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Satellite observations have been widely used to measure methane (CH4) emissions from the oil and gas (O&G) industry, particularly by revealing previously undocumented, very large emission events and basin-level emission estimates. However, the performance of retrieving CH4 mixing ratios from the short-wave infrared band of passive remote sensing instruments is spatially and temporally varied due to sunlight, earth surface properties, and atmospheric conditions. Thus, the reliability of satellites is also varied. To assess the reliability of passive remote sensing satellite instruments for routine monitoring of CH4 emissions, we investigated the global observational coverage of the TROPOMI (onboard the Sentinel-5P), which has been providing a daily global CH4 mixing ratio since 2017. A 0.1° x 0.1° gridded global map that indicates the average number of days with valid observations from TROPOMI from 2019 to 2021 was generated by following the measurement retrieval quality-assurance threshold (≥0.5). We found TROPOMI had promising observational coverage over dryland regions (maximum: 58.6%) but limited coverage over tropical regions and high latitudes (minimum: 0%). Cloud cover and solar zenith angle were the primary factors at high latitudes, while aerosol optical thickness was the primary factor over dryland regions. To further assess the country-level reliability of satellites for detecting and quantifying CH4 emissions from the O&G sector, we extracted the average annual TROPOMI observational coverage (TOC) over O&G infrastructure for 160 countries. Seven of the top-10 O&G-producing countries had an average annual TOC < 10% (< 36 days per year), which indicates the limited ability to routinely identify large emissions events, track their duration, and quantify emissions rates using inverse modelling. We further assessed the potential performance of the latter by combining TOC and the uncertainties from the global O&G inventory. Results inverse modeling with CH4 measurements from TROPOMI may only be accurate for quantifying emissions from O&G sectors in countries located in dryland and mid-latitude regions. Conclusively, the current passive-sensing satellites have low potential for frequent monitoring of large methane emissions from O&G sectors in countries located in tropical and high latitudes (e.g., Canada, Russia, Brazil, Norway, and Venezuela). Therefore, alternative methods should be considered for routine emissions monitoring in the corresponding regions.

The occurrence and emissions of methane (CH4) from above-ground urban natural gas infrastructure is poorly understood. Compared to below-ground infrastructure, these facilities are relatively easy to monitor and maintain and present an opportunity for cost-effective CH4 reductions. We present a case study and methodology for detecting, attributing, and quantifying CH4 emissions from fence line measurements at above-ground natural gas facilities in the City of Calgary, Alberta, Canada. We produced bounding-box concentration maps by walking around the outer fence of 33 facilities with a backpack-configured trace gas analyzer and a tablet with integrated GPS. Wind measurements were acquired simultaneously from a fixed location on site with a 3D sonic anemometer. We fused geolocation, CH4 concentration, and wind data to determine the likelihood each facility was emitting. We found one definitive leak by carrying out measurements directly alongside an exposed section of pipe. Based on the presence of methyl mercaptan (CH3SH) odor, peak ΔCH4, and the difference between downwind and upwind ΔCH4, we interpret a high plausibility that 22 facilities were emitting CH4, followed by 2 with a medium plausibility, and 8 with a low plausibility. Once verified to plausibly emit, these data were used to estimate emissions flux at six facilities where near-field obstructions were limited. The estimated emissions flux for six facilities was 66.31 mg CH4 s-1, or 2.1 tonnes CH4 yr-1 if this flux remained constant. Overall, this study indicates most above-ground natural gas facilities surveyed in Calgary were emitting CH4. These facilities represent easy mitigation targets for reducing CH4 emissions and improving environmental performance. To our knowledge, this is the first study to integrate qualitative and quantitative information to predict detection plausibility in a complex measurement setting.Implications: The fence line methodology outlined in this study represents an extension of source assessment modes in the US EPA's Other Test Method 33A for human portable systems. This has implications for standardization of emissions measurement in situations where other platforms (e.g., vehicles) are less effective due to access limitations. We believe the methodology presented could become a recognized standard based on performance from controlled testing and added to the regulatory toolkit for emissions verification and compliance.

We present observations, measurements, and modeling of an enigmatic eolian bedform pattern of cross-wind alternating, wind-parallel corridors of megaripples and smaller bedforms (“megaripple stripes”). Megaripple corridors have taller bedforms, longer wavelengths, and coarser surface sediment than intervening smaller bedform corridors. We document examples from Earth (Argentina, Namibia, United States, Iran, Peru, and China) and Mars. Using a reduced complexity model, we show that megaripples and megaripple stripes initiate under the influence of two eolian transport length scales: long-hop saltons and short-hop reptons. The self-organizing stripe pattern manifests in a narrow range of repton concentrations and develops into more typical megaripples as the surface repton concentration increases. We show that the three-dimensional topography of simulated megaripple stripes closely resembles natural megaripple stripes at Oceano Dunes, California, USA. By tracking repton surface concentration and spatial autocorrelation during simulations, we show that the striped pattern initiates from local repton concentrations of sufficient size to serve as megaripple nuclei that seed the striped pattern. Results suggest that megaripple stripes may have a simple and robust formation mechanism.

Small aerial drones are used in a growing number of commercial applications. However, drones cannot fly in all weather, which impacts their reliability for time-sensitive operations. The magnitude and global variability of weather impact is poorly understood. We explore weather-limited drone flyability (the proportion of time drones can fly safely) by comparing historical wind speed, temperature, and precipitation data to manufacturer-reported thresholds of common commercial and weather-resistant drones with a computer simulation. We show that global flyability is highest in warm and dry continental regions and lowest over oceans and at high latitudes. Median global flyability for common drones is low: 5.7 h/day or 2.0 h/day if restricted to daylight hours. Weather-resistant drones have higher flyability (20.4 and 12.3 h/day, respectively). While these estimates do not consider all weather conditions, results suggest that improvements to weather resistance can increase flyability. An inverse analysis for major population centres shows the largest flyability gains for common drones can be achieved by increasing maximum wind speed and precipitation thresholds from 10 to 15 m/s and 0-1 mm/h, respectively.

