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NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗

Modeling Functional Organic Chemistry in Arctic Rivers: An Idealized Siberian System

Rivers of the Arctic will become ever more important for the global climate, since they carry a majority of continental dissolved organic carbon flux into the rapidly changing polar ocean. Aqueous organics comprise a wide array of functional groups, several of which are likely to impact coastal and open water biophysical properties. Light attenuation, interfacial films, aerosol formation, gas release and momentum exchange can all be cited. We performed Lagrangian kinetic modeling for the evolution of riverine organic chemistry as the molecules in question make their way from the highlands to Arctic outlets. Classes as diverse as the proteins, sugars, lipids, re-condensates, humics, bio-tracers and small volatiles are all included. Our reduced framework constitutes an idealized northward flow driving a major hydrological discharge rate and primarily representing the Russian Lena. Mountainous, high solute and tundra sources are all simulated, and they meet up at several points between soil and delta process reactors. Turnover rates are parameterized beginning with extrapolated coastal values imposed along a limited tributary network, with connections between different terrestrial sub-ecologies. Temporal variation of our total dissolved matter most closely resembles the observations when we focus on the restricted removal and low initial carbon loads, suggesting relatively slow transformation along the water course. Thus, channel combinations and mixing must play a dominant role. Nevertheless, microbial and photochemical losses help determine the final concentrations for most species. Chemical evolution is distinct for the various functionalities, with special contributions from pre- and post-reactivity in soil and delta waters. Several functions are combined linearly to represent the collective chromophoric dissolved matter, characterized here by its absorption. Tributaries carry the signature of lignin phenols to segregate tundra versus taiga sources, and special attention is paid to the early then marine behaviors of low molecular weight volatiles. Heteropolycondensates comprise the largest percentage of reactive carbon in our simulations due to recombination/accumulation, and they tend to be preeminent at the mouth. Outlet concentrations of individual structures such as amino acids and absorbers lie above threshold values for biophysical influence, on the monolayer and light attenuation. The extent of coastal spreading is examined through targeted regional box modeling, relying on salinity and color for calibration. In some cases, plumes reach the scale of peripheral arctic seas, and amplification is expected during upcoming decades. Conclusions are mapped from the Lena to other boreal discharges, and future research questions are outlined regarding the bonding type versus mass release as permafrost degrades. Dynamic aqueous organic coupling is recommended for polar system models, from headwaters to coastal diluent.

54 ENVIRONMENTAL SCIENCES↗

Effects of Intrusive Confining Units on Groundwater Flow at Pahute Mesa, Nevada National Security Site

Geological, geophysical, hydrogeological, and hydrological evidence indicates that feeder dikes to rhyolitic lava flows may play a role as confining units in the groundwater flow system underlying the Pahute Mesa (PM) area of underground nuclear testing at the Nevada National Security Site (NNSS) (Figure 1). Of geological significance, the PM testing area is largely situated within the Silent Canyon caldera complex (SCCC), which includes both tuffs and lavas that were fed by (and are connected to) intrusive rock units such as feeder dikes prior to and during volcanic eruptions (Orkild et al., 1968; Byers et al., 1976a). Groundwater modeling results presented in this report support extension of “pool-dam” and “breach scenario” concepts presented in Jackson and Fenelon (2018) and Jackson et al. (2021) to low-permeability intrusive confining units (ICUs) such as feeder dikes that are expected to dissect and ring silicic calderas. As laterally extensive, steeply-dipping, and sub-parallel planar structures, ICUs may further compartmentalize groundwater flow in some areas of the volcanic aquifer system at PM. ICUs may explain unusually high horizontal hydraulic gradient southwest of Cheshire. Breaching of an ICU within which the Cheshire test was emplaced may explain changes in water levels before and after the Cheshire test was detonated in the U-20n emplacement hole on 2/14/76 (USDOE, 2015b). This analysis of the effects of ICUs on groundwater flow at PM addresses a need to evaluate uncertainty in the conceptual model or structural aspects of hydrologic source term (HST) or corrective action unit (CAU) models for groundwater flow and contaminant transport (FFACO, 1996, as amended). At Cheshire and possibly other test locations at PM, downgradient extent of radionuclide contamination may be overpredicted by not including the confining effects of ICUs. On the other hand, contaminant extent may be underpredicted by not considering transient flow effects and/or the re-equilibrated flow field caused by breaching of an ICU by an underground nuclear test. Near Cheshire, the effects of ICUs may be most apparent and impactful to the groundwater flow system at PM because of an unusual combination of thickness, extent, and frequency of dikes transecting the saturated CHLFA4 aquifer and feeding into the overlying unsaturated rhyolite lava of Windy Wash. Chapters 2, 3, and 4 present geological, geophysical, hydrogeological, and hydrological evidence for ICUs at PM. Chapters 5 and 6 examine effects of ICUs on groundwater flow including analysis by groundwater modeling.

