USGS Science⌕ Search

SEARCH · USGS Science

Results for “Environmental Modeling and Software”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11Linked to original sources
USGS2012

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

Techniques and Methods↗
USGS2016

Using spatial capture–recapture to elucidate population processes and space-use in herpetological studies

The cryptic behavior and ecology of herpetofauna make estimating the impacts of environmental change on demography difficult; yet, the ability to measure demographic relationships is essential for elucidating mechanisms leading to the population declines reported for herpetofauna worldwide. Recently developed spatial capture–recapture (SCR) methods are well suited to standard herpetofauna monitoring approaches. Individually identifying animals and their locations allows accurate estimates of population densities and survival. Spatial capture–recapture methods also allow estimation of parameters describing space-use and movement, which generally are expensive or difficult to obtain using other methods. In this paper, we discuss the basic components of SCR models, the available software for conducting analyses, and the experimental designs based on common herpetological survey methods. We then apply SCR models to Red-backed Salamander ( Plethodon cinereus ), to determine differences in density, survival, dispersal, and space-use between adult male and female salamanders. By highlighting the capabilities of SCR, and its advantages compared to traditional methods, we hope to give herpetologists the resource they need to apply SCR in their own systems.

Journal of Herpetology↗
USGS2014

Hydraulic modeling development and application in water resources engineering

The use of modeling has become widespread in water resources engineering and science to study rivers, lakes, estuaries, and coastal regions. For example, computer models are commonly used to forecast anthropogenic effects on the environment, and to help provide advanced mitigation measures against catastrophic events such as natural and dam-break floods. Linking hydraulic models to vegetation and habitat models has expanded their use in multidisciplinary applications to the riparian corridor. Implementation of these models in software packages on personal desktop computers has made them accessible to the general engineering community, and their use has been popularized by the need of minimal training due to intuitive graphical user interface front ends. Models are, however, complex and nontrivial, to the extent that even common terminology is sometimes ambiguous and often applied incorrectly. In fact, many efforts are currently under way in order to standardize terminology and offer guidelines for good practice, but none has yet reached unanimous acceptance. This chapter provides a view of the elements involved in modeling surface flows for the application in environmental water resources engineering. It presents the concepts and steps necessary for rational model development and use by starting with the exploration of the ideas involved in defining a model. Tangible form of those ideas is provided by the development of a mathematical and corresponding numerical hydraulic model, which is given with a substantial amount of detail. The issues of model deployment in a practical and productive work environment are also addressed. The chapter ends by presenting a few model applications highlighting the need for good quality control in model validation.

Book chapter↗
USGS2014

An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming

Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders. With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, social-value information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems.

Colorado;Wyoming↗
USGS1991

System requirements specification for the U.S. Geological Survey's National Water Information System II

The U.S. Geological Survey's Water Resources Division is designing and developing a new computer software system for processing and storing hydrologic data. This system, the National Water Information System (NWIS-II) will replace the current water-data and information systems: the National Water Data Storage and Retrieval System (WATSTORE), the National Water Data Exchange (NAWDEX), and the National Water-Use Information System, as well as the current National Water Information System (NWIS-I). The new system will be utilized across the Nation on the Distributed Information System (DIS-II), a network of 32-bit microcomputers on a wide-area network of desktop workstations and related hardware. The purpose of the NWIS-II System Requirements Specification is to integrate requirements described by eight User Groups representing the disciplines for Surface Water, Ground Water, Water Quality, Water Sediment, Water Use, Biology, Geographic Information, and National Water Data Exchange. The requirements specified in this document will serve as the framework for subsequent design and development activities throughout the life cycle of NWIS-II to ensure that the development products reflect the needs of the users. Specification details and associated data-base plans are contained in the description of the integrated functional requirements, the logical data model and the data dictionary, the plan for transferring data from the existing system to NWIS-II, and the descriptions of performance requirements and design constraints. The NWIS-II will be consistent across hydrologic disciplines and the other major Division software systems. The color-graphics desktop environment of NWIS-II will utilize multi-window and multi-tasking capabilities with multilevel of help for the users. Data will be distributed among nodes and be automatically accessible during input, editing, verification and analysis of data. Hydrologic data will be cataloged independent of the Environmental Protection Agency's storage and retrieval (STORET) codes. Character, digital, and graphical data will be entered into NWIS-II from digital and analog recorders, external files, or keyboard through standard and user-defined input forms. Data will be verified manually or automatically during input, retrieval, and editing of data. Numerous reference lists will be maintained so that entry of codes on forms will not be required. User-defined series of computer actions for standard programs will be supported for processing basic data and other frequently repeated processes. Data will be verified and exchanged through links to other DIS-II software, including a Geographic Information System, and selected external software. Quality assurance of data will include aging of data through change on status type and tracking access violations. Output of data will be to a variety of media in standard and user-defined formats. The data base will be preserved by operations such as backup, recovery, audit trails, archiving, and data histories. In addition, an index of water data from USGS and other agencies will be maintained.

