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At least 343 records · Page 19Linked to original sources
USGS2023

Reconstructing missing data by comparing interpolation techniques: Applications for long-term water quality data

Missing data are typical yet must be addressed for proper inferences or expanding datasets to guide our limnological understanding and management of aquatic systems. Interpolation methods (i.e., estimating missing values using known values within the dataset) can alleviate data gaps and common problems. We compared seven popular interpolation methods for predicting substantial missingness in a long-term water quality dataset from the Upper Mississippi River, U.S.A. The dataset included 80,000 sampling sites collected over 30 yr that had substantial missingness for total nitrogen (TN), total phosphorus (TP), and water velocity. For all three interpolated water quality variables, random forests had very high prediction accuracy and outperformed the methods of ordinary kriging, polynomial regressions, regression trees, and inverse distance weighting. TP had a mean absolute error (MAE) of 0.03 mg (L-TP) −1 , TN had a MAE of 0.39 mg (L-TN) −1 , and water velocity had a MAE of 0.10 m s −1 . The random forests' error rates were mapped and showed low spatiotemporal variability across the riverscape, indicating high model performance across many habitat types and large spatial scales. In the current era of “big data,” interpolation becomes an imperative step prior to ecological analyses yet remains unfamiliar and underutilized. Our research briefly describes the importance of addressing missingness and provides a roadmap to conduct model intercomparisons of other big datasets. We also share adaptable data analysis scripts, which allows others to readily conduct interpolation comparisons for many limnology applications and contexts.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2011

New global hydrography derived from spaceborne elevation data

To study the Earth system and to better understand the implications of global environmental change, there is a growing need for large-scale hydrographic data sets that serve as prerequisites in a variety of analyses and applications, ranging from regional watershed and freshwater conservation planning to global hydrological, climate, biogeochemical, and land surface modeling. Yet while countless hydrographic maps exist for well-known river basins and individual nations, there is a lack of seamless high-quality data on large scales such as continents or the entire globe. Data for many large international basins are patchy, and remote areas are often poorly mapped. In response to these limitations, a team of scientists has developed data and created maps of the world's rivers that provide the research community with more reliable information about where streams and watersheds occur on the Earth's surface and how water drains the landscape. The new product, known as HydroSHEDS (Hydrological Data and Maps Based on Shuttle Elevation Derivatives at Multiple Scales), provides this information at a resolution and quality unachieved by previous global data sets, such as HYDRO1k [ U.S. Geological Survey (USGS) , 2000].

Eos, Transactions, American Geophysical Union↗
USGS2025

U.S. Geological Survey Colorado River Basin science and technology collaboration meetings on drought (2021)—Synthesis of findings

Ongoing, prolonged, and severe drought and water overuse during the first two decades of the 21st century have reduced water supplies of the Colorado River Basin, with effects cascading to ecosystems and human communities throughout the basin. In June and July 2021, the U.S. Geological Survey (USGS) Colorado River Basin Actionable and Strategic Integrated Science and Technology initiative team held a series of 12 collaboration meetings with USGS scientists and managers to discuss complicated, integrated science challenges and solutions related to drought in the Colorado River Basin. These Science and Technology collaboration meetings were structured to identify challenges experienced by meeting participants when working on complex problems, explore opportunities for coproducing scientific information, and envision future collaborative programs that leverage new technology. The 12 meetings were attended by 79 USGS staff representing 43 unique affiliations (for example, USGS science centers, mission areas, and regional offices). Meeting participants submitted 865 individual responses to six general discussion prompt topics (“Challenges,” “Knowledge Gaps,” “Existing Capabilities,” “Strategies and Actions,” “Example Applications,” and “Next Steps”) using a structured online collaboration tool. However, specific questions or tasks from each general discussion prompt varied by meeting topic. Terms from the USGS Thesaurus ( https://apps.usgs.gov/thesaurus/ ) and USGS Data Lifecycle Model ( https://www.usgs.gov/data-management/data-lifecycle ) were used to identify and summarize participant responses relevant to science integration, stakeholder engagement, and information management technology. From these responses, opportunities for the Colorado River Basin Actionable and Strategic Integrated Science and Technology initiative to facilitate science integration in the Colorado River Basin are highlighted in this report, including (a) pursuing specific interdisciplinary research topics that require integrating knowledge across spatial and temporal scales, (b) connecting scientists across disciplines, (c) reducing barriers to stakeholder engagement, (d) identifying new technologies, and (e) facilitating data access. Multiple strategies for designing future Science and Technology collaboration meetings are also outlined in this circular to better collect and analyze participant responses.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2022

