Flipping through field notebooks…
Integrates LiDAR, geophysics, and remote sensing to characterize how soil, vegetation, and bedrock properties vary across mountain watersheds and drive hydrological function.
Mountain watersheds like those surrounding the Rocky Mountain Biological Laboratory are remarkably heterogeneous: within just a few hundred meters, snowpack depth, soil moisture, vegetation type, and even the depth and fracturing of underlying bedrock can change dramatically. Understanding this heterogeneity matters because the Gunnison Basin and the broader Upper Colorado River Basin supply water to tens of millions of people downstream, and the way snow, soil, plants, and rock interact controls how much of that water actually reaches streams. Mapping watershed structure — what lies above ground and below — is the foundation for predicting how these systems will respond to earlier snowmelt, drought, and warming temperatures.
Researchers in this area combine remote sensing (measurements made from satellites, airplanes, and drones) with geophysics (techniques that image the subsurface) to build a comprehensive picture of the critical zone — the thin layer of Earth from the top of the forest canopy down through soil and weathered bedrock where life, water, and rock interact. Key tools include LiDAR, which uses laser pulses to map terrain and forest structure; the Normalized Difference Vegetation Index (NDVI), a satellite-derived measure of how green and photosynthetically active vegetation is; and electrical resistivity tomography, which sends electrical currents into the ground to map soil moisture, bedrock fractures, and subsurface layering. The Green Chromatic Coordinate, a drone-based color metric, serves as a proxy for plant greenness and evapotranspiration — the combined water loss from soil evaporation and plant transpiration.
Several concepts recur throughout the findings below. Foresummer drought sensitivity describes how much peak plant productivity drops in years with a dry early growing season (May–June). Aspect (the compass direction a slope faces) and microtopography (small bumps and depressions) create local differences in sun exposure and water pooling. Functional zonation refers to dividing a watershed into zones with similar snow, soil, and plant behavior so that scientists can model large landscapes tractably. Finally, machine learning methods — including Long Short-Term Memory (LSTM) neural networks that learn from time series data — are increasingly used to fuse these diverse measurements into predictions of snow water equivalent, evapotranspiration, and ecosystem response.
Early studies in the East River Watershed near Gothic established that microtopography and aspect exert powerful, fine-scale control on mountain ecosystems. Falco and colleagues showed that fusing LiDAR with surface geophysics could predict plant community distributions at submeter resolution, finding a strong inverse relationship between soil electrical conductivity and slope and demonstrating that soil moisture — driven by microtopography — determines where species like veratrum and sagebrush establish . In parallel, Tran and colleagues used the Community Land Model to quantify evapotranspiration across the same watershed, showing that 55% of annual precipitation is returned to the atmosphere through evapotranspiration and that transpiration alone accounts for roughly half of that flux .
How tree growth and biomass allocation patterns change based on local neighborhood tree density and competition
Normalized Difference Vegetation Index, derived from satellite imagery to estimate vegetation greenness and photosynthetic activity
The movement of water from the soil to the plant's stomata which is then released into the atmosphere, serving as an indicator of plant water status
Standardized measure of water deficit calculated using the Standardized Precipitation Evapotranspiration Index (SPEI) over 12-month periods
A proxy for subsurface moisture conditions calculated as the log ratio between upslope contributing area and slope angle
The constraint of microbial activity and carbon respiration by water availability in soil systems
Uses full-waveform LiDAR returns processed through adaptive deconvolution and individual tree detection algorithms to map forest structure metrics inc...
Integrates multiple spatial data layers including lidar, airborne geophysics, hyperspectral remote sensing, and satellite data to characterize hillslo...
Time-lapse electrical resistivity imaging using dipole-dipole array configuration to map subsurface electrical conductivity patterns and estimate soil...
Vegetation greenness assessment using Green Chromatic Coordinate as proxy for evapotranspiration rates. Calculates green reflectance normalized by tot...
Time-lapse UAV surveys using RGB and multispectral cameras to monitor vegetation indices (NDVI, GCC) and plant height changes across a hillslope trans...
Comprehensive approach calculating potential evapotranspiration using three established methods (Thornthwaite, Hargreaves, Penman-Monteith) and actual...
