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At least 343 records · Page 19Linked to original sources

USGS2022

Water-budget accounting for tropical regions model (WATRMod) documentation

Regional groundwater recharge commonly is estimated using a threshold-type water-budget approach in which groundwater recharge is assumed to occur when water in the plant-root zone exceeds the soil’s moisture storage capacity. A water budget of the plant-soil system accounts for water inputs (rainfall, fog interception, irrigation, septic-system leachate, and other inputs), water outputs (runoff, evaporation, transpiration, and recharge), and changes in stored water during a specified time interval. Water budgets can be computed on any desired interval, including annual, monthly, daily, and subdaily intervals. In general, uncertainty in recharge estimates is expected to be lower using daily or subdaily intervals relative to monthly and annual intervals. Average recharge rates computed over a period of a year or multiple years are commonly determined from water budgets computed using a daily computation interval capable of capturing rainfall and land-cover changes during the period. This report documents the Water-budget Accounting for Tropical Regions Model, or WATRMod, code that can be used to estimate spatially variable, daily water-budget components in tropical-island and other appropriate settings. The purpose of this report is to provide descriptions of WATRMod’s (1) approach to computing a daily water budget, (2) represented processes, (3) limitations, and (4) execution procedure, input requirements, output files, and example files. The model computes a daily water budget for each hydrologically independent subarea within the overall study area. A subarea is defined by its climatic, soil, land-cover, and human-related (for example, adding irrigation or other water) characteristics. The water-budget model can represent processes including rainfall, fog interception, irrigation, septic-system leachate, direct recharge that bypasses the plant-soil system, runoff, canopy evaporation in forested areas, evapotranspiration, and groundwater recharge. The water-budget model can represent either one of the following different accounting orders: (1) accounting for loss of water by evapotranspiration before accounting for recharge, and (2) accounting for recharge before accounting for evapotranspiration. WATRMod’s limitations include: (1) uncharacterized, subdaily transient changes in water inputs and outputs from the plant-soil system, (2) unrepresented precipitation in the form of snow and sublimation, and (3) routing runoff from one subarea to an adjacent subarea that is not directly represented.

Hawaii↗

USGS2022

Pharmaceuticals and personal care products in passive samplers at seven coastal sites off West Maui, Hawaiʻi:

Passive membrane samplers—semipermeable membrane devices and polar organic chemical integrative samplers—were deployed for 22 continuous days at 7 sites along the West Maui, Hawaiʻi, coastline in February and March 2017 to assess organic contaminants at shallow coral reef ecosystems from diverse upstream inputs. The distribution of organic compounds observed at these coastal sites showed considerable variability; high concentrations of microbially sourced organic compounds observed at all sites, with pentadecane as the predominant normal alkane, showed the relative importance of marine and microbial organic matter to the coastal carbon pool. Pharmaceuticals and personal care products, as well as flame retardants, were also detected at all sites. Of the seven sites sampled, the Kahekili Beach Park site had the highest number of unique contaminants and the Honokōwai Stream site had the highest concentrations of compounds. Two individual compounds, a flame retardant and a fragrance, were ubiquitous across the studied West Maui reefs, including at the least-developed site. A direct correlation to upstream land-use practices or legacy agricultural inputs was not readily observed since polychlorinated biphenyls, pesticides, herbicides, or insecticides were not detected. Results provide a snapshot of relative contaminant abundances as well as inputs to select nearshore environments along the West Maui coastline captured during the 2017 wet season, which was drier than expected. These data can be useful for understanding the range of stressors potentially affecting nearshore ecosystems, such as groundwater inputs and watershed runoff.

