International Observe the Moon Night is an annual worldwide public event that encourages observation, appreciation, and understanding of our Moon and its connection to NASA planetary science and exploration. Everyone on Earth is invited to join the celebration by hosting a public or private event or attending an International Observe the Moon event – and uniting on one day each year to look at and learn about the Moon together. October 5, 2019 marks the 10th annual worldwide celebration of the Moon. Since 2010, an estimated 1.4 million people from across the globe have participated in International Observe the Moon Night events at museums/science centers, libraries, planetaria, observatories, K-12 schools, universities, public parks, community centers, private residences and businesses. Event hosts along with their partners help support and achieve global participation in International Observe the Moon Night. Between 2010 and 2018, a total of 5,551 events were registered worldwide. Over the last nine years, International Observe the Moon Night events have taken place in 107 different countries. Results of the evaluation of International Observe the Moon Night shows that the events continue to be successful in raising visitors’ awareness of lunar science and exploration, providing audiences with information about lunar science and exploration – along with access to lunar mission data and science results, inspiring visitors to want to learn more about the Moon, and providing connections to opportunities to do so. Each year, formative evaluation is used to make recommendations to the International Observe the Moon Night coordinating committee to make iterative changes for the next year. Worldwide evaluation data collection has included registration data, host surveys, visitor surveys, and social media data. The evaluation has been revised over the past ten years based on evolving program goals and resources available. Data collection has also included visitor interviews, observations, and alternative data collection strategies. We will discuss the challenges and successes of different evaluation strategies in evaluating the success of this program. Additionally, we will discuss the challenges and lessons learned in evaluating a large science outreach program that spans across so many countries and sites.

The Maldives archipelago acts for over 25 myrs as a giant natural sediment trap in the eastern Arabian Sea. Drifts and periplatform deposits bear the record of environmental changes such as sea-level fluctuations but also of monsoon-driven changes of the surface and intermediate water mass current regime, and of wind-driven dust influx. Carbonate drifts in the Inner Sea indicate the establishment of a strong wind-driven current regime in the Maldives at 12.9 – 13 Ma. Ten unconformities, dissecting the Miocene to Recent drift sequences, attest to changes in current strength or direction. A major shift in the drift packages is dated at 3.8 Ma that coincides with the end of stepwise platform drowning and a reduction of the OMZ in the Inner Sea. The lithogenic fraction of the Maldives carbonate drifts provides a unique record of atmospheric dust transport during the past 4 myrs as grain size provides proxies for dust flux as well as wind transport capacity. Entrainment and long-range transport of dust in the medium to coarse silt size range is linked to the strength of the Arabian Shamal winds and the occurrence of convective storms which prolong dust transport. Dust flux and the size of dust particles increased between 4.0 and 3.3 Ma, corresponding to the closure of the Indonesian seaway and the intensification of the South Asian Monsoon. Between 1.6 Ma and the Recent, dust flux again increased and shows higher variability, especially during the last 500 kyr. Transport capacity increased between 1.2 and 0.5 Ma but slightly decreased since then. Dust transport varies on orbital timescales, with eccentricity control being the most prominent (400 kyr throughout the record, 100 kyr between 2.0 and 1.3 Ma, and since 1.0 Ma). Higher frequency cycles (obliquity and precession) are most pronounced in wind transport capacity. The published and ongoing studies of IODP Expedition 359 cores show that deposits surrounding carbonate platforms, i.e. carbonate drifts, bear a previously underestimated potential to add substantial knowledge for the understanding of the monsoon evolution on million-year, but also on shorter time scales. Potential targets for further research and drilling are for example the Laccadives, the Mascarene Plateau or the South China Sea platforms.