Weakly supervised spatial deep learning for Earth image segmentation based on imperfect polyline labels

In recent years, deep learning has achieved tremendous success in image segmentation for computer vision applications. The performance of these models heavily relies on the availability of large-scale high-quality training labels (e.g., PASCAL VOC 2012). Unfortunately, such large-scale high-quality training data are often unavailable in many real-world spatial or spatiotemporal problems in earth science and remote sensing (e.g., mapping the nationwide river streams for water resource management). Although extensive efforts have been made to reduce the reliance on labeled data (e.g., semi-supervised or unsupervised learning, few-shot learning), the complex nature of geographic data such as spatial heterogeneity still requires sufficient training labels when transferring a pre-trained model from one region to another. On the other hand, it is often much easier to collect lower-quality training labels with imperfect alignment with earth imagery pixels (e.g., through interpreting coarse imagery by non-expert volunteers). However, directly training a deep neural network on imperfect labels with geometric annotation errors could significantly impact model performance. Existing research that overcomes imperfect training labels either focuses on errors in label class semantics or characterizes label location errors at the pixel level. These methods do not fully incorporate the geometric properties of label location errors in the vector representation. To fill the gap, this article proposes a weakly supervised learning framework to simultaneously update deep learning model parameters and infer hidden true vector label locations. Specifically, we model label location errors in the vector representation to partially reserve geometric properties (e.g., spatial contiguity within line segments). Evaluations on real-world datasets in the National Hydrography Dataset (NHD) refinement application illustrate that the proposed framework outperforms baseline methods in classification accuracy.

ACM Transactions on Intelligent Systems and Techno↗
USGS2014

User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2

Between 2002 and 2006, the Fort Collins Science Center (FORT) at the U.S. Geological Survey (USGS) conducted field surveys, organized workshops, and performed analysis of habitat for trout and shad in the Upper Delaware River Basin. This work culminated in the development of decision support system software (the Delaware River DSS–DRDSS, Bovee and others, 2007) that works in conjunction with the Delaware River Basin Commission’s reservoir operations model, OASIS, to facilitate comparison of the habitat and water-delivery effects of alternative operating scenarios for the Basin. This original DRDSS application was developed in Microsoft Excel and is available to all interested parties through the FORT web site ( http://www.fort.usgs.gov/Products/Software/DRDSS/ ). Initial user feedback on the original Excel-based DSS highlighted the need for a more user-friendly and powerful interface to effectively deliver the complex data and analyses encapsulated in the DSS. In order to meet this need, the USGS FORT and Northern Appalachian Research Branch (NARB) developed an entirely new graphical user interface (GUI) application. Support for this research was through the DOI WaterSmart program ( http://www.doi.gov/watersmart/html/index.php ) of which the USGS component is the National Water Census ( http://water.usgs.gov/watercensus/WaterSMART.html ). The content and methodology of the new GUI interface emulates those of the original DSS with a few exceptions listed below. Refer to Bovee and others (2007) for the original information. Significant alterations to the original DSS include: • We moved from Excel-based data storage and processing to a more powerful database back end powered by SQLite. The most notable effect of this is that the previous maximum temporal extent of 10 years has been replaced by a dynamic extent that can now cover the entire period of record for which we have data (1928–2000). • We incorporated interactive geographic information system (GIS) visualization and dynamic data processing. Previous habitat maps were generated outside of the DSS in an ad hoc process that the end user could not update or investigate. • The original bathymetric data collected in 2005 at the three main stem reaches was augmented with a higher resolution dataset collected in 2010. This new dataset was collected in order to conduct higher resolution (finer pixel size) two-dimensional (2D) hydrodynamic modeling for evaluating dwarf wedgemussel (DWM, Alasmidonta heterodon ) habitat. • Results charts are now substantially more interactive, dynamic, and accessible, which allows users to more easily focus on their particular topics of interest as well as drill down to the source data used to calculate given results.

