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USGS2006

Application of artificial neural networks to assess pesticide contamination in shallow groundwater

In this study, a feed-forward back-propagation neural network (BPNN) was developed and applied to predict pesticide concentrations in groundwater monitoring wells. Pesticide concentration data are challenging to analyze because they tend to be highly censored. Input data to the neural network included the categorical indices of depth to aquifer material, pesticide leaching class, aquifer sensitivity to pesticide contamination, time (month) of sample collection, well depth, depth to water from land surface, and additional travel distance in the saturated zone (i.e., distance from land surface to midpoint of well screen). The output of the neural network was the total pesticide concentration detected in the well. The model prediction results produced good agreements with observed data in terms of correlation coefficient (R = 0.87) and pesticide detection efficiency (E = 89%), as well as good match between the observed and predicted "class" groups. The relative importance of input parameters to pesticide occurrence in groundwater was examined in terms of R, E, mean error (ME), root mean square error (RMSE), and pesticide occurrence "class" groups by eliminating some key input parameters to the model. Well depth and time of sample collection were the most sensitive input parameters for predicting the pesticide contamination potential of a well. This infers that wells tapping shallow aquifers are more vulnerable to pesticide contamination than those wells tapping deeper aquifers. Pesticide occurrences during post-application months (June through October) were found to be 2.5 to 3 times higher than pesticide occurrences during other months (November through April). The BPNN was used to rank the input parameters with highest potential to contaminate groundwater, including two original and five ancillary parameters. The two original parameters are depth to aquifer material and pesticide leaching class. When these two parameters were the only input parameters for the BPNN, they were not able to predict contamination potential. However, when they were used with other parameters, the predictive performance efficiency of the BPNN in terms of R, E, ME, RMSE, and pesticide occurrence "class" groups increased. Ancillary data include data collected during the study such as well depth and time of sample collection. The BPNN indicated that the ancillary data had more predictive power than the original data. The BPNN results will help researchers identify parameters to improve maps of aquifer sensitivity to pesticide contamination. ?? 2006 Elsevier B.V. All rights reserved.

Science of the Total Environment↗

USGS2024

Using mercury and lead stable isotopes to assess mercury, lead, and trace metal source contributions to Great Salt Lake, Utah, USA

Great Salt Lake is a critical habitat for migratory birds that is threatened by elevated metal concentrations, including mercury (Hg) and lead (Pb), and is subject to severe hydrologic changes, such as declining lake level. When assessing metal profiles recorded in Great Salt Lake sediment, a large data gap exists regarding the sources of metals within the system, which is complicated by various source inputs to the lake and complex biogeochemistry. Here, we leverage Hg and Pb stable isotopes to track relative changes in metal source contributions to Great Salt Lake over time. Mercury and Pb concentrations increase in sediments deposited after 1920 and peak between 1965 and 1995, following closure of several local smelters and the onset of increased emission controls. The nominal associations above are confirmed via Hg stable isotopes in pre-1920 background sediments, which reflect atmospheric inputs from regional and global origin, whereas Hg and Pb stable isotopes together indicate that elevated metal concentrations in mid-late 20th century sediments reflect increased mining/smelting inputs. The observed minimal rebound towards pre-1920 Pb isotope signatures in 21st century sediments indicates that mining/smelting inputs, though reduced, remain a primary source of Pb to Great Salt Lake. In contrast, the more pronounced rebound of Hg stable isotope signatures to pre-1920 values indicate a greater contribution of atmospheric inputs of regional/global origin to current Hg inputs, though Hg concentrations are ∼10 times greater than pre-1920 background values due to global increases in atmospheric Hg concentrations or possibly slow recovery from local contamination. The importance of regional/global Hg sources to the system suggests that reductions in Hg bioaccumulation in the open water food webs of Great Salt Lake are more dependent on national and global reductions in Hg emissions and management strategies to limit methylmercury production within system. This work highlights the utility of using coupled Hg and Pb stable isotope values to assess trace metal pollution sources and pathways in aquatic systems.

Utah↗

USGS2004

The geochemical and magnetic record of coal combustion products in West Virginia reservoir sediments and soils

