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USGS2024

Revision of ModelMuse to support the use of PEST software with MODFLOW and SUTRA models

Executive Summary ModelMuse is a graphical user interface for several groundwater modeling programs. ModelMuse was updated to generate the input files for the parameter estimation software suite PEST. The software is used with MODFLOW or SUTRA models to run PEST-based parameter estimation and display the updated model inputs after parameter estimation. The PEST input files can also be used with the PEST++ version 5 software suite. Parameter estimation typically requires defining the parameters being adjusted during calibration and observations for assessing calibration quality. After a parameter is defined in ModelMuse, it can be applied to all or part of a model dataset. Pilot points—a parameterization device that facilitates higher levels of parameterization—can be used to assign spatially variable distributions of model inputs. Parameters can be applied to temporally varying features, such as boundary conditions, by either applying them to all the values in a series in one step or by applying separate parameters to individual members of a series. ModelMuse allows the definition of many observation types from various model output files. For MODFLOW 6 and SUTRA models, new options were added to ModelMuse to allow it to display the changed input after parameter estimation is complete. For MODFLOW–2005 and MODFLOW–NWT models, ModelMuse can import an entire model for visualization. An example illustrates the use of PEST with a MODFLOW 6 model in ModelMuse.

Techniques and Methods↗
USGS2002

Rainfall-runoff characteristics and effects of increased urban density on streamflow and infiltration in the eastern part of the San Jacinto River basin, Riverside County, California

To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.

Water-Resources Investigations Report↗
USGS1980

Calibration and potential uses of a digital water-quality model for the Arkansas River in Pueblo County, Colorado

The U.S. Geological Survey conducted a 1-year study to calibrate and demonstrate the use of a steady-state water quality model for a 42-mile reach of the Arkansas River in Pueblo County, Colo. Based on the calibration, the model is capable of accurately predicting concentrations of carbonaceous biochemical oxygen demand, total organic nitrogen, total nitrite, and total orthophosphate; predicted concentrations of total ammonia, total nitrate, and dissolved oxygen will be somewhat less accurate. Additional data are needed to determine the model's capability to predict concentrations of coliform bacteria. Potential uses of the model were demonstrated by simulating the effects of different waste water discharges on streamflow quality, using water-quality and stream-discharge data provided by the Pueblo Area Council of Governments. Selected results for carbonaceous biochemical oxygen demand and total ammonia from three simulations illustrate the capability of the model. (USGS)

Colorado↗
USGS1980

Evaluation of peak-flow data network of small streams in Missouri

Standard regression models were used as a tool to evaluate the transferability of streamflow characteristics for the small-streams network in Missouri. Station records were divided into segments and tested for adequacy of record length and sample size for two physiographic regions. The standard error of estimate for each calibrated regression model, using increasing record lengths, was compared against the longest period of record in both tests. Results of the study indicate that an increase in the length of small-area streamflow records or additional sampling sites in the data network will not substantially improve the standard error of estimate of the regression model. Therefore, it is recommended that the current (1980) crest-stage network be reduced to a sample large enough to measure the long-term trend and provide information for future capabilities in the field of small-streams hydrology. It is also recommended that additional research be carried out to determine additional variables which could be used to predict floodflows and other types of regression models. (USGS)

Missouri↗
USGS1993

Development, calibration, and testing of ground-water flow models for the Mississippi River Valley alluvial aquifer in eastern Arkansas using one-square-mile cells