Open-File Report↗
USGS2005

Geochemistry and characteristics of nitrogen transport at a confined animal feeding operation in a coastal plain agricultural watershed, and implications for nutrient loading in the Neuse River basin, North Carolina, 1999-2002

Chemical, geologic, hydrologic, and age-dating information collected between 1999 and 2002 were used to examine the transport of contaminants, primarily nitrogen, in ground water and the pathways to surface water in a coastal plain setting in North Carolina. Data were collected from more than 35 wells and 4 surface-water sampling sites located in a 0.59 square-mile basin to examine detailed hydrogeology and geochemical processes affecting nutrient fate and transport. Two additional surface-water sampling sites were located downstream from the primary study site to evaluate basin-scale effects. Chemical and flow data also were collected at an additional 10 sites in the Coastal Plain portion of the Neuse River basin located between Kinston and New Bern, North Carolina, to evaluate loads transported in the Neuse River and primary tributary basins. At the Lizzie Research Station study site in North Carolina, horizontal flow is induced by the presence of a confining unit at shallow depth. Age-dating, chemical, and piezometric data indicate that horizontal flow from the surficial aquifer is the dominant source of ground water to streamflow. Nitrogen applied on cultivated fields at the Lizzie Research Station is substantially reduced as it moves from recharge to discharge areas. Denitrification in deeper parts of the aquifer and in riparian zones is indicated by a characterization of redox conditions in the aquifer and by the presence of excess nitrogen gas. Direct ground-water discharge of nitrate to surface water during base-flow conditions is unlikely to be significant because of strongly reducing conditions that occur in the riparian zones of these streams. Nitrate loads from a drainage tile at the study site may account for much of the nitrate load in the receiving stream, indicating that a major source of nutrients from ground water to this stream is artificial drainage. During base-flow conditions when the streams are not flowing, it is hypothesized that the mineralization of organic matter on the streambed is the source of nitrate and(or) ammonium in the stream. Base flow is a small contributor to nitrogen loads, because both flows and inorganic nitrogen concentrations are low during summer months. Effects of a confined hog operation on ground-water quality also were evaluated. The use of sprayed swine wastes to fertilize crops at the Lizzie Research Station study site since 1995 resulted in increased concentrations of nitrate and other chemical constituents in ground water beneath spray fields when compared to ground water beneath fields treated with commercial fertilizer. The nitrate concentration in ground water from the spray field well increased by a factor of 3.5 after 4 years of spray applications. Nitrate concentrations ranged from 10 to 35 milligrams per liter, and one concentration as high as 56 milligrams per liter was observed in water from this well in spring 2002. This finding is in agreement with findings of other studies conducted in the Coastal Plain of North Carolina that nitrate concentrations were significantly higher in ground water from cultivated fields sprayed with swine wastes than from fields treated with commercial fertilizer. Loads and yields of nitrogen and phosphorus in 14 streams in the Neuse River basin were evaluated for calendar years 2000 and 2001. Data indicate that anthropogenic effects on nitrogen yields were greatest in the first-order stream studied (yields were greater than 2 tons per square mile [ton/mi2] and 1 ton/mi2 or less in second- and higher-order streams) in the Little Contentnea Creek subbasin. Nitrogen yields in streams in the Contentnea Creek subbasin ranged from 0.59 to 2 ton/mi2 with typical yields of approximately 1 ton/mi2. Contentnea Creek near Evansdale had the highest yield (2 ton/mi2), indicating that a major source of nitrogen is upstream from this station. Nitrogen yields were lower at Contentnea Creek at Hookerton in 2000 and 2001 compared to previous yi

Scientific Investigations Report↗
USGS2017

How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.