Western West Virginia lies downwind from numerous coal-fired power plants along the Ohio River Valley. To test whether geochemical and mineralogical impacts from these power plants are detectable on the West Virginia landscape, we obtained reservoir cores, soils, and rocks from two separate sites in West Virginia, one in Harrison County (Hinkel and Deegan Reservoirs) and the other in Roane County (Miletree Run Reservoir). Both have small drainage basins that have the effect of maximizing atmospheric inputs relative to weathering inputs. Sediments from Hinkel Reservoir were dated using the 137 Cs method, and by knowledge of the age of the base of the sedimentary section. Major elements in Hinkel Reservoir sediments do not vary systematically over time, suggesting that the depositional history of these sediments has been relatively constant. In contrast, minor elements and sulfur do show dramatic shifts. Zn, Pb, As, S, Cd, Ge, and Hg all peak during the late 1960s and early 1970s. Polyaromatic hydrocarbons associated with combustion processes likewise show this same behavior. Coincident with these maxima is a peak in isothermal remnant magnetization (IRM), a parameter that is proportional to magnetite abundance. We separated the magnetic fraction of the sediments and examined this fraction petrographically. It is dominated by magnetite with a spherical morphology, which is characteristic of magnetite produced by combustion processes. Chemical analyses on local rocks showed that they were not the likely source for the trace element and magnetite enrichments. To compare soils and reservoir sediments, we normalized geochemical data to Ti; the underlying assumption is that Ti will track physical inputs of soil materials into the reservoir sediments. The normalized sediment data for the elements Zn, Pb, As, and S are all higher for sediments deposited during the late 1960s and early 1970s compared to normalized soil data, implying that soils are not the source for the element enrichments. We thus attribute the enrichment to atmospheric inputs. However, a coal-burning zinc smelter within 10 km of the reservoir site that operated until 1971 may have supplied some or all of the anomalous input: There are no nearby major atmospheric pollution sites near Miletree Run Reservoir. A core from this reservoir was dated based on knowledge of the time it was impounded. Like Hinkel Reservoir, there are no systematic shifts in major element contents over its depositional history. Like Hinkel Reservoir, there are also significant shifts in trace elements and IRM that cannot be explained by local soil sources. Magnetic separates from this reservoir are also dominated by spherical combustion-produced magnetite. Covariance over the period 1930-1980 between magnetite and sulfur with US SO 2 production (which comes dominantly from coal combustion) is strongly suggestive of a significant atmospheric input into Miletree Run Reservoir sediments. The nearest upwind power plants are between 50 and 75 km distant. Thus, relatively long distance transmission of particulate matter from the power plants of the Ohio River Valley is likely in this case.

West Virginia↗

USGS2020

Key components and contrasts in the nitrogen budget across a US-Canadian transboundary watershed

Watershed nitrogen (N) budgets provide insights into drivers and solutions for groundwater and surface water N contamination. We constructed a comprehensive N budget for the transboundary Nooksack River Watershed (British Columbia, Canada, and Washington, USA) using locally derived data, national statistics, and standard parameters. Feed imports for dairy (mainly in the United States) and poultry (mainly in Canada) accounted for 30% and 29% of the total N input to the watershed, respectively. Synthetic fertilizer was the next largest source contributing 21% of inputs. Food imports for humans and pets together accounted for 9% of total inputs, lower than atmospheric deposition (10%). N imported by returning salmon representing marine‐derived nutrients accounted for <0.06% of total N input. Quantified N export was 80% of total N input, driven by ammonia emission (32% of exports). Animal product export was the second largest output of N (31%) as milk and cattle in the United States and poultry products in Canada. Riverine export of N was estimated at 28% of total N export. The commonly used crop nitrogen use efficiency (NUE) metric alone did not provide sufficient information on farming activities but in combination with other criteria such as farm‐gate NUE may better represent management efficiency. Agriculture was the primary driver of N inputs to the environment as a result of its regional importance; the N budget information can inform management to minimize N losses. The N budget provides key information for stakeholders across sectors and borders to create environmentally and economically viable and effective solutions.