Significant water-level declines in the Mississippi River Valley alluvial aquifer prompted the need to better understand the flow system in the aquifer which, in turn, led to the development of digital groundwater flow models of the alluvial aquifer. Two models were developed in the eastern Arkansas study area with the Arkansas River dividing the study area and functioning as a hydrologic boundary to the models. Both models simulate groundwater flow in one layer with recharge entering the aquifer from head-dependent surface infiltration through the overlying confining unit and from seepage through river beds. Digital models were used to simulate flow in the aquifer during seven stress periods between 1918 and 1987. Pumpage used in the simulations ranged from 83,400,000 to 412,000,000 cu ft/d in the north model and from 12,800,000 to 58,500,000 cu ft/d in the south model. Three different spatial and temporal pumpage scenarios were tested to simulate pumpage stress in the models. The pumpage distribution used in the calibrated model was based on a combination of all three scenarios. Several criteria were used during model development to determine how well the model simulated conditions in the aquifer. Potentiometric maps of model-computed water levels were compared to measured data to check the computed water levels and direction of flow. Hydrographs of observation wells were compared to computed water levels at corresponding model cells to assess the temporal distribution of pumpage. A root-mean-square error analysis was performed during calibration by comparing observation-well and model-computed water levels for 1972. Sensitivity analyses were performed to determine the effects of changes in input parameters on computed heads (water levels). Both models were sensitive to changes in recharge and pumpage but the south model generally was less sensitive than the north model.

Water-Resources Investigations Report↗
USGS1993

Geohydrology and simulation of flow and water levels in the aquifer system in the Mud Lake area of the eastern Snake River plain, eastern Idaho

Water users rely on surface water and ground water to irrigate crops and to maintain lakes on wildlife refuges in the 2,200-square-mile Mud Lake study area. Ground-water development between the late 1970's and 1989 increased withdrawals from about 240,000 acre-feet in 1983 to about 370,000 acre-feet in 1990. Concurrent with ground-water development, change from subirrigation to sprinkler irrigation was predicted to reduce recharge by 95,000 acre-feet, according to an independent study. Of the 660,000 acre-feet total estimated recharge from precipitation and irrigation in the study area in 1980, half was in the area in which irrigation methods were changed. Water managers need the ability to evaluate the effects of water-use changes on the future supply of surface water and ground water. Basalt and rhyolite predominate on the surface and in the subsurface of the study area. Total basalt thickness is less than 4,000 feet; total sediment thickness (clay, silt, sand, and gravel) is less than 1,000 feet. Basalt and sediment interbeds contribute to confined ground-water conditions and affect movement and supply of water in parts of the aquifer system. Estimated losses from and gains to perennial streams and lakes in 1980 were each about 110,000 acre-feet. Water-table altitudes ranged from about 4,500 to 6,200 feet above sea level, and water-table gradients were 3 to 120 feet per mile. Underflow from basins tributary to the study area was estimated to be about 450,000 acre-feet in 1980; measured discharge from flowing wells was about 10,000 acre-feet. A five-layer, three-dimensional, finite-difference, numerical ground-water flow model was calibrated by trial-and-error to assumed 1980 steady-state hydrologic conditions to obtain a better understanding of the geohydrology and provide a tool to evaluate water-use alternatives. Water-level gradients simulated by the model were similar to gradients measured in 1980. Simulated underflow across model boundaries for 1980 was 932,000 acre-feet. Simulated losses from and gains to most streams and lakes were within 2 percent of estimated values. Simulated discharge from flowing wells matched measurements for 1980. An attempt to calibrate the numerical model to transient hydrologic conditions in monthly increments from 1981 to 1990 was discontinued because available data did not justify changes that were indicated by model simulations.

Idaho↗
USGS2021

Red knot stopover population size and migration ecology at Delaware Bay, USA, 2021

