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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

CRiSPPy: An advanced hydropower scheduling tool for the Colorado River Storage Project

The Western Area Power Administration (WAPA) plays a vital role in delivering reliable and cost-effective hydroelectric power to millions of customers across the western United States. The Colorado River Storage Project (CRSP) carries out WAPA’s mission in Arizona, Utah, Colorado, New Mexico, Nevada, Wyoming and Texas. Achieving this mission requires effective management of the Colorado River system, and depends on the use of advanced analytical tools and modeling methodologies. For many years, CRSP has relied on the Generation and Transmission Maximization Superlite (GTMax SL) model for its mid-term and long-term hydroscheduling needs. However, the evolving energy market, power system operations, environmental rules, and hydrology conditions, coupled with advancements in computational capabilities, have necessitated the development of a more modern and robust solution. This report introduces the Colorado River Storage Project Python-based (CRiSPPy) model, a new, advanced hydropower scheduling tool developed to address CRSP ever-evolving challenges. CRiSPPy represents a significant leap forward in our ability to model and optimize the operation of the Colorado River system. It incorporates state-of-the-art optimization algorithms, enhanced data management capabilities, and an advanced graphical user interface, providing WAPA CRSP personnel with unprecedented insights and decision-making support. This document details the development, capabilities, and implementation of CRiSPPy. It is intended to serve as a comprehensive resource for WAPA staff, stakeholders, and anyone interested in the future of hydropower scheduling in the Colorado River Basin. We are confident that CRiSPPy will enhance WAPA's mission while adapting to the challenges of a dynamic and increasingly complex environment. The version of CRiSPPy described in this report is the version 2.3. New versions of CRiSPPy will be developed as the tool keeps evolving to address CRSP challenges.

13 HYDRO ENERGY↗
DOE OSTI2026

Wind River Experimental Forest Subcanopy Tower Information Sheet

Wind River was one of three sites that collected 3d sonic anemometer data for an ICOS subcanopy observation study. The three sites were defined by the following features and terrain: a deciduous broadleaf forest in flat terrain (Lanžhot, Czech Republic), a coniferous forest in mountainous terrain (Renon, Italy), and a tall conifer forest in mountain-valley terrain (Wind River, USA). The Wind River subcanopy towers were deployed in a high LAI, old-growth evergreen conifer forest and collected approximately 11 months of data. The site is an ecologically rich temperate rainforest in the western Cascade Mountains, and the biological carbon sink and source strength has been measured since 1998 using eddy covariance on the top of a 74 m tall flux tower (currently called the Wind River NEON tower). Additionally, forest inventory records date back to the 1920s. In 2024, four subcanopy towers were installed near the Wind River NEON tower to measure wind flow in the understory canopy layer for better understanding canopy flow coupling and decoupling in the subcanopy and how this affects the interpretation of overstory fluxes. The subcanopy tower installation was done by Lawrence Livermore National Laboratory and Washington State University (WSU) with collaborations from the University of Utah and the National Ecological Observatory Network (NEON).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigation of Scale-Dependent Groundwater/Surface-water Exchange in Rivers by Gradient Self-Potential Logging: Numerical Modeling and Field Experiments

Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.

Engineering↗
DOE OSTI2020

Differential Impact of Climate Change on the Hydropower Economies of Karakoram and Himalayan River Basins

Water stored in the form of snow and glaciers in the High Mountain Asia (HMA) region regulates the water supply, and resultant water-based economies, that support the livelihoods of millions of people. Trends in the seasonal and long-term melting of snow and glaciers, governed by initial ice reserves, meteorological factors and geographic features, vary across sub-basins in the HMA region. We examined the economic impacts of climate-led changes in river flow in two drainage basins, one each from the Karakoram and Central Himalaya region. We used an integrated assessment framework to estimate the changes in economic value of the hydropower generation from hydropower plants on rivers fed by snow and glacier melt in the two sub-basins. The framework, developed under a NASA High Mountain Asia project, coupled biophysical models (a suite of climate models, snow/glacier-hydrology, and hydropower model) with economic analysis. We compared the differences in estimated river flow over historic and future time using the water balance model in sixteen scenarios (eight climate models and two emissions scenarios) for rivers upstream of hydropower plants in each sub-basin. Using the hydropower model we developed, we estimated the changes in hydropower generation at the Naltar IV hydropower plant, with an 18 MW capacity, located in Hunza, Karakoram, and the Trishuli hydropower plant, with a 19.6 MW capacity, in Trishuli, Central Himalaya. When compared to their baselines, the estimated impact of climate change and temporal variability were higher for the Naltar plant than for the Trishuli plant. Our sensitivity analysis shows that hydropower plants with water storage facilities help reduce the impact of changes, but the estimated impacts are higher for the higher capacity plants. This study provides an example of the differential impacts of climate change on hydropower plants located in rivers fed by varying amounts of snow and glacier melt at different decades in this century. This type of integrated assessment of climate change impact will support the scientific understanding of hydrologic flow and its impacts on a hydropower economy under various climate scenarios, as well as generate information about water resource management in a changing climate.

