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DOE OSTI2023

How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqia$\mathrm{\dot{g}}$vik, Alaska?

Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. Here, we found that higher values of RH (up to 40%) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30% maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physically-based predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Model Data for the Mesh Convergence Study Demonstrating Benefits of Mixed-polyhedral Mesh in Integrated Hydrology Simulations

This archived model data is related to a study introducing a unique method that employs a stream-aligned mixed-polyhedral mesh to effectively and accurately represent river valleys, stream corridors, and narrow engineered channels in integrated hydrology simulations. The study finds that utilizing stream-aligned mixed-polyhedral meshes in integrated hydrology simulations achieves accuracy on par with a finely refined TIN-based mesh while markedly diminishing computational costs. This archive contains scripts and data files needed to generate the ATS model input, including mesh and ATS input files, for all mesh scenarios using the Watershed Workflow package. Additionally, this archive also provides key outputs from the model simulations that are used in the analysis and post-processing scripts to reproduce figures in the manuscript. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Intersection of Hydrologic Change and Hydropower in the United States: Needs for Future Research and Practice

Hydropower is crucial for electric‐grid stability in the context of variable renewables but faces threats from changing hydrology. Here, we summarize the state of the science at the intersection of hydropower operations and planning, hydrologic science, and climate. We focus on the United States, outlining research, development, and training needs. Key knowledge gaps include the risk that intensification of compound extreme events poses to future generation, as well as uncertainties surrounding greenhouse gas emissions from hydropower reservoirs with relevance to hydropower's role in energy decarbonization. Quantifying such impacts and reducing uncertainty are critical where possible, but remaining irreducible or deep uncertainty will require new approaches. Future monitoring and modeling methods must provide a better understanding of the complexity inherent in large watersheds that is critical to managing both hydropower and watersheds in the context of hydrologic change. Yet, research and development will have little impact if they do not inform practice. Standardization and consolidation of platforms are essential for data, modeling, and tool translation to local scales and small operators. An enhanced industry‐academia dialog is pivotal for fostering a robust pipeline of hydropower professionals. Collaboration among researchers, policymakers, authorities, and industry stakeholders emerges as a recurring theme, highlighting the imperative for collective efforts.

13 HYDRO ENERGY↗

DOE OSTI2022

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗

DOE OSTI2024

Declining Reservoir Reliability and Increasing Reservoir Vulnerability: Long-Term Observations Reveal Longer and More Severe Periods of Low Reservoir Storage for Major United States Reservoirs

Hydrological drought is a pervasive and reoccurring challenge in managing water resources. Reservoirs are critical for lessening the impacts of drought on water available for many uses. We use a novel and generalized approach to identify periods of unusually low reservoir storage—via comparisons to operational rule curves and historical patterns—to investigate how droughts affect storage in 250 reservoirs across the conterminous U.S. (CONUS). We find that the maximum amount of water stored in reservoirs is decreasing, and that periods of unusually low storage are becoming longer, more severe, and more variable in (a) western and central CONUS reservoirs, and (b) reservoirs with primarily over-year storage. Results suggest that reservoir storage has become less reliable and more vulnerable to larger deviations from desired storage patterns. These changes have coincided with ongoing shifts to the hydroclimate of CONUS, and with sedimentation further reducing available reservoir storage.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, code, models files

This model-data archive is for a modeling study focused on the effects of artificial drainage on agriculture-dominated watersheds using a fully distributed integrated hydrology model. This study introduced a novel strategy to represent the effects of tile drains and agricultural ditches in a fully distributed basin-scale integrated hydrology model. The numerical experiments in this study reveal the effects of surface and subsurface drainage on various hydrological states and fluxes. The details about the datasets can be found in the "readme" document attached with the dataset.