Data from: Thoma, D.P., S.M. Munson & D.L. Witwicki 2018. Landscape pivot points and responses to water balance in national parks of the southwest...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) du...
The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observ...
1. A recent drying trend that is expected to continue in the southwestern U.S. underscores the need for site-specific and near real-time understanding...
This dataset represents geolocation data associated with field observations and sampling from the Colorado Headwaters Ecological Spectroscopy Study (C...
These studies set the template for an integrated approach: combine satellite and airborne remote sensing with ground-based geophysical imaging and physically based models to characterize watershed structure and function across scales.
A central finding across this body of work is that watershed heterogeneity is not random — it is organized by topography, aspect, and bedrock structure, and these controls can be mapped systematically. Wainwright and colleagues demonstrated that hillslopes are a natural unit for capturing watershed-scale heterogeneity, and that unsupervised clustering of LiDAR, hyperspectral, and airborne electromagnetic data can divide a watershed into zones with characteristic snow, plant, and subsurface signatures (Wainwright et al., 2022). Uhlemann and colleagues then showed that above-ground features visible to remote sensing (vegetation patterns, microtopography) covary with below-ground bedrock properties measured by geophysics, meaning that surface observations can be used to infer hidden subsurface structure across entire watersheds (Uhlemann et al., 2022).
Drought response emerged as a second major theme. Using nearly two decades of Landsat NDVI data, Wainwright and colleagues found that foresummer drought sensitivity is spatially heterogeneous and is positive across 94% of vegetated area, meaning earlier snowmelt and drier early summers consistently reduce peak plant productivity, especially at lower elevations and in grasslands (Wainwright et al., 2020). Subsequent monitoring by Dafflon and colleagues confirmed the mechanism at the hillslope scale: heavy snow years deliver more infiltration and shallower groundwater, supporting higher greenness, while low-snow years with early bare ground produce muted growing seasons (Dafflon et al., 2023). Worsham and colleagues extended this snow-centered view to forests, showing that peak snow water equivalent and snow disappearance rate are the dominant abiotic controls on subalpine conifer forest structure across the watershed (Worsham et al., 2025).
A third thread is the role of machine learning in turning sparse measurements into watershed-scale predictions. LSTM neural networks trained on SNOTEL records produced highly accurate forecasts of snow water equivalent (Meyal et al., 2020), and a hybrid deep-learning approach successfully estimated evapotranspiration and ecosystem respiration in data-sparse mountain settings using only readily available inputs like air temperature, precipitation, and NDVI (Chen et al., 2021). Hybrid data-model approaches have also mapped soil thickness at half-meter resolution, revealing that northeast-facing hillslopes carry deeper soils than southwest-facing ones (Yan et al., 2021).
Early work from 2019–2020 established the feasibility of fusing remote sensing and geophysics in the East River. Recent studies since 2022 have shifted toward finer-resolution monitoring, predictive frameworks, and explicit uncertainty quantification. New distributed temperature profiling systems now resolve soil and snow temperature profiles at unprecedented vertical density and accuracy (Dafflon et al., 2022), while electrical resistivity monitoring combined with hydrological modeling has revealed that subsurface bedrock and vegetation gradients create starkly different hillslope flow paths over distances of tens of meters — shallow lateral flow on thin-soil upper slopes versus vertical infiltration and groundwater dynamics on colluvial lower slopes (Uhlemann et al., 2024). Researchers are also addressing previously overlooked physics: Feldman and colleagues showed that terrain-emitted longwave radiation contributes roughly 22% of surface longwave flux in the Upper Colorado River Basin, an effect commonly omitted from atmospheric models (Feldman et al., 2022).
The frontier is increasingly about using these integrated datasets to guide the next round of measurements. Wainwright and colleagues recently developed a machine-learning workflow that uses remote sensing and hydrological model outputs to identify optimal locations for ecohydrological monitoring, finding that soil moisture variability outperforms static variables like elevation as a predictor of drought sensitivity (Wainwright et al., 2024). Probabilistic hypothesis testing is also entering the field, allowing researchers to formally evaluate competing geological interpretations against geophysical data (Miltenberger et al., 2021).
