What Can Thalweg Profiles Tell Us? A Case Study from Redwood Creek, California
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Watershed Management Council Networker↗
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Influence of anthropogenic alterations on geomorphic response to climate variations and change in San Francisco Bay-Delta and watershed
Global warming and attendant sea-level rise may soon impact geomorphic processes in the Sacramento-San Joaquin River and San Francisco Bay Delta systems. During the past two centuries, dramatic anthropogenic changes in sediment supply and pervasive structural controls on rivers and floodplains have altered geomorphic responses to floods throughout a zone that extends upstream from tidally influenced areas to dams that regulate flow. Current geomorphic responses to floods differ from natural responses due to historical actions that concentrated the pre-disturbance multiple-channel and flood-basin system into single channels isolated by levees from increasingly developed floodplains and flood bypass channels, altered flow and sediment regimes, and caused subsidence of leveed Delta Islands. A review of historic and current geomorphic responses to floods illustrates the dominance of structural controls on geomorphic changes in the lowland part of the Sacramento-San Joaquin system. Current climate-change projections for CA suggest that the total volume of snowmelt runoff that may be shifted from spring and added to winter flows is roughly 5 maf/yr, similar to the volume currently available for flood storage in Sierra Nevadan reservoirs. Changes in timing of reservoir releases to accommodate these changes could add to either the magnitude or duration of winter flood peaks, each causing different geomorphic responses. Increased wintertime flows that accompany already large floods could increase overbank flood extent, erosion, and sedimentation, or alternatively increase the depth and strength of confined flows and increase the risk of levee failures. Runoff released from reservoirs as a relatively constant addition to winter baseflow would increase the duration of bankfull or possibly "levee-full" flows. This scenario could lead to bank and levee failure through increased saturation and seepage erosion. Projected sea level rise of 1-2 m would compound vulnerability of subsided Delta Islands to levee failure during floods and increase upstream backwater flooding. Thus, geomorphic responses to future climate variation and change will be closely tied to infrastructure and reservoir management, with survivability of infrastructure and decisions about timing, magnitude, and duration of flow releases from upstream reservoirs likely to determine the nature of those geomorphic responses.
Watershed Management Council Networker↗
Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities
The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.
Delaware, Maryland, Virginia↗
Council monitoring and assessment program (CMAP): A framework for using the monitoring program inventory to conduct gap assessments for the Gulf of Mexico Region
Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information). Currently, federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) are conducting monitoring activities at various scales around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and coordinated into a network of existing programs by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP), which will suggest opportunities for efficiencies and collaborative cross-program review of performance with other Gulf ecosystem recovery efforts. CMAP was designed and funded to inventory and integrate existing monitoring efforts, improve discovery and accessibility of existing monitoring data, and ensure the collected information supports management decisions. The fundamental approach to building the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping network was to: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.
Alabama, Florida, Georgia, Louisiana, Mississippi,↗
Agencies collaborate, develop a cyanobacteria assessment network
Cyanobacteria are a genetically diverse group of photosynthetic microorganisms that occupy a broad range of habitats on land and water all over the world. They release toxins that can cause lung and skin irritation, alter the taste and odor of potable water, and cause human and animal illness. Cyanobacteria blooms occur worldwide, and climate change may increase the frequency, duration, and extent of these bloom events. Rapid detection of potentially harmful blooms is essential to protect humans and animals from exposure. Information about potential for exposure, such as bloom duration, frequency, and extent, is especially critical for developing environmental management decisions during periods of limited resources and funding. The National Research Council (NRC) report Exposure Science in the 21st Century suggested that effectively assessing and mitigating exposures requires techniques for rapid measurement of a stressor, such as an algal bloom, across diverse geographic, temporal, and biologic scales (e.g., various bloom concentrations) and an enhanced infrastructure to address threats [ NRC , 2012]. The report specifically calls for approaches that use diverse information, such as satellite remote sensing, to identify and understand exposures that may pose a threat to ecosystems or human health. A collaborative effort integrates the work of the U.S. Environmental Protection Agency (EPA), NASA, the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Geological Survey (USGS) to provide an approach for using satellite ocean color capabilities in U.S. fresh and brackish water quality management decisions. The overarching goal of this collaborative project is to detect and quantify cyanobacteria blooms using satellite data records in order to support the environmental management and public use of U.S. lakes and reservoirs. Satellite remote sensing tools may enable policy makers and environmental managers to assess the sustainability of watershed ecosystems and the services they provide, now and in the future. Satellite technology allows us to develop early-warning indicators of cyanobacteria blooms at the local scale while maintaining continuous national coverage.