Open-File Report↗
USGS2002

Factors leading to different viability predictions for a grizzly bear data set

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear ( Ursus arctos horribilis ) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Conservation Biology↗
USGS2004

Phosphorus and suspended sediment load estimates for the Lower Boise River, Idaho, 1994-2002

The U.S. Geological Survey used LOADEST, newly developed load estimation software, to develop regression equations and estimate loads of total phosphorus (TP), dissolved orthophosphorus (OP), and suspended sediment (SS) from January 1994 through September 2002 at four sites on the lower Boise River: Boise River below Diversion Dam near Boise, Boise River at Glenwood Bridge at Boise, Boise River near Middleton, and Boise River near Parma. The objective was to help the Idaho Department of Environmental Quality develop and implement total maximum daily loads (TMDLs) by providing spatial and temporal resolution for phosphorus and sediment loads and enabling load estimates made by mass balance calculations to be refined and validated. Regression models for TP and OP generally were well fit on the basis of regression coefficients of determination (R2), but results varied in quality from site to site. The TP and OP results for Glenwood probably were affected by the upstream wastewater-treatment plant outlet, which provides a variable phosphorus input that is unrelated to river discharge. Regression models for SS generally were statistically well fit. Regression models for Middleton for all constituents, although statistically acceptable, were of limited usefulness because sparse and intermittent discharge data at that site caused many gaps in the resulting estimates. Although the models successfully simulated measured loads under predominant flow conditions, errors in TP and SS estimates at Middleton and in TP estimates at Parma were larger during high- and low-flow conditions. This shortcoming might be improved if additional concentration data for a wider range of flow conditions were available for calibrating the model. The average estimated daily TP load ranged from less than 250 pounds per day (lb/d) at Diversion to nearly 2,200 lb/d at Parma. Estimated TP loads at all four sites displayed cyclical variations coinciding with seasonal fluctuations in discharge. Estimated annual loads of TP ranged from less than 8 tons at Diversion to 570 tons at Parma. Annual loads of dissolved OP peaked in 1997 at all sites and were consistently higher at Parma than at the other sites. The ratio of OP to TP varied considerably throughout the year at all sites. Peaks in the OP:TP ratio occurred primarily when flows were at their lowest annual stages; estimated seasonal OP:TP ratios were highest in autumn at all sites. Conversely, when flows were high, the ratio was low, reflecting increased TP associated with particulate matter during high flows. Parma exhibited the highest OP:TP ratio during all seasons, at least 0.60 in spring and nearly 0.90 in autumn. Similar OP:TP ratios were estimated at Glenwood. Whereas the OP:TP ratio for Parma and Glenwood peaked in November or December, decreased from January through May, and increased again after June, estimates for Diversion showed nearly the opposite pattern ? ratios were highest in July and lowest in January and February. This difference might reflect complex biological and geochemical processes involving nutrient cycling in Lucky Peak Lake, but further data are needed to substantiate this hypothesis. Estimated monthly average SS loads were highest at Diversion, about 400 tons per day (ton/d). Average annual loads from 1994 through 2002 were 144,000 tons at Diversion, 33,000 tons at Glenwood, and 88,000 tons at Parma. Estimated SS loads peaked in the spring at all sites, coinciding with high flows. Increases in TP in the reach from Diversion to Glenwood ranged from 200 to 350 lb/d. Decreases in TP were small in this reach only during high flows in January and February 1997. Decreases in SS, were large during high-flow conditions indicating sediment deposition in the reach. Intermittent data at Middleton indicated that increases and decreases in TP in the reach from Glenwood to Middleton were during low- and high-flow conditions, respectively. All constituents increased in the r

