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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tracking snowmelt during hydrological surface processes using a distributed hydrological model in a mesoscale basin on the Tibetan Plateau

We report that mountain snowpack is an important water resource for the high altitude and latitude regions where the terrain is complex. However, the snowmelt pathway and its actual contribution to streamflow and soil moisture are rarely reported and remain unclear in such regions. To fill in this knowledge gap, we incorporate a snowmelt pathway tracking algorithm to a high-resolution physics-based distributed-hydrology-soil-vegetation model (DHSVM), to track snowmelt movement and quantify snowmelt contributions in the surface hydrologic processes. A simple reservoir operation scheme is also incorporated in the model. The modified model is applied to a dammed meso-scale watershed in the northeast Tibetan Plateau, China to study the snow and reservoir effects. The results show that annual snow contribution to soil moisture (SC-SM) and snow contribution to streamflow (SC-S) significantly decrease over 1965-2019. At a monthly scale, SC-SM has the largest amplitude at the top soil layer and its peak in the deeper layer lags behind the upper layer, and mean monthly SC-S at all stations show bimodal distributions corresponding to snowfall season. Reservoir regulation has subtle impacts (≤2.0%) on SC-S. If the current climate change rate continues, monthly and annual streamflow at the outlet will decrease primarily due to snowpack reduction. To mitigate climate change impacts, better water resource management is needed in this watershed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Floating Photovoltaics in Hydropower Reservoirs in the United States

This report presents a comprehensive analysis of the feasibility of floating photovoltaics (FPV) in federally regulated reservoirs within the continental United States (CONUS) and to present a methodology for capturing the true costs of deployment, potential environmental impacts, and regulatory pathways for open-loop hydropower reservoirs. It is intended for stakeholders who may not be solar industry experts but who are interested in exploring the potential for FPV in their reservoirs. While there are promising opportunities, particularly in enhancing dissolved oxygen (DO) levels and potentially improving compliance with existing hydropower licenses, the current capital costs of FPV are not yet competitive with traditional land-based solar installations at the utility-scale when comparing the LCOE results. A competitive financial outlook is achievable when applying a 30% Investment Tax Credit (ITC) and considering a 5% reduction from the baseline capital expenditures (CapEx) at the Tuckertown Reservoir in North Carolina case study. The study is structured around three key pillars of research: technical potential, environmental impacts and regulatory considerations, and technoeconomic analysis. This report provides a nationwide assessment of the opportunities for FPV in terms of capacity, measured in direct current megawatts (MWDC), in reservoirs managed by the U.S. Bureau of Reclamation (USBR), the U.S. Army Corps of Engineers (USACE), and the Federal Energy Regulatory Commission (FERC). Additionally, the report introduces a heuristic model for estimating the CapEx of utility-scale FPV projects (1–100 MW), offering a baseline cost estimate for stakeholders. Finally, the report applies these models to a case study of a hydropower reservoir in North Carolina to present site-specific results.

13 - HYDRO ENERGY↗
DOE OSTI2020

River Regulation Alleviates the Impacts of Climate Change on US Thermoelectricity Production

Climate change and anthropogenic activities can both influence stream temperature, which is a critical indicator of thermoelectric power generation potential. Previous studies emphasized the vulnerability of power-generation systems to climate warming (ref 1, 2). Despite the fact that two-thirds of the global rivers are regulated by dams (ref 3), the relative impacts of water management and climate change on stream temperature and thermoelectric production have not yet been evaluated. Using an integrated modeling system applied to the conterminous United States, simulations confirm the dominant role of climate change in shaping the future trends of stream temperature. However, water management, reservoir regulation in particular, can mitigate the stream temperature warming and reduce the frequency and magnitude of extreme high stream temperatures through redistribution of the seasonal streamflow. Moreover, water management can alleviate the loss of power plant usable capacity from climate change to the level of reduced warming from emission mitigation. By regulating the flow and temperature regimes, water management is a promising adaptation measure to alleviate climate change induced effects in the water-energy nexus.

