit data. We developed a tool for InSAR time-series analysis and data visualization. To detect unknown deformation signatures from large volumes of InSAR data, we employed computer vision ideas for feature detection independent of scale, well known through their success in the Scale Invariant Feature Transform (SIFT). We used multi-scale Laplacian-of-Gaussian (LoG) filters to find local maxima and minima in a coarse deformation solution, corresponding to “bowls” of uplift and subsidence, respectively. This allowed us to drastically cut down processing time of high-resolution InSAR products. As a validation, our method successfully detected all sinkhole locations, injection-related uplift signals and production-related subsidence signals as reported in Kim and Lu (2017) over a 100 km x 100km search area without the need for manual inspection. We then examined the Dallas Fort Worth Basin area for evidence of deformation near wastewater injection and oil/gas production sites. We begin to quantify the uncertainty from common noise sources to produce more confident time-series results.

The National Water Model (NWM) currently requires the post-processing of forecast discharges to produce forecast flood inundation maps (FIM) to support the National Weather Service’s mission of protecting life and property. Height Above Nearest Drainage (HAND) is a means of detrending digital elevation models (DEM) by normalizing elevations to the nearest, relevant drainage line (creeks, rivers, etc). It’s worthy of producing high-resolution FIMs at large spatial scales and frequent time steps using reach-averaged synthetic rating curves. However, HAND based FIMs suffer from a known limitation caused by independent catchments that lack the ability to cross catchment boundaries and ridgelines. To counter this constraint, a version of HAND known as Generalized Mainstems (GMS) is proposed that reduces the Horton-Strahler stream order of the stream network. To demonstrate skill enhancement, we constructed HAND derived at three different stream resolutions including the NWM full resolution (FR), the NWM mainstems (MS) resolution, and the NWM GMS resolution stream networks. The FR stream network contains all NWM forecast locations and the MS resolution stream network contains all river segments at or downstream of NWS river forecast points. GMS contains all segments within the FR stream resolution but instead of deriving HAND by accounting for all river segments at once, it is derived independently at the level path (LP) scale. LPs are unique identifiers propagated upstream from a sub-basin’s outlet along the direction of maximum flow distance and repeated recursively until all segments are assigned LP identifiers. These serve as processing units for HAND dataset production and FIMs are made at the LP scale. These FIMs are then mosaiced together, effectively turning the stream network into discrete groups of homogenous unit stream order by removing the influence of neighboring tributaries. Improvement in mapping skill on the order of 2% points of Critical Success Index for MS and 2% points more for GMS is demonstrated by comparing to HEC-RAS FIMs. Additionally, both Probability of Detection and False Alarm Ratio improve which can be partly explained by a positive correlation of stream order with river stage at fixed discharge values within the synthetic rating curves produced by HAND.

The terrestrial energy balance represents a measure of the excess energy stored in the climate system. A possible measurement of this variable can be made at the top of the atmosphere by quantifying the imbalance between the incoming solar flux and the outgoing reflected and infrared flux. This is the objective of the UltraViolet and infrared Sensors at high Quantum efficiency on-board a small SATellite (UVSQ-SAT) mission, validating miniaturized technologies on-board a CubeSat with 1U standards (about 11 cm x 11 cm x 11 cm). This satellite was put into orbit in January 2021 by SpaceX’s Falcon 9 launcher and is totally functional. In order to measure the various fluxes with accuracy it is necessary to know precisely the orientation of the satellite at each time. Indeed, the knowledge of this orientation makes it possible to dissociate the various fluxes and to correct them from the angle to the considered source (Earth, Sun). To do so, two methods were implemented to retrieve the satellite’s attitude based on Sun and Nadir pointing along with inertial measurement unit (IMU) data. To ensure more accurate knowledge of the attitude determination in every configuration (daylight and eclipse), neural networks were implemented based on the available sensors. A multilayer perceptron was thus trained in order to find the orientation of the satellite. Based on the attitude retrieved the different flux were computed at each time from the sensors signals. We present here the development and the outcomes of the neural network applied to in-orbit data recovered from the UVSQ-SAT mission.

