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At least 667 records · Page 37

Quantifying the Uncertainty of the Future Hydrological Impacts of Climate Change: Comparative Analysis of an Advanced Hierarchical Sensitivity in Humid and Semiarid Basins

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. Further, the results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions.

54 ENVIRONMENTAL SCIENCES↗

The Amazon and La Plata River Basins as Moisture Sources of South America: Climatology and Intraseasonal Variability

Abstract Land‐atmosphere interactions are critical for precipitation (PPT) over South America where terrestrial evapotranspiration (ET) constitutes a significant fraction of moisture for rainfall over the ecologically and socio‐economically vital Amazon (AMZ) and La Plata (LPB) river basins. We quantify the contribution of ET from AMZ and LPB to PPT over the continent with a focus on the intraseasonal time scale. Using numerical water tracers embedded in the Weather Research and Forecasting model we track the moisture originating from the two basins. Our findings indicate that approximately 40% of annual rainfall over the eastern foothills of the Andes originates as AMZ ET, and nearly 30% of rainfall over northern Argentina originates as LPB ET. Analysis of moisture transport during both phases of the dominant intraseasonal oscillation pattern over South America reveals an intraseasonal “sloshing” of LPB moisture between the South Atlantic convergence zone (SACZ) and southeastern South America (SESA) regions. AMZ and LPB each supply approximately 6% of moisture for SACZ PPT during periods of intraseasonal enhancement (positive anomalies), highlighting the importance of moisture from the Atlantic Ocean. For the SESA region, LPB supplies 26% of the moisture for PPT during periods of intraseasonal enhancement while AMZ supplies 5%.

54 ENVIRONMENTAL SCIENCES↗

Utah FORGE: Earth Model Mesh Data for Selected Surfaces

This submission contains a number of data files with vertices of meshed/interpolated surfaces used in the Phase 2B earth model. Examples include land surface (based on 10-meter DEM), the granitoid-basin fill contact, several faults, and also interpolated temperature isosurfaces for 175 and 225 degrees C. All data are georeferenced to UTM, zone 12N, NAD 83, NAVD 88.

15 GEOTHERMAL ENERGY↗

How Much Global Burned Area Can Be Forecast on Seasonal Time Scales Using Sea Surface Temperatures?

Large-scale sea surface temperature (SST) patterns influence the interannual variability of burned area in many regions by means of climate controls on fuel continuity, amount, and moisture content. Some of the variability in burned area is predictable on seasonal timescales because fuel characteristics respond to the cumulative effects of climate prior to the onset of the fire season. Here we systematically evaluated the degree to which annual burned area from the Global Fire Emissions Database version 4 with small fires (GFED4s) can be predicted using SSTs from 14 different ocean regions. We found that about 48 of global burned area can be forecast with a correlation coefficient that is significant at a p < 0.01 level using a single ocean climate index (OCI) 3 or more months prior to the month of peak burning. Continental regions where burned area had a higher degree of predictability included equatorial Asia, where 92% of the burned area exceeded the correlation threshold, and Central America, where 86% of the burned area exceeded this threshold. Pacific Ocean indices describing the El Nino-Southern Oscillation were more important than indices from other ocean basins, accounting for about 1/3 of the total predictable global burned area. A model that combined two indices from different oceans considerably improved model performance, suggesting that fires in many regions respond to forcing from more than one ocean basin. Using OCI-burned area relationships and a clustering algorithm, we identified 12 hotspot regions in which fires had a consistent response to SST patterns. Annual burned area in these regions can be predicted with moderate confidence levels, suggesting operational forecasts may be possible with the aim of improving ecosystem management.

