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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Basin-Scale Relicensing Opportunity

This dataset contains 1,261 hydropower facilities with associated Federal Energy Regulatory Commission (FERC) relicensing metrics. Anticipated FERC license renewal dates are summarized by river reach for observing areas of opportunities for basin-wide collaboration on environmental mitigations. Identifying rivers and basins with facilities that have similar anticipated Federal Energy Regulatory Commission (FERC) relicensing dates may be one potential indicator that multiple licensees within the same basin may be willing to collaborate on a basin-scale relicensing effort. The hydropower relicensing process requires long-term resource allocation by agencies, hydropower owner/operators, non-governmental organizations, and tribal, state, and federal governments. Basin-scale hydropower relicensing has begun to receive attention as a potential solution for reducing licensing timelines, costs, and uncertainty which can provide benefits to a broad spectrum of participants in the licensing process. This dataset contains one a data file in comma separated (*.csv) format, a data dictionary in *.csv format, and a user guide in *.pdf format. These data are also available as an interactive web map available at:

13 HYDRO ENERGY↗
DOE OSTI2023

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025). The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052. This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. In addition to the readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) and subfolders containing data, figures, and scripts. The data folder contains datasets used for the analyses in the manuscript in image, text-delimited or geospatially-referenced formats. The figures folder contains the figures from the manuscript in different formats. The scripts folder contains all of the scripts used to complete the analyses in the manuscript. All files are .csv, .rds, .dbf, .prj, .shp, .shx, .jpg, .png, .R, .Rproj, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Explicit quantification of residence and flushing times in the Salish Sea using a sub-basin scale shoreline resolving model

The Salish Sea, located in the Pacific Northwest region of North America has complex currents and circulation features distributed over numerous interconnected deep basins with islands. Increased risk of exposure to oil spills and untreated wastewater from maritime emergencies and treatment plant failures have led to a need for quantifying residence and flushing characteristics at a sub-basin scale using a shoreline resolving hydrodynamic model. An unstructured grid model of the Salish Sea was developed using FVCOM with a ≈75-100m shoreline resolution. In addition to 7 tides and 23 salinity and temperature monitoring stations, an extensive currents data set from 135 stations collected over a span of three years was used for skill assessment and validation. Explicit forward computations were then conducted to define and quantify residence and flushing times in various sub-basins of interest using (a) Lagrangian particles and (b) Numerical/virtual dye experiments. The results in most basins show expected seasonal variability with longer flushing time associated with summer lower tides and lower freshwater inflows. However, contrary to expectation, flushing time is significantly longer in wintertime in large fjord-like basins such as Hood Canal (≈138 days), likely due to increased stratification and reduced mixing. The flushing time for the Puget Sound region of the Salish Sea is ≈115 days, while Georgia Basin is 240 days when analyzed as stand-alone basins with zero background concentrations. When examined as part of the flushing of the entire Puget Sound filled with virtual dye, the compounded flushing times for embedded sub-basins can be significantly longer in order of magnitudes and largely dictated by the flushing time of Puget Sound. The computed residence and flushing time scales tabulated over 36 sub-basins provide an improved understanding of water renewal in the system, informing pollution management actions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Energy↗
NASA NTRS1991

Basin-scale estimates of oceanic primary production by remote sensing - The North Atlantic

The monthly averaged CZCS data for 1979 are used to estimate annual primary production at ocean basin scales in the North Atlantic. The principal supplementary data used were 873 vertical profiles of chlorophyll and 248 sets of parameters derived from photosynthesis-light experiments. Four different procedures were tested for calculation of primary production. The spectral model with nonuniform biomass was considered as the benchmark for comparison against the other three models. The less complete models gave results that differed by as much as 50 percent from the benchmark. Vertically uniform models tended to underestimate primary production by about 20 percent compared to the nonuniform models. At horizontal scale, the differences between spectral and nonspectral models were negligible. The linear correlation between biomass and estimated production was poor outside the tropics, suggesting caution against the indiscriminate use of biomass as a proxy variable for primary production.