Small aerial drones are used in a growing number of commercial applications. However, drones cannot fly in all weather, which impacts their reliability for time-sensitive operations. The magnitude and global variability of weather impact is poorly understood. We explore weather-limited drone flyability (the proportion of time drones can fly safely) by comparing historical wind speed, temperature, and precipitation data to manufacturer-reported thresholds of common commercial and weather-resistant drones with a computer simulation. We show that global flyability is highest in warm and dry continental regions and lowest over oceans and at high latitudes. Median global flyability for common drones is low: 5.7 h/day or 2.0 h/day if restricted to daylight hours. Weather-resistant drones have higher flyability (20.4 and 12.3 h/day, respectively). While these estimates do not consider all weather conditions, results suggest that improvements to weather resistance can increase flyability. An inverse analysis for major population centres shows the largest flyability gains for common drones can be achieved by increasing maximum wind speed and precipitation thresholds from 10 to 15 m/s and 0–1 mm/h, respectively.

Yardangs are streamlined ridges that form in arid environments on Earth and Mars through wind-driven abrasion of consolidated substrates. Currently, there is limited consensus on the mechanisms that initiate and establish patterns of yardangs on the landscape. In this work, we examine the spatial organization of yardangs in the Campo de Piedra Pomez ignimbrite deposit of northwestern Argentina and identify evidence of antecedent controls on yardang patterns and formation. We mapped 14,826 yardangs in the region using a high-resolution digital elevation model (DEM) and satellite imagery. We classified yardangs as points using a two-stage decision rule based on morphology and spectral characteristics. Point pattern analysis shows that yardangs in the study area are not randomly distributed and commonly exhibit directional anisotropy in point pattern. The anisotropic pattern manifests as bands of closely-spaced yardangs oriented transverse to the dominant northwesterly wind direction. We hypothesize that banding is controlled by pre-existing antecedent topography in the bedrock, such as fumaroles or ridges associated with pyroclastic flow deposits. We present evidence from other locations on Earth and Mars to illustrate that the transverse banding is a common pattern in yardang landscapes.

Aeolian rat-tails (ARTs) are a previously undocumented, regionally-ubiquitous aeolian abrasion feature observed on matrix-supported ignimbrite surfaces in the Puna Plateau of Northwest Argentina. ARTs consist of an abrasion-resistant lithic clast projecting above the surface with a lee tail or ‘keel’ in the more erodible matrix. Size is controlled by the dimensions of the windward lithic clast, ranging from centimetre to meter scale; spatial density varies with clast content, which may reflect variations in ignimbrite facies. Field observations suggest ARTs follow a definable evolutionary sequence. First, an abrasion-resistant lithic clast contained within the ignimbrite is exposed to abrasion at the surface. Impacts from abrading particles erode the softer ignimbrite matrix adjacent to the clast. The clast shelters the leeward surface under a unimodal abrasion direction, creating a tail that tapers downwind and elongates as the clast emerges. Clasts become dislodged from the matrix as the surrounding surface erodes, ultimately destroying the feature if the clast is small enough to be mobilized directly by wind or impacting particles. This evolutionary sequence explains the morphology of ARTs and the presence of loose clasts on the ignimbrite surface, which contributes to the development of other landforms in the region, such as periodic bedrock ridges, yardangs, and megaripples. Satellite and rover images suggest similar features also exist on Mars. Because the formation and preservation of ARTs is contingent on unimodal abrasion direction, their orientation can be used as an indicator of long-term aeolian sediment transport direction.

Transverse aeolian ridges (TARs) are a distinct aeolian bedform found on Mars. The formative processes, evolution, and geological significance of TARs is poorly understood. Fundamentally, it is unknown whether TARs are dunes, mega-ripples, or another bedform type. We examined aeolian bedforms in the Lut Desert of Iran as a terrestrial analog for Martian TARs. From an objective sampling strategy with high-resolution satellite imagery, we developed a large morphometric dataset for comparison with existing Martian TARs. We also examined the dynamics of the Lut bedforms between 2004 and 2012 to determine if they were static or migrating. Results indicate that the range in the dimensions (length, width, height, and wavelength) of the Lut bedforms and Martian TARs overlap, suggesting Lut bedforms are a viable terrestrial TAR analog. Our sample yielded median values of 55.18 m, 9.80, 1.02 m, and 20 m for length (longest planview axis), width (shortest planview axis), height, and wavelength, respectively. Cumulative log-frequency plots of morphometric parameters suggest the sample is from a single population and process mechanism. Although the vast majority of Lut bedforms examined were static between 2004 and 2012, some migrated up to 0.09 myr −1 on average. This is much slower than nearby dunes (4–12 myr −1 ), but is explained by the existence of a surface lag of coarse particles on the TAR-like bedforms. The combination of morphometry, surface sedimentology, and slow migration rate indicate the Lut bedforms are mega-ripples, which provides evidence supporting interpretation of Martian TARs as mega-ripples. Testing the mega-ripple hypothesis for Martian TARs requires measurements of their sedimentology, which may be possible with the Mars Science Laboratory rover Curiosity, as well as expanded measurements of TAR morphometry to constrain their size, shape, and scaling.

UAV incidents were analyzed using data from Transport Canada’s Civil Aviation Daily Occurrence Reporting System (CADORS). Between 5 November 2005 and 31 December 2016 a total of 355 incidents were reported in Canadian airspace. The largest number involved UAV sightings (66.5%) and close encounters with piloted aircraft (22.3%). These incidents increased markedly after 2013, with the highest number in British Columbia, followed by Ontario, Quebec, Alberta, and Manitoba. The vast majority of UAV incident reports were filed by pilots of piloted aircraft. Typically, airspace at altitudes greater than 400 feet above ground level (AGL) is off limits to UAVs; however, of the 270 incidents in the CADORS database with UAV altitude reported, 80.4% were above 400 feet AGL and 62.6% were above 1000 feet AGL. Of the 268 incidents with reported horizontal distance to the nearest aerodrome, 74.6% occurred or likely occurred within five nautical miles (M), and of those 92.4% and 76.6% were reported above 100 and 300 feet AGL, respectively. Collectively, the CADORS data indicate that the overwhelming majority of UAV incidents reported in Canada were airspace violations. These results can guide future risk mitigation measures, hardware and software solutions, and educational campaigns to increase airspace safety.