Zhang, Xiao↗
DOE OSTI2025

Applying a Multisector Scenario Framework to Evaluate Past and Future Public Surface Water Supply Infrastructure Strategies in Texas

Datasets supporting the index model and scenario analysis used in evaluating surface water supply strategies across different water system types in Texas. These data underpin the scenario development and application of five key indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets are organized by system type—stream reaches (flowlines), waterbodies, and reservoirs—and include both raw and standardized index values. The integrated datasets also provide scenario classifications (original and adjusted) based on infrastructure and planning priorities, enabling comparison across Shared Socioeconomic Pathways (SSPs). Additional strategy-level data are included to support evaluation of state-level new reservoir projects in relation to cost and availability tradeoffs. Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions Folder: Index_model_database.zip Subfolder: Stream_reach.zip Fl_wf.csv, Fl_wq.csv, Fl_er.csv, Fl_wf_wtcUV.csv, Fl_wf_wtcnoUV.csv, Fl_allfac_wic1.csv, Fl_allfac_wic2.csvDatasets for computing WAI, WQI, ERI, WTC, and WIC for surface water systems classified as stream reaches (flowlines). Subfolder: Waterbody.zip Wb_wf.csv, Wb_wq.csv, Wb_er.csv, Wb_wf_wtcUV.csv, Wb_wf_wtcnoUV.csv, Wb_allfac_wic1.csv, Wb_allfac_wic2.csvEquivalent index model datasets for waterbodies, reflecting hydrologic and infrastructure attributes specific to impounded natural systems. Subfolder: Reservoir.zip Rs_wf.csv, Rs_wq.csv, Rs_er.csv, Rs_wf_wtcUV.csv, Rs_wf_wtcnoUV.csv, Rs_allfac_wic1.csv, Rs_allfac_wic2.csvIndex model datasets specific to regulated reservoir systems, incorporating both resource indicators and cost parameters. Folder: Integrated data.zip combined_merged_data.csv, combined_merged_data_scenario.csvDatasets integrating index model indicators (both raw and scaled) with scenario classifications, including adjustments reflecting SSP-aligned transitions and planning shifts. Folder: Additional data.zip wai_supplystrat_wic_merged.csvCurated dataset capturing proposed major reservoir-based municipal water supply strategies in Texas. Integrates site-level planning data with estimated capital infrastructure costs and water availability scores for comparative assessment.

geospatial↗
DOE OSTI2023

Using Data-Driven Prediction of Downstream 1D River Flow to Overcome the Challenges of Hydrologic River Modeling

Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools.

13 HYDRO ENERGY↗
DOE OSTI2020

Reservoirs Modify River Thermal Regime Sensitivity to Climate Change: A Case Study in the Southeastern United States

Seasonal thermal stratification in reservoirs changes the thermal regime of regulated river systems as well as stream temperature responses to climate change. Cold releases from reservoir hypolimnion can depress downstream river temperature during warm seasons. Recent large-scale climate change studies on stream temperature have largely ignored reservoir thermal stratification. In this study, we used established models to develop a framework which considers water demand and reservoir regulation with thermal stratification, and applied this model framework to the southeastern US. About half of all 271 reservoirs in our study area retain strong thermal stratification by the 2080s (2070-2099) under RCP8.5 even as median residence times decrease to 60 days from 69 days in the historic period (1979-2010). Reservoir impacts on downstream temperatures become slightly weaker in the future because of higher air temperature and stronger solar radiation. We defined a “cooling potential” to quantify the thermal energy that a water body can absorb before exceeding a water temperature threshold. In the future, higher river temperatures will reduce the cooling potential for all river segments, but more so for river segments minimally impacted by thermal stratification. Reservoir impacts on cooling potential remain strong for river segments downstream of reservoirs with strong thermal stratification. We conducted a sensitivity analysis to evaluate the robustness of our findings to errors in the hydrological simulations. While river segments subject to reservoir regulation are more sensitive to errors in hydrology than those without regulation impacts, our overall findings do not materially change due to these errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Long-life rechargeable ion batteries having ion reservoirs