The earliest human migration from Sunda (South-East Asian archipelago) to Sahul (Australia and New Guinea) is still heavily debated with proposed timings between c.65-45kaBP depending on the evidence base and interpretation of the data. As part of the EU funded ACROSS project, focused on the mode and route of early migration in to SAHUL, we are undertaking an integrated interpretative study of the evolving submerged landscapes for the Late Pleistocene of the NW Australian Shelf. Oil and gas industry 3D and 2D seismic data, with some core/borehole data, are being used to determine lowstand palaeo-environments and shoreline positions. This information is informing modelling of ocean tide and current patterns that may have been influenced. The seismic is being interpreted supplemented by using time-slices on relative impedance inverted post-stack data. Layer stripping, seismic geomorphology, sequence boundary and depth analysis are being applied to datasets in the Bonaparte Basin, Kimberley Shelf and Arafura regions of Australia’s North-West Shelf area. Interpretation of the seismic data is constrained by dated stratigraphy in shallow cores with lower bounds determined from oil/gas well bores. MIS stages 1-4 are identified, however, the seismic response is a composite of time periods due to varying sedimentation rates, non-depositional hiatuses and minimal vertical seismic travel time covering this interval which limits the analysis to the top 50ms TWT (c. 40-45 m) of events below the seabed. This paper reviews the workflows that have been developed to maximise the fine scale detail that can be recovered for a range of terrestrial and marine environments. Procedures include inverse-Q, impedance inversion, spectral decomposition and time-slicing relative to seabed. High resolution 2D seismic data is also being used to augment and inform the interpretation of the conventional oil/gas 3D seismic data. Data examples will be presented showing the geomorphological characteristics (river channels, avulsions, levees, drainage channels, dunes and near shore carbonate reefs) of the lowstand and transgressive landscapes during this period. The palaeo-reconstructions are now being developed from the interpreted seismic geomorphology for the specific consideration of human seaborne travel.

The development of semi-distributed hydrological models that reflect the dominant processes controlling streamflow spatial variability is a challenging task. In small, well-instrumented headwater catchments the model can be built taking advantage of knowledge derived from extensive fieldwork activities; that is, however, not possible in much larger catchments where, usually, these models are actually needed. To address this problem, we propose a new methodology where we analyze the correlations between hydrological signatures, catchments characteristics, and climatic indices to get insights about the hydrological functioning of the catchment and to guide the decisions involved in the development of a semi-distributed model. The methodology is tested in the Thur catchment (Switzerland, 1702 km2); in a first stage we show how to identify catchment characteristics and climatic indices that control streamflow variability; in a second stage, we use these findings to develop a set of model experiments aimed at determining an appropriate model representation for the catchment. Results show that only models that account for the influencing factors indicated by the correlation analysis are able to represent correctly the observed streamflow signatures, confirming our understanding of the processes happening in the catchment.

In this study, we improve estimates of groundwater usage across the Mississippi Alluvial Plain (MAP) in support of an ongoing USGS effort to model the groundwater resources of the region. Previously, the USGS developed a lookup table based on flowmeter data that estimates water use based on average water use for each crop type, for specific regions and precipitation amounts. The latest iteration of this model is known as Aquaculture and Irrigation Water-Use Model (AIWUM) 1.1 and we refer to our method as AIWUM 2.0. Here, we apply gradient boosted trees (GBT) to predict groundwater use across the MAP from 2014-2019. The predictor variables include well locations (latitude and longitude), crop type, precipitation, maximum temperature (the average daily maximum from April - September), total evapotranspiration estimated with MOD16, and surface run-off (TerraClimate). The existing flowmeter data over the Mississippi Delta were randomly split into training (80%) and validation (20%) data. The following parameters in the GBT algorithm were tuned: the number of estimators, learning rate, maximum tree depth, the objective function, and the percentage of training data that are randomly sampled in the training process. We observe very low model overfitting where the training error metrics are R2 = 0.58, mean absolute error (MAE) = 0.30 ft, and root mean square error (RMSE) = 0.51 ft, respectively, and the corresponding test metrics are R2 = 0.49, MAE = 0.32 ft, and RMSE = 0.51 ft. This is an improvement over AIWUM 1.1, where the corresponding R2, MAE, and RMSE were 0.27, 0.40 ft, and 0.67 ft. These water use estimates will result in an improved ability to accurately model groundwater flow in this aquifer, which accounts for roughly 20% of the total groundwater pumping in the United States.