Using HiRISE digital terrain models (DTMs), we developed a large morphological dataset to examine the three-dimensional shape, size, and scaling of Martian transverse aeolian ridges (TARs). Considerable debate exists on the characteristic morphology of TARs and the origins of these enigmatic bedforms. Some researchers suggest polygenesis or multiple classes of similar bedforms. Reliably characterizing the morphology of TARs is an essential prerequisite to developing and evaluating process-based models of TAR genesis and unraveling aeolian processes on the surface of Mars. We present measurements of TAR morphology from a large, DTM-derived dataset (n = 2295). We focused on TARs with ‘simple’ morphologies in order enable more defensible discretization. Histograms and cumulative log-frequency plots of morphometric parameters (length, width, height, elongation ratio, and wavelength) indicate the sample represents a continuum of bedforms from a single population. A typical TAR from our dataset is 88.5 m long (longest planview axis), 17.3 m wide (shortest planview axis), 1.3 m tall, and has a wavelength of 25.8 m. Combined with these data, the bulk of evidence presented to date suggests that interpreting TARs as megaripples is the most viable working hypothesis.

New mobile platforms such as vehicles, drones, aircraft, and satellites have emerged to help identify and reduce fugitive methane emissions from the oil and gas sector. When deployed as part of leak detection and repair (LDAR) programs, most of these technologies use multi-visit LDAR (MVL), which consists of four steps: (a) rapidly screen all facilities, (b) triage by emission rate, (c) follow-up with close-range methods at the highest-emitting sites, and (d) conduct repairs. The proposed value of MVL is to identify large leaks soon after they arise. Whether MVL offers an improvement over traditional single-visit LDAR (SVL), which relies on undirected close-range surveys, remains poorly understood. We use the Leak Detection and Repair Simulator (LDAR-Sim) to examine the performance and cost-effectiveness of MVL relative to SVL. Results suggest that facility-scale MVL programs can achieve fugitive emission reductions equivalent to SVL, but that improved cost-effectiveness is not guaranteed. Under a best-case scenario, we find that screening must cost < USD 100 per site for MVL to achieve 30% cost reductions relative to SVL. In scenarios with non-target vented emissions and screening quantification uncertainty, triaging errors force excessive close-range follow-up to achieve emissions reduction equivalence. The viability of MVL as a cost-effective alternative to SVL for reducing fugitive methane emissions hinges on accurate triaging after the screening phase.

Alternative leak detection and repair (alt-LDAR) programs are being introduced by regulators to provide flexibility in how oil and gas producers manage fugitive methane emissions. However, emissions reduction equivalence must be established between a proposed program and a regulatory standard. We present LDAR-Sim, an open-source, agent-based numerical model for evaluating LDAR program performance. Novel functionality includes the ability to: (1) set facility-specific LDAR requirements, (2) simultaneously deploy multiple technologies, (3) integrate screening and close-range methods, (4) include environmental constraints, and (5) explore the impact of design emissions on screening technologies. We demonstrate LDAR-Sim in two case studies with diverse LDAR programs deployed on real assets. We find that equivalence determinations depend on explicit definition of reference standards, including weather and labour availability. Screening program performance is sensitive to the confounding presence of design emissions and to decision-making strategies that guide follow-up inspections. When comparing programs, differences in simulated performance are sensitive to leak production and null repair rates, two elusive parameters used in previous studies. Future work should better constrain empirical inputs and validate specific LDAR programs as alt-LDAR deployment increases. Regulators and producers can use LDAR-Sim to facilitate the adoption of emerging technologies but should be aware of its limitations.

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

Subglacial bed forms (drumlins, ribbed moraines, and megascale glacial lineations) are enigmatic repetitive flow-parallel and flow-transverse landforms common in glaciated landscapes. Their evolution and morphology are a potentially powerful constraint for ice sheet modeling, but there is little consensus on bed form dynamics or formative mechanisms. Here we explore shallow sediment bed form dynamics via a simple model that iterates (i) down-flow till flux, (ii) pressure gradient-driven till flux, and (iii) entrainment and deposition of sediment. Under various boundary conditions, replicas of subglacial bed forms readily emerge. Bed form dynamics mirror those in subaqueous and aeolian domains. Transitions between ribbed moraines and elongate flow-parallel bed forms are associated with increasing ice speeds and declining sediment thickness. These simulations provide quantitative flux estimates and suggest that widely observed transitions in shallow sediment subglacial bed forms (e.g., ribbed moraines to drumlinoids to megascale glacial lineations) are manifestations of subtle variations in ice velocity and sediment thickness.