Hawaii↗

USGS1992

Modifications of the U.S. Geological Survey modular, finite-difference, ground-water flow model to read and write geographic information system files

This report documents modifications to the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model, commonly called MODFLOW, so that it can read and write files used by a geographic information system (GIS). The modified model program is called MODFLOWARC. Simulation programs such as MODFLOW generally require large amounts of input data and produce large amounts of output data. Viewing data graphically, generating head contours, and creating or editing model data arrays such as hydraulic conductivity are examples of tasks that currently are performed either by the use of independent software packages or by tedious manual editing, manipulating, and transferring data. Programs such as GIS programs are commonly used to facilitate preparation of the model input data and analyze model output data; however, auxiliary programs are frequently required to translate data between programs. Data translations are required when different programs use different data formats. Thus, the user might use GIS techniques to create model input data, run a translation program to convert input data into a format compatible with the ground-water flow model, run the model, run a translation program to convert the model output into the correct format for GIS, and use GIS to display and analyze this output. MODFLOWARC, avoids the two translation steps and transfers data directly to and from the ground-water-flow model. This report documents the design and use of MODFLOWARC and includes instructions for data input/output of the Basic, Block-centered flow, River, Recharge, Well, Drain, Evapotranspiration, General-head boundary, and Streamflow-routing packages. The modification to MODFLOW and the Streamflow-Routing package was minimized. Flow charts and computer-program code describe the modifications to the original computer codes for each of these packages. Appendix A contains a discussion on the operation of MODFLOWARC using a sample problem.

Open-File Report↗

USGS1995

Seismic Sources and Recurrence Rates as Adopted by USGS Staff for the Production of the 1982 and 1990 Probabilistic Ground Motion Maps for Alaska and the Conterminous United States

The construction of a probabilistic ground-motion hazard map for a region follows a sequence of analyses beginning with the selection of an earthquake catalog and ending with the mapping of calculated probabilistic ground-motion values (Hanson and others, 1992). An integral part of this process is the creation of sources used for the calculation of earthquake recurrence rates and ground motions. These sources consist of areas and lines that are representative of geologic or tectonic features and faults. After the design of the sources, it is necessary to arrange the coordinate points in a particular order compatible with the input format for the SEISRISK-III program (Bender and Perkins, 1987). Source zones are usually modeled as a point-rupture source. Where applicable, linear rupture sources are modeled with articulated lines, representing known faults, or a field of parallel lines, representing a generalized distribution of hypothetical faults. Based on the distribution of earthquakes throughout the individual source zones (or a collection of several sources), earthquake recurrence rates are computed for each of the sources, and a minimum and maximum magnitude is assigned. Over a period of time from 1978 to 1980 several conferences were held by the USGS to solicit information on regions of the United States for the purpose of creating source zones for computation of probabilistic ground motions (Thenhaus, 1983). As a result of these regional meetings and previous work in the Pacific Northwest, (Perkins and others, 1980), California continental shelf, (Thenhaus and others, 1980), and the Eastern outer continental shelf, (Perkins and others, 1979) a consensus set of source zones was agreed upon and subsequently used to produce a national ground motion hazard map for the United States (Algermissen and others, 1982). In this report and on the accompanying disk we provide a complete list of source areas and line sources as used for the 1982 and later 1990 seismic hazard maps for the conterminous U.S. and Alaska. These source zones are represented in the input form required for the hazard program SEISRISK-III, and they include the attenuation table and several other input parameter lines normally found at the beginning of an input data set for SEISRISK-III.

Open-File Report↗

USGS2007

Data sources and compilation: Chapter 27 in Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California

Geologic, production, and exploration/discovery-history data are used by the U.S. Geological Survey to aid in the assessment of petroleum resources. These data, as well as the broad knowledge and experience of the assessing geologists, are synthesized to provide, for each assessment unit, geologic and exploration models upon which estimates are made of the number and sizes of undiscovered accumulations for conventional assessment units or number and total recoverable volumes of untested cells for continuous assessment units (input data for resource calculations). Quantified geologic information and trends in production and exploration/discovery-history data with respect to time and exploration effort provide guides for the estimating parameters of variables recorded on the input-data forms (input data) used to calculate petroleum resources. An Assessment Review Team reviews proposed geologic and exploration models and input data for each assessment unit in formal assessment meetings. The Assessment Review Team maintains the accuracy and consistency of the assessment procedure during the formal assessment meetings.