climate change↗
DOE OSTI2023

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.

Opperman, Jeffrey J.↗
DOE OSTI2020

Policy Innovation and Governance for Irrigation Sustainability in the Arid, Saline San Joaquin River Basin

This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same resource management issues are being played out in arid, agricultural regions around the world. The first part of this paper provides an introduction to some of the early issues impacting the expansion of irrigated agriculture primarily on the west side of the San Joaquin Valley and the policy and capital investments that were used to address salinity impairments to the use of the San Joaquin River (SJR) as an irrigation water supply. Irrigated agriculture requires large quantities of water if it is to be sustained, as well as supply water of adequate quality for the crop being grown. The second part of the paper addresses these supply issues and a period of excessive groundwater pumping that resulted in widespread land subsidence. A joint federal and state policy response that resulted in the facilities to import Delta water provided a remedy that lasted almost 50 years until the Sustainable Groundwater Management Act of 2014 was passed in the legislature to address a recurrence of the same issue. The paper describes the current state of basin-scale simulation modeling that many areas, including California, are using to craft a future sustainable groundwater resource management policy. The third section of the paper deals with unique water quality issues that arose in connection with the selenium crisis at Kesterson Reservoir and the significant threats to irrigation sustainability on the west side of the San Joaquin Valley that followed. The eventual policy response to this crisis was incremental, spanning two decades of University of California-led research programs focused on finding permanent solutions to the salt and selenium contamination problems constraining irrigated agriculture, primarily on the west side. Arid-zone agricultural drainage-induced water quality problems are becoming more ubiquitous worldwide. One policy approach that found traction in California is an innovative variant on the traditional Total Maximum Daily Load (TMDL) approach to salinity regulation, which has features in common with a scheme in Australia’s Hunter River Basin. The paper describes the real-time salinity management (RTSM) concept, which is geared to improving coordination of west side agricultural and wetland exports of salt load with east side tributary reservoir release flows to improve compliance with river salinity objectives. RTSM is a concept that requires access to continuous flow and electrical conductivity data from sensor networks located along the San Joaquin River and its major tributaries and a simulation model-based decision support designed to make salt load assimilative capacity forecasts. Web-based information dissemination and data sharing innovations are described with an emphasis on experience with stakeholder engagement and participation. The last decade has seen wide-scale, global deployment of similar technologies for enhancing irrigation agriculture productivity and protecting environmental resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

CO2 partial pressure and fluxes in the Amazon River Plume using in situ and remote sensing data

Estimations of the global carbon budget include a quantitative understanding of the evolving processes that occur along river-to-ocean gradients. However, high spatiotemporal resolution observations of these processes are limited. Here we present in situ measurements of the partial pressure of CO2 (pCO2) made through the Amazon River plume (ARP) during different discharge seasons, from 2010-2012. We evaluated the spatiotemporal distribution of pCO2 using Soil Moisture and Ocean Salinity (SMOS) satellite observations for each hydrologic period in the ARP. Regression models were used to estimate pCO2 at the ARP for the period of 2010-2014. From these distributions we calculated sea-air gas exchange of CO2 between the plume waters and the atmosphere (F_co2^sea). Intra-annual variability of F_co2^sea was related to discharge at the river mouth and ocean currents as well as trade winds in the plume. Climatic events during the study period had a significant impact on the F_co2^sea. Including the plume area closer to the river mouth makes the ARP a net source of CO2 with an annual net sea-air flux of 8.6 ±7.1 Tg C y-1 from 2011-2014.