The Puna Plateau of northwestern Argentina is a promising region for analogue investigations of Martian aeolian processes owing to its high altitude, low atmospheric pressure, aridity, geology, and widespread granular and bedrock aeolian landforms. Despite a growing body of research about the region's enigmatic aeolian landforms, little is known about the contemporary aeolian environment, processes, and landscape dynamics. To address this gap, we used a combination of modelled weather data, satellite imagery, and field measurements to characterize the wind regime, aeolian sediment transport, and allied surface changes. The study focused on the Campo de Piedra Pomez (CPP) – a volcanic landscape with a variety of Mars analogue landforms: gravel-mantled megaripples, yardangs, ventifacts, periodic bedrock ridges, and aeolian rat-tails. Modelled weather data from the European Center for Medium-Range Forecasting's ERA-Interim reanalysis dataset confirm the contemporary dominance of northwesterly winds in this region, consistent with the primary orientation of yardangs. These data also indicate the presence of less frequent southeasterly winds, which may explain why re-entrant profiles are observed on the southeast flanks of a small portion of the yardang population, and why some aeolian rat-tails point to the northwest. Observations from multi-temporal satellite imagery indicate that deposition and displacement of small sediment patches overlying ignimbrite bedrock is relatively common across the region. Samples retrieved from sediment traps deployed over one year in the region suggest a broad range of particle densities are mobilized by wind, which implies a wide range of wind speed for fluid entrainment. Conventional aeolian transport models do not consider the effects of particle density variations on transport processes. However, in areas with multiple density sediment present, our results point towards a need for aeolian models to consider density when quantifying and qualifying sediment transport.

Periodic bedrock ridges (PBRs) are unexplained aeolian landforms discovered on Mars. PBR morphology and length scale resemble megaripples or small reversing dunes, but PBRs are eroded directly into bedrock. In this article we describe the first identified terrestrial PBRs from the Puna plateau of Argentina and present a hypothesis for their formation. The PBRs have formed in ignimbrite bedrock and are morphologically similar to nearby gravel megaripples. Observations along a landscape continuum provide basis for a genetic link between PBRs and gravel megaripples. First, gravel megaripples develop from lithics and pumice eroded from ignimbrite. The lithic clasts organize on the surface, forming megaripple crests and locally protecting the underlying ignimbrite. Exposed ignimbrite in troughs between the megaripples erodes and deepens as the ignimbrite topography evolves into a series of wind-transverse bedrock ridges (incipient PBRs) that mimic the pattern of overlying megaripples. The megaripples and incipient PBRs migrate downwind together and develop patterning indicative of bedform interactions with collisions, lateral linking, and ejections. PBRs emerge when the supply of lithics decreases and the crests become exposed by megaripple detachment. With crests exposed, PBRs appear to evolve into scalloped terrain due to abrasion. On Mars, the juxtaposition of megaripples and PBRs in some areas implies a similar evolutionary pathway whereby the megaripples seed PBR pattern. It may be possible for PBRs to develop through direct abrasion of bedrock; however, the mechanism(s) required to form wind-transverse PBRs as opposed to the more common wind-parallel features (yardangs) has yet to be identified.

Yardangs are enigmatic wind-parallel ridges sculpted by aeolian processes that are found extensively in arid environments on Earth and Mars. No general theory exists to explain the long-term evolution of yardangs, curtailing modeling of landscape evolution and dynamics of suspended sediment release. We present a hypothesis of yardang evolution using relative rates of sediment flux, interyardang corridor downcutting, yardang denudation, substrate erodibility, and substrate clast content. To develop and sustain yardangs, corridor downcutting must exceed yardang vertical denudation and deflation. However, erosion of substrate yields considerable quantities of sediment that shelters corridors, slowing downcutting. We model the evolution of yardangs through various combinations of rates and substrate compositions, demonstrating the life span, suspended sediment release, and resulting landscape evolution. We find that yardangs have a distinct and predictable evolution, with inevitable demise and unexpectedly dynamic and autogenic erosion rates driven by subtle differences in substrate clast composition.

In this paper we present a new software tool that automatically fetches, downloads and consolidates climate data from a Web database where the data are contained on multiple Web pages. The tool is called the Canadian Climate Data Scraping Tool (CCDST) and was developed to enhance access and simplify analysis of climate data from Canada's National Climate Data and Information Archive (NCDIA). The CCDST deconstructs a URL for a particular climate station in the NCDIA and then iteratively modifies the date parameters to download large volumes of data, remove individual file headers, and merge data files into one output file. This automated sequence enhances access to climate data by substantially reducing the time needed to manually download data from multiple Web pages. To this end, we present a case study of the temporal dynamics of blowing snow events that resulted in ~3.1 weeks time savings. Without the CCDST, the time involved in manually downloading climate data limits access and restrains researchers and students from exploring climate trends. The tool is coded as a Microsoft Excel macro and is available to researchers and students for free. The main concept and structure of the tool can be modified for other Web databases hosting geophysical data.

We present an analysis of 10 dune fields to test a model-derived hypothesis of dune field activity. The hypothesis suggests that a quantifiable threshold exists for stabilization in unidirectional wind regimes: active dunes have slipface deposition rates that exceed the vegetation deposition tolerance, and stabilizing dunes have the opposite. We quantified aeolian sand flux, slipface geometry, and vegetation deposition tolerance to directly test the hypothesis at four dune fields (Bigstick, White Sands Stable, White Sands Active, and Cape Cod). We indirectly tested the hypothesis at six additional dune fields with limited vegetation data (Hanford, Ano Nuevo, Skagen Odde, Salton Sea, Oceano Stable, and Oceano Active, “inverse calculation sites”). We used digital topographic data and estimates of aeolian sand flux to approximate the slipface deposition rates prior to stabilization. Results revealed a distinct, quantifiable, and consistent pattern despite diverse environmental conditions: the modal peak of prestabilization slipface deposition rates was 80% of the vegetation deposition tolerance at stabilized or stabilizing dune fields. Results from inverse calculation sites indicate deposition rates at stabilized sites were near a hypothesized maximum vegetation deposition tolerance (1 m a−1), and active sites had slipface deposition rates much higher. Overall, these results confirm the hypothesis and provide evidence of a globally applicable, simple, and previously unidentified predictor for the dynamics of vegetation cover in dune fields under unidirectional wind regimes.

We describe an integrated system combining an unmanned aerial vehicle (UAV) and open path methane instrument for detecting leaks in natural gas infrastructure. Reducing methane emissions from the n...