In this work, we develop a data-driven subgrid-scale (SGS) model using a fully convolutional neural network (CNN) for large eddy simulation of forced 2D turbulence. Forced 2D turbulence is a fitting prototype for many large-scale geophysical and environmental flows (where rotation and/or stratification dominate) and has been widely used as a testbed for novel techniques, including machine-learning-based SGS modeling. We first conduct direct numerical simulation (DNS) and obtain training, validation, and testing data sets by applying a Gaussian spatial filter to the DNS solution. With the filtered DNS (FDNS) data in hand, we train the CNN with the filtered state variables. A priori analysis shows that the CNN-predicted SGS term accurately captures the inter-scale energy transfer. A posteriori analysis indicates that the LES-CNN outperforms the physics-based models in both short-term prediction and long-term statistics. Although the CNN-based model is promising in predicting the SGS term, it requires big data to perform satisfactorily. In the small-data limit, the LES-CNN generates artificial instabilities and thus leads to unphysical results. We propose three remedies for the CNN to work in the small-data limit, i.e., data augmentation and group convolution neural network (GCNN), leveraging the rotational equivariance of the SGS term and incorporating a physical constraint on the SGS enstrophy transfer. The SGS term is both translational and rotational equivariant in a square periodic flow field. While primitive CNN can capture the translational equivariance, the rotational equivariance can be accounted for by either including rotated snapshots in the training data set or by a GCNN that enforces rotational equivariance as a hard constraint. Additionally, The SGS enstrophy transfer constraint can be implemented in the loss function of the CNN. A priori and a posteriori analyses show that the CNN/GCNN with knowledge/constraints of rotational equivariance and SGS enstrophy transfer enhances the SGS model and allows the data-driven model to work stably and accurately in a small-data limit. These findings can potentially help the ongoing efforts in using machine-learning for SGS modeling in weather/climate models, where high-quality training data are scarce and instabilities have been reported in many past studies.

The development of thermodynamic modeling techniques and availability of updated thermodynamic databases and activity-composition (a-X) relations, call for an evaluation of modeling pressure-temperature (P-T) paths of metabasites. In this study, eclogite from the Tso Morari UHP terrane, NW India, is used as a representative metabasite to compare P-T paths generated from the widely used THERMOCALC (TC) and Theriak-Domino (TD) programs. We also evaluate the effect of using the most updated thermodynamic database ds 62 (Holland and Powell 2011) relative to an older version ds 55 (Holland and Powell 1998), and the most updated garnet a-X relations of White et al. (2014) (W14) relative to an older version of White et al. (2007) (W07), while accounting for the effect of garnet fractionation. The following modeling protocols were assessed: (1) TC33: TC v3.33 with ds 55 and garnet a-X relations of W07; (2) TC47: TC v3.47 with ds 62 and garnet of W14; (3) TDG: TD with ds 62 and garnet of W14, and (4) TDW: TD with ds 62 and garnet of W07. TC47 and TDG modeling protocols yield a similar peak metamorphic P-T of 34 ± 1.5 kbar at 544 ± 15 °C and 551 ± 12 °C, respectively; while TC33 and TDW modeling yield similar peak P-T results: 26 ± 1 kbar at 565 ± 8 °C and 28.5 ± 1.5 kbar at 563 ± 13 °C, respectively. Results indicate that all four modeling protocols generally provide consistent thermodynamic simulations regarding metamorphic compositional and temperature evolution; however, the pressure generated by protocols using W14 (TC47 and TDG) is 5–8 kbar higher than that predicted by protocols using W07 (TC33 and TDW). The difference in peak pressure results for the modeling protocols (TC47 and TDG vs. TC33 and TDW) are beyond the suggested uncertainty using mineral isopleth thermobarometry in pseudosections: ± 50 °C and ± 1 kbar at 2σ (Powell and Holland 2008). This study illustrates that the choice of garnet a-X relations can affect predictions of peak pressure regardless of program choice, as well as the need of comparison between modeling predictions and petrological observations.