Washington, British Columbia↗

USGS2013

Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas

We applied Hyperion sensor satellite data acquired by the National Aeronautics and Space Administration’s Earth Observing-1 (EO-1) satellite in conjunction with reconnaissance surveys to map the occurrences of the invasive Chinese tallow tree (Triadica sebifera) in the Toledo Bend Reservoir study area of northwestern Louisiana and northeastern Texas. The rationale for application of high spectral resolution EO-1 Hyperion data was based on the successful use of Hyperion data in the mapping of Chinese tallow tree in southwestern Louisiana in 2005. In contrast to the single Hyperion image used in the 2005 project, more than 20 EO-1 Hyperion and Advanced Land Imager (ALI) images of the study area were collected in 2009 and 2010 during the fall senescence when Chinese tallow tree leaves turn red. Atmospherically corrected reflectance spectra of Hyperion imagery collected at ground and aerial observation locations provided the input datasets used in the program for spectral discrimination analysis. Discrimination analysis was used to identify spectral indicator sets to best explain variance contained in the input databases. The expectation was that at least one set of Hyperion-based indicator spectra would uniquely identify occurrences of red-leaf Chinese tallow tree; however, no combination of Hyperion-based reflectance datasets produced a unique identifier. The inability to discover a unique spectral indicator resulted primarily from relatively sparse coverage by red-leaf Chinese tallow tree within the study area (percentage of coverage was less than 5 percent per 30- by 30-meter Hyperion pixel). To enhance the performance of the spectral discrimination analysis, leaf and canopy spectra of Chinese tallow tree were added to the input datasets to guide the indicator selection. In addition, input databases were segregated by land class obtained from an ALI-based landcover classification in order to reduce the input variance and to promote spectral discrimination of red-leaf Chinese tallow tree. Although no unique spectral identifier for red-leaf Chinese tallow tree was uncovered with these enhanced methods, in some cases predicted spatial patterns throughout the Hyperion images revealed alignment with vegetation associations within each land class that was often observed to contain Chinese tallow trees. These instances were associated particularly with the addition of helicopter-based spectra to the input databases. It was attempted to extend such predictions of likely occurrences of Chinese tallow tree by mapping six of the nine Hyperion swaths and four of the nine land classes, but this attempt produced uncertain results that could not be fully evaluated for accuracy. Even though the final mapping showed promise in identifying likely Chinese tallow tree occurrences, the low percentage of occurrences hindered mapping performance and validation. Results of the mapping suggested that successful detection of Chinese tallow tree in the study area would require a spectral sensor similar to the Hyperion but with a higher ground-level spatial resolution. Although the Hyperion-based spectral mapping did not provide the desired results, the associated field (ground and aerial) surveys did provide for a qualitative assessment of the overall Chinese tallow tree distribution within the study area. Ground and aerial surveys suggested that Chinese tallow tree occurrences were uncommon and were without an observed pattern in relation to proximity to the Toledo Bend Reservoir. Although uncommon and scattered, Chinese tallow trees and shrubs most commonly existed along forest edges, water edges, and fence lines, probably most in line with seed dispersal by birds. Chinese tallow trees were observed to be more densely dispersed within some scrublands and grasslands than were observed in pine, hardwood, and mixed forests.

Louisiana;Texas↗

USGS2025

Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20

Executive Summary The Hiram M. Chittenden (Ballard) Locks and Lake Washington Ship Canal connect freshwater Lake Washington and saline Shilshole Bay of Puget Sound in Seattle, Washington. The locks and canal allow for ships to traverse this reach. Anadromous salmonids also migrate through, transitioning between saline and freshwater environments, and making use of a fish ladder at the locks when traveling upstream. WEST Consultants, Inc., constructed a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) simulating flow, water temperature, and salinity for the Ballard Locks and the Lake Washington Ship Canal. An initial model was built for calendar years 2014–15, and the model was updated using a more recent and modern dataset for calendar years 2016–20. The U.S. Army Corps of Engineers requested that the U.S. Geological Survey review this model and its documentation to evaluate the technical aspects of its development and calibration. Findings from this review include the following: Overall, the Lake Washington Ship Canal CE-QUAL-W2 model was well-documented and constructed largely following typical model-development methods. The Lake Washington Ship Canal model was built with CE-QUAL-W2 model version 4.5, compiled and released by Portland State University in April 2021. CE-QUAL-W2 updates and improvements are regularly released with bug fixes and new features, so any model updates would benefit from the use of the most-recent software release. The model grid that represents the Lake Washington Ship Canal bathymetry was 9.2 kilometers (5.7 miles) long, matching the expected length of the waterway. The deepest model segments were near sampling site LLLW (Large Locks site) near the locks. Lake Union is reported to constitute most of the volume of the Lake Washington Ship Canal and is depicted as such in the model grid. The model includes several water outflows at Ballard Locks, including the large and small locks, a saltwater drain, a spillway, smolt flumes, and a fish ladder. Flows from the spillway, smolt flumes, and fish ladder were combined into one structure outflow in the model and assigned one withdrawal elevation from the Lake Washington Ship Canal. The smolt flume and spillway withdraw from the same elevation, but the fish ladder flow withdraws from a higher elevation in Lake Washington Ship Canal, and that flow could be separated into its own withdrawal. The model input files were created using the Coordinated Universal Time standard instead of the more typical choice of using local standard time. This is not incorrect, but sub-daily results would need to be converted to local time for science-communication purposes. The meteorological dataset had some unexpected anomalies, such as a baseline shift in the wind-speed dataset. Other nearby meteorological datasets could be used instead or used to correct the current meteorological inputs. The upstream boundary was configured with water-temperature data from a continuous monitor buoy in Lake Washington. The boundary salinity was set at 0 parts per thousand for the duration of the model simulation. A more realistic estimate of salinity at the upstream boundary could be constructed using data from the same buoy. Saline inflow at the downstream boundary of the Lake Washington Ship Canal model through lock exchanges at the large lock was included as a tributary in the model. Salinity and temperature inputs in this tributary at the large locks were set as constant values for the entire simulation. Saline inflow through the small lock was not included in the model because few data were available, and the input was likely to be small because of the smaller surface area and volume of the small lock relative to the large lock. The model did not include any flow, water temperature, or salinity inputs to the Lake Washington Ship Canal other than at the locks and at the upstream boundary. Any point sources, small tributaries, or stormwater inputs were omitted from the model. It is unclear whether this is a substantial omission relative to model results. Most model parameters were set as defaults or to reasonable values. However, the value of the WINDH parameter, the height of the wind speed measurement, was different than the height of the meteorological site. Compared to measured data, the model simulated water-surface elevations and water temperatures with reasonable accuracy. Differences in the modeled and measured salinities revealed some opportunities to improve the simulation of salinity, both baseline salinity and the salinity maxima in summer and autumn.