An aspect of the present disclosure is an electrochemical device that includes a first electrode, an ion reservoir electronically connected to the electrode by a first circuit, an electrolyte positioned between the first electrode and the ion reservoir and ionically connecting the first electrode and the ion reservoir, and a regulating element, where the regulating element is positioned between the first electrode and the ion reservoir, the regulating element electronically and/or ionically connects the ion reservoir and the first electrode, and the regulating element limits the transfer of at least one of electrons and/or ions between the ion reservoir and the first electrode.

Smith, Kandler Alan↗
DOE OSTI2026

Insights from a coupled thermo-hydro-mechanical analysis of a layered high-temperature thermal energy storage reservoir

Coupled thermal-hydraulic-mechanical (THM) modeling is applied to investigate the performance of a seasonal high-temperature aquifer thermal energy storage operation based on data and conditions from current site investigations at the Geostorage Forsthaus pilot project in Bern (Switzerland). The model includes subhorizontal sand lenses of various lengths and dips that are embedded in a low permeability clay matrix. Thermal energy storage is simulated by seasonal injection and withdrawal of hot (up to 90 °C) water from a main well, with reservoir pressure regulated by two auxiliary wells at a distance of about 70 m from the main well. The results show how targeted injection into deeper permeable storage formations, along with active deep well pressure control, can effectively minimize geomechanical impact and the potential risk of damaging subsurface storage and sealing formations, or even surface facilities. With such pressure control, the subsurface mechanical responses are dominated by thermal strain and stress, which can be monitored with subsurface fiber optics. The study demonstrates how coupled THM modeling can be applied for the design of a safe and efficient thermal energy storage operation, and how subsurface fiber optic monitoring can be applied for performance confirmation, allowing for more confident operational forecasting.

Rutqvist, Jonny↗
DOE OSTI2022

Shifts in hydropower operation to balance wind and solar will modify effects on aquatic biota

To avoid negative consequences to freshwater biota from climate change, society must complete the transition from fossil to renewable electricity sources. However, temporal patterns in hydropower generation (and flow releases that affect aquatic biota) may change with increased wind and solar penetration. We used power cost modeling to characterize current and future within-day and seasonal patterns in hydropower generation across the Eastern Interconnection in a wet and a dry year. Compared to the baseline, future hydropower generation across the grid decreased during the day and increased before dawn and after dusk. At a project level, such a pattern would suggest 'double peaking' operation (up- and down-ramping before dawn and after dusk, with lower releases midday). Variation in generation was higher in wet years than dry years, foreshadowing possible flow constraints on hydropower flexibility. At the grid scale, projected ramping rates were higher in all seasons. A review of the ecological literature suggests that these changes would shift the timing of invertebrate drift and elevate the risk of nest scouring during up-ramping and the risk of stranding or dewatering during down ramping. Thermal conditions may be moderated by increased ramping. Strategies for adapting to future shifts in the renewable portfolio range from re-regulation in reservoir cascades to providing flow refuge (structures and vegetation) below individual projects. Coordinated basin-scale operation can distribute peaking operation to maintain grid support while restricting local ramping at critical ecological times. In addition, research to design hybrid renewable systems that add battery storage is needed to understand how we can mitigate future risks to aquatic communities while promoting the use of renewable energy. This study, which is among the first to examine ecological side-effects of the shift to renewable energy in freshwater ecosystems, lays out a path toward understanding and navigating changes to flow regimes under the energy transition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Offshore Geologic Carbon Storage (GCS) Inventory

The Offshore Geological Carbon Storage Inventory Web Map is an online web mapping application designed to help users explore and visualize the Offshore Geologic Carbon Storage Inventory. This dataset is an inventory of offshore geologic carbon storage (GCS) projects and studies, gathered to summarize ongoing GCS efforts taking place offshore globally. This inventory includes both actualized projects as well as characterization studies and aggregates a variety of attribute fields for each project / study. It is intended to be used for research and comparison purposes, see full disclaimer and credits.