Many important questions remain. How will the tight coupling between snowpack, soil moisture, and plant productivity change as snow disappears earlier and rain replaces snow at mid-elevations? How transferable are watershed zonation schemes developed in the East River to other basins with different bedrock, vegetation, and climate? Can subsurface properties — fracture density, soil thickness, bedrock weathering — be predicted reliably from surface remote sensing alone, or will geophysical ground-truthing always be required? How can three-dimensional radiation effects, lateral subsurface flow, and root water uptake be efficiently represented in the large-scale models used for water resource planning? Addressing these questions over the next decade will require sustained, co-located measurements of snow, soil, vegetation, and subsurface properties, paired with machine-learning frameworks that honestly quantify uncertainty when extrapolating beyond the conditions in which they were trained.
Chen, J., Dafflon, B., Tran, A. P., Falco, N., & Hubbard, S. S. (2021). A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration. Hydrology and Earth System Sciences. →
Dafflon, B., et al. (2023). Advanced monitoring of soil-vegetation co-dynamics reveals the successive controls of snowmelt on soil moisture and on plant seasonal dynamics in a mountainous watershed. Frontiers in Earth Science. →
Dafflon, B., Wielandt, S., Lamb, J., et al. (2022). A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature. The Cryosphere. →
Falco, N., Wainwright, H., Dafflon, B., et al. (2019). Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data. Journal of Geophysical Research: Biogeosciences. →
Feldman, A. F., et al. (2022). Three-Dimensional Surface Downwelling Longwave Radiation Clear-Sky Effects in the Upper Colorado River Basin. Geophysical Research Letters. →
Meyal, A. Y., Versteeg, R., et al. (2020). Automated Cloud Based Long Short-Term Memory Neural Network Based SWE Prediction. Frontiers in Water. →
Miltenberger, A., et al. (2021). Probabilistic Evaluation of Geoscientific Hypotheses With Geophysical Data. Application to Electrical Resistivity Imaging of a Fractured Bedrock Zone. Journal of Geophysical Research. →
Tran, A. P., Rungee, J., Faybishenko, B., Dafflon, B., & Hubbard, S. S. (2019). Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed. Water. →
Uhlemann, S., Dafflon, B., Wainwright, H. M., et al. (2022). Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics. Science Advances. →
Uhlemann, S., et al. (2024). Variations in bedrock and vegetation cover modulate subsurface water flow dynamics of a mountainous hillslope. Water Resources Research. →
Wainwright, H. M., et al. (2024). Model and remote-sensing-guided experimental design and hypothesis generation for monitoring snow-soil-plant interactions. Frontiers in Water. →
Wainwright, H. M., Steefel, C., Trutner, S. D., et al. (2020). Satellite-derived foresummer drought sensitivity of plant productivity in Rocky Mountain headwater catchments: spatial heterogeneity and geological-geomorphological control. Environmental Research Letters. →
Wainwright, H. M., Uhlemann, S., Franklin, M., et al. (2022). Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions. Hydrology and Earth System Sciences. →
Worsham, M., et al. (2025). Abiotic influences on continuous conifer forest structure across a subalpine watershed. Remote Sensing of Environment. →
Yan, Q., et al. (2021). A hybrid data-model approach to map soil thickness in mountain hillslopes. Earth Surface Dynamics. →
Soil electrical conductivity measured via electrical resistivity tomography to estimate soil moisture and subsurface properties
The number and extent of fractures in bedrock that control fluid flow and transport properties
The slope of peak NDVI as a linear function of the June Palmer Drought Severity Index, representing plant productivity responses to early growing seas...
Floodplain regions that follow the meandering pattern of rivers and serve as scaling motifs for ecosystem modeling
Metric quantifying the topographic position of a site relative to surrounding landscape
The near-surface environment where rock, soil, water, air, and living organisms interact and drive Earth surface processes
Type of recurrent neural network capable of learning temporal dependencies in sequential data through gated memory cells
Combining multiple sensor platforms and measurement approaches for comprehensive characterization
Measure of vegetation greenness calculated as G/(R+G+B) used as proxy for evapotranspiration
National Ecological Observatory Network Airborne Observation Platform flights acquiring LiDAR, imaging spectroscopy, and high-resolution camera imager...
Harmonized Landsat 8 and Sentinel-2 imagery processed through continental-scale algorithms to create vegetation index time series and estimate phenoph...