Amazon↗
DOE OSTI2023

Dissolved Oxygen and Temperature Data from the Hyporheic Zone of the East River Watershed July 2017 to October 2018

Dissolved oxygen (DO) is critical for aquatic ecosystems. Our focus is on the long-term DO dynamics in hyporheic zone of rivers, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. The study site is the alpine East River watershed in Colorado, USA, meander A downstream from the pump house. Opti O2 probes were deployed in the water column and directly within the river-bed at 10, 20, and 35 cm depth (38°55'23.38"N, 106°57'4.21"W, 9046.88m) to monitor DO and temperature. A continuous data stream from July 24, 2017 to Oct 24, 2018 was autonomously telemetered to the cloud. This 14-month DO and temperature time series were obtained without any servicing for maintenance or data downloads; additionally the ability to remotely verify probe performance during field deployment was essential to confirm data validity during winter freeze-in and hydrological/weather events, such as spring melt and summer monsoons. We investigate the variations in dissolved oxygen dynamics of this snow-pack dominated watershed during a comparatively low flow water year (2018) and a relatively normal water year (2017), enabled by distinctive, in-situ, high frequency (∆t = 5min) sensors that provided a continuous time-series from the undisturbed study site over multiple seasons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Timeseries Unlabeled and Labeled Photos, Modeled Stream Elevation, and (Meta)Data of Variably Inundated Streams Across The Yakima River Basin, Washington, United States (v2)

This dataset is associated with the “River Monitoring Photos” (RMP) study and subsequent manuscript (Bao et al. 2025. Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence doi: 10.1016/j.envsoft.2025.106715). Game camera timeseries photos were collected to evaluate stream variable inundation via changes in width. A subset of photos was labeled for training the YOLOv8 and Mask2Former models and used to segment water surface fractions from all the game camera photos.This data package was originally published in March 2024. It was updated in October 2025 (v2) to add additional photos and files associated with the manuscript (i.e., processed data, labeled photos, and trained models). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to a 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 dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; and (5) folders containing game camera photos and manuscript-associated files. Each Yakima River Basin site has a folder that contains subfolders for each month photos were collected. There is also a folder for files associated with the manuscript which has subfolders for labeled data, trained models, Yakima River Basin site water surface fractions, and USGS site water surface fractions. All files are .csv, .json, .txt, .yaml, .pth, .pt, or .pdf. We thank the Confederated Tribes and Bands of 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.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Automated Detection of Instability-Inducing Channel Geometry Transitions in Saint-Venant Simulation of Large-Scale River Networks

A new sweep-search algorithm (SSA) is developed and tested to identify the channel geometry transitions responsible for numerical convergence failure in a Saint-Venant equation (SVE) simulation of a large-scale open-channel network. Numerical instabilities are known to occur at “sharp” transitions in discrete geometry, but the identification of problem locations has been a matter of modeler’s art and a roadblock to implementing large-scale SVE simulations. The new method implements techniques from graph theory applied to a steady-state 1D shallow-water equation solver to recursively examine the numerical stability of each flowpath through the channel network. The SSA is validated with a short river reach and tested by the simulation of ten complete river systems of the Texas–Gulf Coast region by using the extreme hydrological conditions recorded during hurricane Harvey. The SSA successfully identified the problematic channel sections in all tested river systems. Subsequent modification of the problem sections allowed stable solution by an unsteady SVE numerical solver. The new SSA approach permits automated and consistent identification of problem channel geometry in large open-channel network data sets, which is necessary to effectively apply the fully dynamic Saint-Venant equations to large-scale river networks or for city-wide stormwater networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Determining flow directions in river channel networks using planform morphology and topology

Abstract. The abundance of global, remotely sensed surface water observations has accelerated efforts toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Staying Current: A Community Readiness Framework for Marine Energy Applied to River Current Energy in Alaska

