Variability in precipitation frequency, intensity and duration deeply affect vegetation and erosion yields. Under climate change scenarios, alterations in precipitation are expected but it is not well understood how it could affect erosion rates and what is the role of vegetation on landscape geomorphic response. Traditional erosion models normally include basic representations of vegetation that do not account for the dynamic character of biomass variability and feedbacks with hydrological and erosion/deposition processes. Hence, using a new modelling frameworks that account for the effect of varying vegetation cover on erosion, and that includes climate change scenarios is needed. Here we use a new model: COPLAS, a tool that couples a Landform Evolution Model with dynamic vegetation and carbon pools modules to investigate the response of landscapes to climate change. The vegetation module includes a coupled photosynthesis-stomatal conductance representation that responds to climatic data inputs as temperature, CO2 concentration and water availability. We use the model to simulate the erosional and geomorphic responses of dynamic vegetation in Howard Springs (Australia) to predicted changes in daily precipitation under future CO2 concentrations of about 940 ppm. The model was calibrated using Ozflux site historical data. Catchment scale simulations were run for a period of 100 years for three scenarios (bare soil, constant and dynamic vegetation) using a daily time step. We found that, for our study case, bare soil produces on average 139% more erosion than the constant vegetation case and 124% more than the dynamic vegetation case. Moreover, an increase in precipitation of around 23% induces an increase of 25%, 35% and 43% in the erosion rates for dynamic vegetation, constant vegetation and bare soil respectively, while a decrease in 26% reduces it in 36%, 60% and 59%. This could be explained by the nonlinear relation between erosion and vegetation (higher rainfall induces higher erosion potential which can be counteracted by an increase in vegetation cover leading to a decrease in soil erodibilty). This finding highlights the importance of considering the dynamic character of vegetation in order to understand the nonlinear relations between fluvial erosion and vegetation cover.

It is now known that many spiral density waves in Saturn’s C ring are forced by resonant gravitational interactions with the planet’s nonradial oscillations. Observations of their periods have the power to reveal new information concerning subtle aspects of the planet’s internal structure. The properties of a certain class of nonradial oscillations, consisting of the inertial and rotational normal modes (i-modes and r-modes), are particularly sensitive to small departures of the internal density stratification from adiabatic, and may be especially useful in revealing such departures and their implications for any compositional gradients residing inside Saturn. We calculate the frequencies and eigenfunctions (shapes) of the i-modes and r-modes for a given suite of internal structure models and determine the Lindblad resonance locations and periods of the density waves they excite in the C ring. We find that for reasonable models of Saturn’s internal structure, the i-mode and r-mode frequencies overlap the range of frequencies of the slowest density waves observed in the C ring, that is, those having pattern speeds similar to Saturn’s rotation rate. In addition, the presence of observable density waves forced by r-modes requires Saturn to possess (at least) two statically stable (non-convective) regions, one in the deep interior and the other in the outer molecular hydrogen envelope. The inner zone is most likely stabilized by a significant compositional gradient, the outer zone by a compositional gradient, by baroclinic processes, or both. Unresolved questions remain. Currently, the model predicts that if energy is equipartitioned among the i-modes, then some slow density waves should be detectable at radii inside ~84500 km in the C ring. None have been observed inside this radius. In addition, the source of excitation of the normal modes remains to be identified. We are currently exploring whether they can draw their energy from baroclinic instability in the outer stable zone. These questions will be addressed at length at the meeting. This work is supported by the NASA SSW program.

Potential evapotranspiration (ETp), defined as the amount of water that would be lost by evaporation and transpiration from an area in the absence of water limitation, is an import hydrometeorological variable. Accurate estimation ETp is critical for a wide range of applications including predictions of, irrigation water requirement, groundwater recharge, stream discharge, drought and wildfires. Long-term change in ETp is considered an indicator of the impact of climate change on ecosystem functioning. A wide range of physically-based and empirical models have been developed to estimate ETp. These methods can be explained in terms of their complexity data requirements. The most complex and demanding models (e.g., Penmann-Montheith) require measurements of radiation, temperature, windspeed, and vapor pressure and have been shown to provide very close approximation of physically measured ET from unstressed systems. On the other extreme, the simplest models require only temperature data (e.g., Thornthwaite, 1948) and are the most commonly implemented. However, without site-specific calibration, methods that depend solely on temperature achieve only modest accuracy. Here we present a machine-learning (ML) approaches that utilize hourly and sub-hourly temperature records to produce predictions that are comparable with the more complex methods that require full meteorological datasets. Specifically, we show that ML algorithms can learn the patterns of temperature fluctuations that are related to attenuation of potential solar radiation. We anticipate the approach developed here will be valuable for estimation of historical ETp as well as for short-term forecasting using temperature forecasts.