Chen, Yang↗

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗

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↗

Future increases in Amazonia water stress from CO 2 physiology and deforestation

Several different drivers are contributing to climate change within the Amazon basin, including forcing from greenhouse gases and aerosols, plant physiology responses to rising CO 2 , and deforestation. Attribution among these drivers has not been quantified for Shared Socioeconomic Pathway (SSP) climate simulations. Here we identify the contribution of CO 2 physiology and deforestation to future hydroclimate change in the Amazon basin by combining information from four experiments and eight different Earth system models in Coupled Model Intercomparison Project Phase 6. Together, forcing from CO 2 physiology and deforestation account for about 44% of the projected annual precipitation decline, 48% of surface relative humidity decline and 11% of warming over the Amazon basin by 2100 for SSP3-7.0. Further, other Coupled Model Intercomparison Project Phase 6 SSP simulations have similar contributions from the two drivers. Insight from our attribution analysis can aid in identifying research priorities aimed at reducing uncertainty in future projections of water availability, carbon dynamics and wildfire risk.

54 ENVIRONMENTAL SCIENCES↗

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↗

A groundwater convection model for Rio Grande rift geothermal resources

It has been proposed that forced convection, driven by normal groundwater flow through the interconnected basins of the Rio Grande rift is the primary source mechanism for the numerous geothermal anomalies along the rift. A test of this concept using an analytical model indicates that significant forced convection must occur in the basins even if permeabilities are as low as 50-200 millidarcies at a depth of 2 km. Where groundwater flow is constricted at the discharge areas of the basins forced convection can locally increase the gradient to a level where free convection also occurs, generating surface heat flow anomalies 5-15 times background. A compilation of groundwater data for the rift basins shows a strong correlation between constrictions in groundwater flow and hot springs and geothermal anomalies, giving strong circumstantial support to the convection model.

Morgan, P.↗

Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES) Final Technical Report for effort at the University of Texas at Austin Award DE-SC0008083 March 2016 - August 2017

Mass loss from the Greenland and Antarctic ice sheets is accelerating. Although ice sheet models have improved in recent years, much work is needed to make these models robust and efficient on continental scales and to quantify uncertainties in their projected outputs. The University of Texas at Austin's role in the PISCEES project is to provide guidance on how best to apply uncertainty quantification strategies to evaluating uncertainties in simulations of Greenland and Antarctic contributions to sea level rise in response to environmental forcing. Here we report on several activities that involved project members at UTA including Section 2.1 where we provide a broader overview of challenges to use UQ methods on ice ow modeling. Within Section 2.2 we describe the progress and challenges that remain for implementing important aspects of our "end-to-end" UQ work flow. In sum, we had a break-through in realizing the potential for implementing Active Subspace strategies making use of existing experiments exploring the sensitivity of the Greenland ice sheet flow to uncertain basal traction parameters. Section 2.3 presents progress that is being made to explore the effect of uncertainties in bed topography on stability of Thwaites basin, West Antarctica, using the BISICLES ice flow model. This effort is joint with Dan Martin at LBNL and a graduate student being co-mentored by Jackson. The results provide a compelling test case for the BISICLES ice flow model to address an important science question concerning the role of uncertain boundary conditions on ice sheet contributions to sea level rise.