Red Knots ( Calidris canutus rufa ) stop at Delaware Bay during northward migration to feed on eggs of horseshoe crabs ( Limulus polyphemus ). The northward migration of C. c. rufa coincides with the spawning of horseshoe crabs whose eggs are the perfect food for a migrating Red Knot (Karpanty et al. 2006, Haramis et al. 2007). Horseshoe crabs are therefore an important food resource for Red Knots as well as other shorebirds at Delaware Bay. Horseshoe crabs have been harvested since at least 1990 for use as bait in American eel ( Anguilla rostrata ) and whelk ( Busycon ) fisheries (Kreamer and Michels 2009). In the late 1990s and early 2000s the number of Red Knots found at Delaware Bay declined dramatically from ~50,000 to ~13,000 (Niles et al. 2008). At the same time the number of horseshoe crabs harvested also declined and avian conservation biologists hypothesized that unregulated harvest of horseshoe crabs from Delaware Bay in the 1990s prevented sufficient refueling during stopover for successful migration to the breeding grounds, nesting, and survival for the remainder of the annual cycle (McGowan et al. 2011). The harvest of horseshoe crabs in the Delaware Bay region has been managed by the Atlantic States Marine Fisheries Commission (ASMFC) since 2012 using an Adaptive Resource Management (ARM) framework (McGowan et al. 2015b). The ARM framework was designed to constrain the harvest so that number of spawning crabs would not limit the number of Red Knots stopping at Delaware Bay during migration. This management framework to achieve multiple objectives requires an estimate each year of both the crab population and the Red Knot stopover population size to inform harvest recommendations (McGowan et al. 2015a). We have estimated the stopover population size using mark-resight data on individually-marked birds and a Jolly-Seber model for open populations since 2011.

Delaware, New Jersey↗
USGS2016

Simulated effects of groundwater withdrawals from aquifers in Ocean County and vicinity, New Jersey

Rapid population growth since the 1930s in Ocean County and vicinity, New Jersey, has placed increasing demands upon the area’s freshwater resources. To examine effects of groundwater withdrawals, a three-dimensional groundwater-flow model was developed to simulate the groundwater-flow systems of five area aquifers: the unconfined Kirkwood-Cohansey aquifer system and Vincentown aquifer, and three confined aquifers— the Rio Grande water-bearing zone, the Atlantic City 800-foot sand, and the Piney Point aquifer. The influence of withdrawals is evaluated by using transient groundwater-flow model simulations that incorporate three withdrawal schemes. These are (1) no-withdrawal conditions; (2) 2000–03 withdrawal conditions, using reported monthly withdrawals at all production wells from January 2000 through December 2003; and (3) maximum-allocation withdrawal conditions using the maximum withdrawal allowed by New Jersey Department of Environmental Protection permits at each well. Particle tracking analysis, using results from model simulations, delineated particle flow paths from production wells to the point of recharge, and estimated particle travel times. Compared with no-withdrawal conditions, 2000–03 withdrawal conditions reduced the amount of groundwater flow out of the Kirkwood-Cohansey aquifer system into streams, increased the net flow of water into other layers, reduced net flow into or out of storage, and reduced flow from the Kirkwood-Cohansey aquifer system to constant head cells. Freshwater discharging to the Barnegat Bay-Little Egg Harbor estuary from streams and groundwater is essential to maintaining the ecology of the bay. Examination of selected stress periods indicates that simulated base flow in streams flowing into the Barnegat Bay-Little Egg Harbor estuary is reduced by as much as 49 cubic feet per second for 2000 to 2003 withdrawal conditions when compared with no-withdrawal conditions. In the three confined aquifers, water levels during periods of low recharge and high withdrawals, and high recharge and low withdrawals, were examined to determine seasonal effects on the confined flow systems. The simulated potentiometric surface of the Rio Grande water-bearing zone and the Atlantic City 800-foot sand during selected stress periods indicates substantial declines from no-withdrawal conditions to 2000–03 conditions as a result of groundwater withdrawals. Cones of depression in Toms River Township, Seaside Heights and Seaside Park Boroughs, and Barnegat Light Borough developed in the potentiometric surface of the Piney Point aquifer in response to withdrawals. Maximum-allocation withdrawals decreased flow out of the Kirkwood-Cohansey aquifer system to constant head cells, increased flow out of the aquifer system to adjacent and lower layers, and reduced groundwater discharge to streams when compared with 2000–03 withdrawal conditions. Increases in withdrawals from the Rio Grande water-bearing zone, the Atlantic City 800-foot sand, and the Piney Point aquifer result in an increase in simulated net groundwater flow into these aquifers. Base-flow reduction from 2000–03 conditions to maximum-allocation conditions of 25 to 29 cubic feet per second in all streams draining to the Barnegat Bay-Little Egg Harbor also is indicated. Potentiometric surfaces of the Rio Grande water-bearing zone, Atlantic City 800-foot sand, and the Piney Point aquifer during two stress periods of simulated maximum-allocation withdrawal conditions indicated the expansion of several cones of depression developed during 2000–03 withdrawals. Simulation of average 2000–03 withdrawal conditions indicated the extent to which the groundwater-flow system is susceptible to potential saltwater intrusion into near-shore wells. Travel time from recharge to discharge location ranged from 11 to approximately 50,700 years in near-shore Kirkwood-Cohansey aquifer system wells. Those in Seaside Heights Borough, in Island Beach State Park (Berkeley Township), and in Ship Bottom Borough have particle travel times from 140 to 12,000 years and flow paths that originated under Barnegat Bay or the Atlantic Ocean from the simulation of average maximum-allocation withdrawal conditions. Travel time along flow paths to wells screened in the Rio Grande water-bearing zone and the Atlantic City 800-foot sand from recharge to discharge point ranged from nearly 530 years to greater than 3.73 million years from the simulation of average 2000–03 withdrawal conditions. Particle tracking indicated that most wells screened in these aquifers derived a large part of their recharge from the Oswego River Basin, with a small portion of flow originating either beneath Barnegat Bay or to the east beneath the Atlantic Ocean. Travel time along flow paths that start beneath either Barnegat Bay or the Atlantic Ocean ranged from 2,300 to approximately 134,000 years from the simulation of average maximum-allocation withdrawal conditions."