Professional Paper↗

USGS2022

Multi-decadal sandbar response to flow management downstream from a large dam—The Glen Canyon Dam on the Colorado River in Marble and Grand Canyons, Arizona

Sandbars are an important resource in the Colorado River corridor in Marble and Grand Canyons, Arizona, downstream from Glen Canyon Dam. Sandbars provide aquatic and riparian habitat and are used as campsites by river runners and hikers. The study area is the Colorado River between Glen Canyon Dam and Diamond Creek, which is about 388 kilometers (241 miles) downstream from the dam. Closure of Glen Canyon Dam in 1963 and subsequent flow regulation reduced the sediment supply, limited the magnitude and frequency of floods, and increased the magnitude of baseflows. The result has been widespread erosion of sandbars and expansion of native and non-native vegetation on previously bare sand deposits in this debris-fan dominated canyon river. This study reports on the on-going long-term measurement program of Northern Arizona University, initiated in 1990 with the Bureau of Reclamation, and now also with the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center. We report on all sandbar measurements made between 1990 and 2020 to demonstrate the multi-decadal response of the sandbar monitoring sites resulting from flow regulation by Glen Canyon Dam. Because only one study site is located in Glen Canyon, the 25 kilometer (15.5 miles) reach just below Glen Canyon Dam, analyses of sandbar response are only made for the next two canyon segments in the down-river direction, Marble Canyon (388 kilometers [99 miles]) and Grand Canyon (265 kilometers [165 miles]), respectively, where the majority of study sites are located. We show that a majority of monitoring sites increased in volume during a period of frequent controlled floods intended to rebuild sandbars. In the period from 2004 to 2020, which included seven controlled floods, a median discharge of 350 cubic meters per second (m 3 /s), and greater than average tributary sand inputs in more than half of the years, net deposition occurred at 86 percent of long-term monitoring sites. This period was preceded by a period of net erosion (1990–2003) when there was one controlled flood greater than the nominal powerplant capacity of 940 m 3 /s. During this period the median discharge from Glen Canyon Dam was 376 m 3 /s and greater than average sand inputs occurred in only 36 percent of those years. At the end of the monitoring period in 2020, 61 percent of the study sites measured since 1990 underwent a net increase in sand volume. For the entire 31-year period, these trends were statistically significant for all six sandbar types studied, indicating that increased frequency of controlled flooding maintained sandbar volume at the majority of sites monitored. These floods, also referred to as high-flow experiments (HFEs), are part of a decision-making protocol approved in 2012 for coordinating dam releases timed to occur following large sand inputs to the Colorado River by a major tributary. These findings are based on digital elevation models (DEMs) derived from approximately (~)1,800 repeat surveys of sandbar and channel bed topography made annually, or more frequently, at the 45 long-term monitoring sites, of which 31 have been monitored since 1990 and 14 were added between 1990 and 2008. This large collection of monitoring sites comprises just 7 to 9 percent of all sandbars in Marble and Grand Canyons, respectively. Nevertheless, when compared with measurements of a larger sample, these sites provide consistent characterization of average sandbar response, despite the local variability in channel and debris fan geometry. We use sand volume and normalized sand volume for tracking geomorphic changes of sandbars, because these metrics are sensitive to both changes in sandbar area and sandbar elevation. Based on checkpoint comparisons and repeat measurements, DEM elevation uncertainty was determined to be ±0.05 meter (m) and this uncertainty was used in a spatially uniform estimate of volume uncertainty. We find that the magnitudes of the topographic changes were substantially greater than the measurement uncertainty. Sandbars of similar type throughout both Marble and Grand Canyons have responded similarly during the period of the HFE protocol, despite variations in sand supply and longitudinal extent of those inputs. It should be noted that tributary-supplied sand to Glen Canyon is negligible, much of the riverbed is now armored with cobbles, and the channel bed degradation is irreversible in the current flow and sediment supply regime. Because all these HFEs have been conducted during periods of sediment enrichment, other factors such as vegetation and geomorphic setting are likely the primary causes of variation among the monitoring sites. A larger percentage of the sandbar population, predominantly located in narrow reaches where stage changes are greater, is composed of sandbar types that remain dynamic and consistently aggrade during HFEs. In contrast, wide reaches of the river corridor where stage change is not as great are characterized by sandbars that have been stabilized by vegetation and progressive aggradation during floods. In the former case, a majority of sandbars are likely to remain dynamic, requiring continued use of HFEs to achieve desired management goals. In the latter case, HFEs can do no better than replace the sediment eroded during normal dam operation between high-flow events, as they become less effective because of a diminishing amount of accommodation space available for deposition. Long-term sandbar trajectory and the continued effectiveness of HFEs are related to the differential vegetation establishment at each bar type. Future sandbar monitoring may need to consider the effects of riparian vegetation removal.

