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DOE OSTI2022

Retracted: Monitoring Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin with Multigeneration Pedigrees

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located in tributaries of the mid- and upper Columbia River as well as the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed investigation of the proportion of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and there was an overall rate of less than 1.0% of broodstock that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 14 segregated programs with 0.0–10.0% pNOB, 7 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗

DOE OSTI2022

Density Dependence in Three Snake River Sockeye Salmon Nursery Lakes in Central Idaho

Abstract Snake River Sockeye Salmon Oncorhynchus nerka, listed as an endangered species in 1991, currently inhabit three nursery lakes (Redfish, Pettit, and Alturas lakes) in the Sawtooth Valley, Idaho. Conspecific kokanee (lacustrine Sockeye Salmon) are also present in the lakes. Snake River Sockeye Salmon recovery efforts, initially focused on genetic conservation, are now attempting to rebuild naturally spawning populations using hatchery supplementation. However, in Sockeye Salmon nursery lakes, density dependence is frequently observed when elevated O. nerka abundance leads to declines in zooplankton biomass, body size, and shifts in community composition. In turn, these changes lead to reductions in juvenile O. nerka growth rates, survival, and adult returns. We examined a long-term data set of O. nerka population metrics and associated zooplankton community metrics. We found evidence of density dependence within and among nursery lakes. We detected differences in zooplankton biomass, lengths of preferred zooplankton prey (Daphnia spp. and cyclopoid copepods), parr growth rates, and age-1 smolt size among the three lakes. We found negative relationships between O. nerka density and zooplankton biomass and size. We identified positive relationships between zooplankton biomass and two response variables: smolt size at migration and growth rates of hatchery parr. The relationships were generally similar among lakes. Variable outcomes were a result of differences in O. nerka density (or zooplankton biomass), controlled primarily by the relative proportion of spawning and rearing habitat in each lake. Understanding unique lake habitats, ecological interactions, and the role of density dependence is germane to management of Snake River Sockeye Salmon populations.

Griswold, Robert G.↗

DOE OSTI2023

Multigeneration Pedigrees to Monitor Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located on tributaries of the mid- and upper Columbia River and in the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed for investigation of the proportions of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and overall less than 1.0% of broodstock consisted of fish that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 11 segregated programs with 0.0–10.0% pNOB, 9 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗

DOE OSTI2024

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗

DOE OSTI2021

Integrated energy-water-land nexus planning in the Colorado River Basin (Argentina)

Integrated energy-water-land (EWL) planning promotes synergies and avoids conflicts in ways that sector-specific planning approaches cannot. Many important decisions that influence emerging EWL nexus issues are implemented at regional (e.g., large river basin, electricity grid) and sub-regional (e.g., small river basin, irrigation district) scales. However, actual implementation of integrated planning at these scales has been limited. Simply collecting and visualizing data and interconnections across multiple sectors and sub-regions in a single modeling platform is a unique endeavor in many regions. This study introduces and applies a novel approach to linking together multiple sub-regions in a single platform to characterize and visualize EWL resource use, EWL system linkages within and among sub-regions, and the EWL nexus implications of future policies and investments. This integrated planning methodology is applied in the water-stressed Colorado River Basin in Argentina, which is facing increasing demands for agricultural and fossil fuel commodities. Guided by stakeholders, this study seeks to inform basin planning activities by characterizing and visualizing (1) the basin’s current state of EWL resources, (2) the linkages between sectors within and among basin sub-regions, and (3) the EWL nexus implications of planned future agricultural development activities. Results show that water scarcity, driven in part by human demands that have historically reached 60% of total surface water supply, poses a substantial constraint to economic development in the basin. The Colorado basin has the potential to serve as a testbed for crafting novel and generalizable sub-regional EWL planning approaches capable of informing the EWL planning dialogue globally.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Growth and survival rates of dispersing free embryos and settled larvae of pallid sturgeon ( Scaphirhynchus albus ) in the Missouri River, Montana and North Dakota

We released nearly 1.0 million 1-day post-hatch (dph) and 5-dph pallid sturgeon (Scaphirhynchus albus) free embryos in the Missouri River on 1 July 2019 and sequentially captured survivors at multiple sites through a 240-km river reach to quantify daily growth and survival rates during the early life stages. Genetic analysis was used to assign captured fish to released family lots and known ages. Growth rate was similar (0.74–0.75 mm day –1 ) between the 1- and 5-dph age groups during the 3–4-day dispersal period when water temperature averaged 16.8 °C. Daily survival rate was 0.64 during 1–4 dph for the original 1-dph age group and 0.80 during 5–7 dph for the original 5-dph age group. Total survival during free embryo dispersal (hatch to 9 dph) was estimated as 0.0437. The transition from dispersing as free embryos to settling as benthic larvae was verified for fish originally released as 5 dph. Growth of settled larvae was quantified with a Gompertz model through 75 dph (9 September; 112 mm) when water temperature was 18.8–21.0 °C in the rearing areas. Settled larvae had an estimated daily survival rate of 0.96, and estimated total survival during 9–75 dph was 0.0714. This study provides the first empirical survival estimates for pallid sturgeon early life stages in natural settings and is one of few studies reporting similar information for other sturgeon species. Applications of this work extend to pallid sturgeon restoration programs where population models are being developed to predict recruitment potential and population responses to river management alternatives.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Mass removal efficiencies in water and consequences after a river diversion into coastal wetlands: second thoughts

