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USGS2003

Graphic comparison of reserve-growth models for conventional oil and accumulation

The U.S. Geological Survey (USGS) periodically assesses crude oil, natural gas, and natural gas liquids resources of the world. The assessment procedure requires estimated recover-able oil and natural gas volumes (field size, cumulative production plus remaining reserves) in discovered fields. Because initial reserves are typically conservative, subsequent estimates increase through time as these fields are developed and produced. The USGS assessment of petroleum resources makes estimates, or forecasts, of the potential additions to reserves in discovered oil and gas fields resulting from field development, and it also estimates the potential fully developed sizes of undiscovered fields. The term ?reserve growth? refers to the commonly observed upward adjustment of reserve estimates. Because such additions are related to increases in the total size of a field, the USGS uses field sizes to model reserve growth. Future reserve growth in existing fields is a major component of remaining U.S. oil and natural gas resources and has therefore become a necessary element of U.S. petroleum resource assessments. Past and currently proposed reserve-growth models compared herein aid in the selection of a suitable set of forecast functions to provide an estimate of potential additions to reserves from reserve growth in the ongoing National Oil and Gas Assessment Project (NOGA). Reserve growth is modeled by construction of a curve that represents annual fractional changes of recoverable oil and natural gas volumes (for fields and reservoirs), which provides growth factors. Growth factors are used to calculate forecast functions, which are sets of field- or reservoir-size multipliers. Comparisons of forecast functions were made based on datasets used to construct the models, field type, modeling method, and length of forecast span. Comparisons were also made between forecast functions based on field-level and reservoir- level growth, and between forecast functions based on older and newer data. The reserve-growth model used in the 1995 USGS National Assessment and the model currently used in the NOGA project provide forecast functions that yield similar estimates of potential additions to reserves. Both models are based on the Oil and Gas Integrated Field File from the Energy Information Administration (EIA), but different vintages of data (from 1977 through 1991 and 1977 through 1996, respectively). The model based on newer data can be used in place of the previous model, providing similar estimates of potential additions to reserves. Fore-cast functions for oil fields vary little from those for gas fields in these models; therefore, a single function may be used for both oil and gas fields, like that used in the USGS World Petroleum Assessment 2000. Forecast functions based on the field-level reserve growth model derived from the NRG Associates databases (from 1982 through 1998) differ from those derived from EIA databases (from 1977 through 1996). However, the difference may not be enough to preclude the use of the forecast functions derived from NRG data in place of the forecast functions derived from EIA data. Should the model derived from NRG data be used, separate forecast functions for oil fields and gas fields must be employed. The forecast function for oil fields from the model derived from NRG data varies significantly from that for gas fields, and a single function for both oil and gas fields may not be appropriate.

Bulletin↗

USGS2017

Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014

Fish habitat can degrade in many lakes due to summer blue-green algal blooms. Predictive models are needed to better manage and mitigate loss of fish habitat due to these changes. The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources, developed predictive water-quality models for two agricultural land-use dominated lakes in Minnesota—Madison Lake and Pearl Lake, which are part of Minnesota’s sentinel lakes monitoring program—to assess algal community dynamics, water quality, and fish habitat suitability of these two lakes under recent (2014) meteorological conditions. The interaction of basin processes to these two lakes, through the delivery of nutrient loads, were simulated using CE-QUAL-W2, a carbon-based, laterally averaged, two-dimensional water-quality model that predicts distribution of temperature and oxygen from interactions between nutrient cycling, primary production, and trophic dynamics. The CE-QUAL-W2 models successfully predicted water temperature and dissolved oxygen on the basis of the two metrics of mean absolute error and root mean square error. For Madison Lake, the mean absolute error and root mean square error were 0.53 and 0.68 degree Celsius, respectively, for the vertical temperature profile comparisons; for Pearl Lake, the mean absolute error and root mean square error were 0.71 and 0.95 degree Celsius, respectively, for the vertical temperature profile comparisons. Temperature and dissolved oxygen were key metrics for calibration targets. These calibrated lake models also simulated algal community dynamics and water quality. The model simulations presented potential explanations for persistently large total phosphorus concentrations in Madison Lake, key differences in nutrient concentrations between these lakes, and summer blue-green algal bloom persistence. Fish habitat suitability simulations for cool-water and warm-water fish indicated that, in general, both lakes contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer, without any periods of lethal oxythermal habitat. For Madison and Pearl Lakes, examples of important cool-water fish, particularly game fish, include northern pike ( Esox lucius ), walleye ( Sander vitreus ), and black crappie ( Pomoxis nigromaculatus ); examples of important warm-water fish include bluegill ( Lepomis macrochirus ), largemouth bass ( Micropterus salmoides ), and smallmouth bass ( Micropterus dolomieu ). Sensitivity analyses were completed to understand lake response effects through the use of controlled departures on certain calibrated model parameters and input nutrient loads. These sensitivity analyses also operated as land-use change scenarios because alterations in agricultural practices, for example, could potentially increase or decrease nutrient loads.