Up to now, almost all of the ground motion modeling and hazard assessment for induced seismicity in Groningen, the Netherlands, has been focused on the horizontal components of earthquake waves. Including the vertical component in site response studies is hardly being done for low magnitude earthquakes. Since the top part of the soils in the Netherlands is practically always unconsolidated, the elastic waves generated by deeper (~3000m) seated earthquakes will be subject to transformation when arriving in these layers. Recordings over a range of depth levels in a borehole show most of the amplification in the upper 50 meters of the sedimentary cover. We observe not only a strong amplification from shear waves on the horizontal components, but also from longitudinal waves on the vertical component. Furthermore, the seismic velocities show a large lateral heterogeneity. A better understanding of the vertical component of low magnitude earthquakes (to date, max M=3.6 in Groningen) aims to support the design of re-enforcement measures for buildings in areas affected by induced seismicity. This study focuses on longitudinal wave amplification in a sedimentary basin setting.Generally, the vertical component of ground motion is less than the horizontal, but the longitudinal waves are concentrated in a high frequency band which can cause damage to buildings with vertical periods in this range. Furthermore, interference between the longitudinal and shear waves might contribute to extra damage on structures. In Groningen, a dense borehole network is continuously recording seismic activity. From 19 seismic events with a minimum of magnitude two, transfer functions are retrieved between geophones at 50m depth and accelerometers at the surface, for 70 borehole sites. Peak frequencies and amplitudes derived from the transfer functions, do show significant variability across the region. Highest longitudinal wave amplification is measured in the center of the field, which is also the epicenter of most seismic activity. We investigate if the variations in amplification can be linked to the local geology. Additionally, the possibility and consequences of interference between the shear and longitudinal waves are presented.

The 7.7 ka Cleetwood (Cltwd) eruption of Mount Mazama (Crater Lake, Oregon, USA) began with a Plinian phase emitting 0.5 km3 DRE of rhyodacitic pyroclastic fall material. Explosive activity then transitioned to an effusive stage, with no apparent break, extruding a 0.6 km3 obsidian lava flow. As opposed to other rhyolitic eruptions that exhibit the same sequence of events, the Cltwd eruption ultimately led to the climactic caldera-forming eruption of Mount Mazama. Thermal constraints on both the Cltwd flow backflowing into the caldera and the alteration of climactic pumice deposited directly on the Cltwd flow suggest that the Cltwd eruption preceded the caldera-forming eruption of Crater Lake by a period of only weeks to months. Furthermore, both eruptions produced chemically indistinguishable juvenile material inferring the tapping of the same magmatic source. By analyzing changes in particle size, shape, texture, porosity, and componentry that occur stratigraphically throughout the products of the Cltwd eruption, this study aims to link the shifts in eruption dynamics that occurred during this eruption with the initiation of the subsequent caldera-forming eruption. Preliminary results on the stratigraphy of proximal and medial deposits reveal four major eruptive stages: S1) initiation and initial vent clearing, S2) a sequence of maximum eruption intensity, S3) a pause in eruption followed by the last explosive pulse and S4) the effusion of the Cltwd flow and conduit sealing. Materials composing S1 are homogenous with a brief increased abundance in both banded pumice and obsidian pyroclasts. The layers that define S2 exhibit strong normal grading with tephra at its maximum size. S3 marks the end of the explosive phase with a layer of reverse grading and an increase in lithics, banded pumice, and obsidian pyroclasts. Detailed grain size distributions, componentry and textural analyses are currently being carried out for each stage of the eruption to better constrain and quantify any processes such as changes in conduit size, magma degassing, fragmentation depth, etc., which may cause or reflect a change in magma flow in the conduit and therefore, a shift in the type of activity.