Abstract Salinity control, nutrient additions, and sediment supply were directly or indirectly the rationale for a $220 million coastal wetland restoration project (Davis Pond River Diversion) that began in 2002. We sampled Mississippi River water going in and out of the receiving basin from 1999 to 2018 to understand why wetland loss increased after it began. There was a reduction in inorganic sediments, nitrogen (N), and phosphorus (P) concentrations within the ponding area of 77%, 39% and 34%, respectively, which is similar to that in other wetlands. But the average sediment accumulation of 0.6 mm year −1 inadequately balances the present-day 5.6 mm year −1 sea level rise or the 7.9 ± 0.13 mm year −1 accretion rates in these organic soils. Nutrients added likely reduced live belowground biomass and soil strength, and increased decomposition of the organic matter necessary to sustain elevations. The eutrophication of the downstream aquatic system from the diversion, principally by P additions, increased Chl a concentrations to a category of ‘poor’ water quality. We conclude that this diversion, if continued, will be a negative influence on wetland area and will eutrophy the estuary. It is a case history example for understanding the potential effects arising from proposed river diversions.

Turner, R. Eugene (ORCID:0000000307767506)↗

DOE OSTI2022

Luminescence dosimetry for evaluation of the external exposure in Metlino, upper Techa River valley, Southern Urals, Russia: Analysis of new results

Luminescence dosimetry was applied in the former settlement of Metlino, Southern Urals, Russia as part of a full-scale study to validate the Techa River Dosimetry System (TRDS) 2016 for the upper Techa River region. The village, which was evacuated in 1956, was located 7 km downstream of the release point of liquid radioactive waste by the Mayak plutonium facility. Several brick samples were taken from north-eastern and south-eastern walls of the granary, facing the former Techa river shoreline and floodplain. Samples were all taken at the same height and measured at different depths into the brick. For the majority of brick samples, good Optically Stimulated Luminescence properties of the quartz grains were observed. In some cases, however, strong levels of sensitization and/or signal recuperation were encountered which necessitated adjustment in the measurement protocols. Anthropogenic doses in bricks varied from 1.5 to 6.6 Gy and the horizontal profiles along both walls showed significant variation, which is explained on a qualitative basis. Further, a dose depth profile is observed for selected samples, which is different from the dose depth profile measured and simulated for samples from the north-western wall of the granary in previous studies. This is qualitatively explained by the differences in source configuration.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2025

Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence

Continuous measurement and monitoring of surface water coverage in non-perennial streams are essential for understanding the exchange fluxes between surface and subsurface waters under both inundated and non-inundated conditions. In this study, a wildlife camera photo-based framework was developed to monitor small stream water inundation, depth, discharge, and velocity. Two advanced machine learning models, YOLOv8 and Mask2Former, were utilized to efficiently analyze images captured by wildlife cameras. The accuracy of the framework was validated against on-site depth measurements at six sites in the Yakima River Basin, along with the gage height, discharge, and velocity data from four USGS sites. This approach facilitates long-term, continuous monitoring and quantification of river intermittency and water availability with high precision and low cost, thereby advancing river ecosystem research and management.

machine learning↗

DOE OSTI2020

Temporal flow variations interact with spatial physical heterogeneity to impact solute transport in managed river corridors

The interactions between surface water and groundwater in river corridors lead to temporal fluctuations in subsurface water fluxes which have a critical role on solute transport dynamics. Here, we develop a framework to analyze the relative impacts of different temporal frequencies of the flow field in a spatially heterogeneous aquifer on solute transport. Our analysis indicates that the advection-dispersion equation behaves as a low-pass filter by wiping out the effect of high-frequency velocity fluctuations on the first two spatial moments of the solute plume, namely its center of mass and spreading. The concepts discussed in the theoretical analysis are then applied to understand solute transport dynamics at the 300 Area of the Hanford site (USA) adjacent to the Columbia River. We examine the temporal behavior of the solute plume's spatial moments for different temporal frequencies utilizing geostatistical parameters estimated in the 300 Area. Due to the proximity to the Columbia river, groundwater fluxes at the Hanford site are highly dynamic resulting in a large range of characteristic temporal frequencies. Nonetheless, similar to the theoretical analysis, our results show that the effect of high-frequency fluctuations is filtered, with most of the solute transport dynamics being controlled by fluctuations characterized by a large characteristic period.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Advancing stream temperature prediction with a generalizable large-sample framework across CONUS river reaches

