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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating a Water Tracer Model Into WRF‐Hydro for Characterizing the Effect of Lateral Flow in Hydrologic Simulations

Abstract Most current land models approximate terrestrial hydrological processes as one‐dimensional vertical flow, neglecting lateral water movement from ridges to valleys. Such lateral flow is fundamental at catchment scales and becomes crucial for finer‐scale land models. To test the effect of incorporating lateral flow toward three‐dimensional representations of hydrological processes in the next generation land models, we integrate a water tracer model into the WRF‐Hydro framework to track water movement from precipitation to discharge and evapotranspiration. This hydrologic‐tracer integrated system allows us to identify the key mechanisms by which lateral flow affects the flow paths and transit times in WRF‐Hydro. By comparing modeling experiments with and without lateral routing in two contrasting catchments, we determine the impacts of lateral flow on the transit times of precipitation event‐water. Results show that with limited hydrologic connectivity, lateral flow extends the transit times by reducing (increasing) event‐water drainage loss (accumulation) in ridges (valleys) and allowing reinfiltration of infiltration‐excess flow, which is missing in most land models. On the contrary with high hydrologic connectivity, lateral flow can effectively accelerate the water release to streams and reduce the transit time. However, the transit times are substantially underestimated by the model compared with isotope‐derived estimates, indicating model limitations in representing flow paths and transit times. This study provides some insights on the fundamental differences in terrestrial hydrology simulated by land models with and without lateral flow representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Isotopic fractionation accompanying CO 2 hydroxylation and carbonate precipitation from high pH waters at The Cedars, California, USA

The Cedars ultramafic block hosts alkaline springs (pH > 11) in which calcium carbonate forms upon uptake of atmospheric CO 2 and at times via mixing with surface water. Here, these processes lead to distinct carbonate morphologies with “floes” forming at the atmosphere-water interface, “snow” of fine particles accumulating at the bottom of pools and terraced constructions of travertine. Floe material is mainly composed of aragonite needles despite CaCO 3 precipitation occurring in waters with low Mg/Ca (<0.01). Precipitation of aragonite is likely promoted by the high pH (11.5–12.0) of pool waters, in agreement with published experiments illustrating the effect of pH on calcium carbonate polymorph selection.

58 GEOSCIENCES↗
DOE OSTI2026

SPRUCE Soil Volumetric Water Content in Experimental Plots, Marcell Experimental Forest, Minnesota, 2017-2025

This dataset contains soil volumetric water content (VWC) measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) Experiment. Measurements were made inside SPRUCE experimental plots in the S1 Bog at the US Forest Service Marcell Experimental Forest in northern Minnesota, USA from 2018-2025 (2018-06-14 to 2025-12-31). Observations were made with METER 10HS soil moisture sensors. To reduce bulk density related variability, 10HS sensors were placed inside mesh tubes filled with peat at a standard bulk density. The observations under standard bulk density represent relative differences in water content between hummock and hollow positions, and in response to experimental treatments. Productivity of peatlands, and their keystone species sphagnum, are highly dependent on water availability, which is affected by lateral inputs, precipitation, ground water depth and evapotranspiration. Knowledge of near surface and sphagnum water content is useful to understand peatland function. This dataset contains 8 data files in comma-separate values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
DOE OSTI2025

Exploring Afro-Asian water fluxes in CMIP5 and CMIP6 models: Present-day evaluation and future projections

Accurate representation and projection of water fluxes are vital, particularly in monsoon regions where seasonal variability and changes significantly impact water resources, agriculture, hydroelectric power generation, and the economy. This study uses both CMIP5 and CMIP6 models to investigate the present-day representation of key water flux components (including precipitation, evaporation, water vapor, and moisture advection) over the Afro-Asian region during the summer monsoon (JJAS). We also examine future changes under two emission scenarios and assess the underlying physical mechanisms driving these changes while identifying sources of projection uncertainty. Our results show that both models reasonably capture the present-day characteristics of water flux components, although with noticeable biases. Across most regions, we find that CMIP6 models demonstrate slight improvements over CMIP5 in the representation of these components. In a warmer future, a robust intensification of JJAS precipitation (exceeding 0.25 mm/day) is projected across the Afro-Asian region. This increase is largely driven by the vertical thermodynamic term associated with increasing temperature. We find that model uncertainty is the primary source of uncertainty in water flux projections, accounting for over 50 % of the total variance.

