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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Revised monthly energy generation estimates for 1,500 hydroelectric power plants in the United States

Abstract The U.S. Energy Information Administration (EIA) conducts a regular survey (form EIA-923) to collect annual and monthly net generation for more than ten thousand U.S. power plants. Approximately 90% of the ~1,500 hydroelectric plants included in this data release are surveyed at annual resolution only and thus lack actual observations of monthly generation. For each of these plants, EIA imputes monthly generation values using the combined monthly generating pattern of other hydropower plants within the corresponding census division. The imputation method neglects local hydrology and reservoir operations, rendering the monthly data unsuitable for various research applications. Here we present an alternative approach to disaggregate each unobserved plant’s reported annual generation using proxies of monthly generation—namely historical monthly reservoir releases and average river discharge rates recorded downstream of each dam. Evaluation of the new dataset demonstrates substantial and robust improvement over the current imputation method, particularly if reservoir release data are available. The new dataset—named RectifHyd—provides an alternative to EIA-923 for U.S. scale, plant-level, monthly hydropower net generation (2001–2020). RectifHyd may be used to support power system studies or analyze within-year hydropower generation behavior at various spatial scales.

13 HYDRO ENERGY↗
DOE OSTI2023

Diminishing marginal effect in estimating the dissolved organic carbon export from a watershed

Dissolved organic carbon (DOC) can be initially moved from soils to inland waters with surface runoff, and then mineralized, buried, or eventually delivered to the coastal ocean. This land-to-ocean phase of the DOC flux must be accounted for to comprehensively understand the global carbon cycle. To estimate the terrestrial-aquatic DOC leaching, calculating the product of the riverine DOC concentration and the corresponding river discharge measured at the watershed outlet is a common method. However, it is challenging to frequently and exactly record riverine DOC concentrations, thus the relationship between DOC concentrations and discharges (C-Q relationship) are established and used to interpolate the time-series of DOC concentrations. We found that the widely used time-dependent and time-independent C-Q regression models are weak in representing their altered relationship when the discharge is extremely high, which was named as diminishing marginal effect. In this study, we evaluated the performance of two C-Q regression models and discussed possible reasons for the diminishing marginal effect. We suggest that repeated and long-term measurements of the DOC concentration are required to adequately analyze their relationships, especially during the early spring and seasons with heavy precipitations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Trends and drivers of marine fish landings in Portugal since its entrance in the European Union

Abstract Marine landings in Portugal have decreased at a higher rate than fishing effort in the last 20 years. Identifying the variables driving the quantity and composition of landings is pivotal to understand the dynamics of the fisheries sector, which entails complex social and environmental aspects. In this study, we investigate the main drivers of marine fish landings in continental Portugal between 1989 and 2014. To identify common trends in time series, and quantify the importance of environmental factors, we applied a dynamic factor analysis considering four regions and three types of gear (trawling, purse-seine, and a multi-gear fishery). Our results show the importance of fishing effort as the most relevant factor driving marine landings in Portugal, both at the long and short terms. In addition, the effect of environmental factors such as the winter river discharge and the spring East Atlantic Teleconnection index should not be neglected, probably through mechanisms affecting coastal productivity. We provide a comprehensive amount of information that permits to improve our understanding of the trends of the most important commercial species in Portugal during the period of study.

Bueno-Pardo, Juan↗
DOE OSTI2025

The Arctic

The Arctic environment in 2024 continued on a trajectory that has put it in a state far different from that of the twentieth century. Ongoing accumulation of greenhouse gases in the atmosphere continues to quickly warm the Arctic, resulting in rapid changes in the cryosphere that are driving cascading impacts to climate, ecological, and societal systems. Many weather- and climate-related impacts in the Arctic are the result of compounding change, such as increased riverbank erosion, which is proximately due to increased river discharge from higher seasonal precipitation, yet is also exacerbated by thawing permafrost. However, even individual storms occur within very different ocean and ice conditions than were typically present in the late twentieth century. As a result, the impacts, including high winds, excessive precipitation, and coastal inundation, may be quite different nowadays, as exemplified by the October 2024 storm in northwest Alaska that produced severe coastal flooding in several communities. To share some of these impacts with a wider audience, select extreme weather impacts around the greater Arctic have been highlighted through the inclusion of sidebars in recent State of the Climate Arctic chapters (e.g., Benestad et al. 2023; Thoman et al. 2024).