Platt, Trevor↗
DOE OSTI2022

Numerical Simulation of Commercial-Scale CO2 Storage in a Saline Formation Evaluating Basin-Scale Pressure Interference and CO2 Plume Commingling

Presentation at NETL Carbon Management Project Review Meeting held in Pittsburgh, Pennsylvania, August 15–19, 2022. The presentation provides quantitative evaluation of subsurface pressure interference and emphasizes the importance of interproject coordination among stakeholders associated with multi-project geologic CO2 storage in a shared sedimentary basin.

Wijaya, Nur↗
DOE OSTI2017

Linking basin-scale and pore-scale gas hydrate distribution patterns in diffusion-dominated marine hydrate systems: DIFFUSION-DRIVEN HYDRATE GROWTH IN SANDS

The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1 to 20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two- dimensional and basin-scale three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. As a result, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial.

03 NATURAL GAS↗
DOE OSTI2022

A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion

Abstract. Rivers and river habitats around the world are under sustained pressure from human activities and the changing global environment. Our ability to quantify and manage the river states in a timely manner is critical for protecting the public safety and natural resources. In recent years, vector-based river network models have enabled modeling of large river basins at increasingly fine resolutions, but are computationally demanding. This work presents a multistage, physics-guided, graph neural network (GNN) approach for basin-scale river network learning and streamflow forecasting. During training, we train a GNN model to approximate outputs of a high-resolution vector-based river network model; we then fine-tune the pretrained GNN model with streamflow observations. We further apply a graph-based, data-fusion step to correct prediction biases. The GNN-based framework is first demonstrated over a snow-dominated watershed in the western United States. A series of experiments are performed to test different training and imputation strategies. Results show that the trained GNN model can effectively serve as a surrogate of the process-based model with high accuracy, with median Kling–Gupta efficiency (KGE) greater than 0.97. Application of the graph-based data fusion further reduces mismatch between the GNN model and observations, with as much as 50 % KGE improvement over some cross-validation gages. To improve scalability, a graph-coarsening procedure is introduced and is demonstrated over a much larger basin. Results show that graph coarsening achieves comparable prediction skills at only a fraction of training cost, thus providing important insights into the degree of physical realism needed for developing large-scale GNN-based river network models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Limits on differentiation of melt sheets from basin-scale lunar impacts

In the literature on cratering, one frequently finds allusions to the 'sheet' of impact melt that supposedly forms in the aftermath of any large impact. The presumption seems to be that either (1) most of the impact melt is formed virtually at the surface, or else (2) most of the melt inevitably collects into a near-surface, roughly sill-shaped 'sheet,' soon after the impact. However, in basin-scale impacts on the mature Moon, neither of these scenarios appears likely. Differentiation of impact melts on the Moon is hampered by similarity in density vs. the porous lunar crust, and by the adverse melt/'displaced' matter ratio that results from the lunar g.

Warren, Paul H.↗
DOE OSTI2025

Different methods of estimating riverbed sediment grain size diverge at the basin scale

Introduction: The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (D50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual D50 measurements are time-consuming and ignore larger grains, while approaches to model D50 based on catchment characteristics may over-generalize and miss site-scale heterogeneity. Machine learning-enabled object detection methods like You Only Look Once (YOLO) provides an alternative that enables estimation of D50 that is faster than manual measurements and more site-specific than predictions based on catchment characteristics. Methods: To understand the potential role of object detection methods for improving understanding of D50, we compared D50 estimates made manually, predicted from catchment characteristics, and using a YOLO-enabled approach across the Yakima River Basin. Results: We found distinct differences between methods for D50 averages and variability, and relationships between D50 estimates and basin characteristics. Discussion: We discuss the advantages and limitations of object detection methods versus current methods, and explore potential future directions to combine D50 methods to better estimate spatiotemporal variation of D50, and improve incorporation into basin-scale models.