Arizona↗

USGS2012

Characterization of major-ion chemistry and nutrients in headwater streams along the Appalachian National Scenic Trail and within adjacent watersheds, Maine to Georgia

An inventory of water-quality data on field parameters, major ions, and nutrients provided a summary of water quality in headwater (first- and second-order) streams within watersheds along the Appalachian National Scenic Trail (Appalachian Trail). Data from 1,817 sampling sites in 831 catchments were used for the water-quality summary. Catchment delineations from NHDPlus were used as the fundamental geographic units for this project. Criteria used to evaluate sampling sites for inclusion were based on selected physical attributes of the catchments adjacent to the Appalachian Trail, including stream elevation, percentage of developed land cover, and percentage of agricultural land cover. The headwater streams of the Appalachian Trail are generally dilute waters, with low pH, low acid neutralizing capacity (ANC), and low concentrations of nutrients. The median pH value was slightly acidic at 6.7; the median specific conductance value was 23.6 microsiemens per centimeter, and the median ANC value was 98.7 milliequivalents per liter (μeq/L). Median concentrations of cations (calcium, magnesium, sodium, and potassium) were each less than 1.5 milligrams per liter (mg/L), and median concentrations of anions (bicarbonate, chloride, fluoride, sulfate, and nitrate) were less than 10 mg/L. Differences in water-quality constituent levels along the Appalachian Trail may be related to elevation, atmospheric deposition, geology, and land cover. Spatial variations were summarized by ecological sections (ecosections) developed by the U.S. Forest Service. Specific conductance, pH, ANC, and concentrations of major ions (calcium, chloride, magnesium, sodium, and sulfate) were all negatively correlated with elevation. The highest elevation ecosections (White Mountains, Blue Ridge Mountains, and Allegheny Mountains) had the lowest pH, ANC, and concentrations of major ions. The lowest elevation ecosections (Lower New England and Hudson Valley) generally had the highest pH, ANC, and concentrations of major ions. The geology in discrete portions of these two ecosections was classified as containing carbonate minerals which has likely influenced the chemical character of the streamwater. Specific conductance, pH, ANC, and concentrations of major ions (calcium, chloride, magnesium, sodium, and sulfate) were all positively correlated with percentages of developed and agricultural land uses at the lower elevations of the central region of the Appalachian Trail (including the Green-Taconic-Berkshire Mountains, Lower New England, Hudson Valley, and Northern Ridge and Valley ecosections). The distinctly different chemical character of the streams in the central sections of the Appalachian Trail is likely related to the lower elevations, the presence of carbonate minerals in the geology, higher percentages of developed and agricultural land uses, and possibly the higher inputs of sulfate and nitrate from atmospheric deposition. Acid deposition of sulfate and nitrate are important influences on the acid-base chemistry of the surface waters of the Appalachian Trail. Atmospheric deposition estimates are consistently high (more than 18 kilograms per hectare (kg/ha) for sulfate, and more than 16 kg/ha for nitrate) at both the highest and lowest elevations. However, the lowest elevation (Green-Taconic-Berkshire Mountains, Lower New England, Hudson Valley, Northern Glaciated Allegheny Plateau, and Northern Ridge and Valley ecosections) included the largest spatial area of sustained high estimates of atmospheric deposition. Calcium-bicarbonate was the most frequently calculated water type in the Lower New England and Hudson Valley ecosections. In the northern and southern sections of the Appalachian Trail mix-cation water types were most prevalent and sulfate was the predominate anion. The predominance of the sulfate anion in the surface waters of the northern and southern ecosections likely reflects the influence of sulfate deposition. Although the central portion of the Appalachian Trail has the largest spatial area of high atmospheric acid deposition, the lower ionic strength waters in the northern and southern ecosections of the Appalachian Trail may have been more adversely affected by acid deposition. The low ionic strength of the streams in the White Mountains, Blue Ridge Mountains, and Allegheny Mountains ecosections makes parts of these regions susceptible to seasonal or event-driven episodic acidification, which can be detrimental to health of aquatic and terrestrial ecosystems. Median catchment ANC values were classified into three groups - acidic, sensitive, and insensitive. The White Mountains, Blue Ridge Mountains, and Allegheny Mountains ecosections included the highest frequency of catchments classified as acidic or sensitive. More than 56 percent of the catchments from the White Mountains ecosection were classified as sensitive to acidic inputs. In the Blue Ridge ecosection, 1.6 percent of the catchments were classified as acidic, and 38.2 percent of the catchments were classified as sensitive to acidic inputs. In the Allegheny Mountains ecosection, 17.6 percent of the catchments were classified as acidic, and 29.4 percent of the catchments were classified as sensitive to acidic inputs. Median concentrations of nitrogen species were less than 0.4 mg/L, and median concentrations of total phosphorus were less than 0.02 mg/L along the Appalachian Trail. A comparison of median catchment concentrations of nutrients to estimated national background concentrations demonstrated that concentrations along the Appalachian Trail are generally lower. A comparison of median concentrations of total nitrogen and total phosphorus to the U.S. Environmental Protection Agency's (USEPA) nutrient criteria for the Eastern U.S. ecoregions showed that the concentrations of total nitrogen in the northern section of the Appalachian Trail were generally higher than the USEPA criterion. Similarly, median concentrations of total phosphorus in the southern regions of the Appalachian Trail were approximately twice as high as USEPA criteria. Sections of the Appalachian Trail are adjacent to modest amounts of agricultural and developed land areas. These nonforested land areas may be contributing to the percentage of catchments in which concentrations of total nitrogen and total phosphorus are higher than USEPA nutrient ecoregion criteria.