New Jersey↗
USGS2004

Modeling a three-dimensional river plume over continental shelf using a 3D unstructured grid model

River derived fresh water discharging into an adjacent continental shelf forms a trapped river plume that propagates in a narrow region along the coast. These river plumes are real and they have been observed in the field. Many previous investigations have reported some aspects of the river plume properties, which are sensitive to stratification, Coriolis acceleration, winds (upwelling or downwelling), coastal currents, and river discharge. Numerical modeling of the dynamics of river plumes is very challenging, because the complete problem involves a wide range of vertical and horizontal scales. Proper simulations of river plume dynamics cannot be achieved without a realistic representation of the flow and salinity structure near the river mouth that controls the initial formation and propagation of the plume in the coastal ocean. In this study, an unstructured grid model was used for simulations of river plume dynamics allowing fine grid resolution in the river and in regions near the coast with a coarse grid in the far field of the river plume in the coastal ocean, in the vertical, fine fixed levels were used near the free surface, and coarse vertical levels were used over the continental shelf. The simulations have demonstrated the uniquely important role played by Coriolis acceleration. Without Coriolis acceleration, no trapped river plume can be formed no matter how favorable the ambient conditions might be. The simulation results show properties of the river plume and the characteristics of flow and salinity within the estuary; they are completely consistent with the physics of estuaries and coastal oceans.