Minnesota↗

USGS2022

Physiological and nutritional constraints on zooplankton productivity due to eutrophication and climate change predicted using a resource-based modeling approach

Emerging evidence suggests that zooplankton production is affected by physiological and nutritional constraints due to climate change and eutrophication, which in turn could have broad implications for food-web dynamics and fisheries production. In this study, we developed a resource-based zooplankton production dynamics model that causally links freshwater cladoceran and copepod daily production-to-biomass (P/B) ratios with water temperature, phytoplankton biomass and community composition, and zooplankton feeding selectivity. This model was used to evaluate constraints on zooplankton growth under four hypothetical scenarios: involving natural plankton community seasonal succession; lake fertilization to enhance fisheries production; eutrophication; and climatic warming. Our novel modeling approach predicts zooplankton production is strongly dependent on seasonal variation in resource availability and quality, which results in more complex zooplankton dynamics than predicted by simpler temperature dependent models. For mesotrophic and hypereutrophic lakes, our study suggests that the ultimate control over zooplankton P/B ratios shifts from physiological control during colder periods to strong resource control during warmer periods. Our resource-based model provided important insights into the nature of biophysical control of zooplankton under a changing climate that has crucial implications for food web energy transfer and fisheries production.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS1998

A policy model to initiate environmental negotiations: Three hydropower workshops

How do I get started in natural resource negotiations? Natural resource managers often face difficult negotiations when they implement laws and policies regulating such resources as water, wildlife, wetlands, endangered species, and recreation. As a result of these negotiations, managers must establish rules, grant permits, or create management plans. The Legal‐Institutional Analysis Model (LIAM) was designed to assist managers in systematically analyzing the parties in natural resource negotiations and using that analysis to prepare for bargaining. The LIAM relies on the theory that organizations consistently employ behavioral roles. The model uses those roles to predict likely negotiation behavior. One practical use of the LIAM is when all parties to a negotiation conduct a workshop as a way to open the bargaining on a note of trust and mutual understanding. The process and results of three LIAM workshops designed to guide hydroelectric power licensing negotiations are presented. Our experience with these workshops led us to conclude that the LIAM can be an effective tool to begin a negotiation and that trust built through the workshops can help create a successful result.

Human Dimensions of Wildlife: An International Jou↗

USGS2009

A national look at carbon capture and storage-National carbon sequestration database and geographical information system (NatCarb)