We present the first laboratory tests of Spatial Linear Dark Field Control (LDFC) approaching raw contrasts (5e-7) and separations (1.5–5.2 lambda/D) needed to image jovian planets around Sun-like stars with space-borne coronagraphs like Roman-CGI and image exo-Earths around low-mass stars with future ground-based 30m class telescopes. In four separate experiments and for a range of different perturbations, LDFC largely restores (to within a factor of 1.2–1.7) and maintains a dark hole whose contrast is degraded by phase errors by an order of magnitude. Our implementation of classical speckle nulling requires a factor of 2–5 more iterations and 20–50 DM commands to reach contrasts obtained by spatial LDFC. Our results provide a promising path forward to maintaining dark holes without relying on DM probing and in the low-flux regime, which may improve the duty cycle of high-contrast imaging instruments, increase the temporal correlation of speckles, and thus enhance our ability to image true solar system analogues in the next two decades.

Environmental spatial planning of urban coastal regions is critical for sustainable development and designing of coastal resilience in developing countries. The process of environmental spatial planning in coastal regions involves classification of areas into different categories by retaining the synergy between environmental conservation and urban development. Existing coastal regulations for classification of coastal regions in India are based on the subjective approaches. In this study, a quantitative approach is developed by coupling geospatial science and multicriteria decision making in which we prioritized the different physical coastal features quantitatively based on the environmental sensitivity of particular physical coastal feature for the integrated natural coastal ecosystem. Afterwards, these quantitative ranking values of coastal features are combined with linear weighting schemes to derive distinct categories of urban coastal regions spatially, where each category embodies the unique environmental sensitivity. A final map indicating the environmental sensitivity of different coastal regions is prepared. Uncertainty analysis for different weighting schemes was performed to assess the robustness of the developed approach. Finally, we carried out a comparative assessment of the prevailing method of coastal area classification being used by planning authorities and the application of this quantitative approach along the coast of Mumbai, India. Results of comparison clearly demonstrate the effectiveness of the quantitative approach for environmental spatial planning in urban coastal regions. Essentially, the method is found useful for highlighting the locations which need special consideration by planning authorities for the application of inclusive coastal management measures. Furthermore, this approach is modular and scalable, which will facilitate the environmental spatial planning of urban coastal regions based on scientific principles in different coastal cities in developing countries.

We study the properties of dust in disks to constrain models of planet formation. We measure and analyze the spectral index for the dust continuum emission at millimeter wavelengths for a sample of 24 young disks in the Upper Sco star-forming region. We do this by combining data taken with the ALMA telescope at wavelengths of 2.87 mm and 0.88 mm. Since the age of this region is ∼ 5 - 10 Myr, these results can constrain the properties of small solids in disks at the end of their lifetime. We examine whether dust trapping, which is key to the formation of planetesimals, happens only in much younger disks or if it is efficient all the way towards the end of the disk life cycle. Our results indicate that dust traps are present also in the relatively old disks in our sample, indicating that protoplanetary disks have the potential to form planetesimals during their entire lifetime. Our analysis also quantifies the effects of scattering by dust of the disk emission, a mechanism that has been recently proposed as potentially important to determine the fluxes of protoplanetary disks even at sub-mm/mm wavelengths. From preliminary results, based on the state-of-the-art radiative transfer code RADMC-3d, we infer that scattering is not effective for optically thin disk models, but could potentially play a significant role for optically thick models.