Conference Paper↗
USGS2018

Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States

Regional regression is a common tool used to estimate daily flow-duration curves (FDCs) at ungaged locations. In this report, several refinements to a particular implementation of the regional regression method for estimating FDCs are evaluated by consideration of different methodological options through a leave-one-out cross-validation procedure in the 19 major river basins of the conterminous United States. Regression analyses in this report are based on streamflow data from water years 1981–2013 (October 1, 1980 to September 30, 2013) from 1,378 mostly undisturbed watersheds. Linear regression using selected basin characteristics at 27 quantiles with nonexceedance probabilities ranging from 0.02 to 99.98 percent was applied. The regression computations were primarily by weighted least squares, with left-censored Gaussian regression solved by maximum likelihood in the presence of zero-valued quantiles. The regional regression method as applied to the FDC estimation problem includes several methodological options that require determination of the better of two or more choices. The options considered in this report include (1) the setting of the maximum number of basin characteristics considered in the regression models for each region, (2) the method of placing the quantiles into groups (“flow regimes”) having the same basin characteristics used as independent variables, (3) the maximum number of candidate models retained from regressions at the single-quantile level that are retained for testing of the best model at the flow-regime scale, and (4) whether drainage area should be forced into the models. In all, 5 binary options were considered for most regions, resulting in 32 methodological combinations. Leave-one-out cross-validation predictions of FDC quantiles at each streamgage used in the study were used to evaluate compared options. Various performance measures were computed based on the predicted quantiles; these were combined by region and the methods were ranked for each measure. Based on examination of the ranked methods compared across the measures, the following treatments produced the more accurate results: (1) using fewer basin characteristics (of the two options considered), (2) utilizing a variance of the unit FDC-based method of determining the flow regimes rather than fixed regimes, (3) retaining more models from the quantile-level regressions regime-wide consideration, and (4) forcing drainage area into the regression models. Results of analyses also indicate that performance varies more by region than by methodological option, with FDCs in arid regions and those with a large value of a measure of intraregional FDC heterogeneity being harder to predict, particularly with respect to the low-flow quantiles.

Scientific Investigations Report↗
USGS2013

Quality-assurance plan for groundwater activities, U.S. Geological Survey, Washington Water Science Center

This report documents the standard procedures, policies, and field methods used by the U.S. Geological Survey’s (USGS) Washington Water Science Center staff for activities related to the collection, processing, analysis, storage, and publication of groundwater data. This groundwater quality-assurance plan changes through time to accommodate new methods and requirements developed by the Washington Water Science Center and the USGS Office of Groundwater. The plan is based largely on requirements and guidelines provided by the USGS Office of Groundwater, or the USGS Water Mission Area. Regular updates to this plan represent an integral part of the quality-assurance process. Because numerous policy memoranda have been issued by the Office of Groundwater since the previous groundwater quality assurance plan was written, this report is a substantial revision of the previous report, supplants it, and contains significant additional policies not covered in the previous report. This updated plan includes information related to the organization and responsibilities of USGS Washington Water Science Center staff, training, safety, project proposal development, project review procedures, data collection activities, data processing activities, report review procedures, and archiving of field data and interpretative information pertaining to groundwater flow models, borehole aquifer tests, and aquifer tests. Important updates from the previous groundwater quality assurance plan include: (1) procedures for documenting and archiving of groundwater flow models; (2) revisions to procedures and policies for the creation of sites in the Groundwater Site Inventory database; (3) adoption of new water-level forms to be used within the USGS Washington Water Science Center; (4) procedures for future creation of borehole geophysics, surface geophysics, and aquifer-test archives; and (5) use of the USGS Multi Optional Network Key Entry System software for entry of routine water-level data collected as part of long-term water-level monitoring networks.

Open-File Report↗
USGS2006

JUPITER: Joint Universal Parameter IdenTification and Evaluation of Reliability - An Application Programming Interface (API) for Model Analysis

