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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study. Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Automatic Processing Framework for In Situ Determination of Ecohydrological Root Water Content by Ground-Penetrating Radar

This report concerns Root water content (RWC) as a vital component in water flux in soil-plant-atmosphere continuum. Knowledge of RWC helps to better understand the root function and the soil-root interaction and improves water cycle modeling. However, due to the lack of appropriate methods, field monitoring of RWC is seriously constrained. In this study, we used ground-penetrating radar (GPR), a common geophysical technique, to characterize RWC of coarse roots noninvasively. An automatic GPR data processing framework was proposed to (1) identify hyperbolic root reflections and locate roots in GPR images and (2) extract waveform parameters from the reflected wave of identified roots. These waveform parameters were then used to establish an empirical model and a semiempirical model to determine RWC. We validated the developed models using GPR root data at three antenna center frequencies (500 MHz, 900 MHz, and 2 GHz) that were produced from simulation experiments (with RWC ranging from 70% to 150%) and field experiments in sandy soils (with RWC ranging from 66% to 144%). Our results show that both the empirical and the semiempirical models achieved a good performance in estimating RWC with similar accuracy, i.e., the prediction error [root-mean-square error (RMSE)] was less than 8% for the simulation data and 12% for the field data. For both models, the accuracy of RWC estimation was the highest when applied to 2-GHz data. This study renders a new opportunity to determine RWC under field conditions that enhances the application of GPR for root study and the understanding and modeling of ecohydrology in the rhizosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Towards Trustworthy and Interpretable Deep Learning-assisted Ecohydrological Models

The transformational science question we plan to address is: How do we leverage in-situ observations and simulations from process-based ecohydrological model to construct interpretable and trustworthy deep learning (DL) models for improved reliability of prediction of quantities of interest (QoIs) under hydro-climatic extremes?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

BSEC ecohydrological and water quality fluxes from RHESSys Simulations in USGS gauged watersheds

Baltimore Environmental Social Collaborative (BSEC) Water and Water Quality Simulations from RHESSys Model The repository contains RHESSys (Tague & Band, 2004; source code) simulated ecohydrological and nutrient (nitrogen only) fluxes at daily, basin-average (RHESSys_basin_output) and monthly, grid (RHESSys_patch_output) levels. We currently simulated the following 8 watersheds in Baltimore: Dead Run Baisman Run Scotts Level Branch Moores Run Powder Mill Run Maidens Choice Run Stony Run The watershed boundaries of all studied watersheds are stored in Watershed_Boundary folder. Variables and their units are listed in the metadata. Spatial projection, NAD83 / UTM zone 18N (EPSG:26918) is used for patch-level, netCDF-format files. For more information, please contact Ruoyu Zhang (rz3jr@virginia.edu).

Baltimore MD↗
NASA NTRS2019

Holocene Ecohydrological Variability on the East Coast of Kamchatka

The Late Glacial and Holocene climate of the western North Pacific is less studied than that of the eastern North Pacific. While it is well known that strong east-west gradients in the tropical Pacific Ocean influence terrestrial climate, we seek to better understand how these gradients are expressed in the northern extratropics. Toward this aim, we present an organic and stable isotope geochemical and macrofossil record from a peatland on the east coast of the Kamchatka peninsula. We find that both the early and late Holocene were wetter, with a different assemblage of plants from the middle Holocene, which was drier, with more episodic precipitation. The large ecohydrological changes at several points during the Holocene are contemporaneous with and of the same sense as those we find at places to the east, such as south-central Alaska and to the south, in northern Japan. We also find that the middle Holocene period of warmth, dryness and low carbon accumulation occur contemporaneously with an enhanced east-west gradient in tropical Pacific sea surface temperature. This suggests that hydroclimatic conditions in the subarctic can be influenced by tropical dynamics.