Scientific Investigations Report↗
USGS2021

Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017

The U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated from 2015 to 2017 to assess nutrient concentrations and fluxes across the ocean-estuary boundary at a dike on the Herring River in Wellfleet, Massachusetts. The purpose of this assessment was to characterize environmental conditions prior to a future removal of the dike, which has restricted saltwater inputs into the Herring River watershed for more than 100 years. Water temperature, dissolved oxygen, pH, and specific conductance were monitored continuously, and flow-weighted composite samples were collected approximately twice per month at the ocean-estuary boundary. Bidirectional discharge was computed for the U.S. Geological Survey Herring River at Chequessett Neck Road at Wellfleet, Massachusetts, streamgage (011058798) by using a stage-area rating and index-velocity ratings developed with acoustic Doppler current profile measurements made upstream and downstream from the dike. LOADEST regression modeling software was used to estimate nutrient fluxes (loads) from composite, paired nutrient concentration and discharge data in conjunction with continuous discharge data. Temperature, dissolved oxygen, pH, and specific conductance were also monitored continuously on two tributaries to the Herring River, Pole Dike Creek and Bound Brook, from late-May 2016 to mid-June 2017. Composite or discrete water samples were collected from the tributaries approximately twice per month in most months from late-May 2016 to mid-June 2017 and analyzed for total nitrogen, total phosphorus, and dissolved organic carbon. Flow-weighted concentrations of ammonium, nitrate, and total nitrogen on the Herring River at the dike on the ebb tide generally varied between 0.01 and 0.1, 0.003 and 0.03, and 0.3 and 0.7 milligram per liter as nitrogen, respectively. Flow-weighted concentrations of orthophosphate, total dissolved phosphorus, and total phosphorus generally varied between 0.002 and 0.02, 0.003 and 0.06, and 0.03 and 0.1 milligram per liter as phosphorus, respectively, on the ebb tide. Flow-weighted concentrations of silicate and dissolved organic carbon on the ebb tide generally varied between 0.08 and 3.0 milligrams per liter of silica (silicon dioxide), and 1.7 and 5.6 milligrams per liter of carbon, respectively. Ebb tide concentrations of nitrate were highest in winter and lowest in summer. By contrast, ebb tide concentrations of phosphorus species were highest in late summer and early fall and lowest in winter. Silica and dissolved organic carbon did not exhibit systematic variation in seasonal concentrations. There was uncertainty in estimates of nutrient fluxes, but the LOADEST-estimated fluxes indicated that annual (and in almost all cases seasonal) exports (ebb tides) exceeded inputs (flood tides). Ebb tide concentrations of ammonium, nitrate, total nitrogen, and silica were positively correlated with antecedent cumulative 7-day precipitation.