he Joint Universal Parameter IdenTification and Evaluation of Reliability Application Programming Interface (JUPITER API) improves the computer programming resources available to those developing applications (computer programs) for model analysis. The JUPITER API consists of eleven Fortran-90 modules that provide for encapsulation of data and operations on that data. Each module contains one or more entities: data, data types, subroutines, functions, and generic interfaces. The modules do not constitute computer programs themselves; instead, they are used to construct computer programs. Such computer programs are called applications of the API. The API provides common modeling operations for use by a variety of computer applications. The models being analyzed are referred to here as process models, and may, for example, represent the physics, chemistry, and(or) biology of a field or laboratory system. Process models commonly are constructed using published models such as MODFLOW (Harbaugh et al., 2000; Harbaugh, 2005), MT3DMS (Zheng and Wang, 1996), HSPF (Bicknell et al., 1997), PRMS (Leavesley and Stannard, 1995), and many others. The process model may be accessed by a JUPITER API application as an external program, or it may be implemented as a subroutine within a JUPITER API application . In either case, execution of the model takes place in a framework designed by the application programmer. This framework can be designed to take advantage of any parallel processing capabilities possessed by the process model, as well as the parallel-processing capabilities of the JUPITER API. Model analyses for which the JUPITER API could be useful include, for example: Compare model results to observed values to determine how well the model reproduces system processes and characteristics. Use sensitivity analysis to determine the information provided by observations to parameters and predictions of interest. Determine the additional data needed to improve selected model predictions. Use calibration methods to modify parameter values and other aspects of the model. Compare predictions to regulatory limits. Quantify the uncertainty of predictions based on the results of one or many simulations using inferential or Monte Carlo methods. Determine how to manage the system to achieve stated objectives. The capabilities provided by the JUPITER API include, for example, communication with process models, parallel computations, compressed storage of matrices, and flexible input capabilities. The input capabilities use input blocks suitable for lists or arrays of data. The input blocks needed for one application can be included within one data file or distributed among many files. Data exchange between different JUPITER API applications or between applications and other programs is supported by data-exchange files. The JUPITER API has already been used to construct a number of applications. Three simple example applications are presented in this report. More complicated applications include the universal inverse code UCODE_2005 (Poeter et al., 2005), the multi-model analysis MMA (Eileen P. Poeter, Mary C. Hill, E.R. Banta, S.W. Mehl, and Steen Christensen, written commun., 2006), and a code named OPR_PPR (Matthew J. Tonkin, Claire R. Tiedeman, Mary C. Hill, and D. Matthew Ely, written communication, 2006). This report describes a set of underlying organizational concepts and complete specifics about the JUPITER API. While understanding the organizational concept presented is useful to understanding the modules, other organizational concepts can be used in applications constructed using the JUPITER API.

Techniques and Methods↗
USGS2025

Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020

Frequency analysis on annual peak streamflow (hereinafter, peak flow) is essential to water-resources management applications, including critical structure design (for example, bridges and culverts) and floodplain mapping. Nonstationarity is a statistical property of a peak-flow series such that the distributional properties (the mean, variance, or skew) change either gradually (monotonic trend) or abruptly (shift, step change or change point) through time. Not incorporating or accounting for observed nonstationarity into peak-flow frequency analysis might result in a poor representation of the true probability of large floods and thus misrepresent the actual flood risks to life and property. This report summarizes how hydroclimatic variability might affect the temporal and spatial distributions of peak-flow data in the State of Montana (and northern Wyoming) and is part of a larger study to document peak-flow nonstationarity and hydroclimatic changes across a nine-State region consisting of Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flows. This study was completed in cooperation with the Montana Department of Natural Resources and Conservation. The purpose of this report is to characterize temporal and spatial patterns of nonstationarity in peak flows and hydroclimatology in Montana and northern Wyoming. In this evaluation, peak-flow, daily streamflow, and model-simulated gridded climatic data were examined for monotonic trends, change points, and other statistical properties that might indicate changing climatic and environmental conditions. This report includes background information on the study area, the history of U.S. Geological Survey peak-flow data collection and frequency analysis in Montana, and the review of research relating to hydroclimatic variability and change in Montana. This study might help provide a framework for addressing potential nonstationarity issues in peak-flow frequency updates that commonly are completed by the U.S. Geological Survey in cooperation with other agencies throughout the Nation. The analytical structure of this study includes analyses of monotonic trends and change points in numerous hydroclimatic variables in assigned 30-, 50-, 75-, and 100-year analysis periods. For Montana and part of Wyoming, the 30-, 50-, 75, and 100-year analyses included 157, 70, 48, and 12 streamgages, respectively. For those streamgages, nonstationarities were analyzed in the following variables: (1) climatic variables, including annual and seasonal (winter, spring, summer, and fall) temperature and precipitation; (2) daily streamflow variables, including the annual center of volume duration, annual center of volume median, and peaks over threshold with a mean of four events per year; and (3) annual peak-flow variables, including peak-flow timing and magnitude. A likelihood approach was used to express statistical confidence and assign the nonstationarity results as likely upward or downward (highest statistical confidence), somewhat likely upward or downward (less statistical confidence), or about as likely as not (little statistical confidence; hereinafter, neutral). For the nonstationarity analyses of the climatic, daily streamflow, and peak-flow variables, the results are presented in detail and discussed with respect to statewide patterns and geographic variability. For each of the 30-, 50-, and 75-year analyses, peak-flow change-point and monotonic trend analyses were compiled for streamgages classified with likely downward or likely upward trends. For those streamgages, the associated basin characteristics and nonstationarity results for peak-flow timing, daily streamflow, and climatic variables were investigated and statistically compared to discern associations among other variables that might contribute to the peak-flow nonstationarity results. The 50- and 75-year peak-flow nonstationarities identified in this study are mostly downward, in association with mostly upward temperature and potential evapotranspiration:precipitation monotonic trends. For the 50-, 75-, and 100-year analyses, the peak-flow change points are predominantly downward and are concentrated in the 1970s and 1980s, which indicates general consistency among the longer trend periods. These findings are in association with substantial research documenting globally rising temperature and atmospheric greenhouse gas concentrations that might be largely attributed to anthropogenic activities. Anthropogenic effects might represent long-term (on the order of several decades to more than a century) climate changes that might happen within highly variable natural climate fluctuations. Several paleo studies in the north-central United States have indicated that hydroclimatic extremes (that is, low- and high-streamflow conditions) before European settlement have been outside of extremes since the 1900s. Depending on the interactions of anthropogenic effects and natural climate variability, extreme high-streamflow conditions might occur in the future, even in the presence of long-term downward peak-flow trends.