Assessment↗
DOE OSTI2023

International Offshore Geologic Carbon Storage Story Map

The International Offshore Geologic Carbon Storage Story Map provides an overview of offshore geologic carbon storage (GCS) project maturity on a global scale. This story map reviews the history of CO2 storage in offshore sedimentary basins, basic geologic requirements, project timelines and lessons learned through defined project stage progression, areas previously studied for potential future domestic offshore GCS development, and regulatory considerations within different global regions. This resource is a distillation of information collected and recorded in the Offshore Geologic Carbon Storage Inventory Version 1.0 (https://edx.netl.doe.gov/dataset/offshore-gcs-data-inventory).

Assessment↗
DOE OSTI2021

mosartwmpy: A Python implementation of the MOSART-WM coupled hydrologic routing and water management model

mosartwmpy is a Python implementation of the Model for Scale Adaptive River Transport with Water Management (MOSART-WM). This new version retains the functionality of the legacy model (written in FORTRAN) while providing new features to enhance user experience and extensibility. MOSART is a large-scale river-routing model used to study riverine dynamics of water, energy, and biogeochemistry cycles across local, regional, and global scales (Li et al., 2013). The WM component introduced by Voisin et al. (2013) represents river regulation through reservoir storage and release operations, diversions from reservoir releases, and allocation to sectoral water demands. Each reservoir release is independently calibrated using long-term mean monthly inflow into the reservoir, long-term mean monthly demand associated with this reservoir, and reservoir goals (flood control, irrigation, recreation, etc.). Generic monthly pre-release rules and storage targets are set up for individual reservoirs; however, those releases are updated annually for inter-annual variability (dry or wet year) and daily for environmental constraints such as flow minimum release and minimum/maximum storage levels. The WM model allows an evaluation of the impact of water management over multiple river basins at once (global, continental scales) and with consistent representation of human operations over the full domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins

Droughts across the U.S. have imposed substantial challenges to the management of water resources. Reservoir drought, one type of hydrological drought, is characterized by abnormally low reservoir storage levels, reflecting combined impacts of natural water shortages and water management practices. We investigate how reservoir drought signatures, particularly onset, severity, duration, recovery and frequency, may shift under rising temperatures, and how these shifts vary by reservoir typology and degree of regulation. By coupling atmosphere-land-river models with reservoir operations at ~12-km resolution, we simulated reservoir storage and characterized reservoir droughts across five heavily regulated U.S. basins. Our findings reveal significant regional and functional disparities in reservoir drought resilience under the scenario of rising temperatures. Reservoirs in the Texas-Gulf region are projected to become more resilient, while systems in the Upper Colorado and South Atlantic-Gulf regions face increased risk due to prolonged drought durations and slower recovery. With respect to primary function, reservoirs used for irrigation and hydropower, particularly those with smaller storage capacity and lower degrees of regulation, are most susceptible to future drought stress. These results are valuable in understanding water availability in highly regulated environments, and the influence of hydrometeorological conditions on storage dynamics. Overall, this study provides the first of its kind benchmark for reservoir droughts at a continental scale to support evolving multi-sectoral drought mitigation efforts. Future research is needed to link reservoir drought conditions to actual supply shortages across competing water uses, while leveraging existing adaptive management strategies and coordinated reservoir operations.

reservoir↗
DOE OSTI2020

Thermal extremes in regulated river systems under climate change: an application to the southeastern U.S. rivers