The US Department of Energy's Regional Carbon Sequestration Partnerships (RCSPs) are responsible for generating geospatial data for the maps displayed in the Carbon Sequestration Atlas of the United States and Canada. Key geospatial data (carbon sources, potential storage sites, transportation, land use, etc.) are required for the Atlas, and for efficient implementation of carbon sequestration on a national and regional scale. The National Carbon Sequestration Database and Geographical Information System (NatCarb) is a relational database and geographic information system (GIS) that integrates carbon storage data generated and maintained by the RCSPs and various other sources. The purpose of NatCarb is to provide a national view of the carbon capture and storage potential in the U.S. and Canada. The digital spatial database allows users to estimate the amount of CO 2 emitted by sources (such as power plants, refineries and other fossil-fuel-consuming industries) in relation to geologic formations that can provide safe, secure storage sites over long periods of time. The NatCarb project is working to provide all stakeholders with improved online tools for the display and analysis of CO 2 carbon capture and storage data. NatCarb is organizing and enhancing the critical information about CO 2 sources and developing the technology needed to access, query, model, analyze, display, and distribute natural resource data related to carbon management. Data are generated, maintained and enhanced locally at the RCSP level, or at specialized data warehouses, and assembled, accessed, and analyzed in real-time through a single geoportal. NatCarb is a functional demonstration of distributed data-management systems that cross the boundaries between institutions and geographic areas. It forms the first step toward a functioning National Carbon Cyberinfrastructure (NCCI). NatCarb provides access to first-order information to evaluate the costs, economic potential and societal issues of CO 2 capture and storage, including public perception and regulatory aspects. NatCarb online access has been modified to address the broad needs of a spectrum of users. NatCarb includes not only GIS and database query tools for high-end user, but simplified display for the general public using readily available web tools such as Google Earth???and Google Maps???. Not only is NatCarb connected to all the RCSPs, but data are also pulled from public servers including the U.S. Geological Survey-EROS Data Center and from the Geography Network. Data for major CO 2 sources have been obtained from U.S. Environmental Protection Agency (EPA) databases, and data on major coal basins and coalbed methane wells were obtained from the Energy Information Administration (EIA). ?? 2009 Elsevier Ltd. All rights reserved.

Conference Paper↗

USGS2008

Characterization of Suspended-Sediment Loading to and from John Redmond Reservoir, East-Central Kansas, 2007-2008

Storage capacity in John Redmond Reservoir is being lost to sedimentation more rapidly than in other federal impoundments in Kansas. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, initiated a study to characterize suspended-sediment loading to and from John Redmond Reservoir from February 21, 2007, through February 21, 2008. Turbidity sensors were installed at two U.S. Geological Survey stream gages upstream (Neosho River near Americus and the Cottonwood River near Plymouth) and one stream gage downstream (Neosho River at Burlington) from the reservoir to compute continuous, real-time (15-minute) measurements of suspended-sediment concentration and loading. About 1,120,000 tons of suspended-sediment were transported to, and 100,700 tons were transported from John Redmond Reservoir during the study period. Dependent on the bulk density of sediment stored in the reservoir, 5.0 to 1.4 percent of the storage in the John Redmond conservation pool was lost during the study period, with an average deposition of 3.4 to 1.0 inches. Nearly all (98-99 percent) of the incoming sediment load was transported during 9 storms which occurred 25 to 27 percent of the time. The largest storm during the study period (peak-flow recurrence interval of about 4.6-4.9 years) transported about 37 percent of the sediment load to the reservoir. Suspended-sediment yield from the unregulated drainage area upstream from the Neosho River near Americus was 530 tons per square mile, compared to 400 tons per square mile upstream from the Cottonwood River near Plymouth. Comparison of historical (1964-78) to current (2007) sediment loading estimates indicate statistically insignificant (<90 percent confidence) differences at the Neosho River near Americus and the Cottonwood River near Plymouth, but a significant (>99 percent) decrease in sediment loading at the Neosho River at Burlington. Ninety-percent confidence intervals of streamflow-derived estimates of total sediment load were 7 to 21 times larger than turbidity-derived estimates. Results from this study can be used by natural resource managers to calibrate sediment models and estimate the ability of John Redmond Reservoir to support designated uses into the future.

Scientific Investigations Report↗

USGS2022

Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat

Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.

Frontiers in Remote Sensing↗

USGS1998

Thunder on the Yellowstone revisited: An assessment of management of native ungulates by natural regulation, 1968-1993