Climate change↗
DOE OSTI2020

Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds

Abstract. The partition of cloud and drizzle water path in precipitating clouds plays a key role in determining the cloud lifetime and its evolution. A technique to quantify cloud and drizzle water path by combining measurements from a three-channel microwave radiometer (23.8, 30, and 90 GHz) with those from a vertically pointing Doppler cloud radar and a ceilometer is presented. The technique is showcased using 1 d of observations to derive precipitable water vapor, liquid water path, cloud water path, drizzle water path below the cloud base, and drizzle water path above the cloud base in precipitating stratocumulus clouds. The resulting cloud and drizzle water path within the cloud are in good qualitative agreement with the information extracted from the radar Doppler spectra. The technique is then applied to 10 d each of precipitating closed and open cellular marine stratocumuli. In the closed-cell systems only ~20 % of the available drizzle in the cloud falls below the cloud base, compared to ~40 % in the open-cell systems. In closed-cell systems precipitation is associated with radiative cooling at the cloud top <-100W m -2 and a liquid water path >200 g m -2 . However, drizzle in the cloud begins to exist at weak radiative cooling and liquid water path >~150 g m-2. Our results collectively demonstrate that neglecting scattering effects for frequencies at and above 90 GHz leads to overestimation of the total liquid water path of about 10 %–15 %, while their inclusion paves the path for retrieving drizzle properties within the cloud.

Cadeddu, Maria P.↗
DOE OSTI2022

Soil frost controls streamflow generation processes in headwater catchments

The relationship between snowmelt and spring streamflow is changing under warming temperatures and diminishing snowpack. At the same time, the hydrologic connectivity across catchment landscape elements, such as snowpack and surface wetlands, can play a critical role in controlling the routing of snowmelt to streams. The role of hydrologic connectivity is important in headwater regions of the continental northern latitudes, where catchments have low topographic relief and seasonally frozen ground. Nevertheless, the effects of soil frost on the sequence, timing, and magnitudes of hydrologic events that drive the movement of water from a snowpack to a stream are not fully understood. Therefore, we examine two questions: First, what is the flowpath that snow melt and precipitation from spring rain events takes to generate spring streamflow, and second, what hydrologic, climatic, or landscape variables exert the most control on the magnitude of streamflow? In this work, we use long-term hydrological records from the two reference basins at the Marcell Experimental Forest in northern Minnesota to analyze the cascading effects across precipitation, snow, water table elevation, soil frost, and streamflow in peatland-dominated headwater catchments. We identify a sequence of fill-and-spill effects across the landscape that control the timing of spring streamflow generation. Then, we use stepwise regression to show that soil frost is a key supporting predictor for both the magnitude of streamflow in the spring as it adds significantly to the predictive power of precipitation and water table elevation. Our results highlight the importance of recognizing the role of soil frost, when present, on the partitioning of snowmelt between overland runoff and water table recharge during the critical snowmelt period, as well as the later partitioning between evapotranspiration and subsurface flows.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p-value = 0.00027, R2 = 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p-values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture.

09 BIOMASS FUELS↗
DOE OSTI2023

Mass‐Conserving Downscaling of Climate Model Precipitation Over Mountainous Terrain for Water Resource Applications

Abstract A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined.