54 ENVIRONMENTAL SCIENCES↗

sRecovery Act: Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO 2 Storage

This study focuses on evaluating the feasibility and suitability of using the Jurassic/Triassic (J/TR) sediments of the South Georgia Rift basin (SGR) for CO 2 storage in southern South Carolina and southern Georgia The SGR basin in South Carolina (SC), prior to this project, was one of the least understood rift basin along the east coast of the U.S. In the SC part of the basin there was only one well (Norris Lightsey #1) the penetrated into J/TR. Because of the scarcity of data, a scaled approach used to evaluate the feasibility of storing CO 2 in the SGR basin. In the SGR basin, 240 km (~149 mi) of 2-D seismic and 2.6 km2 3-D (1 mi2) seismic data was collected, process, and interpreted in SC. In southern Georgia 81.3 km (~50.5 mi) consisting of two 2-D seismic lines were acquired, process, and interpreted. Seismic analysis revealed that the SGR basin in SC has had a very complex structural history resulting the J/TR section being highly faulted. The seismic data is southern Georgia suggest SGR basin has not gone through a complex structural history as the study area in SC. The project drilled one characterization borehole (Rizer # 1) in SC. The Rizer #1 was drilled but due to geologic problems, the project team was only able to drill to 1890 meters (6200 feet) instead of the proposed final depth 2744 meters (9002 feet). The drilling goals outlined in the original scope of work were not met. The project was only able to obtain 18 meters (59 feet) of conventional core and 106 rotary sidewall cores. All the conventional core and sidewall cores were in sandstone. We were unable to core any potential igneous caprock. Petrographic analysis of the conventional core and sidewall cores determined that the average porosity of the sedimentary material was 3.4% and the average permeability was 0.065 millidarcy. Compaction and diagenetic studies of the samples determined there would not be any porosity or permeability at depth in SC. In Georgia there appears to be porosity in the J/TR section based on neutron log porosity values. The only zones in Rizer #1 that appear to be porous were fractured diabase units where saline formation water was flowing into the borehole. Two geocellular models were created for the SC and GA study area. Flow simulation modeling was performed on the SC data set. The injection simulation used the newly acquired basin data as well as the Petrel 3-D geologic model that included geologic structure. Due to the new basin findings as a result of the newly acquired data, during phase two of the modeling the diabase unit was used as reservoir and the sandstone units were used as caprock. Conclusion are: 1) the SGR basin is composed of numerous sub-basins, 2) this study only looked at portions of two sub-basins, 3) in SC, 30 million tonnes of CO 2 can be injected into the diabase units if the fracture network is continuous through the units, 4) due to the severity of the faulting there is no way of assuring the injected CO 2 will not migrate upward into the overlying Coastal Plain aquifers, 5) in Georgia there appears to porous zones in the J/TR sandstones, 6) as in SC there is faulting in the sub-basin and the seismic suggest the faulting extends upward into the Coastal Plain making that area not suitable for CO 2 sequestration, 7) the complex faulting observed at both study areas appear to be associated with transfer fault zones (Heffner 2013), if sub-basins in the Georgia portion of the SGR basin can be located that are far away from the transfer fault zones there is a strong possibility of sequestering CO 2 in these areas, and 9) the SGR basin covers area in three states and this project only studied two small areas so there is enormous potential for CO 2 sequestration in other portions the basin and further research needs to be done to find these areas.

58 GEOSCIENCES↗

Intramolecular 13 C isotope distributions of butane from natural gases

A single-step method allowing the measurement of 13 C intramolecular distribution of butane isomers (n- and i-butane) from natural gas samples was developed. The method builds up on the one that has been developed for propane, using on-line pyrolysis followed by isotope analysis of the pyrolytic fragments. The isotopic filiation between n-butane and its pyrolytic fragments was elucidated using samples spiked with 13 C on terminal positions. The isotopic filiation for i-butane could not be shown experimentally due to the lack of commercially available enriched i-butane. We thus used a recent model named Reaction Mechanism Generator (RMG) to assess the origin of the fragments arising from i-butane pyrolysis. Butanes from natural gas samples from the Carnarvon Basin (Australia) and the Arkoma Basin (USA) were analyzed. The results are consistent with a model for thermogenic natural gas generation and suggest that combined intramolecular isotope composition of propane and n-butane can be related to the gas maturity. In addition, the method allows the detection and shed light on the mechanism of n-butane and i-butane biodegradation in natural gas reservoirs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact phenomena as factors in the evolution of the Earth

It is estimated that 30 to 200 large impact basins could have been formed on the early Earth. These large impacts may have resulted in extensive volcanism and enhanced endogenic geologic activity over large areas. Initial modelling of the thermal and subsidence history of large terrestrial basins indicates that they created geologic and thermal anomalies which lasted for geologically significant times. The role of large-scale impact in the biological evolution of the Earth has been highlighted by the discovery of siderophile anomalies at the Cretaceous-Tertiary boundary and associated with North American microtektites. Although in neither case has an associated crater been identified, the observations are consistent with the deposition of projectile-contaminated high-speed ejecta from major impact events. Consideration of impact processes reveals a number of mechanisms by which large-scale impact may induce extinctions.