Natural regulation of native ungulates was initiated in 1968 in Yellowstone National Park (YNP) based on the premise that ungulates would reach an equilibrium with their plant resources. The natural-regulation management model stated: density dependence will regulate ungulates (i.e., a dynamic equilibrium will result between ungulates and their food supply, within some bounds of vegetation and soil effects); and no retrogression of soil and vegetation will occur from elk (Cervus elaphus) grazing during this process. The historical record indicated that elk were abundant in the system and elk were primarily food limited before settlement by European man (i.e., wolves [Canis lupus] and Native Americans were only an adjunct to the density dependent population regulation of ungulates). Density dependence was demonstrated in elk, but not in bison (Bison bison). No widespread evidence of overgrazing was observed through 1993 in study sites within vegetation communities that comprised about 97% of the winter range. No evidence of increased exotics, increased sediment yield, warming or drying of the soil, changes in soil nutrients, or differences in aboveground standing-crop biomass of plants was found between grazed and ungrazed plots. Ungulate herbivory apparently stimulated aboveground production of grasses, enhanced nitrogen and macronutrients in grasses, increased nutrient cycling, and enhanced measures of fitness in 6 common plants. However, exposed soil surface (bare ground and pebbles combined) was 11-18% greater on grazed than ungrazed plots, apparently due to a 71% decline in dead and standing litter on grazed plots. Percent live-plant basal cover, however, did not differ on grazed versus ungrazed plots, and there was no difference in soil microclimate or sediment yield. Differences in the abundance of 12% of the herbaceous species were found in grazed versus ungrazed sites (16 of 128 species); 10 were declines and 6 were increases. Willow (Salix spp.) and aspen (Populus tremuloides) declines predated the new management policy, but their slow declines also continued after 1968. Three uncommon plant species (aspen, willow, and Wyoming big sagebrush [Artemisia tridentata tridentata]) and 1 herbivore (moose [Alces alces]) declined under natural-regulation management. Two uncommon species of woody browse (aspen, Wyoming big sagebrush) were overutilized by ungulates (consumption of >2/3 current annual growth occurred). We conclude the natural-regulation model for YNP was flawed in its assumptions of a single, steady state for the park, based on conditions presumed to exist in 1870 prior to establishment of the national park. The period selected as a standard (1870) was an unusual period characterized by frequent large fires and floods, common wolves, few elk, and a cooler, wetter climate. We also conclude there is a high level of uncertainty surrounding what elk densities were in pre-Columbian times (element 3 of the management model) and what effects wolves and Native Americans had in regulating the elk population.

Wildlife Society Bulletin↗

USGS2008

Base of principal aquifer for the Elkhorn-Loup model area, North-Central Nebraska

In Nebraska, the water managers in the Natural Resources Districts and the Nebraska Department of Natural Resources are concerned with the effect of ground-water withdrawal on the availability of surface water and the long-term effects of ground-water withdrawal on ground- and surface-water resources. In north-central Nebraska, in the Elkhorn and Loup River Basins, ground water is used for irrigation, domestic supply, and public supply; surface water is used in this area for irrigation, recreation, and hydropower production. In recognition of these sometimes competing ground- and surface-water uses in the Elkhorn and Loup River Basins, the U.S. Geological Survey, the Lewis and Clark Natural Resources District, the Lower Elkhorn Natural Resources District, the Lower Loup Natural Resources District, the Lower Niobrara Natural Resources District, the Lower Platte North Natural Resources District, the Middle Niobrara Natural Resources District, the Upper Elkhorn Natural Resources District, and the Upper Loup Natural Resources District agreed to cooperatively study water resources in the Elkhorn and Loup River Basins. The goals of the overall study were to construct and calibrate a regional ground-water flow model of the area and to use that flow model as a tool to assess current and future effects of ground-water irrigation on stream base flow and to help develop long-term water-resource management strategies for this area, hereafter referred to as the Elkhorn-Loup model area. The Elkhorn-Loup model area covers approximately 30,800 square miles, and extends from the Niobrara River in the north to the Platte River in the south. The western boundary of the Elkhorn-Loup model area coincides with the western boundary of the Middle Niobrara, Twin Platte, and Upper Loup Natural Resources Districts; the eastern boundary coincides with the approximate location of the western extent of glacial till in eastern Nebraska. The principal aquifer in most of the Elkhorn-Loup model area is the High Plains aquifer; the principal aquifer in the remaining part of the Elkhorn-Loup model area is an unnamed alluvial aquifer. The upper surface of the geologic units that directly underlie the aquifer is called the 'base of aquifer' in this report. The geologic unit that forms the base of aquifer in the Elkhorn-Loup model area varies by location. The Tertiary-age Brule Formation generally is the base of aquifer in the west; the Cretaceous-age Pierre Shale generally is the base of aquifer in the east. The purpose of this report is to update the altitude and configuration of the base of the principal aquifer in the Elkhorn-Loup model area and a 2-mile buffer area around the Elkhorn-Loup model area, using base-of-aquifer data from test holes, registered water wells, and oil and gas wells within the Elkhorn-Loup model area and a 20-mile buffer area around the Elkhorn-Loup model area that have become available since the publication of earlier maps of the base of aquifer for this area. The base-of-aquifer map is important for the Elkhorn-Loup ground-water flow model because it defines the model's lower boundary. The accuracy of the Elkhorn-Loup ground-water flow model and the accuracy of the model's predictions about the effects of ground-water irrigation on stream base flow are directly related to the accuracy of the model's lower boundary.