Washington↗

USGS1980

A computer program for simulating geohydrologic systems in three dimensions

This document is directed toward individuals who wish to use a computer program to simulate ground-water flow in three dimensions. The strongly implicit procedure (SIP) numerical method is used to solve the set of simultaneous equations. New data processing techniques and program input and output options are emphasized. The quifer system to be modeled may be heterogeneous and anisotropic, and may include both artesian and water-table conditions. Systems which consist of well defined alternating layers of highly permeable and poorly permeable material may be represented by a sequence of equations for two dimensional flow in each of the highly permeable units. Boundaries where head or flux is user-specified may be irregularly shaped. The program also allows the user to represent streams as limited-source boundaries when the streamflow is small in relation to the hydraulic stress on the system. The data-processing techniques relating to ' cube ' input and output, to swapping of layers, to restarting of simulation, to free-format NAMELIST input, to the details of each sub-routine 's logic, and to the overlay program structure are discussed. The program is capable of processing large models that might overflow computer memories with conventional programs. Detailed instructions for selecting program options, for initializing the data arrays, for defining ' cube ' output lists and maps, and for plotting hydrographs of calculated and observed heads and/or drawdowns are provided. Output may be restricted to those nodes of particular interest, thereby reducing the volumes of printout for modelers, which may be critical when working at remote terminals. ' Cube ' input commands allow the modeler to set aquifer parameters and initialize the model with very few input records. Appendixes provide instructions to compile the program, definitions and cross-references for program variables, summary of the FLECS structured FORTRAN programming language, listings of the FLECS and FORTRAN source code, and samples of input and output for example simulations. (USGS)

Open-File Report↗

USGS2006

Nutrients in streams and rivers across the nation — 1992–2001

Nutrient compounds of nitrogen and phosphorus were investigated in streams and rivers sampled as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. Nutrient data were collected in 20 NAWQA study units during 1992-95, 16 study units during 1996-98, and 15 study units during 1999-2001. To facilitate comparisons among sampling sites with variable sampling frequency, daily loads were determined by using regression models that relate constituent transport to streamflow and time. Model results were used to compute mean annual loads, yields, and concentrations of ammonia, nitrate, total nitrogen, orthophosphate, and total phosphorus, which were compared among stream and river sampling sites. Variations in the occurrence and distribution of nutrients in streams and rivers on a broad national scale reflect differences in the sources of nutrient inputs to the upstream watersheds and in watershed characteristics that affect movement of those nutrients. Sites were classified by watershed size and by land use in the upstream watershed: agriculture, urban, and undeveloped (forest or rangeland). Selection of NAWQA urban sites was intended to avoid effects of major wastewater-treatment plants and other point sources, but in some locations this was not feasible. Nutrient concentrations and yields generally increased with anthropogenic development in the watershed. Median concentrations and yields for all constituents at sites downstream from undeveloped areas were less than at sites downstream from agricultural or urban areas. Concentrations of ammonia, orthophosphate, and total phosphorus at agricultural and urban sites were not significantly different; however, concentrations of nitrate and total nitrogen were higher at agricultural than at urban sites. Total nitrogen concentrations at agricultural sites were higher in areas of high nitrogen input or enhanced transport, such as irrigation or artificial drainage that can rapidly move water from cropland to streams (Midwest, Northern Plains, and western areas of the United States). Concentrations were lower in the Southeast, where more denitrification occurs during transport of nitrogen compounds in shallow ground water. At urban sites, high concentrations of ammonia and orthophosphate were more prevalent downstream from wastewater-treatment plants. At sites with large watersheds and high mean-annual streamflow (“large-watershed” sites), concentrations of most nutrients were significantly less than at sites downstream from agricultural or urban areas. Total nitrogen concentrations at large-watershed sites were higher in Midwest agricultural areas and lower in the Western United States, where agricultural and urban development is less extensive. Total phosphorus concentrations at large-watershed sites were higher in areas of greater potential erosion and low overall runoff such as the arid areas in the West. Although not as distinct as seasonal patterns of streamflow, geographic patterns of seasonally high and low concentrations of total nitrogen and total phosphorus were identified in the data. Seasonal patterns in concentrations of total nitrogen generally mirror seasonal patterns in streamflow in the humid Eastern United States but are inverse to seasonal patterns in streamflow in the semiarid interior West. Total phosphorus concentrations typically have the opposite regional relation with streamflow; high concentrations coincide with high streamflows in the interior West. In the NAWQA Program, sites downstream from relatively undeveloped areas were selected to provide a baseline for comparison to sites with potential effects of urban development and agriculture. Concentrations of nitrate, total nitrogen, and total phosphorus at NAWQA undeveloped sites were found to be greater than values reported by other studies for conditions of essentially no development (background conditions). Concentrations at NAWQA undeveloped sites represent conditions of relatively little development and provide insight in comparison to developed areas but should not, in general, be considered to represent background status. The U.S. Environmental Protection Agency has developed nutrient criteria to assist States in setting regional water-quality standards. Regional criteria were exceeded by total nitrogen concentrations at 72 percent of NAWQA undeveloped sites and by total phosphorus concentrations at 89 percent of these sites. Exceedances were even more extensive at sites with greater anthropogenic development upstream. The nitrogen criteria were exceeded at 96 percent of NAWQA sites classified as agricultural, urban, or mixed land use, and the phosphorus criteria were exceeded at 97 percent of these sites. Nationally, outflow loads of all nutrient constituents were strongly correlated to nonpoint-source inputs in the upstream watershed. The variation in input mass explained at least 69 percent of the variation in loads. Correlations between nonpoint-source input rates and outflow yields were not quite as good; variation in input rates explained only about 22-45 percent of the variations in nutrient yields. Estimation of nutrient outflow, on the basis of these correlations, likely could be improved if nationally consistent data were available for additional watershed characteristics.