High river temperatures, or “thermal extremes”, can cause fish mortality and thermoelectric powerplant derating. Under climate change, projected higher air temperature and stronger surface energy fluxes will lead to increased water temperatures, exacerbating thermal extremes. However, cold hypolimnetic releases from thermally stratified reservoirs can depress tailwater temperatures and therefore alleviate thermal extremes. Thermal extremes are more harmful when they coincide with low flows, which we refer to as “hydrologic hot-dry events”. To assess multisectoral impacts of climate change over large regions, we evaluate thermal events according to three impact attributes: duration (D), intensity (I), and severity (S). We apply an established model framework to simulate streamflow and stream temperature over the southeastern US regulated river system. We quantify climate change impacts (by the 2080s under RCP8.5) by comparing historical and future periods and quantify regulation impacts by comparing unregulated and regulated scenarios. We find that climate change will exacerbate thermal extremes (all three metrics) in both unregulated and regulated scenarios, albeit less in the regulated scenario. Thermal mitigation from reservoir regulation will be stronger under climate change, decreasing the three metrics compared to the unregulated case. Even so, thermal extremes in the regulated scenario will still be more severe under climate change, and only 12.2%, 19.7%, and 26.0% of D, I, and S can be mitigated by reservoirs. Despite stronger reservoir stratification, the number of regulated river segments that experience simultaneous high temperature and low flow events (hydrologic hot-dry events) will increase by 21.4% by the 2080s under RCP8.5. These events will have a median annual duration of 10.3 days/year, over 10 times the historical value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling

Abstract. Major multi-reservoir cascades represent a primary mechanism for dealing with hydrologic variability and extremes within institutionally complex river basins worldwide. These coordinated management processes fundamentally reshape water balance dynamics. Yet, multi-reservoir coordination processes have been largely ignored in the increasingly sophisticated representations of reservoir operations within large-scale hydrological models. The aim of this paper is twofold, namely (i) to provide evidence that the common modeling practice of parameterizing each reservoir in a cascade independently from the others is a significant approximation and (ii) to demonstrate potential unintended consequences of this independence approximation when simulating the dynamics of hydrological extremes in complex reservoir cascades. We explore these questions using the Water Balance Model, which features detailed representations of the human infrastructure coupled to the natural processes that shape water balance dynamics. It is applied to the Upper Snake River basin in the western US and its heavily regulated multi-reservoir cascade. We employ a time-varying sensitivity analysis that utilizes the method of Morris factor screening to explicitly track how the dominant release rule parameters evolve both along the cascade and in time according to seasonal high- and low-flow events. This enables us to address aim (i) by demonstrating how the progressive and cumulative dominance of upstream releases significantly dampens the ability of downstream reservoir rules' parameters to influence flow conditions. We address aim (ii) by comparing simulation results with observed reservoir operations during critical low-flow and high-flow events in the basin. Our time-varying parameter sensitivity analysis with the method of Morris clarifies how independent single-reservoir parameterizations and their tacit assumption of independence leads to reservoir release behaviors that generate artificial water shortages and flooding, whereas the observed coordinated cascade operations avoided these outcomes for the same events. To further explore the role of (non-)coordination in the large deviations from the observed operations, we use an offline multi-reservoir water balance model in which adding basic coordination mechanisms drawn from the observed emergency operations is sufficient to correct the deficiencies of the independently parameterized reservoir rules from the hydrological model. These results demonstrate the importance of understanding the state–space context in which reservoir releases occur and where operational coordination plays a crucial role in avoiding or mitigating water-related extremes. Understanding how major infrastructure is coordinated and controlled in major river basins is essential for properly assessing future flood and drought hazards in a changing world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aromatic amino acid metabolism and active transport regulation are implicated in microbial persistence in fractured shale reservoirs