Despite almost a century of study, aeolian sediment transport remains difficult to measure. Low temporal resolution sediment traps filter sub-second scale variability hypothesized to be important, and high resolution electronic sensors are poorly tested, inconsistent, and often produce incomparable particle count outputs. No sediment transport prediction model can be validated or applied without quality empirical transport measurements. Here, we test a popular electronic laser gate sensor (Wenglor YH03PCT8, ‘the Wenglor’) in a wind tunnel. We have 3 goals: (i) assess the reproducibility of Wenglor measurements, (ii) examine saturation potential, and (iii) relate trap-measured sediment flux to particle counts. To assess reproducibility we measured particle counts with two co-located Wenglors. Temporally-autocorrelated sections of the time series occurred where one Wenglor deviated; this is likely the result of lens contamination. To examine saturation potential, we measured saltator velocity to calculate particle concentration within the airstream. Particle concentrations suggest the mean number of particles within the laser sampling volume is consistently less than one. To relate trap-measured sediment flux to particle counts, we used particle size samples to calculate an average mass per counted particle. We relate count predicted mass fluxes to trap-measured mass fluxes with linear regression and obtain the relation: trap flux = 2.1 * Wenglor predicted flux (r2 = 0.99). The constant represents aspects of the Wenglor operation that cannot be directly evaluated. Together, these investigations suggest the Wenglor provides a consistent and low-cost method to measure aeolian saltation flux at a high resolution in non-dusty settings.

Predicting aeolian sediment transport is a long-standing and difficult challenge that is important to a variety of scientific disciplines, including geology, geomorphology, agriculture, meteorology, and climatology. Here, we argue that improvements in predictions of aeolian sediment transport are limited by incompatibilities between empirical measurements and mathematical models. We focus on the spatial and temporal variability in transport. Measurements indicate considerable variability on small time (second) and length (meter) scales, yet models are almost ubiquitously based on assumptions of time and space-invariant transport. Mismatches between measurements and models limit summative predictive capacity by reducing the ability to use measured data to test and drive models. We suggest: (i) revising model conceptualizations and evaluating the representativeness of steady state saltation to constrain the realism of existing models, (ii) improving and optimizing measurement technology to produce more reliable and accurate measurements, (iii) explicitly specifying the scale of measurements, and (iv) designing variable matching tests between models and measurements to work around measurement limitations. Continuing with the status quo, where measurements and models are dealt with separately, is likely to erode summative predictive capacity.

Small unmanned aircraft systems (UASs) are often suited to applications where the cost, resolution, and (or) operational inflexibility of conventional remote sensing platforms is limiting. Remote sensing with small UASs is still relatively new, and there is limited understanding of how the data are acquired and used for scientific purposes and decision making. This paper provides practical guidance about the opportunities and limitations of small UAS-based remote sensing by highlighting a small sample of scientific and commercial case studies. Case studies span four themes: (i) mapping, which includes case studies to measure aggregate stockpile volumes and map river habitat; (ii) feature detection, which includes case studies on grassland image classification and detection of agricultural crop infection; (iii) wildlife and animal enumeration, with case studies describing the detection of fish concentrations during a major salmon spawning event, and cattle enumeration at a concentrated animal feeding operation; (iv) landscape dynamics with a case study of arctic glacier change. Collectively, these case studies only represent a fraction of possible remote sensing applications using small UASs, but they provide insight into potential challenges and outcomes, and help clarify the opportunities and limitations that UAS technology offers for remote sensing of the environment.

Fugitive methane emissions from the oil and gas industry are targeted using leak detection and repair (LDAR) programs. Until recently, only a limited number of measurement standards have been permitted by most regulators, with emphasis on close-range methods (e.g. Method-21, optical gas imaging). Although close-range methods are essential for source identification, they can be labor-intensive. To improve LDAR efficiency, there has been a policy shift in Canada and the United States towards incorporating alternative technologies. However, the suitability of these technologies for LDAR remains unclear. In this paper, we systematically review and compare six technology classes for use in LDAR: handheld instruments, fixed sensors, mobile ground labs (MGLs), unmanned aerial vehicles (UAVs), aircraft, and satellites. These technologies encompass broad spatial and temporal scales of measurement. Minimum detection limits for technology classes range from −1 for Method 21 instruments to 7.1 × 106 g h−1 for the GOSAT satellite, and uncertainties are poorly constrained. To leverage the diverse capabilities of these technologies, we introduce a hybrid screening-confirmation approach to LDAR called a comprehensive monitoring program. Here, a screening technology is used to rapidly tag high-emitting sites to direct close-range source identification. Currently, fixed sensors, MGLs, UAVs, and aircraft could be used as screening technologies, but their performances must be evaluated under a range of environmental and operational conditions to better constrain detection effectiveness. Methane-sensing satellites are improving rapidly and may soon be ready for facility-scale screening. We conclude with a speculative discussion of the future of LDAR, touching on integration, analytics, incentivization, and regulatory pathways.

Dune field reactivation (a shift from vegetated to unvegetated state) has important economic, social, and environmental implications. In some settings reactivation is desired to preserve environmental values, but in arid regions reactivation is typically a form of land degradation. Little is known about reactivation due to a lack of published records, making modeling and prediction difficult. Here we detail dune reactivations from blowout expansion in the Sevier Desert, Utah, USA. We use historical aerial photographs and satellite imagery to track the transition from stable, vegetated dunes to actively migrating sediment in 3 locations. We outline a reactivation sequence: (i) disturbance breaches vegetation and exposes sediment, then (ii) creates a blowout with a deposition apron that (iii) advances downwind with a slipface or as a sand sheet. Most deposition aprons are not colonized by vegetation and are actively migrating. To explore causes we examine local sand flux, climate data, and stream flow. Based on available data the best explanation we can provide is that some combination of anthropogenic disturbance and climate may be responsible for the reactivations. Together, these examples provide a rare glimpse of dune field reactivation from blowouts, revealing the timescales, behaviour, and morphodynamics of devegetating dune fields.

