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USGS2003

Data-based comparisons of moments estimators using historical and paleoflood data

This paper presents the first systematic comparison, using historical and paleoflood data, of moments-based flood frequency methods. Peak flow estimates were compiled from streamflow-gaging stations with historical and/or paleoflood data at 36 sites located in the United States, Argentina, United Kingdom and China, covering a diverse range of hydrologic conditions. The Expected Moments Algorithm (EMA) and the Bulletin 17B historical weighting procedure (B17H) were compared in terms of goodness of fit using 25 of the data sets. Results from this comparison indicate that EMA is a viable alternative to current B17H procedures from an operational perspective, and performed equal to or better than B17H for the data analyzed. We demonstrate satisfactory EMA performance for the remaining 11 sites with multiple thresholds and binomial censoring, which B17H cannot accommodate. It is shown that the EMA estimator readily incorporates these types of information and the LP-III distribution provided an adequate fit to the data in most cases. The results shown here are consistent with Monte Carlo simulation studies, and demonstrate that EMA is preferred overall to B17H. The Bulletin 17B document could be revised to include an option for EMA as an alternative to the existing historical weighting approach. These results are of practical relevance to hydrologists and water resources managers for applications in floodplain management, design of hydraulic structures, and risk analysis for dams. ?? 2003 Elsevier Science B.V. All rights reserved.

Journal of Hydrology↗

USGS2010

Using prediction uncertainty analysis to design hydrologic monitoring networks: Example applications from the Great Lakes water availability pilot project

The importance of monitoring networks for resource-management decisions is becoming more recognized, in both theory and application. Quantitative computer models provide a science-based framework to evaluate the efficacy and efficiency of existing and possible future monitoring networks. In the study described herein, two suites of tools were used to evaluate the worth of new data for specific predictions, which in turn can support efficient use of resources needed to construct a monitoring network. The approach evaluates the uncertainty of a model prediction and, by using linear propagation of uncertainty, estimates how much uncertainty could be reduced if the model were calibrated with addition information (increased a priori knowledge of parameter values or new observations). The theoretical underpinnings of the two suites of tools addressing this technique are compared, and their application to a hypothetical model based on a local model inset into the Great Lakes Water Availability Pilot model are described. Results show that meaningful guidance for monitoring network design can be obtained by using the methods explored. The validity of this guidance depends substantially on the parameterization as well; hence, parameterization must be considered not only when designing the parameter-estimation paradigm but also-importantly-when designing the prediction-uncertainty paradigm.

Scientific Investigations Report↗

USGS2020

Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico

An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.

Alabama, Florida, Georgia, Mississippi, North Caro↗

USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗

USGS2026

Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations

In April 2020, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center introduced a Level 2 provisional Aquatic Reflectance (AR) product for the Landsat 8 Operational Land Imager (OLI), marking the initial phase in developing a standardized global product for Landsat-derived surface water measurements. The goal of USGS EROS aquatic product research and development is to prepare for an operational processing architecture for Landsat Collection 3 in the late 2020s that will enable use of quality-controlled data for emerging Landsat aquatic science applications. To achieve this, we released a subset of the Landsat 8/9 provisional AR products (Crawford et al., 2025, https://doi.org/10.5066/P14MBBRM) and examined its general performance through the Science Algorithms to Operations (SATO) framework alongside quantitative assessment using community made inland water data records (GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments, GLORIA) and radiometric coastal validation platforms (NASA’s Ocean Color component of the Aerosol Robotic Network, AERONET-OC). Variability within the validation datasets indicate that the performance of the Landsat 8/9 provisional AR retrieval is highly context-dependent; errors are minimal in optically simple waters (e.g., clear to moderately turbid coastal waters) but increase considerably in optically complex waters where factors such as elevated levels of turbidity, chlorophyll (Chl a ) concentrations, or colored dissolved organic matter (CDOM) dominate the water column. Additionally, this paper examines key algorithmic considerations for atmospheric correction, highlighting factors that influence accuracy, scalability, and computational efficiency necessary for collection processing in the operational Landsat Product Generation System (LPGS). This paper is intended to communicate with aquatic scientists, satellite oceanographers, and the broader Earth observation community on the origins, requirements, challenges, successes, and future objectives for operationalizing global AR data products for Landsat satellite missions.

Earth System Science Data↗

USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗

USGS2023

Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis

Originally developed for terrestrial science and applications, the US Geological Survey Landsat surface reflectance (SR) archive spanning ~ 40 yr of observations has been increasingly utilized in large-scale water-quality studies. These products, however, have not been rigorously validated using in situ measured reflectance. This letter quantifies and demonstrates the quality of the SR products by harnessing a sizeable global dataset ( N = 1100). We found that the Landsat 8/9 SR in the green and red bands marginally meet the targeted accuracy requirements (30%), whereas the uncertainties in the blue and coastal-aerosol bands ranged from 48% to 110%. We further observed > +25% biases in the visible bands of Landsat 5/7 SR, which can introduce an apparent downward trend when applied in time-series analyses combined with Landsat 8/9. Users must exercise caution when using this archive for trend analyses, and progress in atmospheric correction is required to foster advanced applications of the Landsat archive for aquatic science.