Water Resources Research↗
USGS2025

Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective

Earth System Models (ESM) are crucial for quantifying climate impacts across Earth's interconnected systems and supporting science-based adaptation and mitigation. However, not including end-users, especially decision-makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision-making. While the ESM community increasingly values broad community engagement, end-users may not initially perceive models as useful for local planning. Co-designing models with end-users fosters two-way learning: users better understand models and their outputs, while modelers gain insights into fine-scale local processes like monitoring practices and management priorities. Higher-level co-design can lead to more customized, priority-driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co-design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision-makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high-resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land-atmosphere models. In the Mid-Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four-level framework: (a) Co-design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co-develop New Model Functions. We aim to help researchers consider and compare co-design across diverse modeling projects systematically and coherently.

Alaska, California, Oregon↗
USGS2012

Use of weather types to disaggregate general circulation model predictions

General circulation models (GCMs) simulate climatic conditions with a grid cell resolution on the order of 100,000 km 2 . This resolution is inadequate to assess the effects of climatic change on water resources at a regional scale. A method has been developed that uses weather-type analysis as a tool to spatially disaggregate GCM predictions to make them useful for water resource studies. The method has been applied to the Delaware River basin to predict the effects of doubling atmospheric carbon dioxide on precipitation patterns in the region. An application of the technique to the Delaware River basin indicates that future climatic conditions will show minimal changes in weather-type frequency, implying that air circulation patterns will remain unchanged. Results of this study indicate that changes in regional precipitation patterns under a doubling of atmospheric carbon dioxide will be a result of within-type changes in weather characteristics.

Journal of Geophysical Research↗
USGS2021

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

WIREs Water↗
USGS2018

Application of a luminescence‐based sediment transport model

Quantifying the transport history of sand is a challenging but important goal in geomorphology. In this paper, we take a simple idea that luminescence is bleached during transport and regenerates during storage, and use this as a basis to re‐envision luminescence as a sediment tracer. We apply a mathematical model describing luminescence through an idealized channel and reservoir system and then compare this idealized model to real rivers to see if luminescence can reproduce known sediment transport data. We provide results from application of this luminescence method in three rivers from the mid‐Atlantic region of the United States. This method appears promising. However, as a river system diverges from idealized conditions of the mathematical model, the luminescence data diverge from model predictions. We suggest that spatial variation in the delivery of sediment from hillslopes can be reflected in the channel sediment luminescence and that luminescence acts as a function of landscape dynamics.

Geophysical Research Letters↗
USGS2020

Interpretation of hydrogeologic data to support groundwater management, Bazile Groundwater Management Area, northeast Nebraska, 2019—A case demonstration of the Nebraska Geocloud