Abstract Hydraulic fracturing has unlocked vast amounts of hydrocarbons trapped within unconventional shale formations. This large-scale engineering approach inadvertently introduces microorganisms into the hydrocarbon reservoir, allowing them to inhabit a new physical space and thrive in the unique biogeochemical resources present in the environment. Advancing our fundamental understanding of microbial growth and physiology in this extreme subsurface environment is critical to improving biofouling control efficacy and maximizing opportunities for beneficial natural resource exploitation. Here, we used metaproteomics and exometabolomics to investigate the biochemical mechanisms underpinning the adaptation of model bacterium Halanaerobium congolense WG10 and mixed microbial consortia enriched from shale-produced fluids to hypersalinity and very low reservoir flow rates (metabolic stress). We also queried the metabolic foundation for biofilm formation in this system, a major impediment to subsurface energy exploration. For the first time, we report that H. congolense WG10 accumulates tyrosine for osmoprotection, an indication of the flexible robustness of stress tolerance that enables its long-term persistence in fractured shale environments. We also identified aromatic amino acid synthesis and cell wall maintenance as critical to biofilm formation. Finally, regulation of transmembrane transport is key to metabolic stress adaptation in shale bacteria under very low well flow rates. These results provide unique insights that enable better management of hydraulically fractured shale systems, for more efficient and sustainable energy extraction.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

ELM‐MOSART‐DOC: A Large‐Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States

Riverine dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a crucial role in regional and global carbon cycles. However, the complexities of the underlying mechanisms and limited observations present significant challenges for predictive understanding of DOC at regional or larger scales. Recently, we developed a machine learning‐based (ML) map of DOC transformation rates, bridging the gap between SOC and DOC leaching flux and simplifying terrestrial DOC representation. Building on this advancement, we introduce ELM‐MOSART‐DOC, a DOC module integrated into the riverine component of the Energy Exascale Earth System Model (E3SM)—the Model for Scale Adaptive River Transport (MOSART). ELM‐MOSART‐DOC simulates DOC transport and transformation across both headwater streams and river networks, including those managed. Model validation demonstrates the ability of ELM‐MOSART‐DOC to accurately capture long‐term average DOC concentrations, with Kling‐Gupta Efficiency (KGE) scores of 0.58 and 0.76 at large and local stations, respectively. We further assess the impact of reservoirs through different simulation schemes, revealing that reservoirs significantly alter DOC fluxes by regulating streamflow patterns and promoting DOC mineralization. Model simulations indicate that reservoirs reduce total DOC flux from the Mississippi River into the ocean by 7.5%, with the long‐term average annual export decreasing from 3.34 to 3.14 teragrams (Tg) per year. ELM‐MOSART‐DOC integrates process‐based modeling with ML parameterization to enhance the predictive understanding of riverine biogeochemical processes. This approach reduces uncertainties in modeling regional and global carbon cycle ESMs and provides new insights into carbon cycling and its implications for global environmental change.

Li, Lingbo [Univ. of Houston, TX (United States); ↗
DOE OSTI2025

Improving the prediction of daily reservoir releases over the CONUS using conditioned LSTM

Reservoirs play a vital role in regulating streamflow timing and variability for hydroelectricity, flood control, water supply, irrigation, and recreation. Despite their importance, many reservoirs lack comprehensive operational guidelines, making their management complex due to conflicting operational objectives. Hence traditional policy-based reservoir models often fail to capture real-world conditions accurately and they depend on perfect streamflow predictions, which are not always available. In contrast, data-driven models like Long Short-Term Memory (LSTM) networks offer a robust alternative. This study introduces an approach that integrates reservoir characteristics—such as main use, climate, and maximum capacity—into the LSTM model to enhance reservoir release predictions. Using data from nearly 200 reservoirs in the contiguous United States (CONUS), our conditioned LSTM model (LSTM_cond) was compared with both the vanila LSTM and a traditional policy-based approach. Furthermore, our results show that while both LSTM_cond and LSTM perfoms better than the policy-based approach, LSTM_cond consistently outperforms LSTM for hydroelectric, water supply, irrigation, and recreation reservoirs. The KGE median values for LSTM_cond for out-sample reservoirs are 0.764, 0.565, 0.821, and 0.779, respectively, for the aforementioned reservoir types, which are consistently higher that the corresponding KGE values of 0.737, 0.413, 0.775, and 0.713 of LSTM, demonstrating its advantages in improving generalizability.

CONUS↗