Eos, Earth and Space Science News↗
Low-flow water-quality characterization of the Gore Creek watershed, upper Colorado River basin, Colorado, August 1996
The Upper Colorado River Basin (UCOL) is one of 59 National Water-Quality Assessment (NAWQA) study units designed to assess the status and trends of the Nation?s water quality (Leahy and others, 1990). The UCOL study unit began operation in 1994, and surface-water-quality data collection at a network of 14 sites began in October 1995 (Apodaca and others, 1996; Spahr and others, 1996). Gore Creek, which flows through Vail, Colorado, originates in pristine alpine headwaters and is designated a gold-medal trout fishery. The creek drains an area of about 102 square miles and is a tributary to the Eagle River. Gore Creek at the mouth near Minturn (site 13 in fig. 1) is one of the 14 sites in the UCOL network. This site was selected to evaluate water quality resulting from urban development and recreational land use. The Gore Creek watershed has undergone rapid land-use changes since the 1960?s as the Vail area shifted from traditional mountain ranchlands to a four-season resort community. Residential, recreational, commercial, and transportation development continues near Gore Creek and its tributaries to support the increasing permanent and tourist population of the area. Interstate 70 runs through the watershed from Vail Pass near site 14, along the eastern side of Black Gore Creek, and along the northern side of the main stem of Gore Creek to the mouth of the watershed (fig. 1). A major local concern is how increasing urbanization/recreation affects the water quality, gold-medal trout fishery, and aesthetic values of Gore Creek. An evaluation of the spatial characteristics of water quality in the watershed upstream from site 13 at the mouth of Gore Creek (fig. 1) can provide local water and land managers with information necessary to establish water policy and make land-use planning decisions to maintain or improve water quality. Historical data collected at the mouth of Gore Creek provide information about water quality resulting from land use, but a synoptic sampling is needed to determine the distribution and sources of water-quality constituents at one point in time. In August 1996, a low-flow synoptic sampling for analyses of water-quality properties and constituents at sites in the Gore Creek watershed was done by the U.S. Geological Survey, in cooperation with the Town of Vail, Eagle River Water and Sanitation District, Upper Eagle River Water Authority, and Northwest Colorado Council of Governments, to evaluate the water quality of Gore Creek. The August low-flow period can be important from water-quality and stream ecology perspectives. There is less water available to dilute any contaminants entering the streams, and stream temperatures are highest during August. Physical habitat for aquatic plants and animals is smaller than during most other times of the year. To address these more extreme water-quality and ecological conditions, the synoptic sampling was conducted during the summer low-flow period. Specific objectives of this sampling included: 1. Establish a current data set representing the spatial characteristics of low-flow water-quality conditions in the Gore Creek watershed, and 2. Develop some understanding of land-use and water-quality relations in the watershed. This fact sheet presents hydrologic background information and an analysis of general water-quality properties and constituents, trace elements, and nutrients collected in water samples during low-flow synoptic sampling of the Gore Creek watershed. The U.S. Geological Survey also is conducting a study of the algae and macroinvertebrate communities and physical habitat of streams in the Gore Creek watershed during low flow. This study is designed to provide information about land-use and stream ecology relations in the watershed.
Colorado↗