Thoman, Richard L. [Univ. of Alaska, Fairbanks, AK↗
DOE OSTI2021

Characterizing juvenile salmon predation risk during early marine residence

Predation mortality can influence the distribution and abundance of fish populations. While predation is often assessed using direct observations of prey consumption, potential predation can be predicted from co-occurring predator and prey densities under varying environmental conditions. Juvenile Pacific salmon Oncorhynchus spp. (i.e., smolts) from the Columbia River Basin experience elevated mortality during the transition from estuarine to ocean habitat, but a thorough understanding of the role of predation remains incomplete. We used a Holling type II functional response to estimate smolt predation risk based on observations of piscivorous seabirds (sooty shearwater [ Ardenna griseus ] and common murre [ Uria aalge ]) and local densities of alternative prey fish including northern anchovy ( Engraulis mordax ) in Oregon and Washington coastal waters during May and June 2010–2012. We evaluated predation risk relative to the availability of alternative prey and physical factors including turbidity and Columbia River plume area, and compared risk to returns of adult salmon. Seabirds and smolts consistently co-occurred at sampling stations throughout most of the study area (mean = 0.79 ± 0.41, SD), indicating that juvenile salmon are regularly exposed to avian predators during early marine residence. Predation risk for juvenile coho ( Oncorhynchus kisutch ), yearling Chinook salmon ( O . tshawytscha ), and subyearling Chinook salmon was on average 70% lower when alternative prey were present. Predation risk was greater in turbid waters, and decreased as water clarity increased. Juvenile coho and yearling Chinook salmon predation risk was lower when river plume surface areas were greater than 15,000 km 2 , while the opposite was estimated for subyearling Chinook salmon. These results suggest that plume area, turbidity, and forage fish abundance near the mouth of the Columbia River, all of which are influenced by river discharge, are useful indicators of potential juvenile salmon mortality that could inform salmonid management.

Phillips, Elizabeth M. (ORCID:0000000327752563)↗
DOE OSTI2026

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗
DOE OSTI2022

Data and scripts associated with the manuscript "Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling"

This package contains the data and scripts used in "Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling" (Jiang et al., 2022). The ARW_SWAT.zip file contains the SWAT simulation and the sensitivity analysis result in the American River Watershed. The Portage_SWAT.zip file contains the SWAT simulation and the sensitivity analysis result in the Portage River Watershed. The src folder contains the source code of sensitivity analysis and plotting functions. The notebooks folder contains the Jupyter notebooks for performing sensitivity analysis and other post analyses.Global Sensitivity Analysis (GSA) often is applied to assess the sensitivity of model outputs to their inputs using ensemble simulations. However, increasing model complexity and the associated computational cost have limited the use of most GSA approaches for process-based watershed models. We propose to use Mutual Information (MI) as a computationally efficient GSA method for watershed modeling. Such MI computed from several hundred realizations usually can capture nonlinear relationships between inputs and outputs of interest. We perform MI-based watershed sensitivity analyses in studies of the Portage River Watershed in Ohio and the American River Watershed in Washington. In these studies, MI is used to evaluate the sensitivity of river discharges simulated by the Soil and Water Assessment Tool to no less than 20 parameters for each watershed. Our MI-based sensitivity analyses achieved convergence with about 300~500 realizations, a small fraction of the ensemble size (i.e., several thousand) required by the Sobol method. Nevertheless, MI yields similar sensitivity ranking compared to the Sobol method, especially for sensitive parameters. Our study thus sheds new light on the use of MI as an affordable GSA method for computationally intensive models such as the hyper-resolution, watershed hydrobiogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hydrological dataset for reservoir sedimentation in Texas

This dataset provides comprehensive hydrological information about reservoir sedimentation in Texas, including observed and remotely sensed sediment concentration, river discharge, watershed boundary, lake geometry, reservoir capacity, land use and land cover (LULC), and population data. In-depth interpretation of the dataset is elaborated in in a journal article, entitled " Sedimentation and nonlinear trapping in Texas reservoirs identified using remote sensing and bathymetric survey records (will be accepted soon at Water Resources Research)."