Massachusetts↗
USGS2014

Basin-scale simulation of current and potential climate changed hydrologic conditions in the Lake Michigan Basin, United States

The Great Lakes Restoration Initiative (GLRI) is the largest public investment in the Great Lakes in two decades. A task force of 11 Federal agencies developed an action plan to implement the initiative. The U.S. Department of the Interior was one of the 11 agencies that entered into an interagency agreement with the U.S. Environmental Protection Agency as part of the GLRI to complete scientific projects throughout the Great Lakes basin. The U.S. Geological Survey, a bureau within the Department of the Interior, is involved in the GLRI to provide scientific support to management decisions as well as measure progress of the Great Lakes basin restoration efforts. This report presents basin-scale simulated current and forecast climatic and hydrologic conditions in the Lake Michigan Basin. The forecasts were obtained by constructing and calibrating a Precipitation-Runoff Modeling System (PRMS) model of the Lake Michigan Basin; the PRMS model was calibrated using the parameter estimation and uncertainty analysis (PEST) software suite. The calibrated model was used to evaluate potential responses to climate change by using four simulated carbon emission scenarios from eight general circulation models released by the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3. Statistically downscaled datasets of these scenarios were used to project hydrologic response for the Lake Michigan Basin. In general, most of the observation sites in the Lake Michigan Basin indicated slight increases in annual streamflow in response to future climate change scenarios. Monthly streamflows indicated a general shift from the current (2014) winter-storage/snowmelt-pulse system to a system with a more equally distributed hydrograph throughout the year. Simulated soil moisture within the basin illustrates that conditions within the basin are also expected to change on a monthly timescale. One effect of increasing air temperature as a result of the changing climate was the appreciable increase in the length of the growing season in the Lake Michigan Basin. The increase in growing season will cause an increase in evapotranspiration across the Lake Michigan Basin, which will directly affect soil moisture and late growing season streamflows. Output from the Lake Michigan Basin PRMS model is available through an online dynamic web mapping service available at (http://pubs.usgs.gov/sir/2014/5175/). The map service includes layers for the each of the 8 global climate models and 4 carbon emission scenarios combinations for 12 hydrologic model state variables. The layers are pre-rendered maps of annual hydrologic response from 1977 through 2099 that provide an easily accessible online method to examine climate change effects across the Lake Michigan Basin.

Indiana, Illinois, Michigan, Wisconsin↗
USGS2024

Evaluation of an impulse-response emulator for groundwater contaminant transport modeling

There is a significant need to develop decision support tools capable of delivering accurate representations of environmental conditions, such as ground and surface water solute concentrations, in a timely and computationally efficient manner. Such tools can be leveraged to assess a large number of potential management strategies for mitigating non-point source pollutants. Here, we assess the effectiveness of the impulse-response emulation approach to approximate process-based groundwater model estimates of solute transport from MODFLOW and MT3D over a wide range of model inputs and parameters, with the goal of assessing where in parameter space the assumptions underlying this emulation approach are valid. The impulse-response emulator was developed using the sensitivity analysis utilities in the PEST++ software suite and is capable of approximating MODFLOW/MT3D estimates of solute transport over a large portion of the parameter space tested, except in cases where the Courant number is above 0.5. Across all runs tested, the highest percent errors were at the plume fronts. These results suggest that the impulse-response approach may be suitable for emulation of solute transport models for a wide range of cases, except when high-resolution outputs are needed, or when very low concentrations at plume edges are of particular interest.