The Dynamic Network Experiment 2018 (DNE18) was a virtual experiment designed to quantitatively assess current capabilities for multi-modal data ingestion and processing for nuclear explosion monitoring at the local/regional scale. This assessment will allow us to identify and prioritize remaining challenges that need to be met to achieve desired monitoring capabilities. The experiment was a collaborative effort between Los Alamos National Laboratory, Lawrence Livermore National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories. We describe efforts to test various velocity models for any bias or other recognizable patterns using two-week, analyst-built event (ABE) bulletin. The data set includes over 6000 events manually-built by the analyst using the Utah Seismic Network which includes about 182 seismo-acoustic stations, 152 of which have analyst arrival picks. There are active mines in the state of Utah, many of which are associated with clusters of events. The ABEs include mostly Pg and Lg arrivals for events within Utah and some just outside the state. Global events were also picked that included teleseismic P and S as well as core phases, etc. although these are not included in this study. We test local, regional, and global P and S velocity models (1-D, 2-D, 3-D) for their effect on the event locations, paying attention to overall epicenter shifts, residual reduction, and error ellipses. Many of the event clusters are good candidates for application of relative relocation techniques.

Two major sources of radiation hazards at commercial aviation altitudes have been known for decades and those are galactic cosmic rays (GCRs) as well as solar energetic particles (SEPs). GCRs are produced outside the solar system in high-energy explosive events and consist mostly of energetic protons slowly modulated by the strength of the Sun’s interplanetary magnetic field (IMF). SEPs come from either solar coronal mass ejections (CMEs) related to flaring events or from IMF shocks. In the latter case fast CMEs plow through a slower solar wind creating a shock front to produce energetic protons. Recently, a third radiation source has been identified that originates from relativistic electron precipitation (REP) associated with the Van Allen radiation belts and have been called radiation clouds although a physical perspective is likely to be flight through a γ-ray beam. This ensemble radiation field creates safety concerns for aviation. Because of this safety hazard, a broad community is seeking to i)define the requirements for real-time monitoring of the charged particle radiation environment to protect the health and safety of crew and passengers during space weather events; ii)define the scope and requirements for a real-time reporting system that conveys situational awareness of the radiation environment to orbital, suborbital, and commercial aviation users during space weather events; and iii)develop or improve models for the real-time assessment of radiation levels at commercial flight altitudes. While benchmarks for ionizing radiation related to aviation have included characterizing an occurrence frequency of 1 in 100 years and an intensity level at the theoretical maximum for radiation events, it is also important to develop a baseline radiation environment for GCRs, SEPs, and REPs against which events can be compared. We describe functional, analytical baselines for describing the ionizing radiation environment for commercial aviation based on observations and modeling as part of the NAIRAS, ARMAS, and RADIAN programs.

The study focuses on the estimation and modeling of the temporal rates of major explosions and paroxysms at Stromboli volcano (also named small-scale and large-scale paroxysms respectively). The analysis was further motivated by the paroxysm of July 3rd 2019, which raised, once again, the attention of the scientific community and civil protection authorities on the volcanic hazards of Stromboli. In fact, at the present state of knowledge, major explosions and paroxysms cannot be forecasted based on monitoring data, and a full probabilistic assessment based on past eruption data would be quite useful for scientific and civil protection purposes. In the study we perform a time series analysis either considering the last ~150 years of reconstructed activity and the most recent 35 years. We included the estimation of event rates and rate changes in time. Results clearly highlight that the activity is non-homogeneus in time, with a significant low of activity between about 1960 and 1990. Maximum values of event rates were computed during the first half of last century, for both major explosions and paroxysms, whereas the rate of paroxysms is significantly lower in the last decades with respect to maximum rates. We also accomplish a statistical analysis of the inter-event times, enabling us to determine if the data can be modeled as a Poisson process or not, e.g. if it shows time dependent distributions, recurring cycles, or temporal clusters. The uncertainty quantification on the current and future rates is mainly related to the choice of the modeling assumptions. The study represents a crucial progress towards quantitative hazard and risk assessments at Stromboli, which is particularly relevant for the thousands of people (e.g. tourists, guides and volcanologists) that regularly climb the volcano every year.

We present two models using monitoring data in the production of volcanic eruption forecasts. The first model enhances the well-established failure forecast method introducing an SDE in its formulation. In particular, we developed new method for performing short-term eruption timing probability forecasts, when the eruption onset is well represented by a model of a significant rupture of materials. The method enhances the well-known failure forecast method equation. We allow random excursions from the classical solutions. This provides probabilistic forecasts instead of deterministic predictions, giving the user critical insight into a range of failure or eruption dates. Using the new method, we describe an assessment of failure time on present-day unrest signals at Campi Flegrei caldera (Italy) using either seismic count and ground deformation data. The new formulation enables the estimation on decade-long time windows of data, locally including the effects of variable dynamics. The second model establishes a simple method to update prior vent opening spatial maps. The prior reproduces the two-dimensional distribution of past vent distribution with a Gaussian Field. The likelihood relies on a one-dimensional variable characterizing the chance of material failure locally, based, for instance, on the horizontal ground deformation. In other terms, we introduce a new framework for performing short-term eruption spatial forecasts by assimilating monitoring signals into a prior (“background”) vent opening map. To describe the new approach, first we summarize the uncertainty affecting a vent opening map pdf of Campi Flegrei by defining an appropriate Gaussian random field that replicates it. Then we define a new interpolation method based on multiple points of central symmetry, and we apply it on discrete GPS data. Finally, we describe an application of the Bayes’ theorem that combines the prior vent opening map and the data-based likelihood product-wise. We provide examples based on either seismic count and interpolated ground deformation data collected in the Campi Flegrei volcanic area.