Nitrate, age tracer, and continuous groundwater-level data were interpreted in conjunction with airborne electromagnetic (AEM) survey data to understand the movement of nitrate within the Bazile Groundwater Management Area (BGMA) in northeastern Nebraska. Previously published age tracer data and nitrate data indicated vertical stratification of groundwater quality. Younger groundwater sampled within shallow parts of the aquifer had higher concentrations of nitrate, with 70 percent exceeding the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter. In contrast, groundwater sampled from deeper parts of the aquifer indicated that nitrate concentrations were less than 2 milligrams per liter and that groundwater likely recharged prior to widespread use of commercial fertilizer. The hydrostratigraphic interpretation of AEM profiles indicated that shallow and deep monitoring wells were often screened within the same homogenous zone of aquifer material. In contrast, test-hole logs indicated that there often are fine-grained layers within these homogenous zones that separate the shallow and deep monitoring well screens, but these fine-grained layers are not detected by the AEM technique because of decreased resolution of the AEM technique with depth. The stratification of groundwater ages and nitrate concentrations likely was caused by groundwater-flow paths of different length, location and time of recharge, and denitrification. Within paleochannels interpreted from AEM and test-hole data, pesticides detected in groundwater generally coincide with elevated nitrate concentrations. Continuous groundwater-level data from four monitoring well nests indicated that groundwater pumping can impose or increase downward hydraulic gradients and facilitate the downward movement of nitrate into deeper parts of the High Plains aquifer. Given the density of irrigation wells within the BGMA, this effect on the hydraulic gradient is likely prevalent in other areas of the BGMA. Understanding seasonal water-level changes can allow water managers to better predict and assess the hydraulic gradient and the vulnerability of groundwater in deeper parts of the High Plains aquifer. Nitrate, age tracer, and continuous groundwater-level data within the BGMA were interpreted in conjunction with AEM data as a case demonstration of the Nebraska Geocloud. The Nebraska Geocloud was initiated to protect taxpayer investments in AEM data collection and realize maximum benefit of these data by creating a publicly available, online digital database for long-term data storage. The Lower Platte North, Lower Platte South, Papio-Missouri River, Nemaha, Lower Loup, Central Platte, Upper Elkhorn, Lower Elkhorn, Lower Niobrara, and Lewis and Clark Natural Resources Districts; the University of Nebraska-Lincoln Conservation and Survey Division, Nebraska Natural Resources Commission, Nebraska Department of Natural Resources; and the U.S. Geological Survey entered a cooperative agreement to begin a program of data management and research aimed at understanding the best use of AEM for groundwater sustainability and management. Resulting case-study interpretations are provided to guide use of the Nebraska Geocloud to assess water-quality conditions and can be used by water managers and staff to address applicable water resource problems.

Nebraska↗
USGS1982

Susitna Hydroelectric Project: terrestrial environmental workshop and preliminary simulation model

The technical feasibility, economic viability, and environmental impacts of a hydroelectric development project in the Susitna River Basin are being studied by Acres American, Inc. on behalf of the Alaska Power Authority. As part of these studies, Acres American recently contracted LGL Alaska Research Associates, Inc. to coordinate the terrestrial environmental studies being performed by the Alaska Department of Fish and Game and, as subcontractors to LGL, several University of Alaska research groups. LGL is responsible for further quantifying the potential impacts of the project on terrestrial wildlife and vegetation, and for developing a plan to mitigate adverse impacts on the terrestrial environment. The impact assessment and mitigation plan will be included as part of a license application to the Federal Energy Regulatory Commission (FERC) scheduled for the first quarter of 1983. The quantification of impacts, mitigation planning, and design of future research is being organized using a computer simulation modelling approach. Through a series of workshops attended by researchers, resource managers, and policy-makers, a computer model is being developed and refined for use in the quantification of impacts on terrestrial wildlife and vegetation, and for evaluating different mitigation measures such as habitat enhancement and the designation of replacement lands to be managed by wildlife habitat. This report describes the preliminary model developed at the first workshop held August 23 -27, 1982 in Anchorage.