Limnology and Oceanography Letters↗

USGS2024

The 3D Elevation Program—Supporting Florida's economy

Introduction Florida has the longest coastline of any State in the contiguous United States, and its coastal resources are one of the main drivers of its economic growth. High-quality elevation data are beneficial for use in emergency management, especially for hurricane response, recovery, and mitigation, as well as for coastal zone management, flood risk management, infrastructure planning, agriculture, forestry, and natural resources management. Having regional or statewide elevation data coverage that was collected at about the same time allows for improved results from in-depth modeling and more meaningful analysis to support the State’s Chief Science Officer, Geographic Information Officer, State agencies, water management districts, and local governments that will use these data for decision making. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.

Florida↗

USGS2007

Meeting the challenge of policy-relevant science: lessons from a water resource project

Water resource scientists face complex tasks in evaluating aspects of water projects, but relatively few assessment procedures have been applied and accepted as standard applications. Decision-makers often rely on environmental assessments to evaluate the value and operation of projects. There is often confusion about scientists' role in policy decisions. The scientist can affect policy-making as an expert withess, an advocate or a surrogate. By understanding the policy process, scientists can make their work more “policy relevant.” Using the Terror Lake hydro project in Alaska as a guide, three lessons are discussed: (1) not all problems are able to be solved with technology; (2) policy-relevant technology is rarely imposed on a problem; and (3) the scientist need not just react to the policy process, but can have an impact on how that process unfolds.

Journal of the American Water Resources Associatio↗

USGS2018

Patterns, pace and processes of water-quality variability: Examples from a long-studied estuary

Environmental time series have rich information content that is invaluable for measuring and understanding changes over time and guiding policies to manage change. I extracted information from measurements of 10 water‐quality constituents in upper San Francisco Bay from 1975 to 2016, one of the longest observational records in a U.S. estuary. Changes were detected at every time scale captured by monthly sampling. Long‐term trends included increased ammonium (+53%), nitrate + nitrate (+50%), silicate (+14%), Secchi depth (+42%), and decreased chlorophyll a (Chl a ) (−74%) and suspended particulate matter (−45%). Changes at the decadal scale included abrupt shifts (Chl a , nitrate + nitrite) and oscillations between shorter trends of increase and decrease (Secchi depth, phosphate). Long‐term trends were not expressed equally across all seasons, and seasonal patterns of change varied across constituents. These examples illustrate key features of environmental variability at the land–sea interface: (1) water‐quality components change continually at time scales from months to decades; (2) patterns of seasonal, multiyear, and multidecadal change are complex and vary across constituents; (3) primary drivers of change are freshwater inflow, the master regulator of estuarine dynamics, and human activities such as river damming, water diversions, wastewater discharge, environmental policies, and species introductions; (4) extracting the full information content of time series requires multiple analyses, each revealing a different layer of insight into how changes develop over time; (5) water‐quality variability is nonstationary, so future changes cannot be forecast reliably; (6) repeated observation is an essential method of Earth system science with applications in the design and performance measures of environmental policies.

California↗

USGS2024

Novel data in recreation monitoring—Summary proceedings from interagency workshops in 2019 and 2023

Two interagency workshops were held in 2019 and 2023 in Fort Collins, Colorado, to discuss the use of novel data in recreation monitoring. During the workshops, the phrase “novel data in recreation monitoring” was primarily used to refer to data from social media, mobile device applications, and other online secondary sources. The goals of these workshops were to share information across agencies and researchers on the state of the science and applications for using novel data and to collectively discuss best practices for using novel data for understanding recreation on public lands and waters. Presentations during the workshops focused on use-cases, current applications, and the current state of research (as of the time of the workshops) for using novel data in recreation monitoring. Group discussions during the workshops focused on the strengths and limitations of novel data sources, potential approaches for integrating new and emerging data sources and methods with traditional approaches, and research and management needs. This report provides the proceedings of the 2019 and 2023 interagency workshops on novel data in recreation monitoring.

Scientific Investigations Report↗

USGS2011

Developing climate data records and essential climate variables from landsat data

The series of Landsat missions has compiled the longest record of satellite observation of the Earth’s land surface, extending for more than 38 years for most areas of the globe. Landsat data are particularly important as long term climate data records because the scale of observation is sufficient to differentiate between natural and human drivers of land cover change. The USGS has established consistent radiometric calibration across the Landsat TM and ETM+ sensors, and have extended the calibration back to the earlier MSS sensors. The USGS is developing capabilities to create fundamental climate data records (FCDRs), thematic climate data records (TCDRs), and essential climate variables (ECVs) from the Landsat data archive. Two high priority TCDRs were identified: surface reflectance and land surface temperature because they have direct application or are required as input to the generation of ECVs. We will focus development on a few of the terrestrial ECVs that have a high potential for being derived from Landsat data, that include land cover, albedo, fire disturbance, surface water, snow and ice, and leaf area index (LAI). We are collaborating with scientists who have demonstrated successful algorithm development and application of these science products to develop a framework of processing capabilities to support research projects and land management applications, along with an independent strategy for product validation. Our goal is to scale the creation and validation of these products from specific sites in the conterminous U.S. and Alaska, for extension to continental and global scales.