Effusive and explosive eruptions often occur from the same volcano, yet the reasons behind such a wide ranging eruptive behaviour remain poorly understood. Here we explore the role of various physical parameters focusing on the explosive-effusive-explosive basaltic andesite eruptions of Kelud volcano, Indonesia in 1990, 2007, and 2014, respectively. Through phase equilibria experiments, we find the magma storage conditions feeding explosive and effusive eruptions are broadly similar at 975 +/- 39 Celsius, 175 +/- 25 MPa, and 4-6 wt. % water in the melt. We also estimated magma ascent rates from halogen diffusion profiles in zoned apatite, and found that ascent rates of the 2007 dome (0.003-0.05 m/s) are at least one order of magnitude slower than those recorded by apatite from 1990 and 2014 explosive eruptions (more than 0.1 m/s). Comparison of the atmospheric sulfur dioxide mass released during the explosive eruptions with that dissolved in the melt shows that explosive eruptions accumulated an excess fluid phase prior to eruption of up to 0.1 Mt sulfur dioxide, whereas such fluid accumulation was not associated with the 2007 effusive eruption, given that the system was much more open during its inter-eruptive repose. The calculated viscosity and magma ascent rates also overlap with independent constraints from magma discharge rates for these same eruptions. We propose that the presence of an excess fluid phase played a critical role in controlling the observed eruption style. Implications of our findings indicate that the presence of an excess fluid phase should be taken into account when modelling eruptive processes, and parameters associated with fluid accumulation and degassing could be monitored for signs of unrest before explosive events.

Thermal stratification can lead to the damping of turbulence, which reduces the mixing of solutes in a fluid body, and in turn, affects river health. A series of Direct Numerical Simulation (DNS) solutions sweeping through a range of four different channel radius of curvature is obtained to investigate the effect of curvature on stratification in meandering thermally stratified turbulent open channel flow. This range of radius of curvature will cover a range of the curvature parameter 0.2 < γ <1.5, which is typical of rivers in the sharp to mild curvature range. Here γ = C_f^-{1} (H/R_{min} is a dominant control parameter with respect to velocity redistribution in curved open-channel flow, where C_f is the Chezy friction coefficient, R_{min} the minimum radius of curvature, which occurs at the meander apex, H the meander height. An internal heat source models radiative heating from above following an exponential Beer’s law profile, which varies with height due to progressive absorption. Based on the DNS results, the present paper addresses two issues. Firstly, the influence of changing curvature on the complex tri-cellular pattern of the secondary flow is investigated, including the distribution of turbulent stresses. Secondly, the effect of changing curvature on the degree of stratification is analysed. Stratification can be characterised by the friction Richardson number Ri_τ = (βgHΔΦ)/u^2_τ, and the bulk Richardson number Ri_b = (βgHΔΦ)/u^2_{bulk}. Here ΔΦ is the difference between the mean temperature at the top and bottom of the channel, u_τ the mean friction velocity on the solid surfaces bounding the channel, u_{bulk} the domain averaged streamwise velocity, β the volumetric coefficient of expansion and g gravity. Stratification can also be viewed in terms of the transfer of energy from mean flow kinetic energy to potential energy via buoyancy fluxes. We study the effect of curvature on stratification by investigating its effect on the friction and bulk Richardson numbers, the global available, background, total potential energy, and the domain averaged kinetic energy. It is found that with the increase of curvature, Ri_τ and Ri_{bulk} decrease, while available potential energy increases due to increased overturning of the flow, indicating that increasing curvature leads to a decrease in the level of stratification.