Aeolian dune fields mantle the Earth in both vegetated (stable) and unvegetated (active) states. Changes in state are poorly understood; in particular, little is known about reactivation (devegetation) from a vegetated state. Available evidence indicates that dune reactivation can be driven by changes in aridity, increased wind speed, fire, biogenic disturbance, human disturbance, or a combination of the previous. How these controls fit together and define the reactivation potential of dune fields is presently unknown. Here we develop a framework to describe reactivation potential for a specific case: presently vegetated, supply-limited dune fields that develop blowouts under a unidirectional wind. We first define a conceptual model of blowout expansion, and then split the functions of vegetation in a stable dune field into: (i) maintenance of a protective skin, and (ii) blowout suppression. We model reactivation as disturbance breaking through the protective skin, which forms a blowout that is either (i) suppressed by colonizer species, or (ii) capable of advancing downwind and reactivating part of the dune field. The capacity for disturbance to break through the protective skin is a function of disturbance magnitude, area, and resistance of the skin. The blowout suppression capacity of a dune field is a function of sediment flux, blowout depth (related to geomorphology), and colonizer species vitality. By plotting a given dune field with two variables (protective skin breach rate and blowout suppression capacity) we define four states: (i) stable, (ii) blowout dominated, (iii) reactivating, or (iv) stable but disturbance susceptible. We reinforce the conceptual model with qualitative examples and discussion of experiments on grassland-stabilized dunes in Canada. Overall, our framework provides a starting point for quantifying the reactivation potential of vegetated dune fields.

Aerodynamic roughness ( z 0 ) is a widely used parameter describing the effective roughness of a surface to fluid flow, commonly measured with wind profiling. Wind profiling is time-consuming, equipment intensive, spatially limited, and requires specific wind conditions. To solve this, satellite and airborne remote sensing and ground-based proxies have been developed to measure and relate physical surface roughness to profile-measured aerodynamic roughness. However, for un-vegetated settings, most satellite and airborne remote sensing proxies are, generally, incapable of estimating sub-meter roughness and ground-based measurements are spatially limited and time-consuming. This paper presents a new method for estimating physical roughness using terrestrial laser scanning (TLS) point cloud data. TLS data provide a centimeter-scale, three-dimensional, spatially contiguous representation of a surface. At seven sites with different roughness conditions (silt playa to boulder covered) we compared TLS metrics of surface roughness to wind profile estimates of z 0 . From point clouds, the mean height ( h TLS ) and root-mean squared height ( RMSH ) of roughness elements were calculated. Manual measurements of clast dimensions, height, and density were used to guide point cloud processing. Results indicate a strong positive linear relation between z 0 and h TLS ( r 2 = 0.99, p z 0 and RMSH ( r 2 = 0.96, p z 0 based on empirical relations developed with wind profiling in un-vegetated terrain. With further testing, TLS could improve operational parameterizations of z 0 for use in large scale atmosphere-surface models.

[1] The transport of sand in saltation is driven by the persistently unsteady stresses exerted by turbulent winds. Based on coupled high-frequency observations of wind velocity and sand flux on a desert dune during intermittent saltation, we show here how observations of saltation by natural winds depend significantly on the timescale and method used for determining shear stress and sand flux. The correlation between sand flux and excess shear stress (stress above a threshold value) systematically improves for longer averaging timescale, T, and is better for stress determined by the law-of-the-wall versus the Reynolds stress method. Fitting parameters for the stress-flux relationship do not converge with increasing T, which may be explained by the nonstationary nature of wind velocity statistics. We show how it may be possible, based on the scale-dependent statistics of stress fluctuations, to rescale saltation flux predictions for wind observations made at different timescales. However, our observations indicate hysteresis and time lags in thresholds for initiation and cessation of saltation, which complicate threshold-based approaches to predicting sediment transport at different timescales.

Small unmanned aircraft systems (sUAS) are a relatively new type of aerial platform for acquiring high-resolution remote sensing measurements of Earth surface processes and landforms. However, despite growing application there has been little quantitative assessment of sUAS performance. Here we present results from a field experiment designed to evaluate the accuracy of a photogrammetrically-derived digital terrain model (DTM) developed from imagery acquired with a low-cost digital camera onboard an sUAS. We also show the utility of the high-resolution (0.1 m) sUAS imagery for resolving small-scale biogeomorphic features. The experiment was conducted in an area with active and stabilized aeolian landforms in the southern Canadian Prairies. Images were acquired with a Hawkeye RQ-84Z Areohawk fixed-wing sUAS. A total of 280 images were acquired along 14 flight lines, covering an area of 1.95 km2. The survey was completed in 4.5 h, including GPS surveying, sUAS setup and flight time. Standard image processing and photogrammetric techniques were used to produce a 1 m resolution DTM and a 0.1 m resolution orthorectified image mosaic. The latter revealed previously un-mapped bioturbation features. The vertical accuracy of the DTM was evaluated with 99 Real-Time Kinematic GPS points, while 20 of these points were used to quantify horizontal accuracy. The horizontal root mean squared error (RMSE) of the orthoimage was 0.18 m, while the vertical RMSE of the DTM was 0.29 m, which is equivalent to the RMSE of a bare earth LiDAR DTM for the same site. The combined error from both datasets was used to define a threshold of the minimum elevation difference that could be reliably attributed to erosion or deposition in the seven years separating the sUAS and LiDAR datasets. Overall, our results suggest that sUAS-acquired imagery may provide a low-cost, rapid, and flexible alternative to airborne LiDAR for geomorphological mapping.