Accurately predicting stream temperature in ungauged basins remains a critical challenge for water resource management, thermoelectric power plant cooling, and ecosystem conservation. Large-sample machine learning models trained on hundreds of well-monitored river basins have shown remarkable performance; however, such models have yet to be developed solely using forcing data that can be readily extracted to simulate stream temperatures anywhere in the contiguous United States (CONUS). In this study, we present a scalable, large-sample deep learning framework using Long Short-Term Memory (LSTM) networks to simulate daily stream temperatures in ungauged basins across the CONUS. The framework leverages both modeled reanalysis of meteorological and streamflow inputs as well as static attributes available for all 2.7 million CONUS river reaches in the National Hydrography Dataset Plus (NHDPlusV2). By generating dynamical inputs from predefined thermally relevant upstream contributing areas, rather than the entire upstream basin, the model also offers improvements in very large basins where full-basin averaging can dilute the most important influences on stream temperature. Evaluated across 300 basins, the model achieves a median Mean Absolute Error (MAE) of 1.1 °C and a Nash-Sutcliffe Efficiency (NSE) of 0.95 on temporally and spatially distinct test folds—comparable to models trained exclusively using meteorological and streamflow observational data. The flexible, high-performing framework generalizes to any unmonitored river reach without significant regulation or unnatural thermal input immediately upstream, substantially expanding predictive capabilities in data-scarce regions.

Hydrology↗

DOE OSTI2026

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3° C and + 4° C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.

Climate change impact study↗

DOE OSTI2026

Drying of the Himalayan Indus-Ganges-Brahmaputra Rivers: Understanding Causes and Management as a “One Water” Resource

Here, the Himalayan mega-rivers, the Indus, the Ganges (Ganga), and the Brahmaputra (Tsang Po), together known as the IGB, are three of the largest river systems (RS) in the world (Figure 1a). These transboundary rivers have acted as the lifeline of South Asia for the past several thousand years, and their fluvial plains have acted as the cradle of human civilization. At present, these plains sustain some of the densest and largest global populations (about 1 billion people, ∼15% of the global population) by providing water for agriculture, drinking water, industry, navigation, and hydropower.

Mukherjee, Abhijit [Indian Inst. of Technology (II↗

DOE OSTI2020

Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

Abstract Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.

Hadjimichael, Antonia↗

DOE OSTI2022

Organizational Principles of Hyporheic Exchange Flow and Biogeochemical Cycling in River Networks Across Scales

Hyporheic zones increase freshwater ecosystem resilience to hydrological extremes and global environmental change. However, current conceptualizations of hyporheic exchange, residence time distributions, and the associated biogeochemical cycling in streambed sediments do not always accurately explain the hydrological and biogeochemical complexity observed in streams and rivers. Specifically, existing conceptual models insufficiently represent the coupled transport and reactivity along groundwater and surface water flow paths, the role of autochthonous organic matter in streambed biogeochemical functioning, and the feedbacks between surface-subsurface ecological processes, both within and across spatial and temporal scales. While simplified approaches to these issues are justifiable and necessary for transferability, the exclusion of important hyporheic processes from our conceptualizations can lead to erroneous conclusions and inadequate understanding and management of interconnected surface water and groundwater environments. This is particularly true at the landscape scale, where the organizational principles of spatio-temporal dynamics of hyporheic exchange flow (HEF) and biogeochemical processes remain largely uncharacterized. This article seeks to identify the most important drivers and controls of HEF and biogeochemical cycling based on a comprehensive synthesis of findings from a wide range of river systems. We use these observations to test current paradigms and conceptual models, discussing the interactions of local-to-regional hydrological, geomorphological, and ecological controls of hyporheic zone functioning. This improved conceptualization of the landscape organizational principles of drivers of HEF and biogeochemical processes from reach to catchment scales will inform future river research directions and watershed management strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Physics–Informed Neural Networks of the Saint–Venant Equations for Downscaling a Large–Scale River Model

Large-scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics near the river-ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state-of-the-art physics-informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one-dimensional (1-D) Saint-Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN-based downscaling can produce more reasonable subgrid solutions of the along-channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path towards improving emulation capabilities in large-scale models to characterize fine-scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗

DOE OSTI2023

River thorium concentrations can record bedrock fracture processes including some triggered by distant seismic events

Fractures are integral to the hydrology and geochemistry of watersheds, but our understanding of fracture dynamics is very limited because of the challenge of monitoring the subsurface. Here we provide evidence that long-term, high-frequency measurements of the river concentration of the ultra-trace element thorium (Th) can provide a signature of bedrock fracture processes spanning neighboring watersheds in Colorado. River Th concentrations show abrupt (subdaily) excursions and biexponential decay with approximately 1-day and 1-week time constants, concentration patterns that are distinct from all other solutes except beryllium and arsenic. The patterns are uncorrelated with daily precipitation records or seasonal trends in atmospheric deposition. Groundwater Th analyses are consistent with bedrock release and dilution upon mixing with river water. Most Th excursions have no seismic signatures that are detectable 50 km from the site, suggesting the Th concentrations can reveal aseismic fracture or fault events. We find, however, a weak statistical correlation between Th and seismic motion caused by distant earthquakes, possibly the first chemical signature of dynamic earthquake triggering, a phenomenon previously identified only through geophysical methods.

58 GEOSCIENCES↗