Conference Paper↗

USGS2018

Coastal National Elevation Database

The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models. CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.

Fact Sheet↗

USGS2011

U.S. Geological Survey archived data recovery in Texas, 2008-11

The 2008–11 data rescue and recovery efforts by the U.S. Geological Survey (USGS) Texas Water Science Center resulted in an efficient workflow process, database, and Web user interface for scientists and citizens to access archived environmental information with practical applications. Much of this information is unique and has never been readily available to the public. The methods developed and lessons learned during this effort are now being applied to facilitate recovering archived information requested by USGS scientists, cooperators, and the general public.

Texas↗

USGS2000

A passive integrative sampler for mercury vapor in air and neutral mercury species in water

A passive integrative mercury sampler (PIMS) based on a sealed polymeric membrane was effective for the collection and preconcentration of Hg0. Because the Hg is both oxidized and stabilized in the PIMS, sampling intervals of weeks to months are possible. The effective air sampling rate for a 15 x 2.5 cm device was about 21-equivalents/day (0.002 m3/day) and the detection limit for 4-week sampling was about 2 ng/m3 for conventional ICP-MS determination without clean-room preparation. Sampling precision was ??? 5% RSD for laboratory exposures, and 5-10% RSD for field exposures. These results suggest that the PIMS could be useful for screening assessments of Hg contamination and exposure in the environment, the laboratory, and the workplace. The PIMS approach may be particularly useful for applications requiring unattended sampling for extended periods at remote locations. Preliminary results indicate that sampling for dissolved gaseous mercury (DGM) and potentially other neutral mercury species from water is also feasible. Rigorous validation of the sampler performance is currently in progress. (C) 1999 Elsevier Science Ltd.A passive integrative mercury sampler (PIMS) based on a sealed polymeric membrane was effective for the collection and preconcentration of Hg0. Because the Hg is both oxidized and stabilized in the PIMS, sampling intervals of weeks to months are possible. The effective air sampling rate for a 15??2.5 cm device was about 21-equivalents/day (0.002 m3/day) and the detection limit for 4-week sampling was about 2 ng/m3 for conventional ICP-MS determination without clean-room preparation. Sampling precision was ???5% RSD for laboratory exposures, and 5-10% RSD for field exposures. These results suggest that the PIMS could be useful for screening assessments of Hg contamination and exposure in the environment, the laboratory, and the workplace. The PIMS approach may be particularly useful for applications requiring unattended sampling for extended periods at remote locations. Preliminary results indicate that sampling for dissolved gaseous mercury (DGM) and potentially other neutral mercury species from water is also feasible. Rigorous validation of the sampler performance is currently in progress.

Chemosphere - Global Change Science↗

USGS2015

PRMS-IV, the precipitation-runoff modeling system, version 4

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

Techniques and Methods↗

USGS1997

National Mapping Division Strategic Direction 1997

The mission of the U.S. Geological Survey's (USGS) National Mapping Division (NMD) is to meet the Nation's need for basic geopspatial data, ensuring access to and advancing the application of these data and other related earth science information for users worldwide.

Report↗

USGS2024

Development of high surface area organosilicate nanoparticulate thin films for use in sensing hydrophobic compounds in sediment and water

The scope of this study was to apply advances in materials science, specifically the use of organosilicate nanoparticles as a high surface area platform for passive sampling of chemicals or pre-concentration for active sensing in multiple-phase complex environmental media. We have developed a novel nanoporous organosilicate (NPO) film as an extraction phase and proof of concept for application in adsorbing hydrophobic compounds in water and sediment. We characterized the NPO film properties and provided optimization for synthesis and coatings in order to apply the technology in environmental media. NPO films in this study had a very high surface area, up to 1325 m 2 /g due to the high level of mesoporosity in the film. The potential application of the NPO film as a sorbent phase for sensors or passive samplers was evaluated using a model hydrophobic chemical, polychlorinated biphenyls (PCB), in water and sediment. Sorption of PCB to this porous high surface area nanoparticle platform was highly correlated with the bioavailable fraction of PCB measured using whole sediment chemistry, porewater chemistry determined by solid-phase microextraction fiber methods, and the Lumbriculus variegatus bioaccumulation bioassay. The surface-modified NPO films in this study were found to highly sorb chemicals with a log octanol-water partition coefficient (K ow ) greater than four; however, surface modification of these particles would be required for application to other chemicals.

Biosensors↗