Scientific Investigations Report↗

USGS2013

Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50

Groundwater from the surficial aquifer system and Upper Floridan aquifer in the Dougherty Plain and Marianna Lowlands in southwestern Georgia, northwestern Florida, and southeastern Alabama is affected by elevated nitrate concentrations as a result of the vulnerability of the aquifer, irrigation water-supply development, and intensive agricultural land use. The region relies primarily on groundwater from the Upper Floridan aquifer for drinking-water and irrigation supply. Elevated nitrate concentrations in drinking water are a concern because infants under 6 months of age who drink water containing nitrate concentrations above the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter as nitrogen can become seriously ill with blue baby syndrome. In response to concerns about water quality in domestic wells and in springs in the lower Apalachicola–Chattahoochee–Flint River Basin, the Florida Department of Environmental Protection funded a study in cooperation with the U.S. Geological Survey to examine water quality in groundwater and springs that provide base flow to the Chipola River. A three-dimensional, steady-state, regional-scale groundwater-flow model and two local-scale models were used in conjunction with particle tracking to identify travel times and areas contributing recharge to six groundwater sites—three long-term monitor wells (CP-18A, CP-21A, and RF-41) and three springs (Jackson Blue Spring, Baltzell Springs Group, and Sandbag Spring) in the lower Apalachicola–Chattahoochee–Flint River Basin. Estimated nitrate input to groundwater at land surface, based on previous studies of nitrogen fertilizer sales and atmospheric nitrate deposition data, were used in the advective transport models for the period 2002 to 2050. Nitrate concentrations in groundwater samples collected from the six sites during 1993 to 2007 and groundwater age tracer data were used to calibrate the transport aspect of the simulations. Measured nitrate concentrations (as nitrogen) in wells and springs sampled during the study ranged from 0.37 to 12.73 milligrams per liter. Average apparent ages of groundwater calculated from measurements of chlorofluorocarbon, sulfur hexafluoride, and tritium from wells CP-18A, CP-21A,and RF-41 were about 23, 29, and 32 years, respectively. Average apparent ages of groundwater from Baltzell Springs Group, Sandbag Spring, and Jackson Blue Spring were about 16, 18, and 19 years, respectively. Simulated travel times of particles from the six selected sites ranged from less than 1 day to 511 years; both the minimum and maximum particle travel times were estimated for water from Jackson Blue Spring. Median simulated travel times of particles were about 30, 38, and 62 years for Jackson Blue Spring, Sandbag Spring, and Baltzell Springs Group, respectively. Study results indicated that travel times for approximately 50 percent of the particles from all spring sites were less than 50 years. The median simulated travel times of particles arriving at receptor wells CP-18A, CP-21A, and RF-41 were about 50, 35, and 36 years, respectively. All particle travel times were within the same order of magnitude as the tracer-derived average apparent ages for water, although slightly older than the measured ages. Travel time estimates were substantially greater than the measured age for groundwater reaching well CP-18A, as confirmed by the average apparent age of water determined from tracers. Local-scale particle-tracking models were used to predict nitrate concentrations in the three monitor wells and three springs from 2002 to 2050 for three nitrogen management scenarios: (1) fixed input of nitrate at the 2001 level, (2) reduction of nitrate inputs of 4 percent per year (from the previous year) from 2002 to 2050, and (3) elimination of nitrate input after 2001. Simulated nitrate concentrations in well CP-21A peaked at 7.82 milligrams per liter in 2030, and concentrations in background well RF-41 peaked at 1.10 milligrams per liter in 2020. The simulated particle travel times were longer than indicated by age dating analysis for groundwater in well CP-18A; to account for the poor calibration fit at this well, nitrate concentrations were shifted 21 years. With the shift, simulated nitrate concentrations in groundwater at CP-18A peaked at 13.76 milligrams per liter in 2026. For groundwater in Baltzell Springs Group, Jackson Blue Spring, and Sandbag Spring, simulated nitrate concentrations peaked at 3.77 milligrams per liter in 2006, 3.51 milligrams per liter in 2011, and 0.81 milligram per liter in 2018, respectively, under the three management scenarios. In management scenario 3 (elimination of nitrate input after 2001), simulated nitrate concentrations in Baltzell Springs Group decreased to less than background concentrations (0.10 milligram per liter) by 2033, and in Sandbag Spring concentrations decreased to less than background by 2041. Simulations using nitrate management scenarios 1 (fixed input of nitrate at 2001 levels) and 2 (reduction of 4.0 percent per year) indicate that nitrate concentrations in groundwater may remain above background concentrations through 2050 at all sites.