Although scarcely described, intense summer precipitation events in central Chile aren’t an unknown phenomenon, their recurrence is estimated at 40 years. In the last 5 years, 2 heavy rainfall episodes triggered massive debris flows in the San Jose de Maipo county of the Metropolitan Region, located on the upper Maipo river basin, where average precipitation for summer months is only 7 mm. A summary of the current knowledge of the January 28 to 31, 2021 summer rain event is presented. The episode has been attributed to a Zonal Atmospheric River (ZAR), which allowed for a direct transfer of vapour and moisture on a W-E trajectory perpendicular to the Chilean coast. The latter favoured high altitude precipitation, with 0 degree isotherm estimated at 3.700 m a.s.l. On a local range, the snow line was observed between 2,800-3,100 m a.s.l. The event precipitation reached unprecedented values over 60 mm on all stations along the Maipo valley, with a local maximum of 117 mm. 3 pulses have been accounted for rainfall, with a maximum intensity of 11 mm/hour; at the peak of the pulses the Maipo river flow increased 8 times its pre-event flow of 60 m/s. In the following days after the event, 55% of the Upper Maipo basin was covered with snow. Due to sudden higher temperatures a consequent rapid snow melt increased the turbidity of the Maipo river, compromising freshwater supply. Agriculture was also affected, mainly grapes. According to the National Geological and Mining Service, over 120 landslides were triggered during the event, most of them being debris flows with some rock fall affecting the main roads. 700 persons were affected, more than 100 houses resulted with damages, 50 with severe damages and 33 destroyed, mostly at the San Alfonso village. Cost of infrastructure’s lost was estimated over US$4MM. Luckily, there weren’t any fatalities. This feature contrasts with the 25 February 2017 debris flow episode in the same region, with 8 fatal victims. Although local inhabitants have coexisted with this kind of hazards since historical times, uninterrupted urban growth on mountain areas has contributed substantially to an increase in the level of exposure. In this case, the accurate forecasting of the ZAR coupled with an effective risk communication avoided fatalities, nonetheless, it is most likely that this kind of phenomenon will occur again.

In this study, contaminant transport behaviour in the aquifer system (140 m × 180 m × 5 m) was analyzed using a 3-D groundwater flow and contaminant transport model viz. MODFLOW2005 and MT3DMS. The impacts of hydrodynamic dispersion parameters on the conservative contaminant plume dynamics were analyzed for homogeneous and heterogeneous aquifer systems with low permeability porous media (LPPM). The spatio-temporal distribution of contaminant concentration and breakthrough curves (BTCs) at 12 observation wells were used to analyze the transport dynamics due to conservative contaminant released from a single point source over a hypothetical study area for a period of 1 year (365 days). Results from MODPATH show a significant variation in the pathway of groundwater for homogeneous and heterogeneous aquifer systems. During the source loading period, a very low value of concentration of order 10-9 mg/m3 was observed in the LPPM region. The spatial distribution of contaminant plume for aquifer system with LPPM varied largely as compared to homogeneous aquifer system. The maximum value of concentration in the aquifer with LPPM was found to be ~40% higher than the homogeneous system after source removal. After the source removal, the maximum value of 1.98 mg/m3 was observed for the homogeneous system at a location away from pumping and extraction well after 730 days; however, for a heterogeneous system with LPPM, the maximum value of 2.57 mg/m3 was observed. An early breakthrough was observed for αL= 54 m as compared to αL= 9 m for homogeneous aquifer system, clearly depicting the effect of longitudinal dispersivity on BTC. However, effects of dispersivity on the rising and falling limbs of the BTC were negligible for heterogeneous aquifer system with LPPM. Further, an impact of LPPM and longitudinal dispersivity on the peak concentration value at observation well (OBS-7) was undistinguishable. The numerical simulations carried out in this study mimic the realistic heterogeneous aquifer conditions and highlighted the relevance of LPPM and associated transport processes on contaminant transport dynamics at field-scale, which was usually overlooked.

This study presents the major ion concentrations of waters in the upper Indus River and its Tributaries with the aim to reveal the hydrochemical characteristics and its controlling factors. There is a lack of water chemistry study in the upper Indus River basin especially in the Rivers/streams flowing from and through permafrost and glaciers. Water samples were collected from mainstream and its tributaries in July 2019. The physical parameters (like pH, EC, TDS) were measured in the field, and major ions (Mg2+, K+, Ca2+, Na+, Cl−, SO42−, and NO3−) and Si were analyzed in the laboratory. The results revealed that in the study region Ca2+ and HCO3− were the dominant ions and it has diverse nature of geological formation. The total dissolved solids (TDS) within the Indus River varies from 132.0 mg/l to 217.0 mg/l generally decreasing from upstream to downstream, under the influence of the semi-arid climatic conditions and relatively lower anthropogenic interference in the UIRB. The high concentrations of Na+ and K+ in the saline lakes (Pangong lake) sample were mainly affected by evaporation. Rock weathering is the dominant controlling factor for the water chemistry of the UIRB, and more specifically crystalline rocks and sedimentary carbonates. Different methods were utilized to identify the controlling mechanism of river geochemistry in the UIRB as silicate weathering in general with variable degrees of carbonate weathering and small contribution by evaporite weathering respectively. The present study provided the foundation for the overall water chemistry characteristics of the whole Indus River basin as well as glacier-fed Himalayan Rivers.