Scientific Investigations Map↗

USGS2015

Water-budgets and recharge-area simulations for the Spring Creek and Nittany Creek Basins and parts of the Spruce Creek Basin, Centre and Huntingdon Counties, Pennsylvania, Water Years 2000–06

This report describes the results of a study by the U.S. Geological Survey in cooperation with ClearWater Conservancy and the Pennsylvania Department of Environmental Protection to develop a hydrologic model to simulate a water budget and identify areas of greater than average recharge for the Spring Creek Basin in central Pennsylvania. The model was developed to help policy makers, natural resource managers, and the public better understand and manage the water resources in the region. The Groundwater and Surface-water FLOW model (GSFLOW), which is an integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Groundwater Flow Model (MODFLOW-NWT), was used to simulate surface water and groundwater in the Spring Creek Basin for water years 2000–06. Because the groundwater and surface-water divides for the Spring Creek Basin do not coincide, the study area includes the Nittany Creek Basin and headwaters of the Spruce Creek Basin. The hydrologic model was developed by the use of a stepwise process: (1) develop and calibrate a PRMS model and steady-state MODFLOW-NWT model; (2) re-calibrate the steady-state MODFLOW-NWT model using potential recharge estimates simulated from the PRMS model, and (3) integrate the PRMS and MODFLOW-NWT models into GSFLOW. The individually calibrated PRMS and MODFLOW-NWT models were used as a starting point for the calibration of the fully coupled GSFLOW model. The GSFLOW model calibration was done by comparing observations and corresponding simulated values of streamflow from 11 streamgages and groundwater levels from 16 wells. The cumulative water budget and individual water budgets for water years 2000–06 were simulated by using GSFLOW. The largest source and sink terms are represented by precipitation and evapotranspiration, respectively. For the period simulated, a net surplus in the water budget was computed where inflows exceeded outflows by about 1.7 billion cubic feet (0.47 inches per year over the basin area); storage increased by about the same amount to balance the budget. The rate and distribution of recharge throughout the Spring Creek, Nittany Creek, and Spruce Creek Basins is variable as a result of the high degree of hydrogeologic heterogeneity and karst features. The greatest amount of recharge was simulated in the carbonate-bedrock valley, near the toe slopes of Nittany and Tussey Mountains, in the Scotia Barrens, and along the area coinciding with the Gatesburg Formation. Runoff extremes were observed for water years 2001 (dry year) and 2004 (wet year). Simulated average recharge rates (water reaching the saturated zone as defined in GSFLOW) for 2001 and 2004 were 5.4 in/yr and 22.0 in/yr, respectively. Areas where simulations show large variations in annual recharge between wet and dry years are the same areas where simulated recharge was large. Those areas where rates of groundwater recharge are much higher than average, and are capable of accepting substantially greater quantities of recharge during wet years, might be considered critical for maintaining the flow of springs, stream base flow, or the source of water to supply wells. The slopes of the Bald Eagle, Tussey, and Nittany Mountains are relatively insensitive to variations in recharge, primarily because of reduced infiltration rates and steep slopes.

Pennsylvania↗

USGS2012

Simulation of daily streamflows at gaged and ungaged locations within the Cedar River Basin, Iowa, using a Precipitation-Runoff Modeling System model

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota. The Precipitation-Runoff Modeling System model accurately simulated streamflow at four of six uncalibrated sites within the basin. Overall, there was good agreement between simulated and measured seasonal and annual volumes throughout the basin for calibration and validation sites. The calibration period ranged from 0.2 to 20.8 percent difference, and the validation period ranged from 0.0 to 19.5 percent difference across all seasons and total annual runoff. The Precipitation-Runoff Modeling System model tended to underestimate lower streamflows compared to the observed streamflow values. This is an indication that the Precipitation-Runoff Modeling model needs more detailed groundwater and storage information to properly model the low-flow conditions in the Cedar River Basin.