54 ENVIRONMENTAL SCIENCES↗

The evolution of dam induced river fragmentation in the United States

It is established that dams decrease river connectivity; however, previous global scale studies of river fragmentation focused on a small subset of the largest dams. In the United States, mid-sized dams, which are too small for global databases, account for 96% of major anthropogenic structures and 48% of reservoir storage. We conduct a national evaluation of the evolution of anthropogenic river bifurcation over time that includes more than 50,000 nationally inventoried dams. Mid-sized dams account for 73% of anthropogenically created stream fragments nationally. They also contribute disproportionately to short fragments (less than 10 km), which is particularly troubling for aquatic habitats. Here we show that dam construction has essentially reversed natural fragmentation patterns in the United States. Prior to human development, smaller river fragments and less connected networks occurred in arid basins while today we show that humid basins are the most fragmented due to human structures.

54 ENVIRONMENTAL SCIENCES↗

700,000 years of tropical Andean glaciation

Our understanding of the climatic teleconnections that drove ice-age cycles has been limited by a paucity of well-dated tropical records of glaciation that span several glacial–interglacial intervals. Glacial deposits offer discrete snapshots of glacier extent but cannot provide the continuous records required for detailed interhemispheric comparisons. By contrast, lakes located within glaciated catchments can provide continuous archives of upstream glacial activity, but few such records extend beyond the last glacial cycle. Here a piston core from Lake Junín in the uppermost Amazon basin provides the first, to our knowledge, continuous, independently dated archive of tropical glaciation spanning 700,000 years. We find that tropical glaciers tracked changes in global ice volume and followed a clear approximately 100,000-year periodicity. An enhancement in the extent of tropical Andean glaciers relative to global ice volume occurred between 200,000 and 400,000 years ago, during sustained intervals of regionally elevated hydrologic balance that modified the regular approximately 23,000-year pacing of monsoon-driven precipitation. Millennial-scale variations in the extent of tropical Andean glaciers during the last glacial cycle were driven by variations in regional monsoon strength that were linked to temperature perturbations in Greenland ice cores; these interhemispheric connections may have existed during previous glacial cycles.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Nominal Energy Storage at Existing Hydropower Reservoirs in the US

Long-term planning and operation of hydropower reservoirs require an understanding of both water and energy storage. As energy storage needs of the evolving grid increase, we must account for the water and energy storage potential of these reservoirs. Given the limitations of current data on existing hydropower, we compile statistics related to storage volume and hydraulic head from publicly available data sets and examine differences in descriptions of US hydropower storage. Assembled characteristics are used to calculate nominal energy storage capacity, a simple measure of potential to generate power from a given volume of water, not factoring in detailed constraints. Inventory-based estimates of energy storage are calculated at 2,075 dams, which helps put the potential for US hydropower to support energy storage in context with similar evaluations in other regions and with other energy storage technologies. The national energy storage capacity ranges between 34.5 and 45.1 TWh depending on the information used, with 52% of energy storage located at the 10 largest reservoirs in the US. Energy storage capacities are also calculated at 236 dams with historical volume and elevation data. Finally, reservoir inflows provide context for the storage volumes and sensitivities to hydrologic variability. Larger reservoirs with greater storage volume to inflow ratios are concentrated in the Western US, but the majority of hydropower reservoirs store less than the annual inflow. We address several infrastructure and water resource informatics challenges and highlight remaining issues, including representing seasonal or shorter variability in water volumes and representing connected hydropower facilities.