grain size distribution↗
DOE OSTI2026

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗
NASA NTRS2009

One-Hundred-km-Scale Basins on Enceladus: Evidence for an Active Ice Shell

Stereo-derived topographic mapping of 50% of Enceladus reveals at least 6 large-scale, ovoid depressions (basins) 90-175 km across and 800-to-1500 m deep and uncorrelated with geologic boundaries. Their shape and scale are inconsistent with impact, geoid deflection, or with dynamically supported topography. Isostatic thinning of Enceladus ice shell associated with upwellings (and tidally-driven ice melting) can plausibly account for the basins. Thinning implies upwarping of the base of the shell of 10-20 km beneath the depressions, depending on total shell thickness; loss of near-surface porosity due to enhanced heat flow may also contribute to basin lows. Alternatively, the basins may overly cold, inactive, and hence denser ice, but thermal isostasy alone requires thermal expansion more consistent with clathrate hydrate than water ice. In contrast to the basins, the south polar depression (SPD) is larger (~350 wide) and shallower (~0.4-to-0.8 km deep) and correlates with the area of tectonic deformation and active resurfacing. The SPD also differs in that the floor is relatively flat (i.e., conforms roughly to the global triaxial shape, or geoid) with broad, gently sloping flanks. The relative flatness across the SPD suggests that it is in or near isostatic equilibrium, and underlain by denser material, supporting the polar sea hypothesis of Collins and Goodman. Near flatness is also predicted by a crustal spreading origin for the "tiger stripes (McKinnon and Barr 2007, Barr 2008); the extraordinary, high CIRS heat flows imply half-spreading rates in excess of 10 cm/yr, a very young surface age (~250,000 yr), and a rather thin lithosphere (hence modest thermal topography). Topographic rises in places along the outer margin of the SPD correlate with parallel ridges and deformation along the edge of the resurfaced terrain, consistent with a compressional, imbricate thrust origin for these ridges, driven by the spreading.

Schenk, Paul M.↗
NASA NTRS2020

Basin-Scale River Runoff Estimation from GRACE Gravity Satellites, Climate Models and In Situ Observations: a Case Study in the Amazon Basin

River runoff is estimated as a water budget residual using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage time series, ERA5 reanalysis data, and precipitation observations for January 2003 through December 2015 for the Obidos upstream drainage basin and for the entire Amazon basin. Estimated runoff based on the water budget agrees remarkably well with in situgauge observations at Obidos, especially at seasonal time scales, with nearly perfect phase agreementbut slightly larger seasonal amplitude. The discrepancy in the seasonal amplitude maybe attributed to underestimation of river gauge runoff during the wet season when water overflows the riverbanks. The ERA5 model appears to overestimate long-term mean evapotranspiration in the Amazon by ~2 cm/monthb ased on comparisons with precipitation and runoff observations. Using precipitation data based on satellites and gauge observations relative to gauge observations alone improved agreement between water budget runoff estimates and in situ runoff observations. Seasonal variations in ERA5 simulated runoff are about twice as large as those from in situobservations and show a large phase lag as well. Water budget based runoff for the entire Amazon (~ 7,200 km3averaged 29over the 13 yr period) is significantly larger than observed runoff (~5,700 km3) at notably larger than previous estimates for the entire Amazon. These differences may be partly related to submarine runoff from the Amazon basin that cannot be captured by surface gauges.

Jianli Chen↗
NASA NTRS2016

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗
DOE OSTI2022

Basin-scale biogeography of marine phytoplankton reflects cellular-scale optimization of metabolism and physiology

Extensive microdiversity within Prochlorococcus, the most abundant marine cyanobacterium, occurs at scales from a single droplet of seawater to ocean basins. To interpret the structuring role of variations in genetic potential, as well as metabolic and physiological acclimation, we developed a mechanistic constraint-based modeling framework that incorporates the full suite of genes, proteins, metabolic reactions, pigments, and biochemical compositions of 69 sequenced isolates spanning the Prochlorococcus pangenome. Optimizing each strain to the local, observed physical and chemical environment along an Atlantic Ocean transect, we predicted variations in strain-specific patterns of growth rate, metabolic configuration, and physiological state, defining subtle niche subspaces directly attributable to differences in their encoded metabolic potential. Predicted growth rates covaried with observed ecotype abundances, affirming their significance as a measure of fitness and inferring a nonlinear density dependence of mortality. Our study demonstrates the potential to interpret global-scale ecosystem organization in terms of cellular-scale processes.

59 BASIC BIOLOGICAL SCIENCES↗