Montana, Wyoming↗
USGS1990

Preconditioned Conjugate-Gradient 2 (PCG2), a computer program for solving ground-water flow equations

This report documents PCG2: a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model. PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options: modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers. Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.

Water-Resources Investigations Report↗
USGS2023

Preliminary machine learning models of manganese and 1,4-dioxane in groundwater on Long Island, New York

Manganese and 1,4-dioxane in groundwater underlying Long Island, New York, were modeled with machine learning methods to demonstrate the use of these methods for mapping contaminants in groundwater in the Long Island aquifer system. XGBoost, a gradient boosted, ensemble tree method, was applied to data from 910 wells for manganese and 553 wells for 1,4-dioxane. Explanatory variables included soil properties, groundwater flow, land use, and other features that describe the hydrogeology and geochemistry of the aquifer system. Four models were developed to predict the probability of manganese concentrations greater than a detection level of 10 micrograms per liter (μg/L) and greater than three threshold concentrations (50, 150, and 300 μg/L) relevant to drinking-water quality. One model was developed to predict the probability of 1,4-dioxane concentrations greater than a detection level of 0.07 μg/L. The 1,4-dioxane model was limited geographically to Suffolk County because of data availability. Predictions were made for two layers in the upper glacial aquifer and three layers in the Magothy aquifer, which are the upper two of the three major aquifers of the Long Island aquifer system. The objective of the study described in this report was to demonstrate the application of the methods rather than to develop precise estimates of manganese or 1,4-dioxane concentrations at any given location. The predictive models developed in the study are considered preliminary in the sense that they are an initial effort at developing these kinds of models specifically for Long Island. The models could be improved by the inclusion of additional data, by the use of methods to improve the modeling of infrequent high concentrations of manganese and 1,4-dioxane (above threshold concentrations), and by including more explanatory variables that specifically describe conditions and contaminant sources on Long Island. Nonetheless, the distribution of model predictions and the influence of explanatory variables in the models were consistent with the expected relations between contaminant concentrations and groundwater-flow-system characteristics and the distribution of manmade sources. Mapped predictions indicated that manganese detections were more probable in the upper glacial aquifer and along the southern shore of Long Island, consistent with the distribution of anoxic conditions in groundwater in the Long Island aquifer system. Manganese was infrequently predicted at concentrations greater than thresholds of concern for drinking-water quality in any of the aquifer layers. Detections of 1,4-dioxane were predicted in the western, more highly developed parts of Suffolk County, in the upper glacial aquifer and the top and middle layers of the Magothy aquifer, and in northwestern Suffolk County in the bottom layer of the Magothy aquifer. Although preliminary in nature and based on limited data, these mapped predictions can be used to generally identify areas where manganese and 1,4-dioxane may be present at concentrations of concern to prioritize areas for future monitoring and to guide future modeling and mapping efforts.