Alabama, Florida, Georgia↗

USGS2019

Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California

Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration. The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.

California, Oregon↗

USGS2019

User’s manual for the Draper climate-distribution software suite with data‑evaluation tools

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiring distributed inputs of climate data beyond what is available from observations collected at climate stations. To prepare inputs required for model-mapping units across the study area, climate data (temperature and precipitation) are distributed by combining data from gridded surfaces of mean-monthly climate-data values with (often) widely spaced daily point observations. Examples of climate-data files used to develop PRMS-formatted input files for the Merced River Basin Precipitation-Runoff Modeling System (PRMS) are included in this manual. The Draper Climate-Distribution Software Suite (Draper Suite) consists of the Draper climate-distribution program (Draper) and several supporting pre- and post-processing applications. Draper combines spatially distributed input in the form of monthly averaged values for precipitation, maximum temperature, and minimum temperature with daily observed data from climate stations to estimate distributed climate-data values at predefined locations across a study area (typically a drainage basin) on a daily time step. Alternative methods are used when station data are limited or missing for a particular day. Draper uses a set of required and optional input and output files with defined formats and naming conventions. A shell application also is available to manage multiple runs of the Draper application. Other applications in the Draper Suite include (1) a tool to find and interactively remove outliers in the input data, (2) a tool to check and enforce a minimum daily temperature range, and (3) a tool to view output diagnostic information as time-series graphs. These tools can be used iteratively to evaluate and improve the results from Draper as part of a workflow involving physically based environmental models, such as the Precipitation-Runoff Modeling System (PRMS).

Techniques and Methods↗

USGS1996

Regional nitrogen budgets and riverine N & P fluxes for the drainages to the North Atlantic Ocean: Natural and human influences

We present estimates of total nitrogen and total phosphorus fluxes in rivers to the North Atlantic Ocean from 14 regions in North America, South America, Europe, and Africa which collectively comprise the drainage basins to the North Atlantic. The Amazon basin dominates the overall phosphorus flux and has the highest phosphorus flux per area. The total nitrogen flux from the Amazon is also large, contributing 3.3 Tg yr −1 out of a total for the entire North Atlantic region of 13.1 Tg yr −1 . On a per area basis, however, the largest nitrogen fluxes are found in the highly disturbed watersheds around the North Sea, in northwestern Europe, and in the northeastern U.S., all of which have riverine nitrogen fluxes greater than 1,000 kg N km −2 yr −1 . Non-point sources of nitrogen dominate riverine fluxes to the coast in all regions. River fluxes of total nitrogen from the temperate regions of the North Atlantic basin are correlated with population density, as has been observed previously for fluxes of nitrate in the world's major rivers. However, more striking is a strong linear correlation between river fluxes of total nitrogen and the sum of anthropogenically-derived nitrogen inputs to the temperate regions (fertilizer application, human-induced increases in atmospheric deposition of oxidized forms of nitrogen, fixation by leguminous crops, and the import/export of nitrogen in agricultural products). On average, regional nitrogen fluxes in rivers are only 25% of these anthropogenically derived nitrogen inputs. Denitrification in wetlands and aquatic ecosystems is probably the dominant sink, with storage in forests perhaps also of importance. Storage of nitrogen in groundwater, although of importance in some localities, is a very small sink for nitrogen inputs in all regions. Agricultural sources of nitrogen dominate inputs in many regions, particularly the Mississippi basin and the North Sea drainages. Deposition of oxidized nitrogen, primarily of industrial origin, is the major control over river nitrogen export in some regions such as the northeastern U.S. Using data from relatively pristine areas as an index of change, we estimate that riverine nitrogen fluxes in many of the temperate regions have increased from pre-industrial times by 2 to 20 fold, although some regions such as northern Canada are relatively unchanged. Fluxes from the most disturbed region, the North Sea drainages, have increased by 6 to 20 fold. Fluxes from the Amazon basin are also at least 2 to 5 fold greater than estimated fluxes from undisturbed temperate-zone regions, despite low population density and low inputs of anthropogenic nitrogen to the region. This suggests that natural riverine nitrogen fluxes in the tropics may be significantly greater than in the temperate zone. However, deforestation may be contributing to the tropical fluxes. In either case, projected increases in fertilizer use and atmospheric deposition in the coming decades are likely to cause dramatic increases in nitrogen loading to many tropical river systems.