Nichols, Jonathan↗
DOE OSTI2013

Updating the US Hydrologic Classification: An Approach to Clustering and Stratifying Ecohydrologic Data

Hydrologic classifications unveil the structure of relationships among groups of streams with differing stream flow and provide a foundation for drawing inferences about the principles that govern those relationships. Hydrologic classes provide a template to describe ecological patterns, generalize hydrologic responses to disturbance, and stratify research and management needs applicable to ecohydrology. We developed two updated hydrologic classifications for the continental US using two streamflow datasets of varying reference standards. Using only reference-quality gages, we classified 1715 stream gages into 12 classes across the US. By including more streamflow gages (n=2618) in a separate classification, we increased the dimensionality (i.e. classes) and hydrologic distinctiveness within regions at the expense of decreasing the natural flow standards (i.e. reference quality). Greater numbers of classes and higher regional affiliation within our hydrologic classifications compared to that of the previous US hydrologic classification (Poff, 1996) suggested that the level of hydrologic variation and resolution was not completely represented in smaller sample sizes. Part of the utility of classification systems rests in their ability classify new objects and stratify analyses. We constructed separate random forests to predict hydrologic class membership based on hydrologic indices or landscape variables. In addition, we provide an approach to assessing potential outliers due to hydrologic alteration based on class assignment. Departures from class membership due to disturbance take into account multiple hydrologic indices simultaneously; thus, classes can be used to determine if disturbed streams are functioning within the realm of natural hydrology.

dams↗
DOE OSTI2019

Spatio-temporal heterogeneity in soil water stable isotopic composition and its ecohydrologic implications in semiarid ecosystems

Spatio-temporal heterogeneity in soil water content is recognized as a common phenomenon, but heterogeneity in the hydrogen and oxygen isotope composition of soil water, which can reveal processes of water cycling within soils, has not been well studied. New advances are being driven by measurement approaches allowing sampling with high density in both space and time. Using in situ soil water vapour probe techniques, combined with conventional soil and plant water vacuum distillation extraction, we monitored the hydrogen and oxygen stable isotopic composition of soil and plant waters at paired sites dominated by grasses and Gambel's oak ( Quercus gambelii ) within a semiarid montane ecosystem over the course of a growing season. We found that sites spaced only 20 m apart had profoundly different soil water isotopic and volumetric conditions. We document patterns of depth- and time-explicit variation in soil water isotopic conditions at these sites and consider mechanisms for the observed heterogeneity. We found that soil water content and isotopic variability were damped under Q. gambelii , perhaps due in part to hydraulic redistribution of deep soil water or groundwater by Q. gambelii in these soils relative to the grass-dominated site. We also found some support for H isotope discrimination effects during water uptake by Q. gambelii . In this ecosystem, the soil water content was higher than that at the neighbouring Grass site, and thus, 25% more water was available for transpiration by Q. gambelii compared with the Grass site. This work highlights the role of plants in governing soil water variation and demonstrates that they can also strongly influence the isotope ratios of soil water. The resulting fine-scale heterogeneity has implications for the use of isotope tracers to study soil hydrology and evaporation and transpiration fluxes to improve understanding of water cycling through the soil–plant–atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydraulic redistribution by deeply rooted grasses and its ecohydrologic implications in the southern Great Plains of North America

Perennial bioenergy crops with deep (>1 m) rooting systems, such as switchgrass (Panicum virgatum L.), are hypothesized to increase carbon storage in deep soil. Deeply rooted plants may also affect soil hydrology by accessing deep soil water for transpiration, which can affect soil water content and infiltration in deep soil layers, thereby affecting groundwater recharge. Using stable H and O isotope (δ 2 H and δ 18 O) and 3 H values, we studied the soil water conditions at 20–30 cm intervals to depths of 2.4–3.6 m in paired fields of switchgrass and shallow rooted crops at three sites in the southern Great Plains of North America. We found that soil under switchgrass had consistently higher soil water content than nearby soil under shallow-rooted annual crops by a margin of 15%–100%. Soil water content and isotopic depth profiles indicated that hydraulic redistribution of deep soil water by switchgrass roots explained these observed soil water differences. To our knowledge, these are the first observations of hydraulic redistribution in deeply rooted grasses, and complement earlier observations of dynamic soil water fluxes under shallow-rooted grasses. Hydraulic redistribution by switchgrass may be a strategy for drought avoidance, wherein the plant may actively prevent water limitation. Furthermore, this raises the possibility that deeply rooted grasses may be used to passively subsidize soil water to more shallow-rooted species in inter-cropping arrangements.