Lee, Jiyong [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Influences on Discharge Partitioning on a Large River Delta: Case Study of the Mississippi-Atchafalaya Diversion, 1926-1950

The modern Mississippi River (M.R.) Delta is plumbed by the Mississippi and Atchafalaya rivers, setting water and sediment dispersal pathways for Earth’s fifth-largest river system. The Atchafalaya River’s (A.R.) partial annexation of discharge from the M.R., particularly between 1926 and 1950, prompted warnings of a rapid river avulsion and the construction of the Old River Control Structure to regulate flow. Natural and anthropogenic causes of this discharge annexation are difficult to disentangle. Here, we develop and validate a hydrodynamic model of flow partitioning through the historic channel network. We then isolate how several key changes to the system affected discharge partitioning and stage at the A.R.-M.R. diversion. Simulations show that erosion of the upper A.R. can account for 73% of the water discharge increase. Dredging in the lower A.R. between 1932 and 1950 can account for 35% of the water discharge increase, and was also an important control on shear stress distribution. The lower M.R. was slightly erosional during this period, and therefore hindered the A.R. discharge increase. Significant lacustrine delta deposition in A.R. had little effect on partitioning. These findings highlight the importance of A.R. enlargement processes on avulsion dynamics at this site. Given the essential nature of this river junction to the society, transportation, and commerce of the United States, improved attribution of discharge increases may lead to future management strategies that are broadly impactful.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine Learning Assisted Gap-Filled Discharge Data for the East River Community Watershed, Colorado, for Water Years 2014-2021

This dataset contains a collection of machine learning assisted gap-filled discharge data created for all discharge stations across the East River Watershed, Colorado. This data was generated by using raw discharge data collected by Rosemary Carroll, and conducting a random forest machine learning analysis to gap-fill discharge data across all years at the hourly time level. Discharge data with gaps creates problems for analysis of measured and modeled fluxes of carbon and nitrogen exported out of each sub-watershed. Gap-filled data is also required as an input to surface water models, which helps to address our main research question related to how snowmelt timing impacts the timing and magnitude of nitrogen exports. Data is provided in one csv file.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2023

Data and scripts associated with "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams."

This data package is associated with the publication "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams." in review at Limnology and Oceanography (Roley et al. 2023). This study focuses on understanding ecosystem metabolism for the Hanford Reach of the Columbia River in Washington state, a free-flowing stretch with a substantial discharge. Large rivers have been overlooked compared to small and medium rivers due to the challenges associated with measurements. Our study presents novel ways to address these challenges and highlights that metabolism patterns in large rivers differ from those observed in small-medium rivers and requires the application of knowledge and tools beyond those implemented for smaller rivers.This data package includes the data and R scripts for the analyses described in Roley et al. 2023. It includes dissolved oxygen and temperature data from a dissolved oxygen HOBO sensor, light data collected from the National Solar Radiation Database (https://nsrdb.nrel.gov/) and hydrologic variables estimated from the MASS-1 model (Niehus et al.; 2014). It also includes metabolism estimates (gross primary production, ecosystem respiration, and net ecosystem production) estimated via streamMetabolizer (Appling et al.; 2018). All analyses in the paper can be replicated with these data and scripts.The data package is comprised of one main data folder. The folder includes (1) file-level metadata (flmd); (2) a data dictionary (dd) for each data file; (3) data files; and (4) R scripts for metabolism estimates and data analysis. All files are .R, .csv, or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