Over time, I have worked on a suite of data infrastructure projects, ranging from small to large and simple to complex. Some have been successful, others less so, and a couple are so notorious they are generally not mentioned in polite company. Sometimes the outcome was predictable—well-organized and well-managed projects are likely to succeed, and those with clear flaws often don’t rise above them—but sometimes it was unexpected. Building effective data infrastructure is not a solved problem, it is an area of research in and of itself, and the larger the project, the more difficult and uncertain it is. For each of my current and past projects, I consider their greatest strength, their showcase best practice, their weaknesses, and their epic fails, as well as the external and internal factors that contributed to positive or negative outcomes. Despite the heterogeneity, certain patterns emerge as lessons learned: Listening to your users is critical, and there are no short-cuts; it requires a long-term investment, including cultivating individual relationships. Good is better than more; hardening infrastructure is time consuming but critical for adoption. Have a clear mission with concrete benefits to a defined user community, and expand thoughtfully from there. In spite of our best intentions, meeting emerging community expectations usually requires a catalyst. External groups identifying best practices, mini-grants for implementation, and multi-project groups collaborating to rise together give needed nudges. Interestingly, I have never been involved with a project that failed because it picked the wrong technology. It can cause pain and consume resources, but I have not seen a terminal impact. Finally, invest in the people behind the infrastructure. Committed, engaged staff supported by ongoing professional development, rational management, and sufficient autonomy can, and regularly do, accomplish the impossible.

Increased space-time resolution of hydrologic information in combination with better understanding of hydrologic processes allowed evolution of rainfall-runoff modeling from lumped mode to distributed mode. Relatively, lumped modeling is simple, less data intensive and use less computing resources; typically, semi-distributed modeling falls between lumped- and distributed modeling on a scale of various parameters including modeling complexity, data and computing resources. To understand the influence modeling complexity and hydrologic information on performance of hydrologic models in monsoon driven river basins, we performed a hydrological study on Sabari River Basin, from a tributary of Godavari river basin, delineated at three different spatial scales. Then, The Hydrologic Engineering Center- Hydrologic Modeling System (HEC-HMS) model driven in both event- and continuous modes in lumped and semi-distributed modes. The model calibrated and then validated using various verification metrics. Analysis of verification metrics provided insights on different aspects of flood forecasting

Global Positioning System (GPS) measurements reveal rapid incoherent crustal motions at various points in the longitudinal valley along the eastern coast of Taiwan, exhibiting a strong effect of the collision between the Philippine sea plate and the Eurasian plate. Dynamic Time Warping (DTW) can identify the subtle crustal motion patterns by comparing two GPS position daily fluctuations (non-tidal, non-seasonal and non-CME). We applied a nonparametric, hierarchical agglomerative clustering algorithm based on the DTW for 27 three-component, GPS daily fluctuations from 2007 to 2018 near the eastern coast of Taiwan. Agglomerative Clustering algorithm categorized the east coast tectonics of Taiwan into 3 geographical clusters based on pairwise DTW distance metrics - on the Chengkung Fault (related to 2003 Mw6.8 Chengkung Earthquake), inside Longitudinal Valley, others. Principal Component Analysis on the clustered three-component time series delineates their group movement patterns.

