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The field profiling lidar #ZX300-773 was deployed on the ground in an open field 880 m south of the Wind River NEON tower in summer 2025. It was co-located with LLNL's Halo XR+ scanning lidar (z05) and Argonne's Waggle Node to capture mountain-valley flows during the warm summer season. The zip files contain high frequency data. The excel files are 10-min averages.
NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.
Synthetic aperture radar (SAR) imagery of the Wind River Range area in Wyoming is compared with visible and near-infrared imagery of the same area. Data from the Seasat L-Band SAR and an aircraft X-Band SAR are compared with Landsat Return Beam Vidicon (RBV) visible data and near-infrared aerial photography and topographic maps of the same area. It is noted that visible and near-infrared data provide more information than the SAR data when conditions are the most favorable. The SAR penetrates clouds and snow, however, and data can be acquired day or night. Drainage density detail is good on SAR imagery because individual streams show up well owing to riparian vegetation; this causes higher radar reflections which result from the 'rough' surface which vegetation creates. In the winter image, the X-Band radar data show high returns because of cracks on the lake ice surfaces. High returns can also be seen in the L-Band SAR imagery of the lakes due to ripples on the surface induced by wind. It is concluded that the use of multispectral data would optimize analysis of hydrologic features.
ABSTRACT Under the United States Clean Water Act, states are required to periodically assess state waters to determine compliance with water quality criteria (including temperature) and then to develop total maximum daily loads (TMDLs) for impaired waters as necessary to bring them into compliance. We compared the performance of mechanistic stream temperature models (HeatSource, QUAL2K, and QUAL2Kw) applied to the mainstem of three TMDL watersheds (Middle Fork John Day, OR; Wind River, WA; South Fork Nooksack, WA) with that of spatial stream network (SSN) models applied to the full watersheds and used these to evaluate the potential effectiveness of restoration strategies. SSN models performed well with slightly lesser accuracy (RMSE = 0.47–0.87) for mainstem predictions than mechanistic models (RMSE = 0.4) but provided additional benefits to inform management, including information on spatial and temporal heterogeneity of restoration effectiveness throughout the watershed. Of the four scenarios considered (restoration of riparian zones to potential natural vegetation, channel narrowing, increasing flow by restricting irrigation withdrawals, and combined applications), riparian zone restoration was consistently the most effective in reducing temperatures at the outlet, mainstem, and throughout the watersheds. Predicted restoration effectiveness for thermal regimes varied significantly both within and among watersheds. A focus on water quality criteria exceedance only at the watershed outlet or along the mainstem reach can obscure knowledge of restoration potential for fish habitat in tributaries and headwaters, potential for creation of thermal refuge areas along the mainstem critical for maintaining migration corridors, and thermal regime heterogeneity across space and time.
Organic compounds such as urea and cyanate can serve as nitrogen (N) sources for nitrifying microorganisms, including ammonia-oxidizing archaea (AOA) and bacteria (AOB), complete ammonia-oxidizing (comammox) bacteria, and nitrite-oxidizing bacteria (NOB). Here we investigated metagenome-assembled genomes (MAGs) for all four nitrifier guilds generated from hydrologically variable floodplain sediments of the Wind River Basin (WRB; Riverton, WY, USA) for their genetic potential to utilize organic N compounds. A vast majority of WRB nitrifier MAGs harbored urease (ure) and at least one urea transporter ( utp, urt, dur3 ). AOA were the most abundant and phylogenetically diverse nitrifiers in WRB floodplain sediments. Several AOA MAGs encoded cyanase ( cynS ), nitrilase ( nit1 ), omega-amidase ( nit2 ), nitrile hydratase ( nthA ), and genes related to purine degradation, including biuret hydrolase ( biuH ), oxamic transcarbamylase ( allFGH ), and catabolic carbamate kinase ( allK ). AOA often encoded an uncharacterized amidohydrolase collocated with biuH , rather than allophanate hydrolase ( atzF ). A small number of AOA encoded atzF , functioning in an unknown pathway. AOB and comammox were of relatively low abundance and taxonomic diversity and were present only at certain depths in WRB; however, they encoded triuret/biuret degradation genes ( trtA, biuH , and atzH ), and in comammox, these genes were also collocated with allFGHK . The genetic potential of ammonia oxidizers in the WRB floodplain suggests that organic N may support nitrification in this system. The proposed pathways for utilizing purine degradation products other than urea potentially expand the known metabolic capabilities of AOA, AOB, and comammox bacteria and reveal the possibility for cryptic N cycling between microbial community members.
A field research program was begun in 1969 and intensified in 1970 on the physiology and biophysical responses of second-growth Douglas fir infected with root rot fungus. A double tramway system was suspended between three 100-foot instrument towers to carry sensors for measuring the energy response from above both healthy and infected trees. Processing and analysis was completed of airborne multispectral scanner imagery collected over the Wind River research area in 1969. Likelihood ratio processing of three-channel infrared data and Euclidean distance analysis of ten-channel spectrometer data did not identify incipient root rot infection outside the training sets. In all cases infected fir was misclassified as healthy fir. It was concluded from careful examination of physiological data that Poria root rot infection has little effect on water metabolism and energy exchange. What was identified was a low-grade stress that affects respiration and metabolism over long periods of time. This led to minor changes in the external physical symptoms of Poria-infected trees which was revealed only in the shortwave reflectance data.
There are no author-identified significant results in this report. The analysis of six MSS-5 frames covering most of the western half of Wyoming is discussed. The frames under consideration covered the following areas: (1) Rock Springs, (2) Western Wind River Basin, and (3) Bighorn Basin-Absarokas Mountains. Miscellaneous observations concerning identification of natural and man-made structures are included.