Data acquired using a Riegl Q1560 dual-channel LiDAR system mounted on a Piper Navajo aircraft. Survey complied with USGS QL1 standard with point dens...
Time-lapse photography using Moultrie M40 cameras mounted at 45° angle to capture plot-level vegetation greenness and calculate Green Chromatic Coordi...
Field observations of vegetation samples collected using tablet computers and digital forms targeting different vegetation types.
Processing of Landsat NDVI time series to quantify foresummer drought sensitivity as the slope of peak NDVI versus June Palmer Drought Severity Index....
Deriving individual-scale species data from co-acquired imaging spectrometry data.
Processing waveform LiDAR data using Optech LMS software and custom IDL waveform processor to synchronize GPS time tags and geolocate waveforms.
Inversion of AEM data to produce regional cross-sections constraining electrical properties of subsurface to ~500m depth. Creates resistivity and IP m...
Derivation of hydraulic permeability and porosity from ERT data through petrophysical relationships for model parameterization.
A novel approach combining LSTM neural networks with process-based ecological understanding to predict evapotranspiration and ecosystem respiration. T...
Numerical solution of the one-dimensional Richards equation using PFLOTRAN software to simulate soil water flow and generate synthetic soil moisture d...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
This dataset contains the files to run a ParFlow-CLM integrated hydrologic model simulation for Maina et al., HESS, 2022. It also contains the associa...
This package is part of the Watershed Function SFA project and contains a remote sensing dataset acquired at the East River, Colorado. The remote sens...
This data package includes 6 csv files that include Community Land Model (CLM) simulations for three Fluxnet sites (i.e., US-NR1, US-GLE and US-VCM) a...
Aerial imagery was collected at the Lower Montane site (Pumphouse) in the East River Watershed, Colorado during the spring, summer, and fall seasons o...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
The purpose of this data set is to provide a means of characterizing the bedrock variability both within a single borehole location and across the Eas...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine w...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observ...
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of ...
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of ...
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of ...
Soil moisture, temperature and electrical conductivity have been monitored with 5TE sensors (Decagon Inc.) located at 10 and 50 cm depth at 4 differ...
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of ...
This data package presents snow depths data from distributed temperature probes at 18 locations near Snodgrass catchment, Colorado. These data show th...
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to No...
Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observ...
This dataset contains time-lapse Electrical Resistivity Tomography (ERT) data along a transect located on the northeast-facing hillslope at the lower ...
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to No...
This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine w...
The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observ...
This dataset contains the files to run a ParFlow-CLM integrated hydrologic model simulation for Maina et al., HESS, 2022. It also contains the associa...
This dataset contains the files to run a ParFlow-CLM integrated hydrologic model simulation for Maina et al., HESS, 2022. It also contains the associa...
The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of ...
This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respi...
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to No...
This data release consists of 1,984 line-kilometers of airborne electromagnetic (AEM), magnetic data and radiometric data collected from October to No...
This dataset contains stream bed topography data from the Lower Montane site in the East River Watershed, Colorado. It is intended to support hydro-bi...
This dataset contains the files to run a ParFlow-CLM integrated hydrologic model simulation for Maina et al., HESS, 2022. It also contains the associa...
Time-lapse imagery was collected using an automated RGB camera mounted on a pole at the base of the northeast-facing hillslope at the Lower Montane si...
This dataset contains the files to run a ParFlow-CLM integrated hydrologic model simulation for Maina et al., HESS, 2022. It also contains the associa...
This report contains details of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) assignable asset (AA) flight over...
Soil moisture, temperature, and electrical conductivity have been monitored at multiple depths (between 10 and 50 cm) at 4 locations along a northeast...
This data package contains spatial data layers and processing scripts used in Wainwright, H.M. et al. 2021, “Watershed zonation approach for tractably...
These data were compiled for monitoring riparian zone trends and changes in the Navajo Nation as part of a study to document riparian ecosystem health...
This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, ai...
This release archives the code base for the manuscript Worsham et al., "Abiotic influences on continuous conifer forest structure across a subalpine w...
These data were compiled for monitoring riparian zone trends and changes in the Navajo Nation as part of a study to document riparian ecosystem health...
This is the AmeriFlux version of the carbon flux data for the site US-UR4 Gunnison - UCRB. Site Description - This site is located in Gunnison, Colora...