Thanks to the Unistellar network, citizen scientists and ordinary people all over the world can now enjoy the wonders of the night sky while also making important scientific discoveries. More than 5,000 people who own an eVscope—a digital, smart, and portable telescope—are doing precisely that thanks to a collaboration between Unistellar and scientists at the SETI Institute. The eVscope has already achieved many significant breakthroughs, including the detection by 79 observers of 85 transits by Jupiter-sized exoplanets, 281 asteroid occultations (including forty-five positive ones), and three shape and spin solutions for near-Earth asteroids. The network has also lent important support to NASA’s TESS mission by making transatlantic observations of an exoplanet transit, and to NASA’s Lucy mission by profiling Trojan asteroids this spacecraft will soon visit. These data are collected by observers in Europe, North America, Japan, Australia, and New Zealand, and the Unistellar network will soon expand to the rest of Asia and to South America, ensuring that each of these accomplishments is the product of coordinated efforts by hundreds or even thousands of observers across the globe. Our team is also working with NASA to develop several education programs involving the Girl Scouts of America, and community colleges around the US designed to connect teachers, professors, amateur astronomy clubs, and informal education partners. Our goal is to give every observer of the night sky the chance to experience the thrill of space exploration while we also educate young people to ensure that they are ready to carry humanity to and across the next frontier.

The human health risk assessment (HHRA) of groundwater system in the vicinity of Chandigarh dumping site was conducted, assuming oral ingestion and dermal contact exposure scenarios. Observed data of lead (Pb) concentration in the leachate was used to compute cancer risk (CR) by integrating unsaturated 1-D leaching model with probabilistic HHRA framework. The 99 percentile and maximum value of lead (Pb) concentration at the water table was estimated as 0.089 mg/L and 0.506 mg/L, respectively, for pre-monsoon season, higher than the safe limit of 0.050 mg/L. In contrast, for the post-monsoon season, only the maximum value of Pb concentration exceeded the safe limit. Results from 10,000 Monte Carlo simulations showed that the 99 percentile and maximum value of CR for all the sub-populations during pre-monsoon exceeded the safe limit (>10 ) via oral ingestion exposure to Pb-contaminated groundwater. The 95 percentile value of CR for adult sub-population was estimated as 1.05 x 10 for premonsoon; however, for the post-monsoon season, only maximum values of CR exceeded the safe limit. The cancer risk estimates for the pre-monsoon and post-monsoon seasons via skin dermal contact exposure were found to be lower than the safe level, posing no danger to human health. Among sub-populations, the order of posing CR was found to be in the order as adults (>18 years) > child I (1-5 years) > teen (11-18 years) > child II (6-10 years). Uncertainty analysis showed that the lead concentration (>95% variance contribution), as a major contributor towards uncertainty in the risk estimates, while event duration (t ), exposure duration (ED), and ingestion rate (IR) were observed as minor contributors. The approach presented in this study considered the uncertainty in the unsaturated leaching model parameters along with uncertainty in the exposure model parameters, thus can help decision-makers in estimating risk from open dumping sites with minimal data availability.

Mosquitoes in recent years have increased greatly in numbers due to the rapidly changing climate and rising temperatures. With this change comes suitable habitats for mosquitoes which are the most efficient killers in all of the animal kingdom due to the number of death from mosquito-borne diseases. If we were able to pinpoint the certain areas that mosquitoes are most attracted to we could in theory slow or even prevent the spread of mosquitoes. In our project, the research was conducted to find a correlation between the color and size of the traps to the amount of mosquitos that are present. With our findings, we were able to conclude that the bigger the traps, the faster the mosquitoes would be attracted to that area. We also found that the different traps would hold similar densities of mosquito larvae per square inch.