Flood risk assessment and the design of protection measures often require the estimation of high water levels of a given probability of exceedance, i.e. design flood levels. The common approach for the estimation of design flood levels has typically three main steps. First, direct measurements of annual maximum water levels in a river cross-section are converted into annual maximum flows by using a rating curve. Second, a probability distribution function is fitted to these annual maximum flows to derive discharges of a desired probability of exceedance, i.e. design peak flows. Third, a hydraulic model is applied to derive the corresponding design flood levels. Each of the three steps is associated with significant uncertainties, affecting the accuracy of estimated design flood levels. In this study, we compare this common approach with an alternative one based on the statistical analysis of time series of annual maximum water levels. The rationale behind this study is that high water levels are directly measured and often come along with higher precision and accuracy than peak flows. While the direct use of high water levels is typical in coastal flood hazard and risk assessment, the potential of this approach in the context of river flooding has not been sufficiently explored. In this study we compare the common approach with an alternative approach based on statistical analysis of annual maximum water levels.

Combining direct imaging astrometry and long-baseline radial velocity (RV) measurements of stellar binaries can provide precise constraints on their 3D orbits and yield dynamical masses for both components. We applied the combination of these methods to study HD104304, a binary system with a decades-long orbit containing a G8IV subgiant and a recently-discovered M dwarf companion. Using radial velocities collected over a timespan of two decades by Keck/HIRES and astrometry calculated from adaptive optics images taken by Keck/NIRC2, we explored models to jointly fit the astrometric orbital motion and RV trend. Previous studies of this system (Howard & Fulton, 2016) were unable to distinguish between two and three body solutions using RVs alone. However, we are able to break this degeneracy by incorporating images into the fit. We make 13-sigma dynamical mass measurements of the primary and secondary, and find that a slightly eccentric solution (e=0.3) is required. However, the dynamical mass we measure for the primary (~1.8 solar masses) is significantly higher than its well constrained spectroscopic mass of 1.02 solar masses. This hints at the need for a three-body solution to accurately model the observed trend in the HD 104304 system.

Lower ionosphere is difficult to probe for conventional measurements, as its altitude range is too low for the satellite and too high for atmospheric balloons. Recently, an alternative method to study lower ionosphere is using lightning signatures. In this work，we investigate the daytime fluctuations of lower ionosphere by analyzing the time domain VLF/LF waveform emitted by Narrow Bipolar Events (NBEs), which were recorded by an eight-station lightning location network called Jianghuai-Area Sferic Array (JASA) for a systemic real-time monitoring of lower ionosphere. JASA has been developed in 2012 and improved as a real-time lightning location network since 2018. We analyze numerous thunderstorm-day data and the preliminary results show that the lower ionosphere virtual height descends linearly at a rate of 5.9 km/h during sunrise, whereas rises linearly at a rate of 8.6 km/h during sunset. Moreover, the lower ionosphere virtual height short-time fluctuation is significantly modulated by the solar radiations’ flux density recorded by GOES satellite and the lower ionosphere diurnal variation pattern exhibiting a significant asymmetry, indicating that electron production in the lower ionosphere is dominated by the effect of solar radiation accelerating the neutral atmospheric molecules

Light absorption in the photosynthetically active (400 – 700 nm) spectral region is necessary for plant CO2 fixation via photosynthesis. Light absorption in excess of that which can be used for photosynthesis may result in photoinhibition and/or other processes detrimental to normal plant function. Plants have evolved several photoprotective mechanisms to reduce light absorption under stressful conditions. For example, leaf-level reflectance and transmittance increased as a result of chloroplast movement within leaf cells in response to water stress in greenhouse-grown maize and soybean. This has implications for detecting (as a signal and noise) diurnal and stress-related changes in canopy reflectance in field-grown crops. These changes were recently investigated in the field using newly developed instrumentation systems and software. Two hyperspectral spectrometers, an Ocean Optics QE Pro (0.3 nm resolution in the 650 - 813 nm range) and a Flame (2.0 nm resolution in the 340 - 1028 nm range) are coupled through optical shutters to a downward looking fiber (25° field of view) and an upward looking fiber with cosine corrector. The spectrometers can be configured to see sky or surface targets concurrently or separately. This new configuration offers concurrent measures of derived solar induced fluorescence (SIF), and visible and near infrared reflectance on a mobile platform, acquiring spatially averaged responses. Our goal is to use SIF as an indicator of the level of photosynthetic activity in comparison to reflectance-derived indication of photoprotective response. In conducting data acquisition, several technical issues arose. Different spectrometer integration times, due to differing radiometric sensitivities and changing sky conditions, causes differences in measured reflectance between the two spectrometers. Also the approach highlighted the difficulty of obtaining reliable system calibration under varying sky conditions when using near-Lambertian reference panels. While results are promising in detecting SIF along with more conventional remote sensing spectral resolution, further research is needed to refine data acquisition to ensure quality reflectance measurements. We report on technical issues and on our success in tying photoprotection to changes in photosythentic activity.