There are no author-identified significant results in this report. An experimental plan for enhancing spectral features related to the chemical composition of geological targets in ERTS multispectral scanner data is described. The experiment is designed to produce visible-reflective infrared ratio images from ERTS-1 data. Iron compounds are promising remote sensing targets because they display prominent spectral features in the visible-reflective infrared wavelength region and are geologically significant. The region selected for this ERTS experiment is the southern end of the Wind River Range in Wyoming. If this method proves successful it should prove useful for regional geologic mapping, mineralogical exploration, and soil mapping. It may also be helpful to ERTS users in scientific disciplines other than geology, especially to those concerned with targets composed of mixtures of live vegetation and soil or rock.
There are no author-identified significant results in this report. Remotely sensed multispectral scanner and return beam vidicon imagery from ERTS-1 is being used for: (1) water depth measurements in the Virgin Islands and Upper Lake Michigan areas; (2) mapping of the Yellowstone National Park; (3) assessment of atmospheric effects in Colorado; (4) lake ice surveillance in Canada and Great Lakes areas; (5) recreational land use in Southeast Michigan; (6) International Field Year on the Great Lakes investigations of Lake Ontario; (7) image enhancement of multispectral scanner data using existing techniques; (8) water quality monitoring of the New York Bight, Tampa Bay, Lake Michigan, Santa Barbara Channel, and Lake Erie; (9) oil pollution detection in the Chesapeake Bay, Gulf of Mexico southwest of New Orleans, and Santa Barbara Channel; and (10) mapping iron compounds in the Wind River Mountains.
The author has identified the following significant results. The Wyoming ERTS investigation has been hindered only slightly by incomplete ERTS data sets and lack of coverage. Efforts to map cultural development, vegetation distributions, and various geomorphologic features are underway. Tectonic analysis of the Rock Springs area has isolated two linear features that may be very significant with regard to the regional structure of central Wyoming. Studies of the fracture systems of the Wind River Mountains are being completed. The fracture map, constructed from ERTS-1 interpretations, contains a great deal of structural information which was previously unavailable. Mapping of the Precambrian metasedimentary and metavolcanic terrain of the Granite Mountains is nearing completion, and interpretation of ERTS supporting aircraft data has revealed deposits of iron formation.
The author has identified the following significant results. Fractures of regional extent in the Wind River Mountains of Wyoming were mapped from ERTS-1 imagery. Most previously mapped fractures were confirmed by the ERTS-1 image study, and many new fractures were discovered. In one area, the ERTS-1 imagery appeared to give superior results to ground studies.
The author has identified the following significant results. Significant results of the Wyoming investigation during the first six months include: (1) successful segregation of Precambrian metasedimentary/metavolcanic rocks from igneous rocks; (2) discovery of iron formation within the metasedimentary sequence; (3) mapping of previously unreported tectonic elements of major significance; (4) successful mapping of large scale fractures of the Wind River Mountains; (5) sucessful distinction of some metamorphic, igneous, and sedimentary lithologies by color-additive viewing of ERTS images; (6) mapping and interpretation of glacial features in western Wyoming; and (7) development of techniques for mapping small urban areas.
Ratio mapping of Wind River Range iron ore deposits from ERTS-1 imagery
The author has identified the following significant results. Preliminary results of a spectral ratioing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS-1 analog ratio images were found generally better than either ERTS-1 single channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS-1 spatial resolution are seen as well in ERTS-1 ratio and single channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS-1 data. Good preliminary quantitative agreement between ERTS-1 derived ratios and laboratory derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps. Empirical atmospheric corrections indicate that atmospheric corrections are needed to make the ratio method, and possibly other types of data processing, consistent over large geographical and temporal displacements.
Preliminary results of a spectral rationing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS analog ratio images were found generally better than either ERTS single-channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS spatial resolution are seen as well in ERTS ratio and single-channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS data. Good preliminary quantitative agreement between ERTS-derived ratios and laboratory-derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps.
The author has identified the following significant results. Significant results of the Wyoming ERTS-1 investigation during the first six months (July-December 1972) included: (1) successful segregation of Precambrian metasedimentary/metavolcanic rocks from igneous rocks, (2) discovery of iron formation within the metasedimentary sequence, (3) mapping of previously unreported tectonic elements of major significance, (4) successful mapping of large scale fracture systems of the Wind River Mountains, (5) successful distinction of some metamorphic, igneous, and sedimentary lithologies by color additive viewing, (6) mapping of large scale glacial features, and (7) development of techniques for mapping small urban areas.
The relation of aereal extent of snow cover to the average monthly runoff in a given watershed was investigated by comparing runoff records with a series of snowcover maps. Studies using the high spatial resolution available with ERTS-1 imagery were carried out for the Wind River Mountains watersheds in Wyoming, where it was found that the empirical relationship varied with mean elevation of the watershed. In addition, digital image enhancement techniques are shown to be useful for identifying glacier features related to extent of snowcover, moraine characteristics, and debris average. Longer wavelength observations using sensors on board the Nimbus 5 Satellite are shown to be useful for indicating crystal size distributions and onset of melting on glacier snow cover.
In this study, a technique and procedures using General Electric IMAGE 100 system were derived for performing a snow cover analysis of small watersheds for quasi-operational application. The study area was the Wind River Mountains of west central Wyoming. A small watershed, namely, Dinwoody Creek was selected as a test site. LANDSAT data and U-2 imagery were used in the analysis. From a minimal snowcover LANDSAT scene, multispectral analysis was performed yielding the distribution of forest, bare rock, grassland, water, and snow within the watershed. The forest and bare rock themes were saved and registered with other scenes containing greater snow cover. Likewise, elevation contours from a digitized map were stored and superimposed over the snowpack areas.