Groundwater↗
USGS2014

Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a starting point, for other watersheds. This report describes each of the model elements with sufficient detail to guide the primary target audience, the NPS resource specialist, to run the model, interpret the results, change the input data to explore hypotheses, and ultimately modify and improve the model. Running the model and interpreting the results does not require modeling expertise on the part of the user. Additional companion publications will highlight other aspects of the model, such as its development, the rationale behind the methodological approach, scenario testing, and discussions of its use. System dynamics models consist of three basic elements: stocks , flows , and converters . Stocks are measurable quantities that can change over time, such as animal populations. Flows are any processes or conditions that change the quantity in a stock over time (Ford, 1999), are expressed in the model as a rate of change, and are diagrammed as arrows to or from stocks. Converters are processes or conditions that change the rate of flows. A converter is connected to a flow with an arrow indicating that it alters the rate of change. Anything that influences the rate of change (such as different environmental conditions, other external factors, or feedbacks from other stocks or flows) is modeled as a converter. For example, the number of fish in a population is appropriately modeled as a stock. Mortality is modeled as a flow because it is a rate of change over time used to determine the number of fish in the population. The density-dependent effect on mortality is modeled as a converter because it influences the rate of morality. Together, the flow and converter change the number, or stock, of juvenile coho. The instructions embedded in the stocks, flows, converters, and the sequence in which they are linked are processed by the simulation software with each completed sequence composing a model run. At each modeled time step within the model run, the stock counts will go up, down, or stay the same based on the modeled flows and the influence of converters on those flows. The model includes a user-friendly interface to change model parameters, which allows park staff and others to conduct sensitivity analyses, incorporate future knowledge, and implement scenarios for various future conditions. The model structure incorporates place holders for relationships that we hypothesize are significant but data are currently lacking. Future climate scenarios project stream temperatures higher than any that have ever been recorded at Olema Creek. Exploring climate change impacts on coho survival is a high priority for park staff, therefore the model provides the user with the option to experiment with hypothesized effects and to incorporate effects based on future observations.

California↗
USGS2017

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why ); (2) the Process by which the public was involved in model building or evaluation (the how ); (3) the Partnerships formed (the who ); and (4) the Products that resulted from these efforts (the what ). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Ecological Applications↗
USGS2000

Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry

Current methods of monitoring beach morphology changes commonly involve the establishment of Global Positioning System profiles that are surveyed on a regular basis. Although this method produces precise measurements of coastal topography, it is costly in time and effort and may result in large data gaps between profiles. Much of our understanding of coastal dynamics is thus limited by profile spacing and survey frequency. Softcopy photogrammetry is increasingly being used as an alternative to assess shoreline change and study beach morphodynamics. This method of producing three-dimensional topographic models and orthophotographs from digitized aerial photography can aid in filling in the gaps between established profiles. A limiting factor to this technology is the cost of obtaining high-resolution aerial photography. We have developed an aerial mapping system designed to collect data in an efficient and cost-effective way. We use a small-format aerial photography system that can be mounted on a variety of small aircraft on short notice. After a flight, the photographs are scanned, and softcopy photogrammetry software is used to create both DTMs (Digital Terrain Models) and orthophotographs. The DTMs can be compared with existing profiles for accuracy, and volumetric changes can be computed. The orthophotos are used to make precise measurements of the position and morphology of shoreline features. This aerial mapping system is advantageous over previous methods of beach morphology change monitoring because it allows for rapid response to storm events and provides a cost-effective method of establishing a continual monitoring program in erosion hazard areas.

Environmental Geosciences↗
USGS2026

3D semantic mapping of surface geological features

Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.

Computers & Geosciences↗
USGS2022

Areas contributing recharge to priority wells in valley-fill aquifers in the Neversink River and Rondout Creek drainage basins, New York