Iowa↗

USGS2006

Instantaneous unit hydrograph evaluation for rainfall-runoff modeling of small watersheds in North and South Central Texas

Data from over 1,600 storms at 91 stations in Texas are analyzed to evaluate an instantaneous unit hydrograph (IUH) model for rainfall-runoff models. The model is fit to observed data using two different merit functions: a sum of squared errors function, and an absolute error at the peak discharge time (QpMAX) function. The model is compared to two other models using several criteria. Analysis suggests that the Natural Resources Conservation Service Dimensionless Unit Hydrograph, Commons' Texas hydrograph, and the Rayleigh IUH perform similarly. As the NRCS and Commons' models are tabulations, the Rayleigh model is an adequate substitute when a continuous model is necessary. The adjustable shape parameter in the Rayleigh model does not make any dramatic improvement in overall performance for these data, thus fixed shape hydrographs are adequate for these watersheds. ?? 2006 ASCE.

Journal of Irrigation and Drainage Engineering↗

USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗

USGS2001

Balancing Ground-Water Withdrawals and Streamflow in the Hunt-Annaquatucket-Pettaquamscutt Basin, Rhode Island

Ground water withdrawn for water supply reduces streamflow in the Hunt-Annaquatucket-Pettaquamscutt Basin in Rhode Island. These reductions may adversely affect aquatic habitats. A hydrologic model was prepared by the U.S. Geological Survey in cooperation with the Rhode Island Water Resources Board, Town of North Kingstown, Rhode Island Department of Environmental Management, and Rhode Island Economic Development Corporation to aid water-resource planning in the basin. Results of the model provide information that helps water suppliers and natural-resource managers evaluate strategies for balancing ground-water development and streamflow reductions in the basin.

Fact Sheet↗

USGS2016

The 3D elevation program - Precision agriculture and other farm practices

A founding motto of the Natural Resources Conservation Service (NRCS), originally the Soil Conservation Service (SCS), explains that “If we take care of the land, it will take care of us.” Digital elevation models (DEMs; see fig. 1) are derived from light detection and ranging (lidar) data and can be processed to derive values such as slope angle, aspect, and topographic curvature. These three measurements are the principal parameters of the NRCS LidarEnhanced Soil Survey (LESS) model, which improves the precision of soil surveys, by more accurately displaying the slopes and soils patterns, while increasing the objectivity and science in line placement. As combined resources, DEMs, LESS model outputs, and similar derived datasets are essential for conserving soil, wetlands, and other natural resources managed and overseen by the NRCS and other Federal and State agencies.