Aeolian transport of sand and dust is driven by turbulent winds that fluctuate over a broad range of temporal and spatial scales. However, commonly used aeolian transport models do not explicitly account for such fluctuations, likely contributing to substantial discrepancies between models and measurements. Underlying this problem is the absence of accurate sand flux measurements at the short time scales at which wind speed fluctuates. Here, we draw on extensive field measurements of aeolian saltation to develop a methodology for generating high-frequency (25 Hz) time series of total (vertically-integrated) saltation flux, namely by calibrating high-frequency (HF) particle counts to low-frequency (LF) flux measurements. The methodology follows four steps: (1) fit exponential curves to vertical profiles of saltation flux from LF saltation traps, (2) determine empirical calibration factors through comparison of LF exponential fits to HF number counts over concurrent time intervals, (3) apply these calibration factors to subsamples of the saltation count time series to obtain HF height-specific saltation fluxes, and (4) aggregate the calibrated HF height-specific saltation fluxes into estimates of total saltation fluxes. When coupled to high-frequency measurements of wind velocity, this methodology offers new opportunities for understanding how aeolian saltation dynamics respond to variability in driving winds over time scales from tens of milliseconds to days., 61 pages, 14 main text figures, 4 supporting figures, 2 tables

Changes in surface conditions on cold-climate aeolian dunes are pronounced; during winter dunes are wet, snow covered, and/or frozen for extended periods of time. It is unknown how the critical wind speed for sediment transport (“threshold”) varies and how threshold may influence sediment transport predictions. Although the impact of surface conditions on threshold has been examined in synthetic experiments (wind tunnels), complicated feedbacks between threshold, sand transport, and surface conditions that occur in natural environments suggest that a ground-based empirical approach may provide enhanced insight. In this study we investigate threshold variability for 73 days during fall–winter–spring surface conditions from 18 November 2008 to 30 May 2009 in the Bigstick Sand Hills of Saskatchewan, Canada. Simultaneous measurements of threshold and atmospheric variables (air temperature, relative humidity, solar radiation, wind speed and direction) were used to examine the extent to which surface erodibility was regulated by meteorology. Time‐lapse images of the surface from a co-located camera were used for quality control and interpreting changes in the surface affecting threshold. Results reveal that threshold varied throughout the deployment (25–75% quartiles: 6.92–8.28 m s− 1; mean: 7.79 m s− 1). Threshold variability was especially evident at two scales: (i) event timescale and (ii) seasonal timescale. Event-scale variability peaked during mid-winter; in one event the threshold varied by 6 m s− 1 in 2 h with freezing and re-freezing of the surface and relatively constant atmospheric conditions. The causes of event-scale variability are complex though qualitatively related to changes of wind direction, antecedent meteorological conditions, and vertical variations of grain-scale bonding agents such as pore ice and moisture. Seasonal-scale changes manifested as an increase in threshold during fall, peaking in mid-winter, and decreasing in spring. Increased threshold in mid-winter was linked to lower insolation and air temperature, suggesting low erodibility due to the presence of pore ice. Correlation coefficients of threshold versus atmospheric variables yielded relatively weak correlations (air temperature: r = − 0.322; relative humidity: r = 0.388; solar radiation: r = − 0.309) that also varied according to wind direction, suggesting that the link between atmospheric conditions and surface erodibility on cold‐climate dunes is complex. This contrasts with results from field-based studies in warmer climates and controlled wind tunnel experiments, which show a more direct link between atmospheric variables (temperature and humidity) and surface erodibility. Nevertheless, our results do show a seasonal pattern of threshold that could be important for modeling cold-climate aeolian sediment transport.

The introduction of vegetation to bare barchan dunes can result in a morphological transformation to vegetated parabolic dunes. Models can mimic this planform inversion, but little is known about the specific processes and mechanisms responsible. Here we outline a minimalist, quantitative, and process-based hypothesis to explain the barchan–parabolic transformation. The process is described in terms of variations in the stabilization of wind-parallel cross-sectional dune slices. We hypothesize that stabilization of individual ‘dune slices’ is the predictable result of feedbacks initiated from colonization of vegetation on the slipface, which can only occur when slipface deposition rates are less than the deposition tolerance of vegetation. Under a constant vegetation growth regime the transformation of a barchan dune into a parabolic dune is a geometric response to spanwise gradients in deposition rates. Initial vegetation colonization of barchan horns causes shear between the anchored sides and the advancing centre of the dune, which rotates the planform brinkline angle from concave- to convex-downwind. This reduces slipface deposition rate and allows vegetation to expand inward from the arms to the dune centre. The planform inversion of bare barchans dunes into vegetated parabolic dunes ultimately leads to complete stabilization. Our hypothesis raises several important questions for future study: (i) are parabolic dunes transitional landforms between active and vegetation-stabilized dune states? (ii) should stabilization modelling of parabolic dune fields be treated differently than linear dunes? and (iii) are stabilized parabolic dune fields ‘armoured’ against re-activation? Copyright © 2012 John Wiley & Sons, Ltd.

For more than four decades remote sensing images have been used to document and understand the evolution of aeolian sand dunes. Early studies focused on mapping and classifying dunes. Recent advances in sensor technology and software have allowed investigators to move towards quantitative investigation of dune form evolution and pattern development. These advances have taken place alongside progress in numerical models, which are capable of simulating the multitude of dune patterns observed in nature. The potential to integrate remote sensing (RS), spatial analysis (SA), and modeling to predict the future changes of real-world dune systems is steadily becoming a reality. Here we present a comprehensive review of significant recent advances involving RS and SA. Our objective is to demonstrate the capacity of these technologies to provide new insight on three important research domains: (1) dune activity, (2) dune patterns and hierarchies, and (3) extra-terrestrial dunes. We outline how several recent advances have capitalized on the improved spatial and spectral resolution of RS data, the availability of topographic data, and new SA methods and software. We also discuss some of the key research challenges and opportunities in the application of RS and SA dune field, including: the integration of RS data with field-based measurements of vegetation cover, structure, and aeolian transport rate in order to develop predictive models of dune field activity; expanding the observational evidence of dune form evolution at temporal and spatial scales that can be used to validate and refine simulation models; the development and application of objective and reproducible SA methods for characterizing dune field pattern; and, expanding efforts to quantify three-dimensional topographic changes of dune fields in order to develop improved understanding of spatio-temporal patterns of erosion and deposition. Overall, our review indicates a progressive evolution in the way sand dunes are studied: whereas traditional field studies of airflow and sand transport can clarify event-based process–form interactions, investigators are realizing a synoptic perspective is required to address the response of dune systems to major forcings. The integration and evolution of the technologies discussed in this review are likely to form a foundation for future advances in aeolian study.