3H↗
DOE OSTI2014

Characterizing Sub-Daily Flow Regimes: Implications of Hydrologic Resolution on Ecohydrology Studies

Natural variability in flow is a primary factor controlling geomorphic and ecological processes in riverine ecosystems. Within the hydropower industry, there is growing pressure from environmental groups and natural resource managers to change reservoir releases from daily peaking to run-of-river operations on the basis of the assumption that downstream biological communities will improve under a more natural flow regime. In this paper, we discuss the importance of assessing sub-daily flows for understanding the physical and ecological dynamics within river systems. We present a variety of metrics for characterizing sub-daily flow variation and use these metrics to evaluate general trends among streams affected by peaking hydroelectric projects, run-of-river projects and streams that are largely unaffected by flow altering activities. Univariate and multivariate techniques were used to assess similarity among different stream types on the basis of these sub-daily metrics. For comparison, similar analyses were performed using analogous metrics calculated with mean daily flow values. Our results confirm that sub-daily flow metrics reveal variation among and within streams that are not captured by daily flow statistics. Using sub-daily flow statistics, we were able to quantify the degree of difference between unaltered and peaking streams and the amount of similarity between unaltered and run-of-river streams. The sub-daily statistics were largely uncorrelated with daily statistics of similar scope. Furthermore, on short temporal scales, sub-daily statistics reveal the relatively constant nature of unaltered streamreaches and the highly variable nature of hydropower-affected streams, whereas daily statistics show just the opposite over longer temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The ecohydrological context of drought and classification of plant responses

Many recent studies on drought-induced vegetation mortality have previously explored how plant functional traits, and classifications of such traits along axes of, e.g., isohydry–anisohydry, might contribute to predicting drought survival and recovery. As these studies proliferate, the consistency and predictive value of such classifications need to be carefully examined. Here, we outline the basis for a systematic classification of plant drought responses that accounts for both environmental conditions and functional traits. We use non-dimensional analysis to integrate plant traits and metrics of environmental variation into groups that can be associated with alternative drought stress pathways (hydraulic failure and carbon limitation), and demonstrate that these groupings predict physiological drought outcomes using both synthetic and measured data. In doing so, we aim to untangle some confounding effects of environment and trait variations that undermine current classification schemes, advocate for more careful treatment of the environmental context within which plants experience and respond to drought, and outline a pathway towards a general classification of drought vulnerability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AI-Based Integrated Modeling and Observational Framework for Improving Seasonal to Decadal Prediction of Terrestrial Ecohydrological Extremes

Focal Areas: (1) Insight gleaned from complex data (both observed and simulated) using artificial intelligence(AI), big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI (2) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks

Focal Areas: (2) Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (3)Insight gleaned from complex data (both observed & simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ecohydrological controls on root and microbial respiration in the East River watershed of Colorado

The main objective of this project was to conduct exploratory work to quantify how snow and rain water inputs influence the CO2 coming from the soil surface (soil CO2 flux), and its plant and microbial sources, in the East River watershed, near Crested Butte, Colorado. Knowledge gained from this effort laid the groundwork for a more comprehensive (ongoing) follow-on grant that is using a combination of experiments, field observations, machine learning and simulation modeling to fully disentangle these relationships. New field measurements were made at four locations along an elevational transect on Snodgrass Mountain at Rocky Mountain Biological Laboratory. These sites were chosen to differ in total snowpack and water table depth, and included both deciduous (aspen) and evergreen (spruce/fir) forest types. We used automated measurements of soil CO2 concentrations to quantify the total soil CO2 flux, and the vertical CO2 production within the soil profile at each site. Isotope (radiocarbon, 14C) measurements determined how much of the CO2 emitted from the soil surface came from plant respiration (root metabolism) versus microbial respiration (decomposition of soil organic matter) sources. Supporting data on plant phenology and microbial dynamics provided context for the observed variation in respiration sources. This work was motivated by our overarching hypothesis that quantifying belowground plant and microbial processes separately, and how they are influenced by snow and rain inputs, is necessary for understanding and predicting how the East River watershed ecosystems will respond to future environmental change.

54 ENVIRONMENTAL SCIENCES↗