Report↗
USGS2006

Section 3. The SPARROW Surface Water-Quality Model—Theory, application and user documentation

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling technique for relating water-quality measurements made at a network of monitoring stations to attributes of the watersheds containing the stations. The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and diffuse sources on land to rivers and through the stream and river network. The model predicts contaminant flux, concentration, and yield in streams and has been used to evaluate alternative hypotheses about the important contaminant sources and watershed properties that control transport over large spatial scales. This report provides documentation for the SPARROW modeling technique and computer software to guide users in constructing and applying basic SPARROW models. The documentation gives details of the SPARROW software, including the input data and installation requirements, and guidance in the specification, calibration, and application of basic SPARROW models, as well as descriptions of the model output and its interpretation. The documentation is intended for both researchers and water-resource managers with interest in using the results of existing models and developing and applying new SPARROW models. The documentation of the model is presented in two parts. Part 1 provides a theoretical and practical introduction to SPARROW modeling techniques, which includes a discussion of the objectives, conceptual attributes, and model infrastructure of SPARROW. Part 1 also includes background on the commonly used model specifications and the methods for estimating and evaluating parameters, evaluating model fit, and generating water-quality predictions and measures of uncertainty. Part 2 provides a user's guide to SPARROW, which includes a discussion of the software architecture and details of the model input requirements and output files, graphs, and maps. The text documentation and computer software are available on the Web at http://usgs.er.gov/sparrow/sparrow-mod.html .

Techniques and Methods↗
USGS2010

Simulation of streamflow in the McTier Creek watershed, South Carolina

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.

South Carolina↗
USGS2023

Beyond simple trend tests: Detecting significant changes in design-flood quantiles

Changes in annual maximum flood (AMF), which are usually detected using simple trend tests (e.g., Mann-Kendall test (MKT)), are expected to change design-flood estimates. We propose an alternate framework to detect significant changes in design-flood between two periods and evaluate it for synthetically generated AMF from the Log-Pearson Type-3 (LP3) distribution due to changes in moments associated with flood distribution. Synthetic experiments show MKT does not consider changes in all three moments of the LP3 distribution and incorrectly detects changes in design-flood. We applied the framework on 31 river basins spread across the United States. Statistically significant changes in design-flood quantiles were observed even without a significant trend in AMF and basins with statistically significant trend did not necessarily exhibit statistically significant changes in design-flood. We recommend application of the framework for evaluating changes in design-flood estimates considering changes in all the moments as opposed to simple trend tests.

Geophysical Research Letters↗
USGS2013

Velocity Mapping Toolbox (VMT): a processing and visualization suite for moving-vessel ADCP measurements

The use of acoustic Doppler current profilers (ADCP) for discharge measurements and three-dimensional flow mapping has increased rapidly in recent years and has been primarily driven by advances in acoustic technology and signal processing. Recent research has developed a variety of methods for processing data obtained from a range of ADCP deployments and this paper builds on this progress by describing new software for processing and visualizing ADCP data collected along transects in rivers or other bodies of water. The new utility, the Velocity Mapping Toolbox (VMT), allows rapid processing (vector rotation, projection, averaging and smoothing), visualization (planform and cross-section vector and contouring), and analysis of a range of ADCP-derived datasets. The paper documents the data processing routines in the toolbox and presents a set of diverse examples that demonstrate its capabilities. The toolbox is applicable to the analysis of ADCP data collected in a wide range of aquatic environments and is made available as open-source code along with this publication.

Earth Surface Processes and Landforms↗
USGS2007

Hydrological applications of Landsat imagery used in the study of the 1973 Indus River flood, Pakistan

During August and September 1973, the Indus River Valley of Pakistan experienced one of the largest floods on record, resulting in damages to homes, businesses, public works, and crops amounting to millions of rupees. Tremendous areas of lowlands were inundated along the Indus River and major tributaries. Landsat data made it possible to easily measure the extent of flooding, totaling about 20,000 km 2 within an area of about 400,000 km 2 south from the Punjab to the Arabian Sea. The Indus River data were used to continue experimentation in the development of rapid, accurate, and inexpensive optical techniques of flood mapping by satellite begun in 1973 for the Mississipi River floods. The research work on the Indus River not resulted in the development of more effective procedures for optical processing of flood data and synoptically depicting flooding, but also provided potentially valuable ancillary information concerning the hydrology of much of the Indus River Basin.

Indus River Basin↗