13 HYDRO ENERGY↗

Riverine bacterioplankton and phytoplankton assembly along an environmental gradient induced by urbanization

In the Anthropocene, human activities are intensifying stresses on biological communities across ecosystems. Knowledge on how environmental changes influence microbial community dynamics is crucial but currently limited. Here we unraveled ecological processes generating distribution patterns of bacterioplankton and phytoplankton communities in a river draining an urbanizing watershed in southern China. In this ecosystem, longitudinal environmental heterogeneity and directional flow potentially have counteracting effects on planktonic community assembly. Using simultaneously multiple approaches, we showed that the observed compositional patterns result from an interplay of stochastic and deterministic processes, indicating that dispersal via fluvial connectivity could not override local selective pressures. Successional shifts in the relative importance of the above processes were associated with trends in climatic factors. High diversity was observed at the intermediate levels of ecological processes alongside intense inter-species interactions maintained by a few keystone taxa. Altogether, interactions between climatic conditions, landscape and hydrology control plankton community dynamics.

54 ENVIRONMENTAL SCIENCES↗

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗

Integrating science for water security governance

Hydrological extremes are intensifying globally, increasing the complexity of decisions required to ensure water security. Advances in hydrological science, modeling, and data systems have expanded the technical frontier of water research, yet uptake of scientific insights in policy and management decisions remains limited. This persistent science–policy gap is not primarily a failure of knowledge generation or robustness, but an institutional challenge shaped by how scientific and governance systems are organized, coordinated, and connected to support the effective use of scientific knowledge. These challenges are particularly pronounced in multi-level and transboundary water governance, where decisions span jurisdictions and require coordination across institutional and political boundaries. We synthesize research at the science–policy interface and evidence from water security initiatives to show how institutional arrangements, scientific tool development, and research practices enable or constrain the sustained use of scientific knowledge in water-security governance processes. Building on these insights, we develop ‘shared decision infrastructure’ as a framing to describe how scientific knowledge is embedded within the institutional, relational, and procedural arrangements that connect science to decision-making processes over time. We translate this framing into a practical intervention roadmap centered on institutional design, tool translation, sustained co-production, and outcome-oriented evaluation to support the integration of science into ongoing governance processes. By positioning science as shared decision infrastructure, the roadmap clarifies how researchers can design scientific efforts that support more coordinated, accountable, and adaptive water security decisions amid deepening uncertainty.

M whitney, Kristen [NASA Goddard Space Flight Cent↗

Lessons learned from replicating services for flood prediction and monitoring in Asia to the assessment of hurricane impacts in Central America

In October and November 2020, two dangerous back-to-back hurricanes, Eta and Iota, made landfall in Central America. The SERVIR program - a joint effort of NASA and the U.S. Agency for International Development, and whose motto is “connecting space to village” was able to leverage two tools originally developed for use in other regions for predicting and assessing the flood impacts of the hurricanes. The GEOGLoWS Streamflow Prediction tool - originally implemented in the Hindu Kush Himalayan region - was used for predicting potential flooding ahead of landfall by Eta and Iota. In conjunction, the Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) framework - originally developed along with SERVIR-Mekong - was used for post-event flood mapping, leveraging its ability to map floods in cloud-covered areas using synthetic aperture radar (SAR) imagery from the Copernicus program. Both tools were used in support of disaster coordination efforts being led by the Central American Regional Disaster Prevention Center (CEPREDENAC), in conjunction with its sister agency, the Regional Water Resources Committee (CRRH). The support provided to regional entities - and to their stakeholder national governments - served as an example of rapid generation of Earth observation products for disaster response. Feedback on those products was also provided, especially in terms of the implications of (i) calibration of predicted river volumes, and (ii) the latency of the input Earth observation imagery and attempts to map the floods’ maximum extents. An upcoming NASA DEVELOP project will also seek to strengthen the capability of CEPREDENAC and CRRH to apply HYDRAFloods for future extreme events. The application of the tools also provides a useful case study on capacity building, in terms of how Earth observation data and models can be replicated across regions.