Agricultural Watersheds↗

DOE OSTI2022

Modeling the role of lateral surface flow in low‐relief polygonal tundra

Abstract Ice‐wedge polygon troughs play an important role in controlling the hydrology of low‐relief polygonal tundra regions. Lateral surface flow is confined to troughs only, but it is often neglected in model projections of permafrost thermal hydrology. Recent field and modeling studies have shown that, after rain events, increases in trough water levels are significantly more than the observed precipitation, highlighting the role of lateral surface flow in the polygonal tundra. Therefore, understanding how trough lateral surface flow can influence polygonal tundra thermal hydrology is important, especially under projected changes in temperatures and rainfall in the Arctic regions. Using an integrated cryohydrology model, this study presents plot‐scale end‐of‐century projections of ice‐wedge polygon water budget components and active layer thickness with and without trough lateral surface flow under the Representative Concentration Pathway 8.5 scenario. Trough lateral surface flow is incorporated through a newly developed empirical model, evaluated against field measurements. The numerical scenario that includes trough lateral surface flow simulates discharge (outflow from a polygon) and recharge (rain‐induced inflow to a polygon trough from upslope areas), while the scenario that does not include trough lateral surface flow ignores recharge. The results show considerable reduction (about 100–150%) in evapotranspiration and discharge in rainy years in the scenarios ignoring trough lateral surface flow, but less effect on soil water storage, in comparison with the scenario with trough lateral surface flow. In addition, the results demonstrate long‐term changes (~10–15 cm increase) in active layer thickness when trough lateral surface flow is modeled. This study highlights the importance of including lateral surface flow processes to better understand the long‐term thermal and hydrological changes in low‐relief polygonal tundra regions under a changing climate.

Jan, Ahmad↗

DOE OSTI2021

Coupling Surface Flow with High-performance Subsurface Reactive Flow and Transport Code PFLOTRAN

Water exchange between the surface and subsurface is important for both water resource management and environmental protection. In this paper, we develop coupled surface and subsurface flow simulation capability in a parallel subsurface flow and reactive transport code PFLOTRAN. We sequentially couple the diffusion wave-based surface flow with the subsurface flow governedby the Richards equation in PFLOTRAN. These two flow domains are linked with a boundary condition switching method that ensures continuity of pressure and flux at the surface-subsurface interface. We verify the coupled code against other existing hydrologic models and observation data using a number of numerical experiments. The coupled hydrological model exhibits good performance in strong parallel scaling tests. The new coupled surface and subsurface simulator significantly advance community simulation capability towards improving integrated hydrologic and biogeochemical understanding of complex systems such as watersheds and river corridors. Keywords: Surface flow, Integrated hydrological modeling, Boundary condition switching, Parallel computing

Wu, Runjian↗

DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗

DOE OSTI2023

Flow Directions and Ages of Subsurface Water in a Salt Marsh System Constrained by Isotope Tracing

Salt marshes are dynamic hydrologic systems where terrestrial groundwater, terrestrial surface water, and seawater mix due to bi-directional flows and pressure gradients. Due to the counteracting terrestrial and marine forcings that control these environments, we do not comprehensively understand water fluxes in these complex coastal systems. To understand the water sources, flow directions, and velocities in salt marsh porewater, we employed a combination of geochemical tracers and analytical models across a hillslope-to-salt marsh continuum in a salt marsh experiencing daily inundation of estuarine surface water (SW) from tides and mixing of fresh seasonal groundwater. We used tritium ( 3 H) as a hydrologic tracer to assess porewater ages and stable water isotope ($\delta$ 2 H and $\delta$ 18 O) analyses to separate isotopically distinct estuarine and terrestrial groundwater across different depths and landscape positions in the study transect. We employed electrical conductivity to constrain the role of source mixing and evapotranspiration in salt marsh hydrology. Salinity and stable isotopes revealed that transpiration, rather than evaporation, increased subsurface water salinity to concentrations above estuarine SW during summer. Elevated salinity at depth indicated that salt marsh subsurface water is recharged during the dry growing season. Seasonal recharge patterns drive long-term deep subsurface water dynamics across the salt marsh, with 3 H ages of 3–7 years, and daily tidal cycles drive short-term shallow porewater dynamics with 3 H ages of 0 ± 3.6 years. Furthermore, our conceptual understanding of the spatiotemporal changes in SW-subsurface water interactions at the terrestrial-marine interface quantifies the hydrological constraints we are missing to improve our understanding of biogeochemical cycles within the salt marsh.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Physical Controls on the Hydrology of Perennially Ice-Covered Lakes, Taylor Valley, Antarctica (1996–2013)