Environmental decision- and policy-making must contend with uncertainty about the future that can hinder proactive environmental decisions, forcing environmental managers into reactive postures. To help prevent this, a variety of methods exist for exploring potential environmental futures and associated uncertainties. Producing environmental futures benefit those involved by supporting a systems-level understanding and expanding thinking beyond “business as usual”. We review environmental and non-environmental programs that use indicators to inform environmental futures for decision- and policy-making. Review objectives are to: 1) identify and discuss key environmental futures program attributes, and 2) propose program attributes that support their successful uptake in decision processes. Attributes discussed include purpose and audience, methods, addressing uncertainty and assumptions, relationship to indicator programs, how program values and biases are addressed, the role of goals, and how success is measured and defined. We conclude with recommendations for environmental futures programs that can be successfully integrated into environmental decisions. These include: combining multiple environmental futures methods to provide complementary insights or highlight inconsistencies in assumptions, including a schematic of assumptions and drivers, and defining success criteria, whenever possible. These can help increase the acceptance of environmental futures products in decision-making and increase their short-term and long-term contributions.

Thermophilic composting within ecological-based sanitation systems (EcoSan) facilitates a biogeochemical transformation of pathogenic solid materials into a sanitary organic soil amendment. Recent work suggests that, in addition to recycling nutrients and eliminating pathogens, thermophilic composting during EcoSan can lower greenhouse gas emission compared to other waste treatment practices, however empirical observations of gas fluxes are few. Data are particularly lacking from urban areas in the global south where innovation in sanitary infrastructure is a sustainable development priority. We quantified greenhouse gas emissions with intensive chamber-based flux sampling over three cycles of thermophilic composting at an established EcoSan operation serving an urban community in northern Haiti. We asked: (1) How do dynamics of greenhouse gases vary throughout the lifetime of the compost pile and the different operational stages? (2) What fraction of initial carbon and nitrogen content is lost via gas fluxes and how does this compare to internationally defined emissions factors? (3) How can different pile management options further mitigate emissions? We found methane emissions were highest in the thermophilic stage, ranging from 5-20 µmol m-2 s-1, and dominated the global warming potential of the entire operation. Approximately 0.1-0.5% of initial pile carbon was emitted as methane while only 0.05-0.3% of initial pile nitrogen was emitted as nitrous oxide, both at the low end of IPCC emissions factor ranges for manure composting. In paired-pile experiments, we found that improved pile drainage could further mitigate methane emissions, as could use of a thinner layer of cover material. This study provides some of the first detailed observations of greenhouse gas dynamics during the thermophilic composting of human waste and our results suggest that climate mitigation potential associated with composting-based EcoSan is greater than previously thought.