The 2020 Monte Cristo Earthquake sequence in western Nevada began with a M6.5 shock on 5/15/20, and was the largest to occur in Nevada since 1954. The event exhibited left-lateral slip along an eastward extension of the Candelaria fault and extensive distributed surface faulting in the epicentral area. Groundwater monitoring and strain analysis were conducted to evaluate hydrochemical effects on the regional groundwater systems following the initial event. Physio-chemical monitoring, (started on 5/16 and still ongoing) includes measurements of temperature (temp), pH, specific conductance (SpC), flow rate, alkalinity and collection of samples for major ions and trace element analysis. Since sites had not been monitored prior to the initial shock, measurements were evaluated against a year of post-event data to gauge response to seismicity. Four sites were monitored: a well from Columbus Marsh (CM) located 5 km from the epicenter; an artesian thermal well from Fish Lake Valley (FL); a well at Willow Ranch (WR) tapping cool water above the FL waters; and a spring along Mina Dump Road (MD) located 15 km north of the Candelaria fault on the Benton Springs Fault. GPS and InSAR measurements were used to create a model of the slip from which we estimated coseismic strain at each sampling location. All but one sample site, MD, experienced positive dilation and CM experienced the greatest amount of strain (15-17 microstrains). Hydrologic and chemical changes were observed following the initial shock, varying between sites. CM had significantly lower SpC values in the week following the event, as well as changes in major ion composition. Other sites showed minor changes; MD showed fluctuations in pH values and FL experienced a slight drop in temp. These waters showed minimal changes in major ions and trace elemental composition. Clear responses were observed throughout three >M5 aftershocks (6/30/20, 11/13/20, and 12/1/20), especially in SpC and alkalinity. A remarkable change in elemental concentration (an increase in Ca, K, SO4, Fe, and decrease in Na, Cl, Li, and Ba) was observed in CM. WR experienced a transient increase in temp measured two weeks prior to the 11/13/20 earthquake. Strain analyses of the smaller (>M5) events are planned to further evaluate observed responses and to clarify factors affecting groundwater response.

The Delaware River is a major freshwater supplier of New York City (NYC). Nearly half of NYC drinking water is supplied by inter-basin transfer of surface water stored in reservoirs within the upper reaches of the Delaware River. In its lower reaches, the Delaware River is a tidal estuary, and upstream freshwater discharge provides a critical control on estuary salinity. During the record 1950–1960’s drought, NYC water withdrawals exacerbated low flows. Estuary salinity reached levels that threatened freshwater intakes and groundwater recharge, resulting in legal action and Supreme Court decrees. We revisit this classic case study in coupled human and natural systems using the Energy Exascale Earth System Model (E3SM). The E3SM water management sub-model is updated to include inter-basin water transfer and reservoir-specific operating rules. Model simulations are developed to investigate competition between NYC water demand and in-stream flow targets needed to maintain estuary salinity within regulatory guidelines under historic and future climate. To our knowledge, this is a first demonstration of an Earth System Model simulation with inter-basin water transfer, which, in this study area, provides water for nearly five million people living outside the Delaware River basin in New York City and New Jersey.

Seismology data is overgrowing and is outpacing the development of processing algorithms. This tremendous increase in high-quality data can help better understand the earthquake processes related to the geology of active seismic regions such as the Hindu Kush. Most traditional detection algorithms are computationally inefficient compared to the amount of seismological data available and fail to detect low magnitude and noisy events. Deep learning algorithms are known for their applicability on large datasets with less runtime. Event detection and phase detection can be considered a supervised deep-learning problem quite similar to image recognition. In this study, we have implemented a hierarchical attention mechanism-based deep learning model for simultaneously phase picking and earthquake detection. This model is trained using Stanford Earthquake Dataset (STEAD), a globally disturbed labeled seismic dataset. We used this trained deep learning model to detect earthquake signals and pick P and S phases in the Hindu Kush - Pamir region for twelve months of continuous data spread across 83 different stations. A rigorous selection criterion based on detection, P and S phase probabilities, and other parameters has been used to associate the phases from different stations and to locate the earthquake. Our model detected almost seve times more earthquakes than previously existed in the catalog. The algorithm picked P and S phases with a high level of precision, comparable to human analyst picks. Furthermore, pinpointing these events allowed us to define the S-shaped seismic zone in the Pamir-Hindu Kush region and better comprehend the deformation caused by Eurasian- Indian plate motion.