Geology↗
DOE OSTI2025

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; 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. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗
DOE OSTI2022

Changing Trends in Drought Patterns over the Northeastern United States Using Multiple Large Ensemble Datasets

Since the infamous extreme drought of the 1960s, the climate of the northeastern United States (NEUS) has generally trended toward warmer and wetter conditions. Nonetheless, there is mounting evidence that short-term droughts will continue to pose a significant risk for this region. To better explore the processes governing events such as these, climate models have adopted more complex representations of the fully coupled atmosphere–land–ocean–sea ice system; however, large uncertainties in future projections still persist, with internal variability necessitating large ensembles to understand trends in both rare and high-impact extreme events such as rapidly developing droughts (a term here that includes flash droughts developing on monthly scales). In this study, seven large ensemble (LE) models are employed to answer the outstanding question: How are the frequency and character of drought in the NEUS changing under a warming climate? We find that most LE models indicate the NEUS will experience a long-term wetting trend with more “extremely wet” months, but also more frequent short-term extreme droughts. These changes are associated with increasing precipitation, atmospheric water demand, and climate variability. We also conclude that discrepant trends in precipitation and evapotranspiration variability will lead to increasing anticorrelation of these variables, which is relevant to the intensification of rapidly developing drought, particularly in the spring season. These changes are associated with an increase in evapotranspiration from plants, brought by an earlier emergence of the growing season and denser vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microwave Radiometer: Meteorological Temperature Profiler (raw)

The microwave radiometer profiler (MWRP) provides vertical profiles of temperature, humidity, and cloud liquid water content as a function of height or pressure at approximately 5-minute intervals for nearly all weather conditions. The profiles are derived from measurements of absolute microwave radiances (expressed as "brightness temperatures") obtained at 12 frequencies in the range of 22-30 GHz and 51-59 GHz. The data are useful for input to numerical weather forecast models and others that require continuous, high-temporal-resolution profiles. The microwave radiance measurements are useful for testing models of microwave radiation transfer used to derive the profiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of “seasonally variable regimes becoming more variable”. Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vegetation Response to Rising CO 2 Amplifies Contrasts in Water Resources Between Global Wet and Dry Land Areas

Rising atmospheric CO 2 impacts on vegetation physiological processes can alter land feedbacks on precipitation and water resources, but understanding of regional differences in these changes is uncertain. We investigate the impact of rising CO 2 on land water resources for different wetness levels using four Earth system models. We find an overall tendency of runoff to increase across all wetness levels. However, runoff increases in wet regions are much larger than those in dry regions, especially in wet seasons. This substantial amplification of contrasts between wet and dry regions increases at 3% per 100 ppm increase in CO 2 relative to the historical period, reaching 18% for a quadrupling of CO 2 , quantified by a new wetting contrast index (WCI). Physiological effects suppress evapotranspiration more in wet than dry regions, which has a larger contribution than radiative forcing to the amplification of runoff contrast, reshaping the spatial distribution of future land water resources.

58 GEOSCIENCES↗
DOE OSTI2020

Projected increase of the East Asian summer monsoon ( Meiyu ) in Taiwan by climate models with variable performance

Abstract The active phase of the East Asian summer monsoon (EASM) in Taiwan during May and June, known as Meiyu , produces substantial precipitation for water uses in all sectors of society. Following a companion study that analysed the historical increase in the Meiyu precipitation, the present study conducted model evaluation and diagnosis based on the EASM lifecycle over Taiwan. Higher and lower skill groups were identified from 17 Couple Model Intercomparison Project Phase 5 (CMIP5) models, with five models in each group. Despite the difference in model performance, both groups projected a substantial increase in the Meiyu precipitation over Taiwan. In the higher skill group, weak circulation changes and reduced low‐level convergence point to a synoptically unfavourable condition for precipitation. In the lower skill group, intensified low‐level southwesterly winds associated with a deepened upper level trough enhance moisture pooling. Thus, the projected increase in Meiyu precipitation will likely occur through the combined effects of (1) the extension of a strengthened North Pacific anticyclone enhancing southwesterlies; and (2) more systematically, the Clausius–Clapeyron relationship that increases precipitation intensity in a warmer climate. The overall increase in the Meiyu precipitation projected by climate models of variable performance supports the observed tendency toward more intense rainfall in Taiwan and puts its early June 2017 extreme precipitation events into perspective.

Tung, Yu‐Shiang↗