New York↗
USGS2019

Interactions between resident risk perceptions and wildfire risk mitigation: Evidence from simultaneous equations modeling

Fire science emphasizes that mitigation actions on residential property, including structural hardening and maintaining defensible space, can reduce the risk of wildfire at a home. Accordingly, a rich body of social science literature investigates the determinants of wildfire risk mitigation behaviors of residents living in fire-prone areas. Here, we investigate relationships among wildfire hazards, residents’ risk perceptions, and conditions associated with mitigation actions using a combination of simulated wildfire conditions, household survey responses, and professionally assessed parcel characteristic data. We estimate a simultaneous model of these data that accounts for potential direct feedbacks between risk perceptions and parcel-level conditions. We also compare the use of self-reported versus assessed parcel-level data for estimating these relationships. Our analysis relies on paired survey and assessment data for approximately 2000 homes in western Colorado. Our simultaneous model demonstrates dual-directional interactions between risk perceptions and conditions associated with mitigation actions, with important implications for inference from simpler approaches. In addition to improving general understanding of decision-making about risk and natural hazards, our findings can support the effectiveness of publicly supported programs intended to encourage mitigation to reduce society’s overall wildfire risk.

Fire↗
USGS2006

Revisiting Frazier's subdeltas: enhancing datasets with dimensionality, better to understand geologic systems

Scientific knowledge from the past century is commonly represented by two-dimensional figures and graphs, as presented in manuscripts and maps. Using today's computer technology, this information can be extracted and projected into three- and four-dimensional perspectives. Computer models can be applied to datasets to provide additional insight into complex spatial and temporal systems. This process can be demonstrated by applying digitizing and modeling techniques to valuable information within widely used publications. The seminal paper by D. Frazier, published in 1967, identified 16 separate delta lobes formed by the Mississippi River during the past 6,000 yrs. The paper includes stratigraphic descriptions through geologic cross-sections, and provides distribution and chronologies of the delta lobes. The data from Frazier's publication are extensively referenced in the literature. Additional information can be extracted from the data through computer modeling. Digitizing and geo-rectifying Frazier's geologic cross-sections produce a three-dimensional perspective of the delta lobes. Adding the chronological data included in the report provides the fourth-dimension of the delta cycles, which can be visualized through computer-generated animation. Supplemental information can be added to the model, such as post-abandonment subsidence of the delta-lobe surface. Analyzing the regional, net surface-elevation balance between delta progradations and land subsidence is computationally intensive. By visualizing this process during the past 4,500 yrs through multi-dimensional animation, the importance of sediment compaction in influencing both the shape and direction of subsequent delta progradations becomes apparent. Visualization enhances a classic dataset, and can be further refined using additional data, as well as provide a guide for identifying future areas of study.

Gulf Coast Association of Geological Societies Tra↗
USGS2001

Geologic framework of the San Juan structural basin of New Mexico, Colorado, Arizona, and Utah, with emphasis on Triassic through Tertiary rocks

The San Juan Basin Regional Aquifer-System Analysis began in 1984. This report describes rocks of Triassic through Tertiary age in the basin and also describes the regional geologic and stratigraphic framework of the basin's multilayered aquifer system. Maps showing altitude of top, depth to top, and thickness of major geologic units were prepared using geographic information system technology. Results presented form the basis for ground-water flow modeling and geochemical studies of the basin.

Professional Paper↗