The question of the reliability of GPS measurement as an index for intraplate seismicity is raised here. Geodetic measurement of slip rate along the Longmenshan Fault -a thrust structure that straddles the border of the Indo-Australian Plate and Eurasian Plate produced 􀂦gures as low as 3mm/year, despite this low return, the magnitude 7.9 Wenchuan earthquake occurred along this fault. Similar pattern was discovered in both the New Madrid, South Carolina and Wabash seismic zones, where geodetic derived strain rates of less than 2mm/yr fail to account for the recurrence of magnitude 7 earthquakes every 500 years. Other intraplate settings like Europe, Australia, South Africa showed similar results, hence leading us to question how reliable a tool geodetic measurement is in predicting the likelihood of earthquakes occurring in the future. I conclude that seismic hazard assessment of intraplate earthquakes based solely on geodetic strain rate measurement and the location of occurrence of past (historic) earthquakes is spatially limited and could be misleading, this is because where strain release occurred (as past earthquakes) does not necessarily have to be the exact location where strain accrual for future earthquakes take place, as evidenced by the inability of the GPS strain rate to resolve seismic moment release in all of the seismic zones in Central-Eastern United States . Strain release in the future might occur on a distant unidentified fault through transient stress perturbation -one that might have been erroneously classified as ‘safe’ based on near-zero strain rate picked up by today‘s GPS measurements.

Slow-Slip Events (SSEs) haven been observed along the Hikurangi subduction zone of the North Island of New-Zealand. They occur both in the shallow plate interface (<15km depth) and at the deeper end of the seismogenic-zone (>30km depth). Some slow slip events in New-Zealand are also accompanied by tectonic tremors, although tremor is not as common at the Hikurangi subduction zone compared to other subduction zones. We present a systematically generated catalog of low-frequency earthquakes (LFEs) for the central Hikurangi margin. To detect preliminary LFEs from the continuous seismic data we used a Matched-Filter technique with template waveforms from the tectonic tremor catalog of Romanet & Ide [2019]. The resulting detections were gathered as families and an innovative stacking technique was used to extract high-quality waveforms in order to build a set of LFE templates for a second Matched-Filter search. From these second generation detections, we developed a methodology to continuously scan the entire dataset for coherent impulsive waveforms similar to LFE that occuring on the subducting plate interface. The LFEs are organized into episodes of intense activity during deep M7 SSEs that occur absit every 5 years beneath the Manawatu region. One of our LFE bursts occurs during a small, deep SSE recognized at the central Hikurangi margin in 2008 (Wallace and Eberhart-Phillips, 2013). We expect that the other LFE episodes highlight small slow transients that have not yet been geodetically observed. In this presentation, we discuss the spatiotemporal evolution of LFEs in regard to potential aseismic transients that can be observed in the GPS data-set acquired by GeoNet.

The current technology used by the Extratropical Surge and Tide Operational Forecast System (ESTOFS) on the East of the US and Gulf of Mexico coasts uses a sub-optimal unstructured grid, that over-resolves some straight portions of the coastline, under-resolves complex estuaries and coastal features, and employs roughly uniform resolution depending on the different water depths. The ESTOFS model is very efficient in terms of computational run time because it was designed for operational use, but accuracy is sub-optimal as the details of the complex inland water bodies is not captured with the 200 m minimum mesh resolution. ADCIRC is a robust high-fidelity depth-integrated model, widely used for the coastal community, including ESTOFS, for tides, storm surge, and wave-induced coastal setup. ADCIRC is a continuous-Galerkin based finite element unstructured grid framework that allows using meshes with a heterogeneous resolution to better represent the complexity of the ocean, shelf and nearshore regions. Recent advances on mesh generation tools now allow generating replicable high-resolution grids in times much shorter than the hand-edited processes used to develop the current version of ESTOFS. This opens the opportunity to study the effect of the different resolutions to represent topo-bathymetric and far inland water body features, in order to reduce the computational cost and improve the accuracy of the models. Thus, the objective of this research is to develop an ADCIRC-based model to accurately and efficiently simulate the dynamics of the ocean and riverine system in the Atlantic coast of the US and Gulf of Mexico for tide/storm predictions. The new ADCIRC-based model will incorporate a representation of the riverine system far up to the point where the ocean has no effect on water levels, efficiently use the resolution to reduce the minimum grid-size from 250 m to 50 m, with no significant increase in the number of nodes, and will combine pseudo-quadrilateral elements to efficiently represent narrow channels. This new generation of ESTOFS will represent a significant enhancement of the current technology for tides and storm surge prediction, but also will set up the required conditions for future approaches focused on coupling inland hydrology to the coastal modeling.