In southeastern New York, the villages of Ellenville, Wurtsboro, Woodridge, the hamlet of Mountain Dale, and surrounding communities in the Neversink River and Rondout Creek drainage basins rely on wells that pump groundwater from valley-fill glacial aquifers for public water supply. Glacial aquifers are vulnerable to contamination because they are highly permeable and have a shallow depth to water table. To protect the quality of these water resources, water managers need accurate information about the areas that contribute recharge to production wells that pump from these aquifers. The New York State Department of Environmental Conservation and the New York State Department of Health designated eight priority wells in this region for which water supply protection is of primary concern. The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation and the New York State Department of Health, began an investigation in 2019 with the general objectives of (1) improving understanding of regional groundwater-flow system, (2) delineating areas contributing recharge to eight priority production wells, and (3) quantifying the uncertainty of these contributing areas in a probabilistic way that can be used to inform decision-making related to priority well source-water protection. To complete these objectives, a MODFLOW 6 groundwater model was created encompassing the eight priority wells and the surrounding flow system, which includes parts of the Neversink River and Rondout Creek Basins in Sullivan County and Ulster County, New York. The model was built using Python tools (such as flopy , modflow-setup , and sfrmaker ) that facilitate transparent and repeatable model development using existing datasets. The model parameters were estimated with a stepwise approach using an iterative ensemble smoother implementation of the Parameter ESTimation software PEST++ (version 5.0.0). We evaluated initial “best guess” parameter bounds with a prior Monte Carlo analysis. Results of the first prior Monte Carlo analysis were used to make informed adjustments to model parameter bounds (typically resulting in expanded bounds), and a second prior Monte Carlo analysis was run to identify improved ranges for model parameters during history matching. The history matching effort produced an ensemble of parameter values for the groundwater-flow model that spans the range of values within prior uncertainty bounds. The ensemble is informed by the historical observation data, within a reasonable range of uncertainty on those observations. This history-matched ensemble was used in a particle tracking Monte Carlo analysis to delineate the areas contributing recharge to priority wells. The groundwater-flow and particle tracking (MODPATH7) models were run once for each ensemble member. Deterministic contributing areas computed for each ensemble member were aggregated to produce maps showing the probability that a location contributes recharge to priority wells. Finally, the particle tracking Monte Carlo analysis was repeated for six pumping scenarios, representing a wide range of possible pumping levels, to incorporate uncertainty in future pumping rates related to population growth or other management decisions. Increasing pumping rates generally led to larger contributing recharge areas and larger areas of high probability that a location contributes recharge to priority wells. These maps show the overall uncertainty of the areas contributing recharge to priority wells in the study area and provide a tool for risk-based decision making for protection of well source water.

New York↗
USGS2018

Revised groundwater-flow model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015