Fact Sheet↗

USGS2005

Grass buffers for playas in agricultural landscapes: A literature synthesis

We summarize current knowledge about grass buffers for protecting small, isolated wetlands in agricultural contexts, including information relevant to protecting playas from runoff containing sediments, nutrients, pesticides, and other contaminants, and information on how buffers may affect densities and productivity of grassland birds. Land-uses surrounding the approximately 60,000 playas within the Playa Lakes Region (PLR), including intensive agriculture, feedlots, and oil extraction, can contribute to severe degradation of playas. Farming and grazing can lead to significant sedimentation in nearby playas, eliminating their ability to hold water, support the region’s biodiversity, or adequately recharge aquifers. Contaminants further degrade habitats and threaten the water quality of underlying aquifers, including the Ogallala Aquifer. Grass buffers hold promise as a management tool to reduce the amount of sediments and contaminants from agricultural runoff that enters playas. Effective buffer width is determined by acceptable sediment-reduction levels, potential water flow and velocity, landscape and soil variables, buffer species, and vegetation structure. Various models have been developed to predict buffer effectiveness; however, most of these models, including those provided by the Natural Resource Conservation Service (NRCS), remain unvalidated. The majority of buffer-effectiveness literature is based on simulated conditions in experimental trays or plots; no published studies of buffer design or effectiveness specifically address playas. Nonetheless, some general patterns have emerged regarding buffer design/effectiveness. Buffers 10–60 m wide are generally considered adequate for trapping most sediments, although in some cases buffers need to be >200 m. The U.S. Fish and Wildlife Service Partners for Wildlife Program in the Southern High Plains recommend a buffer width of ~33 m planted with a diverse mix of native shortgrasses and mixed grasses as a starting point. Most dissolved contaminants, however, are removed from runoff only when they infiltrate the soil, where microbes or other processes can break down or sequester contaminants. Promoting runoff infiltration requires wider buffers with denser stem densities than those required for filtering sediments, which may result in hydrological changes in playas. Ultimately, the balance between runoff and infiltration determines whether or not water eventually reaches a given basin. Long-term buffer effectiveness requires regular maintenance, including excavation to remove overburdens of sediments, repairing vegetation damage, and removing over-mature vegetation or invasions of noxious weeds. Buffers may not be enough to protect playas; best management practices (BMPs; e.g., conservation tillage, contour tilling, and mulching herbicides into soil after application) that diminish soil erosion and contaminant runoff also may be necessary. Nutrient loads in runoff can be minimized by balancing nutrient input with nutrient requirements for livestock and crops. Pesticide application practices also require careful evaluation. Mowing or grazing rather than use of herbicides offer alternatives for suppressing invasive or undesirable plant species in buffers. Future research should entail multiple-scale approaches at regional, wetland-complex, and individual watershed scales. Information needs include direct measures of buffer effectiveness in ‘real-world’ systems, refinement and field tests of buffer-effectiveness models, how buffers may affect floral and faunal communities of playas, and basic ecological information on playa function and playa wildlife ecology. Understanding how wildlife communities respond to patch size and habitat fragmentation is crucial for addressing questions regarding habitat quality of grass buffers in playa systems.

Open-File Report↗

USGS2010

Linking intended visitation to regional economic impact models of bison and elk management

This article links intended National Park visitation estimates to regional economic models to calculate the employment impacts of alternative bison and elk management strategies. The survey described alternative National Elk Refuge (NER) management actions and the effects on elk and bison populations at the NER and adjacent Grand Teton National Park (GTNP). Park visitors were then asked if they would change their number of visits with each potential management action. Results indicate there would be a 10% decrease in visitation if bison populations were reduced from 600 to 400 animals and elk populations were reduced in GTNP and the NER. The related decrease in jobs in Teton counties of Wyoming and Idaho is estimated at 5.5%. Adopting a “no active management” option of never feeding elk and bison on the NER yields about one-third the current bison population (200 bison) and about half the elk population. Visitors surveyed about this management option would take about 20% fewer trips, resulting in an 11.3% decrease in employment. Linking intended visitation surveys and regional economic models represents a useful tool for natural resource planners who must present the consequences of potential actions in Environmental Impact Statements and plans to the public and decision makers prior to any action being implemented.

Human Dimensions of Wildlife↗

USGS2019

Modelling development of riparian ranchlands using ecosystem services at the Aravaipa Watershed, SE Arizona

This paper describes how subdivision and development of rangelands within a remote and celebrated semiarid watershed near the US-Mexico border might affect multiple ecohydrological services provided, such as recharge of the aquifer, water and sediment yield, water quality, flow rates and downstream cultural and natural resources. Specifically, we apply an uncalibrated watershed model and land-change forecasting scenario to consider the potential effects of converting rangelands to housing developments and document potential changes in hydrological ecosystem services. A new method to incorporate weather data in watershed modelling is introduced. Results of introducing residential development in this fragile arid environment portray changes in the water budget, including increases in surface-water runoff, water yield, and total sediment loading. Our findings also predict slight reductions in lateral soil water, a component of the water budget that is increasingly becoming recognized as critical to maintaining water availability in arid regions. We discuss how the proposed development on shrub/scrub rangelands could threaten to sever imperative ecohydrological interactions and impact multiple ecosystem services. This research highlights rangeland management issues important for the protection of open-space, economic valuation of rangeland ecosystem services, conservation easements, and incentives to develop markets for these.

Arizona↗