Biogeochemistry↗

USGS2002

Nitrogen fixation in biological soil crusts from southeast Utah, USA

Biological soil crusts can be the dominant source of N for arid land ecosystems. We measured potential N fixation rates biweekly for 2 years, using three types of soil crusts: (1) crusts whose directly counted cells were >98% Microcoleus vaginatus (light crusts); (2) crusts dominated by M. vaginatus , but with 20% or more of the directly counted cells represented by Nostoc commune and Scytonema myochrous (dark crusts); and (3) the soil lichen Collema sp. At all observation times, Collema had higher nitrogenase activity (NA) than dark crusts, which had higher NA than light crusts, indicating that species composition is critical when estimating N inputs. In addition, all three types of crusts generally responded in a similar fashion to climate conditions. Without precipitation within a week of collection, no NA was recorded, regardless of other conditions being favorable. Low (<1°C) and high (>26°C) temperatures precluded NA, even if soils were moist. If rain or snow melt had occurred 3 or less days before collection, NA levels were highly correlated with daily average temperatures of the previous 3 days ( r 2 =0.93 for Collema crusts; r 2 =0.86 for dark crusts and r 2 =0.83 for light crusts) for temperatures between 1°C and 26°C. If a precipitation event followed a long dry period, NA levels were lower than if collection followed a time when soils were wet for extended periods (e.g., winter). Using a combination of data from a recording weather datalogger, time-domain reflectometry, manual dry-down curves, and N fixation rates at different temperatures, annual N input from the different crust types was estimated. Annual N input from dark crusts found at relatively undisturbed sites was estimated at 9 kg ha –1 year –1 . With 20% cover of the N-fixing soil lichen Collema , inputs are estimated at 13 kg ha –1 year –1 . N input from light crusts, generally indicating soil surface disturbance, was estimated at 1.4 kg ha –1 year –1 . The rates in light crusts are expected to be highly variable, as disturbance history will determine cyanobacterial biomass and therefore N fixation rates.

Biology and Fertility of Soils↗

USGS2011

Spatial interpolation schemes of daily precipitation for hydrologic modeling

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.

Colorado, Georgia↗

USGS2012

The interactive effects of excess reactive nitrogen and climate change on aquatic ecosystems and water resources of the United States

Nearly all freshwaters and coastal zones of the US are degraded from inputs of excess reactive nitrogen (Nr), sources of which are runoff, atmospheric N deposition, and imported food and feed. Some major adverse effects include harmful algal blooms, hypoxia of fresh and coastal waters, ocean acidification, long-term harm to human health, and increased emissions of greenhouse gases. Nitrogen fluxes to coastal areas and emissions of nitrous oxide from waters have increased in response to N inputs. Denitrification and sedimentation of organic N to sediments are important processes that divert N from downstream transport. Aquatic ecosystems are particularly important denitrification hotspots. Carbon storage in sediments is enhanced by Nr, but whether carbon is permanently buried is unknown. The effect of climate change on N transport and processing in fresh and coastal waters will be felt most strongly through changes to the hydrologic cycle, whereas N loading is mostly climate-independent. Alterations in precipitation amount and dynamics will alter runoff, thereby influencing both rates of Nr inputs to aquatic ecosystems and groundwater and the water residence times that affect Nr removal within aquatic systems. Both infrastructure and climate change alter the landscape connectivity and hydrologic residence time that are essential to denitrification. While Nr inputs to and removal rates from aquatic systems are influenced by climate and management, reduction of N inputs from their source will be the most effective means to prevent or to minimize environmental and economic impacts of excess Nr to the nation’s water resources.