Excess nutrient loading to downstream waters has been a persistent environmental concern, especially in agricultural settings. Drainage water management (DWM) is a best management practice intended to reduce nitrogen export from fertilized lands by increasing groundwater levels, slowing the loss of nutrient-rich water and increasing its time in contact with the soil, thus creating greater opportunity for denitrification. This BMP has shown to be effective at reducing dissolved nitrate (TDN) export, but a question remains about potential unintended pollution swapping. The concern is that denitrification could result in nitrous oxide (N2O) emissions and that higher soil moisture could also create suitable conditions for methanogenesis and methane (CH4) emissions. Here we report on two years of monthly static soil gas chamber fluxes and hydrologic nutrient fluxes during a full corn/soybean rotation cycle on the Eastern Shore of Maryland. For N2O, there were significant interactions between season, crop type, and treatment, such as higher fluxes during the fertilization period in the corn year in the DWM treatment, which was consistent with our concern about pollution swapping. However, this brief additional pulse of N2O did not result in a statistically significant increase at an annual scale, nor was there an increase in annual CH4 emissions. At the same time, annual TDN load was significantly lower in the DWM ditches compared to the control. With no significant treatment effect on soil gas fluxes and a significant treatment effect on TDN export, we conclude that pollution swapping of nitrate reduction for greenhouse gases did not occur significantly in this application of DWM to a corn/soybean system. We did, however, find evidence of pollution swapping of phosphorus and nitrogen, as total phosphorus load was higher in the DWM. With more water in the field, the reduced conditions appear to cause a release of soil bound phosphorus. While greenhouse gas production may not be as much of a concern, increased phosphorus export represents a form of pollution swapping that must be accounted for in determining the value of this BMP.

Planetary scientists can face challenges in effectively interacting with audiences. To help address their needs, the Lunar and Planetary Institute (LPI) conducts professional development for planetary scientists through seminars and workshops. LPI also enables scientists to participate in public events, and connects them to requests for speakers. LPI’s Sharing Planetary Science seminars include current educational research and incorporate the participants’ own knowledge and experiences in engaging public audiences. Participants attend in-person or online. Post-session surveys indicate that all participants (100%) have found at least one aspect of each seminar valuable. Resulting resources are available online. www.lpi.usra.edu/education/scientist-engagement. In March 2019, working with the Volatiles, Regolith and Thermal Investigations Consortium for Exploration and Science (VORTICES) program, LPI conducted the first Planetary Scientist Engagement Institute. This 2-day training was attended by 23 planetary scientists from across the U.S. who learned about audience needs, common solar system misconceptions, resources for engaging audiences, addressing controversial topics, partnering to reach diverse audiences, and more. In the follow-up evaluation, all (100%) of participants found that the program met their goals and was useful. LPI has conducted a variety of scientist engagement activities at conferences, including sessions and workshops on communicating with audiences, using social media to share their science, and communicating with news media. All have proven popular. LPI hosts a variety of public events, and enables planetary scientists to participate as speakers and as activity facilitators. LPI connects scientists with requests for presentations, both locally and virtually. Future plans include developing a mechanism for evaluating the process and the perceived impact by the scientists. This poster will include further details of these professional development sessions, their resulting resources, the evaluations, and future plans.

Vehicle-based methane-sensing systems are gaining popularity as tools for monitoring site-level methane emissions from oil and gas (O&G) sites. To measure emissions, vehicles equipped with methane sensors intersect plumes along roads downwind of target sites and acquire measurements in static (parked) or mobile modes. The downwind distance between the emissions source and the measurement location is one of several factors that must be considered in planning these types of surveys. Here we present a method to estimate the suitability of O&G facilities for vehicle-based measurements using downwind distances recommended in OTM 33A and the tracer technique. We present two types of analyses: (1) a historical analysis using weather reanalysis data and (2) an operational analysis using forecast data. The method uses modeled wind direction and geospatial data to identify O&G facilities that have roads between 20 and 200 m downwind for OTM 33A and between 500 m and 3000 m downwind for the tracer technique. We apply the method to O&G facilities in Alberta that will soon require annual or triannual LDAR surveys. For the historical analysis we use ERA-Interim wind data and calculate the vectorial average (resultant) of modeled winds for the period 2009-2018. Of the 35047 O&G facilities examined, we find that 7% are, on average, suitable for OTM 33A and 69% are, on average, suitable for the tracer technique, based solely on downwind distance. We surmise that other factors like landcover, weather conditions (e.g., stability), and topography would likely reduce the candidate pool from these estimates. We demonstrate the operational utility of the method by examining a subset of 100 O&G facilities in southern Alberta and using forecast wind direction from the Canadian High Resolution Deterministic Prediction System (HRDPS), which has a 2.5 km grid spacing. We propose that the method can be used as a screening tool to estimate site suitability for static vehicle-based surveys and that it will likely translate to mobile surveys once the effect of downwind distance is clarified. Other factors can be incorporated in the method once test results are available.