Connecticut, Georgia, Maine, Massachusetts, Maryla↗

USGS2017

Groundwater levels, geochemistry, and water budget of the Tsala Apopka Lake system, west-central Florida, 2004–12

Tsala Apopka Lake is a complex system of lakes and wetlands, with intervening uplands, located in Citrus County in west-central Florida. It is located within the 2,100 square mile watershed of the Withlacoochee River, which drains north and northwest towards the Gulf of Mexico. The lake system is managed by the Southwest Florida Water Management District as three distinct “pools,” which from upstream to downstream are referred to as the Floral City Pool, Inverness Pool, and Hernando Pool. Each pool contains a mixture of deep-water lakes that remain wet year round, ephemeral (seasonal) ponds and wetlands, and dry uplands. Many of the major deep-water lakes are interconnected by canals. Flow from the Withlacoochee River, when conditions allow, can be diverted into the lake system. Flow thorough the canals can be used to control the distribution of water between the three pools. Flow in the canals is controlled using structures, such as gates and weirs. Hydrogeologic units in the study area include a surficial aquifer consisting of Quaternary-age sediments, a discontinuous intermediate confining unit consisting of Miocene- and Pliocene-age sediments, and the underlying Upper Floridan aquifer, which consists of Eocene- and Oligocene-age carbonates. The fine-grained quartz sands that constitute the surficial aquifer are generally thin, typically less than 25 feet thick, within the vicinity of Tsala Apopka Lake. A thin, discontinuous, sandy clay layer forms the intermediate confining unit. The Upper Floridan aquifer is generally unconfined in the vicinity of Tsala Apopka Lake because the intermediate confining unit is discontinuous and breached by numerous karst features. In the study area, the Upper Floridan aquifer includes the upper Avon Park Formation and Ocala Limestone. The Ocala Limestone is the primary source of drinking water and spring flow in the area. The objectives of this study are to document the interaction of Tsala Apopka Lake, the surficial aquifer, and the Upper Floridan aquifer; and to estimate an annual water budget for each pool and for the entire lake system for 2004–12. The hydrologic interactions were evaluated using hydraulic head and geochemical data. Geochemical data, including major ion, isotope, and age-tracer data, were used to evaluate sources of water and to distinguish flow paths. Hydrologic connection of the surficial environment (lakes, ponds, wetlands, and the surficial aquifer) was quantified on the basis of a conceptualized annual water-budget model. The model included the change in surface water and groundwater storage, precipitation, evapotranspiration, surface-water inflow and outflow, and net groundwater exchange with the underlying Upper Floridan aquifer. The control volume for each pool extended to the base of the surficial aquifer and covered an area defined to exceed the maximum inundated area for each pool during 2004–12 by 0.5 foot. Net groundwater flow was computed as a lumped value and was either positive or negative, with a negative value indicating downward or lateral leakage from the control volume and a positive value indicating upward leakage to the control volume. The annual water budget for Tsala Apopka Lake was calculated using a combination of field observations and remotely sensed data for each of three pools and for the composite three pool area. A digital elevation model at a 5-foot grid spacing and bathymetric survey data were used to define the land-surface elevation and volume of each pool and to calculate the changes in inundated area with change