Biogeochemistry↗

USGS2013

Shifts in controls on the temporal coherence of throughfall chemical flux in Acadia National Park, Maine, USA

Major ion and mercury (Hg) inputs to terrestrial ecosystems include both wet and dry deposition (total deposition). Estimating total deposition to sensitive receptor sites is hampered by limited information regarding its spatial heterogeneity and seasonality. We used measurements of throughfall flux, which includes atmospheric inputs to forests and the net effects of canopy leaching or uptake, for ten major ions and Hg collected during 35 time periods in 1999–2005 at over 70 sites within Acadia National Park, Maine to (1) quantify coherence in temporal dynamics of seasonal throughfall deposition and (2) examine controls on these patterns at multiple scales. We quantified temporal coherence as the correlation between all possible site pairs for each solute on a seasonal basis. In the summer growing season and autumn, coherence among pairs of sites with similar vegetation was stronger than for site-pairs that differed in vegetation suggesting that interaction with the canopy and leaching of solutes differed in coniferous, deciduous, mixed, and shrub or open canopy sites. The spatial pattern in throughfall hydrologic inputs across Acadia National Park was more variable during the winter snow season, suggesting that snow re-distribution affects net hydrologic input, which consequently affects chemical flux. Sea-salt corrected calcium concentrations identified a shift in air mass sources from maritime in winter to the continental industrial corridor in summer. Our results suggest that the spatial pattern of throughfall hydrologic flux, dominant seasonal air mass source, and relationship with vegetation in winter differ from the spatial pattern of throughfall flux in these solutes in summer and autumn. The coherence approach applied here made clear the strong influence of spatial heterogeneity in throughfall hydrologic inputs and a maritime air mass source on winter patterns of throughfall flux. By contrast, vegetation type was the most important influence on throughfall chemical flux in summer and autumn.

Maine↗

USGS2004

The springs of Lake Pátzcuaro: chemistry, salt-balance, and implications for the water balance of the lake

Lake Pa??tzcuaro, the center of the ancient Tarascan civilization located in the Mexican altiplano west of the city of Morelia, has neither river input nor outflow. The relatively constant lake-salinity over the past centuries indicates the lake is in chemical steady state. Springs of the south shore constitute the primary visible input to the lake, so influx and discharge must be via sub-lacustrine ground water. The authors report on the chemistry and stable isotope composition of the springs, deeming them representative of ground-water input. The springs are dominated by Ca, Mg and Na, whereas the lake is dominated by Na. Combining these results with previously published precipitation/rainfall measurements on the lake, the authors calculate the chemical evolution from spring water to lake water, and also calculate a salt balance of the ground-water-lake system. Comparing Cl and ??18O compositions in the springs and lake water indicates that 75-80% of the spring water is lost evaporatively during evolution toward lake composition. During evaporation Ca and Mg are lost from the water by carbonate precipitation. Each liter of spring water discharging into the lake precipitates about 18.7 mg of CaCO3. Salt balance calculations indicate that ground water input to the lake is 85.9??106 m3/a and ground water discharge from the lake is 23.0??106 m3/a. Thus, the discharge is about 27% of the input, with the rest balanced by evaporation. A calculation of time to reach steady-state ab initio indicates that the Cl concentration of the present day lake would be reached in about 150 a. ?? 2004 Elsevier Ltd. All rights reserved.

Applied Geochemistry↗

USGS2019

A fuzzy logic approach for estimating recovery factors of miscible CO2-EOR projects in the United States

"Recovery factor (RF) is one of the most fundamental parameters that define engineering and economical success of any operational phase in oil and gas production. The effectiveness of the operation, e.g. CO2-EOR (enhanced oil recovery with carbon dioxide injection), is usually defined by multiplying the resultant recovery factor by the original oil in place. Moreover, investment decisions for such engineering projects are also performed based on predicted recovery factors. Despite its importance, though, it is not easy to predict recovery factors as they are affected by many factors including the type of the recovery process, reservoir type, fluid properties, reservoir heterogeneity, depth, thickness, to name a few. The usual method of estimating recovery factors is laboratory experiments or numerical modeling, each of which has their own limitations due to data requirements, boundary conditions and scale effects. In this work, a fuzzy inference system approach has been adopted to predict miscible CO2-EOR recovery factors of the major field applications in the United States with the premise that it can be used as a guidance tool for making decisions based on different inputs. The fuzzy system was build using a Mamdani-type fuzzy logic inference engine, and by using reservoir data compiled from different sources as inputs and recovery factors gathered from a literature survey. Due to the limited number of field cases that could be used for this purpose, 24 sets of applications were included in the study. Selected input variables were water saturation after waterflood (Sorw), well spacing, porosity, permeability, depth, net pay thickness, initial pressure, API gravity of oil, hydrocarbon pore volume CO2 injected, and reservoir lithology. The type of membership functions were decided based on the system’s predictive performance. The model showed reasonable predictive capability for the field observations of recovery factor despite the complexity of this parameter. In addition, since the fuzzy solution was multi-dimensional due to multiple inputs, system behavior was used to demonstrate response of miscible CO2-EOR recovery factor to different inputs. "

Journal of Petroleum Science and Engineering↗