Marine energy-including wave, tidal, and river current energy-can provide a local energy source for rural and remote communities. Marine energy has the potential to bolster self-sufficiency and create economic opportunities while preserving ecological integrity. Communities may be interested in deploying, testing, and advancing these early-stage technologies to meet their needs. However, limited capacity, workforce constraints, and other barriers can challenge development. To better understand a community's interest in and preparedness for marine energy, we developed a suite of 150 'metrics of readiness.' Organized across seven categories-technical, social, environmental, strategic, governance, economic, financial-and 29 subcategories, the metrics provide a holistic perspective beyond the technical aspects of an energy device. We conducted a desktop application of the metrics of readiness for Igiugig, Alaska. The metrics were applied retrospectively for two points in time: before (2009) and after (2018) in-stream testing of a river current energy device. By documenting changes among categories and subcategories of the metrics, our results show the evolving nature of community readiness for river current energy. They also illustrate how our interdisciplinary framework captures the investment in environmental effects research and commitment to strategic planning that occurred in Igiugig. In future applications, we envision the framework could be used to foster public engagement in marine energy, collaborate with communities in project development, shape capacity building activities, prioritize investments, and inform research needs. While our study focuses on enabling river current energy in Alaska, the metrics of readiness have the potential to inform implementation of other renewable technologies with communities in new geographies.

13 HYDRO ENERGY↗
DOE OSTI2024

Geological study of an outburst flood event in the upper Yangtze River and risk of similar extreme events

Here, outburst flood sediments are studied on the upper course of the Yangtze River (known as the Jinsha River) where is a key region for the development of hydroelectric power. As the history and magnitude of outburst flooding in this stretch of the Jinsha River during historic times has remained largely undocumented, we have endeavored as part of this study to conduct field investigations into, and provide numerical dating (using OSL and 14 C dating techniques) of outburst flood evidence found in the First Bend area of the Yangtze River. Carbonized nutshells and charcoal from the ancient settlement yielded 14 C ages that precisely pinpointed an outburst flood event ~1200–1300 cal yr BP, during China's Tang Dynasty (618–907 CE). However, OSL ages using the minimum age model for all outburst flood samples ranged from 9.1 to 1.8 ka, which was ~0.5–7.8 ka older than the 14 C-dated outburst flood. This discrepancy suggests a potential overestimation of quartz age when dating outburst flood sediments from the Holocene period. Furthermore, using 2D hydraulic modeling, we estimated the magnitude of the aforementioned outburst flood, revealing a reconstructed peak flow discharge of 51,000–55,300 m 3 /s. This discharge was three times greater than the 10,000-year flood for the hydroelectric power station nearest to the study area. Our study underscores the significant role of combining archaeological and geological evidence in enhancing paleoflood hydrology research. Through a multidisciplinary approach, our findings emphasize the importance of paleoflood hydrology studies in comprehending both the latent and catastrophic flood risks in alpine mountain areas amid the context of global warming.

14C dating↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Press and Pulse of Climate Change: Extreme Events in the Colorado River Basin

Extremes in temperature and precipitation are associated with damaging floods, prolonged drought, destructive wildfires, agricultural challenges, compromised human health, vulnerable infrastructure, and threatened ecosystems and species. Often, the steady and progressive trends (or presses) of rising global temperature are the central focus in how climate impacts are described. However, observations of extreme weather events (or pulses) increasingly show that the intensity, duration and/or frequency of acute events are also changing, resulting in greater impacts on communities and the environment. Describing how the influence of extreme events may shape water management in the Colorado River Basin in clear terms is critical to sound future planning and efforts to manage risk. Three scenario planning workshops in 2019 and 2020 were held as part of a Colorado River Conversations series, identifying potential impacts from multiple intersecting extreme events. Water managers identified climate-related events of concern in the Colorado River Basin that necessitate greater attention and adaptive responses. To support efforts to include consideration of climate-change-driven extremes in water management and planning, we explore the current state of knowledge at the confluence of long-term climate shifts and extreme weather in the Colorado River Basin related to the events of concern that were identified by scenario planning participants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling geogenic and atmospheric nitrogen through the East River Watershed, Colorado Rocky Mountains

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. In this study, we develop the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Several calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed. When accounting for recycling of N through plant litter turnover, rock weathering accounts for approximately 12% of the annual dissolved N sources to the watershed in the most probable calibration scenario (0–31% in other scenarios), and 21% (0–44% in other scenarios) when considering only “new” N sources (i.e. geogenic and atmospheric). On an annual scale, instream dissolved N elimination, plant turnover (including cattle grazing) and atmospheric deposition are the most important controls on N cycling.

54 ENVIRONMENTAL SCIENCES↗