The city of Aberdeen, in northeastern South Dakota, requires an expanded and sustainable supply of water to meet current and future demands. Conceptual and numerical models of the glacial aquifer system in the area north of Aberdeen were developed by the U.S. Geological Survey in cooperation with the City of Aberdeen in 2012. The U.S. Geological Survey, in cooperation with the City of Aberdeen, completed a study to revise the original numerical groundwater-flow model using data through water year (WY) 2015 to aid the City of Aberdeen in their development of plans and strategies for a sustainable water supply and to increase understanding of the glacial aquifer system and groundwater-flow system near Aberdeen. The original model was revised to improve the fit between model-simulated values and observed (measured or estimated) data, provide greater insight into surface-water interactions, and improve the usefulness of the model for water-supply planning. The revised groundwater-flow model (hereafter referred to as the “revised model”) presented in this report supersedes the original model. The purpose of this report is to describe a revised groundwater-flow model including data collection, model calibration, and model results for the glacial aquifer system including the Elm, Middle James, and Deep James aquifers north of Aberdeen, South Dakota, using updated hydrologic data through WY 2015. The original numerical model was revised in several ways. The model was modified by adding four new layers, which included a surficial layer, two intervening confining layers, and a shale bedrock layer. The revised model provides an improved understanding of the groundwater-flow system in comparison to the original model. The principal aquifers of the model area include portions of the Elm, Middle James, and Deep James aquifers. The lithologic information used to define and describe the aquifers in the model area was unaltered; however, aquifer properties and boundary conditions were reviewed and updated using geological information reported by the South Dakota Department of Environmental and Natural Resources and information obtained from geophysical investigations for this study. The horizontal extent of the Elm, Middle James, and Deep James aquifers was unaltered from the original model. The thickness of the Deep James aquifer was modified based on interpretations from the geophysical investigations. In general, groundwater in the Elm aquifer flowed from northwest to southeast and locally towards rivers and streams. Similarly, in the Middle James and Deep James aquifers, groundwater also typically flowed southeast. The revisions made to the original model include use of the following MODFLOW stress packages: Recharge, Evapotranspiration, Time-Variant Specified Head, Wells, Drains, and Stream Flow Routing, all of which were updated from the original model except for the Stream Flow Routing Package, which replaced the River Package used in the original model. Model calibration is the process of estimating model parameters to minimize the differences, or residuals, between observed data and simulated values; therefore, Parameter ESTimation (PEST) software was used to optimize model input parameters by matching model-simulated values to observed data. Calibration parameters included horizontal hydraulic conductivity, vertical hydraulic conductivity, specific yield, specific storage, and vertical streambed conductance for stream and drain cells. Multipliers were used to calibrate the recharge and evapotranspiration stresses. Evapotranspiration extinction depth also was adjusted during model calibration. Comparisons to the original model are described to highlight the changes made in the revised model. In general, the revised model adequately simulates the natural system and compares favorably with observed hydrologic data. Simulated water levels were evaluated by comparing them to single water-level observations at selected well locations. The selected wells were the same wells used in the original model. The coefficient of determination value between simulated and observed water levels for the revised model was 0.89 and included simulated and observed values from October 1, 1974 (WY 1975), through September 30, 2015 (WY 2015). The coefficient of determination value for the original model was 0.94 and included simulated and observed values from October 1, 1974, through September 30, 2009. The difference may indicate that the original model could have been overfit to hydraulic head observations because base flow was not simulated. The additional data used in the revised model included some climatically wetter, more extreme periods, such as 2011, in which annual precipitation was 30.9 inches. Average annual precipitation for the original model timeframe, which included data from WYs 1975–2009, was 20.26 inches. Additional precipitation data for WYs 2010–15, included in the revised model timeframe, resulted in an average annual precipitation for WYs 1975–2015 in the model area of 20.6 inches. The larger variability in climate data coupled with the additional water-level data could explain the lower coefficient of determination for water levels in the revised model. The revised model was used to calculate various groundwater-budget components for steady-state and transient conditions for WYs 1975–2015. The time-variant specified-head cells in the revised model had the largest change when compared to the original steady-state model for inflows and outflows. Comparing the transient budget components between the original and the revised models indicated that inflow from recharge and time-variant specified-head cells had the greatest effect on groundwater inflows, and outflow from storage had the greatest effect on groundwater outflows. The simulated potentiometric contours from the revised model were compared with (1) the observed (interpreted) potentiometric surface (layer 2) and the hydraulic head values (layers 4 and 6) and (2) the simulated contours from the original model. The simulated hydraulic gradients and general direction of groundwater flow in the Elm aquifer in the revised model generally matched the observed potentiometric contours, the simulated potentiometric contours from the original model, and general flow directions interpreted to be perpendicular to the contours. Minor discrepancies between simulated potentiometric contours from the revised model and the observed potentiometric contours may be due to the lack of observed data in the model area. The revised model was designed to reduce the limitations of the original model. The revisions were validated by comparing the results of the original model with the revised model. A primary benefit of the revised model is the inclusion of the surficial deposits and the confining units as explicit layers in the model. The addition of the surficial layer was beneficial for three primary reasons: (1) more accurate representation of recharge from precipitation, (2) more accurate representation of groundwater evapotranspiration, and (3) more accurate representation of groundwater and surface-water interactions. The groundwater model is a numeric approximation of a complex physical hydrologic system, and the revised model data were interpolated in regions with sparse data. Additionally, model discretization included averaged and interpolated values for water use, withdrawal rates, and hydraulic conductivity. The revised model provides a useful estimate for hydraulic gradients, groundwater-flow directions, and aquifer response to groundwater withdrawals.

South Dakota↗
USGS2018

Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0

The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site. Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site. The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts. The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.

Massachusetts↗
USGS2022

A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56 ∘ N, 30–100 ∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Earth System Science Data↗