Research into aeolian dune form and dynamics has benefited from simple and abstract cellular automata computer models. Many of these models are based upon a seminal framework proposed by Werner (1995). Unfortunately, most versions of this model are not publicly available or are not provided in a format that promotes widespread use. In our view, this hinders progress in linking model simulations to empirical data (and vice versa). To this end, we introduce an accessible, graphical user interface (GUI) version of the Werner model. The novelty of this contribution is that it provides a simple interface and detailed instructions that encourage widespread use and extension of the Werner dune model for research and training purposes. By lowering barriers for researchers to develop and test hypotheses about aeolian dune and dune field patterns, this release addresses recent calls to improve access to earth surface models.

We outline some misconceptions and methodological deficiencies presented in the comparison of four types of aeolian saltation sensors. Specifically, we clarify the sampling area, operation, and response of the sensors and comment on the methodological challenges for field-based sensor comparisons. The goal of this discussion is to clarify some inconsistencies that may influence the selection of one sensor over another in future research. Indirectly, we hope to highlight research needs and improve the reliability of aeolian transport measurements.

Aeolian sediment transport threshold is commonly defined as the minimum wind speed (or shear stress) required for wind-driven sediment transport. Accurate and consistent quantification of this threshold is essential because it is an input variable in models used to predict wind erosion, dune activity, and dust emissions. The majority of threshold quantification has been performed with analogs (analytical models or wind tunnels); however, in the past few decades field-based approaches to threshold parameterization have become more common. Although several methods of calculating transport threshold from field data are available, their comparability is unknown. To address this issue we collected high resolution sediment transport and wind measurements (1 Hz) on an active sand dune for 11 days and compared four different methods of calculating threshold: (i) time fraction equivalence method (TFEM); (ii) Gaussian time fraction equivalence method (GTFEM); (iii) instantaneous method; and (iv) regression method. Time-paired measurements from the two most widely used methods (TFEM and GTFEM) were strongly correlated ( r = 0.977); however, correlations between other methods varied (from r = 0.861 to r = 0.261). To demonstrate the implications of using different threshold calculation methods we predicted mass transport, which ranged from 63.6 (instantaneous method) to 126.6 kg per crosswind meter (regression method). This inconsistency suggests that the threshold calculation method could have an appreciable impact on transport predictions. Threshold values are similarly inconsistent when the measurement interval is modified. As such, we do not recommend comparing any measured threshold with another. We discuss several strategies that may mitigate the impact of this issue such as clarification of semantics and method standardization. We also discuss several criticisms of field-based threshold measurements and re-conceptualizations that could allow investigators to develop a better understanding of field-based measurements. Overall, results from this study could allow future investigators to improve threshold (and transport) predictions.

Progress in some areas of process-based aeolian sediment transport research is hampered by limited opportunities for data comparison, synthesis, and integration. This is partially due to a lack of reliable comparison methods. Many comparison methods are forms of calibration that are either restrictive (e.g., time-averages only) or non-existent (e.g., for field-based sediment transport thresholds or vertical mass flux profiles). It is believed that the adoption of standard methods for common measurements may improve inter-study comparison, add value and longevity to data, and advance integrative modeling efforts. Examples of approaches in allied disciplines where standards are used routinely are reviewed and we discuss how the mutual benefits of standardized data could outweigh perceived disadvantages. Overall, the goal of this commentary is to encourage discussion, self-assessment, and forethought with regard to measurement methods used in process-based aeolian geomorphology. Copyright © 2011 John Wiley & Sons, Ltd.

Piezoelectric sediment transport sensors (PSTSs) are commonly used to detect aeolian sediment transport. Detection of particles in the near-surface airstream can be used to derive measures of sediment transport threshold, which is an important parameter in sediment transport modeling. However, despite common usage, little comparative field data regarding the detection capabilities of PSTSs are available. This study compares the sediment transport detection of four PSTSs: Sensit H11-B, Sensit H11-LIN (10× configuration), Safire, and Sensit H11-LIN (1× configuration). These sensors were co-located on an active sand dune for 11 days with data measured and recorded at 1 Hz. During this period the relative proportion of time that sediment transport occurred was as follows: Sensit H11-B: 7.212%, Sensit H11-LIN 10×: 3.260%, Safire: 1.832% and, Sensit H11-LIN 1×: 0.089%. These relative differences demonstrate that the transport detection capabilities of the sensors are inconsistent. We find that the cylindrical design and variable sensitivities restrict straightforward prediction of field detection according to sensor specifications. From these data we demonstrate that the response of each sensor influences the estimate of sediment transport threshold. Regardless of the source of variability, the very presence of detection inconsistency is problematic. Overall, results from this investigation indicate that comparison of metrics derived from measures of sediment transport presence/absence (such as threshold) with different PSTSs is, at present, tenuous.

On June 29, 2009, version 1 of the ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) was made available at no cost or restrictions to users worldwide via electronic download. The ASTER GDEM provides expanded spatial coverage and better resolution than other global digital elevation models (DEMs). In this paper we demonstrate how the ASTER GDEM provides new opportunities for investigating large aeolian sand dunes in three-dimensions. Two dune-specific spatial analysis methods are presented to illustrate potential applications of these data for discriminating dune generations and quantifying spatial variations of sediment supply. Moreover, we review how existing and emerging fields of dune pattern analysis and simulation modeling will be able to make significant advances through application of these data, potentially leading to future progress in studies of dune morphodynamics, environmental controls, and paleoenvironmental reconstructions. Copyright © 2010 John Wiley & Sons, Ltd.