Capacity building↗

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗

Advancing Understanding of Deep Convective Anvil Clouds

In this project we use ground-based DOE ARM observations, satellite observations, and Weather Research and Forecasting (WRF) model simulations to arrive at a more complete understanding (or, new theory) of how atmospheric heating profiles in thunderstorm cores drives how quickly air rises in the storms. The rate at which air motion increases or decreases with altitude directly relates to how much cloud mass is ejected laterally into the adjacent atmosphere, which then influences the development and maintenance of “stratiform raining cloud anvils”. Our work has led to new equations connecting the heating in these thunderstorms to these stratiform clouds, with the connection modulated by the stability structure of the atmosphere (i.e., if more stable, then a more rapid change in thunderstorm heating with altitude results in more stratiform cloud, independent of whether over land or ocean, or how organized the thunderstorms are). Improving knowledge of stratiform clouds is important, since they contribute to substantial accumulated rainfall (important to agriculture and local hydrology) as well as radiation, given their large areal extents and lifetime. The radiation impacts likely impact simulated cloud feedback in all Earth System models (ESMs).

54 ENVIRONMENTAL SCIENCES↗

Seeing the Disturbed Forest for the Trees: Remote Sensing Is Underutilized to Quantify Critical Zone Response to Unprecedented Disturbance

Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post-disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground-based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.

54 ENVIRONMENTAL SCIENCES↗

Environmental Extremes: Building a New Research Partnership between the University of Nevada Reno and the Pacific Northwest National Laboratory (Final Report)

This project focused on strengthening research partnership and collaboration between the University of Nevada, Reno (UNR) and the Pacific Northwest National laboratory (PNNL) in two focused areas: wildfires and hydrology in the context of environmental extremes. The goal was to overcome barriers and bring UNR university researchers, students, and postdocs up to speed and entrained into DOE/SC/BER /Earth and Environmental System Science Division’s (EESSD) environmental research enterprise. UNR continues to work with the Earth and Biological Sciences Directorate (EBSD) at PNNL to create a broad new collaborative research program connecting scientists and research faculty at the two institutions. This research partnership has been designed to increase the capabilities and velocities of both institutions by developing long-term relationships between researchers from each institution, exposing university researchers to the deep capabilities in the DOE National Laboratories and user facilities, and establishing a pipeline of skilled and experienced graduate students and postdoctoral researchers ready to work alongside DOE scientists to take on grand challenge science problems. These collaborations are intended to ultimately benefit the public by advancing scientific discovery, unleashing the scientific potentials through collaboration and connection, enriching the technical and scientific competitiveness of our nation, and enabling the development of a skilled workforce to tackle the critical scientific challenges that face our nation’s security, infrastructure, and prosperity.

54 ENVIRONMENTAL SCIENCES↗

Hydropower Infrastructure – LAkes, Reservoirs, and RIvers (HILARRI)

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2024) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2024) These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

13 HYDRO ENERGY↗

Modeling of fluid injection-induced fault reactivation using coupled fluid flow and mechanical interface model

The present study is aimed at developing a numerical model to reproduce coupled hydro-mechanical processes associated with fault reactivation by fluid injection in low permeability rock, as part of the DECOVALEX-2019 project Task B. We proposed a modeling approach for simulating the processes using the TOUGH-FLAC simulator, and modeled a fault reactivation experiment conducted at Mont Terri Rock Laboratory in Switzerland. The first step of the study involved benchmark calculations considering a simplified fault plane and geometry. Fluid flow along a fault was modeled using elements of aperture-sized thickness on the basis of Darcy's law and the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by zero-thickness interface elements in FLAC3D upon which a slip and/or separation is allowed. A methodology to connect a TOUGH2 volume element to a FLAC3D interface element was developed for handling the hydro-mechanical interactions on the fault during fluid injection. Two different fault models for describing the evolutions of hydraulic aperture by elastic fracture opening and failure-induced aperture increase were considered in the benchmark calculations. In the coupling process, the changes in geometrical features and hydrological properties induced by mechanical deformation were continuously updated. The transient responses of the fault and host rock to stepwise pressurization were examined during the simulation. The hydro-mechanical behavior, including the injection flow rate, pressure distribution around the borehole, stress conditions, and displacements in normal and shear directions were monitored in the surrounding rock and along the fault. The results of benchmark calculations suggest that the developed model reasonably represents the hydro-mechanical behavior of a fault and the surrounding rock. This modeling approach was applied to the fault reactivation experiment of the Mont Terri Rock Laboratory. In this interpretive modeling, a parametric study was conducted to examine the effects of input parameters regarding in situ stress and fault properties on the hydro-mechanical responses of the fault to water injection. Then, an optimal parameter set to reproduce the field experiment results was chosen by trial-and-error. The injection flow rate and pressure response during fault reactivation closely matched those obtained at the site, which indicates the capability of the model to appropriately capture the progressive pathway evolution during fault reactivation tests at the site. Finally, the anchor displacements were overestimated by the model, but a fair agreement was obtained in terms of the order of magnitude and the variation tendency.