Grieve, R. A. F.↗

A study of the break-up characteristics of Chena River Basin using ERTS imagery

The author has identified the following significant results. The Chena River Basin was selected because of the availability of ground truth data for comparison. Very good agreement for snow distribution and rates of ablation was found between the ERTS-1 imagery, the snowmelt model, and field measurements. Monitoring snowmelt rates for relatively small basins appears to be practical. The main limitation of the ERTS-1 imagery is the interval of coverage. More frequent overflights providing coverage are needed for the study of transient hydrologic events. ERTS-1 data is most useful when used in conjunction with snowmelt prediction models and existing snow course data. These results should prove very useful in preliminary assessment of hydrologic conditions in ungaged watersheds and will provide a tool for month-to-month volume forecasting.

Carlson, R. F.↗

Train, Inform, Borrow, or Combine? Approaches to Process–Guided Deep Learning for Groundwater–Influenced Stream Temperature Prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

54 ENVIRONMENTAL SCIENCES↗

Dayflow-PR: High-Resolution Streamflow Reanalysis for Puerto Rico, Version 1.0

This dataset presents a high-resolution historical streamflow reanalysis for NHDPlusV2 stream reaches across Puerto Rico (PR) spanning 1950 - 2019. The reanalysis is generated using the calibrated VIC-RAPID hydrologic modeling framework at the Hydrologic Unit Code Sub-basin (HUC08) scale, forced with sub-daily and daily meteorological forcings from Daymet. Runoff is simulated on 1- and 6-km grids, and the resulting total runoff is routed through the NHDPlusV2 river network using the RAPID routing model to produce Naturalized Streamflow Reanalysis. Where complete observational records are available over 1980 - 2019, streamflows are assimilated (substituted) and subsequently routed downstream through the river network to produce Assimilated Streamflow Reanalysis. The dataset includes streamflow outputs from eight distinct hydrologic modeling configurations along with key performanc evaluation metrics at daily and monthly scales, supporting a wide range of water resource applications. This dataset is derived to support the Non-Powered Dam Assessment, as well as 9505 Secure Water Assessment projects for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details, refer to Ghimire et al. (2023), Kao et al. (2024), and Ghimire et al. (2025).

13 HYDRO ENERGY↗

Vitality models found useful in modeling tag-failure times in acoustic-tag survival studies

Abstract Acoustic telemetry studies often rely on the assumption that premature tag failure does not affect the validity of inferences. However, in some cases this assumption is possibly or likely invalid and it is necessary to apply a correction to estimation procedures. The question of which approaches and specific models are best suited to modeling acoustic tag failures has received little research attention. In this short communication, we present a meta-analysis of 42 acoustic tag-life studies, originally used to correct survival studies involving outmigrating juvenile salmonids in the Columbia/Snake river basin. We compare the performance of nine alternative parametric models including common failure–time/survival models and the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013). The tag-life studies used acoustic tags from three different tag manufacturers, had expected lifetimes between 12 and 61 days, and had dry weights ranging from 0.22 to 1.65 g. In 57% of the cases, the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013) fit the tag-failure times best. The vitality models were also the second-best choices in 17% of the cases. Together, the vitality models, log-logistic, (19%), and gamma models (14%) accounted for 90% of the models selected. Unlike more traditional failure–time models (e.g., Weibull, Gompertz, gamma, and log-logistic), the vitality models are capable of characterizing both the early onset of tag failure due to manufacturing errors and the anticipated battery life. We provide further guidance on appropriate sample sizes (50–100 tags) and procedures to be considered when applying precise tag-life corrections in release–recapture survival studies.

Skalski, John R. (ORCID:0000000270702505)↗