In this study, we have developed a hyper-resolution land-surface forcing dataset (temperature, pressure, humidity, wind speed, incident longwave and shortwave radiation) from coarse resolution products using a physically-based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, temperature lapse rate corrections, surface roughness and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. The hourly NLDAS (North America Land Data Assimilation System) forcing data at 0.125° have been downscaled to 500m resolution over the study area during 2015. Results show that correlation coefficients between the downscaled forcing dataset and ground observations are consistently higher and biases are lower than the ones between the NLDAS forcing dataset at their native resolution and ground observations. Results are therefore encouraging as they demonstrate that the 500m forcing dataset has a good agreement with the ground information and can be adopted to force the land surface model for land state estimation. The Noah-MP land surface model is then forced with both the native resolution NLDAS dataset and the downscaled one to simulate surface and root zone soil moisture. Model outputs are compared with in situ soil moisture observations and SMAP (Soil Moisture Active Passive Mission) products at different spatial resolutions. This work will result in a radical improvement over the current state-of-the-art forcing data and will move into the era of hyper-resolution land modeling.

Sea ice plays a crucial role on the ocean and is one of the most sensible indicators of climate change (IPCC 2013). The changing sea ice can be characterized by 4 Essential Climate Variables (ECVs) identified by the World Meteorological Global Organization Climate Observing System implementation plan (WMO Pub No.GCOS-200) : 1) sea ice extent, 2) sea ice concentration, 3) sea ice drift and 4) sea ice thickness. Since the 70ies, these 3 first variables are fairly well observed from space. However, before 2010 and the launch of CryoSat-2, sea ice thickness observations remain sparse and un- homogeneously distributed over time and space. In the Arctic ocean, we will show in this presentation that sea ice thickness time series can be extended to at least 16 years (2002-2017) using Envisat, CryoSat-2 and Sentinel-3 satellites with inter-missions biases calibrated and corrected. Among all potential inter-mission biases, the most impacting is certainly the transition from Low Resolution Mode (LRM) to Synthetic Aperture Radar (SAR) altimetry. This transition is particularly important over sea ice considering that the strong roughness heterogeneity, at basin scale and within the radar footprint, has different signatures in LRM and SAR modes. Here, we will focus on the transition between Envisat and CryoSat-2 common flight period (20010-2012). Results are validated against in situ observations (mooring, airborne, buoys and laser altimetry). This same methodology is applied to produce equivalent long term time series over Antarctica (2002-2017). In the southern ocean, the main difficulties rely on the severe lack of in-situ observations and on the ability to retrieve the snow depth. First results based on the Saral and Cryosat Ka-Ku frequency radar differences will be shown. Finally, we explain how this new global sea ice volume changes will provide new insights on the response to climate change. In particular, the final objective is to revisit the ocean freshwater budget and to provide a new constraint on the land ice melt contribution to sea level rise that is independent from the NASA Gravity Recovery and Climate Experiment measurements.

Demand-side management strategies based on customized feedback have proved their worth in supporting water conservation efforts and behavior change programs. Several studies in both the water and energy sectors report of observed short-term savings deriving from feedback-based programs and awareness campaigns, often based on smart metered data and high levels of customization in presenting information on resource usage to users in the form of past consumption, real-time information, peer comparison, analogies, and resource saving tips. Yet, feedback-based programs are often run as part of experimental trials with a limited duration, and their effectiveness is therefore only evaluated for a short time span, potentially overlooking rebound effects. Assessing the long-term effect of feedback information on behavior change is still an open research question. In this work, we analyze the long-term impacts of a smart-meter fed gamified ICT platform providing customized feedback to water users, which was deployed starting in 2014 in a long experiment trial with over 200 users of the Global Omnium utility in Valencia (Spain). The platform core is a data-driven demand management pipeline that enables water utilities to foster consumer engagement and promote water conservation via customized feedbacks. It includes customized water saving tips, peer-comparison of water usage, and a reward program based on gamification tools and mechanisms. After three years of development and testing from 2014 to 2017, the platform has proven to be very effective in the short-term, when a user is engaged. A 5.7% volumetric water use reduction among Global Omnium users was achieved after the first year of full implementation, along with a 20% approximate water consumption difference with respect to non-platform users. Here, we analyze the smart meter data of the platform users, respectively after one and two years from the end of the funded platform trial period, to assess long-term behavior changes and rebound effects on different groups of platform adopters.