58 GEOSCIENCES↗

Ordovician impacts at sea in Baltoscandia

Northern Europe has an assemblage of Ordovician probable impacts that is exceptional because the structures involved are relatively old yet well preserved because they formed at sea and because they formed within a restricted geological time in a relatively small area. The Tvaren, Kardla, and Lockne structures might not be strictly contemporaneous but all formed near the beginning of the Caradoc Age (about 460 Ma), whereas the Granby structure is about 20 Ma older. The range of diameters is from about 2 km (Tvaren, Granby) to 8 km (Lockne). The stratigraphic succession formed on impact at sea, as uniformly documented by these structures, begins with a breccia lens consisting of basement rocks that are intensely crushed. Owing to expulsion of sea water by the impact, this breccia formed under essentially dry conditions. Later on this breccia was in part hydrothermally altered. It is overlain by backsurge turbidite that formed from fragments of local sedimentary bedrock and crystalline basement when the sea water returned to the crater site. Either the turbidite is simply a Bouma sequence (although quite thick - as much as over 50 m) from very coarse rubble to mud, or it is more complex. After deposition of the backsurge turbidite, or turbidite complex, the craters still remained as 150-200-m-deep holes in the sea bed. Together with the presence of relatively shallow water over the rim wall, this situation created predictable hydrologic conditions for extended histories of sedimentation and biological development at the crater as well as within it. The presence of a concentration of craters within a limited area of well-preserved and accessible Ordovician deposits raises a question about the Ordovician, especially its middle portion, as potentially an age of relatively intense impact activity even in wider areas. In this connection it may be apposite to mention that the only fossil stony meteorites so far recorded in rocks are from the late Early and the Middle Ordovician.

Lindstroem, M.↗

The Connected Isotopic Water Cycle in the Community Earth System Model Version 1

Because of the pervasive role of water in the Earth system, the relative abundances of stable isotopologues of water are valuable for understanding atmospheric, oceanic, and biospheric processes, and for interpreting paleoclimate proxy reconstructions. Isotopologues are transported by both largescale and turbulent flows, and the ratio of heavy to light isotopologues changes due to fractionation that can accompany condensation and evaporation processes. Correctly predicting the isotopic distributions requires resolving the relationships between largescale ocean and atmospheric circulation and smallerscale hydrological processes, which can be accomplished within a coupled climate modeling framework. Here we present the water isotopeenabled version of the Community Earth System Model version 1 (iCESM1), which simulates global variations in water isotopic ratios in the atmosphere, land, ocean, and sea ice. In a transient Last Millennium simulation covering the 850-2005 period, iCESM1 correctly captures the latetwentiethcentury structure of δ(exp 18)O and δD over the global oceans, with more limited accuracy over land. The relationship between salinity and seawater δ(exp 18)O is also well represented over the observational period, including interbasin variations. We illustrate the utility of coupled, isotopeenabled simulations using both Last Millennium simulations and freshwater hosing experiments with iCESM1. Closing the isotopic mass balance between all components of the coupled model provides new confidence in the underlying depiction of the water cycle in CESM, while also highlighting areas where the underlying hydrologic balance can be improved. The iCESM1 is poised to be a vital community resource for ongoing model development with both modern and paleoclimate applications.

Brady, E.↗