20 Year Daily Average Modeled Velocity and Discharge for Openwater Season at Five Communities on Kuskokwim River, Alaska

This dataset includes modeled velocity and discharge at five communities in the middle Kuskokwim River region: Aniak, Chuathbaluk, Crooked Creek, Red Devil and Stony River. Modeled velocities and discharge represent daily averages calculated for the openwater season (OWS) from June 1 - October 18 over the 20 year period 2000-2019 using the raw data described below and included in this archive; full details of methodology are described in (Brown et al. submitted to Renewable Energy). Raw data inputs to inform the modeling process include in-situ measurements of 1) discharge with an acoustic Doppler current meter (ADCP, 600kHz Workhorse Rio Grande by Teledyne RD Instruments) and a global positioning receiver (GPS, Trimble 5700, 5800 and R8) utilizing Real Time Kinematic (RTK) GPS mode over 1-2 days at each site in 2009 or 2010 (Ravens 2014), and 2) river stage with a water level logger (HOBO U20-001-01 by Onset) over 2-9 weeks at each site (Ravens 2014), 3) in addition to a 20 year long-term discharge record collected at the USGS stream gage site in Crooked Creek (USGS 2016). Raw data (discharge and stage) are included in this archive for two additional communities: Lower Kalskag and Sleetmute, where modeled velocities were not calculated due to equipment failure or loss. The USGS stream gage data at Crooked Creek (USGS 2016) and stream gage methodology (Turnipseed and Sauer 2010) are publicly available online, so the data are not duplicated here.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Spatial Trends and Drivers of Bedload and Suspended Sediment Fluxes in Global Rivers

Abstract Bedload is notoriously challenging to measure and model; its dynamics, therefore, remains largely unknown in most fluvial systems worldwide. We present results from a global scale bedload flux model as part of the WBMsed modeling framework that well predict the distribution of water discharge, suspended sediment and bedload. The sensitivity of bedload predictions to river slope, particle size, discharge, river width, and suspended sediment were analyzed, showing the model to be most responsive to spatial dynamics in river discharge and slope. The relationship between bedload and total sediment flux is analyzed globally, and for representative longitudinal river profiles (Amazon, Mississippi, and Lena Rivers). The results show that while the proportion of bedload decreases from headwaters to the coasts, there is considerable variability between basins and along river corridors. The topographic and hydrological longitudinal profiles of rivers are shown to be the key drivers of bedload trends, with fluctuations in slope controlling its more local dynamics. Estimates of water and sediment fluxes to global oceans from 2,067 largest river outlets (draining 67% of the global continental area) are provided. Estimated water discharge at 30,579 km 3 /y corresponds well to past estimates; however, sediment flux is higher. Total global particulate load of 17.8 Gt/y is delivered to global oceans, 14.8 Gt/y as washload, 1.1 Gt/y as bedload, and 2.6 Gt/y as suspended bed material. The largest 25 rivers are predicted to transport more than half of the total sediment flux to global oceans.

Cohen, Sagy↗
DOE OSTI2021

CO2 partial pressure and fluxes in the Amazon River Plume using in situ and remote sensing data

Estimations of the global carbon budget include a quantitative understanding of the evolving processes that occur along river-to-ocean gradients. However, high spatiotemporal resolution observations of these processes are limited. Here we present in situ measurements of the partial pressure of CO2 (pCO2) made through the Amazon River plume (ARP) during different discharge seasons, from 2010-2012. We evaluated the spatiotemporal distribution of pCO2 using Soil Moisture and Ocean Salinity (SMOS) satellite observations for each hydrologic period in the ARP. Regression models were used to estimate pCO2 at the ARP for the period of 2010-2014. From these distributions we calculated sea-air gas exchange of CO2 between the plume waters and the atmosphere (F_co2^sea). Intra-annual variability of F_co2^sea was related to discharge at the river mouth and ocean currents as well as trade winds in the plume. Climatic events during the study period had a significant impact on the F_co2^sea. Including the plume area closer to the river mouth makes the ARP a net source of CO2 with an annual net sea-air flux of 8.6 ±7.1 Tg C y-1 from 2011-2014.

Amazon↗