The McMurdo Dry Valleys, Antarctica, are a polar desert populated with numerous closed-watershed, perennially ice-covered lakes primarily fed by glacial melt. Lake levels have varied by as much as 8 m since 1972 and are currently rising after a decade of decreasing. Precipitation falls as snow, so lake hydrology is dominated by energy available to melt glacier ice and to sublimate lake ice. To understand the energy and hydrologic controls on lake level changes and to explain the variability between neighboring lakes, only a few kilometers apart, we model the hydrology for the three largest lakes in Taylor Valley. Here, we apply a physically based hydrological model that includes a surface energy balance model to estimate glacial melt and lake sublimation to constrain mass fluxes to and from the lakes. Results show that lake levels are very sensitive to small changes in glacier albedo, air temperature, and wind speed. We were able to balance the hydrologic budget in two watersheds using meltwater inflow and sublimation loss from the ice-covered lake alone. A third watershed, closest to the coast, required additional inflow beyond model uncertainties. We hypothesize a shallow groundwater system within the active layer, fed by dispersed snow patches, contributes 23% of the inflow to this watershed. The lakes are out of equilibrium with the current climate. If the climate of our study period (1996–2013) persists into the future, the lakes will reach equilibrium starting in 2300, with levels 2–17 m higher, depending on the lake, relative to the 2020 level.

58 GEOSCIENCES↗

DOE OSTI2025

Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California

ABSTRACT Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using the process‐based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site‐specific data. We designed a novel modelling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modelled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected SLR over the next few decades. The low‐lying Yampah Marsh, the reference site, is likely to be inundated due to future SLR when highest tides arrive, while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.

advanced terrestrial simulator↗

DOE OSTI2024

Spatio–Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Integrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow–CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which are fused in a recurrent loop to produce spatiotemporal predictions of groundwater. We evaluate the model architectures on their ability to reproduce 4D pressure heads, water table depths, and surface soil moisture over the contiguous US at 1 km resolution and daily time steps over the course of a full water year. The FSTR model shows superior performance to the baseline models, producing stable simulations that capture both seasonal and event–scale dynamics across a wide array of hydroclimatic regimes. The emulators provide over 1,000× speedup compared to the original physical model, which will enable new capabilities like uncertainty quantification and data assimilation for integrated hydrologic modeling that were not previously possible. Our results demonstrate the promise of using specialized deep learning architectures like FSTR for emulating complex process–based models without sacrificing fidelity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States

Abstract Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Data-model files associated with the manuscript "Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California"

This package contains the data, simulation setups, notebooks and figures used in “Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California” (Xu et al., 2025). In this study, we selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise on coastal hydrology using the process-based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site-specific data. We designed a novel modeling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modeled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected sea level rise over the next few decades. The low-lying Yampah Marsh, the reference site, is likely to be inundated due to future sea level rise when highest tides arrive; while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.Several files can be found from this data package.1. README.md: This file describes the title, journal, co-authors, abstract, repository structure and model version.2. Simulation_Setups.zip: The file contains the model configuration files (XML format) for ATS. 3. Notebooks.zip: The file contains the Jupyter notebooks for generating the pre- and post-restoration meshes and the meshes of future scenarios. 4. Figures.zip: The file contains the figures used in the manuscript.5. Data.zip: The file contains the data used to drive the model simulations, including watershed and wetlands boundaries, mesh files and references to additional datasets (e.g., meteorological forcing, tidal dataset, DEMs, land cover, soil properties). Also, it contains water level observations at the restored wetland.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

DOE OSTI2023

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Earth Systems↗