in lake stage. Continuous lake-stage and groundwater-level data were used to define the change in storage for each pool. The rainfall data used in the water-budget calculations were based on daily radar reflectance data and measured rainfall from weather stations. Evapotranspiration was computed as a function of reference evapotranspiration, adjusted to actual evapotranspiration using a monthly land-cover coefficient (based on evapotranspiration measurements at stations located in representative landscapes). Surface-water inflows and outflows were determined using stage data collected at a series of streamgages installed primarily at the water-control structures. Discharge was measured under varying flow regimes and ratings were developed for the water-control structures. The discharge data collected during the study period were used to calibrate a surface-water flow model for 2004–12. Flows predicted by the model were used in the water-budget analysis. Net groundwater flow was determined as the residual term in the water-budget equation. The results of the water-budget analysis indicate that rainfall was the largest input of water to Tsala Apopka Lake, whereas evapotranspiration was the largest output. For the 2004–12 analysis period, surface-water inflow accounted for 11 percent of the inputs, net groundwater inflow accounted for 1 percent of inputs (annual periods with positive net groundwater flow were included as inputs, while annual periods with negative net groundwater flow were counted as outputs), and rainfall accounted for the remaining 88 percent. For the same period, the outputs consisted of 2 percent surface-water outflow, 12 percent net groundwater outflow, and 86 percent evapotranspiration. Net groundwater inflows and surface-water/groundwater storage were negligible during the water-budget period but could be important components of the budget in individual years. The net groundwater flow was negative (downward) for 8 out of the 9 years modeled (2004–12), indicating that the Tsala Apopka Lake study area was primarily a recharge area for the underlying Upper Floridan aquifer during this time period. Groundwater-level elevation in paired wells (adjacent wells completed in the surficial aquifer and Upper Floridan aquifer) typically was higher in the surficial aquifer than the Upper Floridan aquifer. However, hydraulic head data indicate that the surficial aquifer often has discharge potential to the surface-water system, especially in the low lying areas near the major lakes. Surficial-aquifer water levels were often higher than lake stages, especially during wet periods, which is likely an indication of aquifer-to-lake seepage in these areas. East of the major lakes, hydraulic head data were nearly equal in the surficial aquifer and Upper Floridan aquifer, which is an indication that the Upper Floridan aquifer is unconfined. Based on deuterium and oxygen stable isotope data collected in December 2011 and December 2012, there was no evidence of recharge to the Upper Floridan aquifer from the wetlands east of the major lakes; aquifer isotopic ratios did not indicate an enriched source, which is typical of lake and wetland sources. West of the major lakes, there was evidence of enriched isotopic ratios in water samples from the Upper Floridan aquifer. Differences in hydraulic head at paired wells in the surficial aquifer and Upper Floridan aquifer indicated that the surficial aquifer has the potential to recharge the Upper Floridan aquifer in the western part of the pools and west of the major lakes.

Florida↗

USGS2020

Spatially referenced models of streamflow and nitrogen, phosphorus, and suspended-sediment loads in streams of the midwestern United States

In this report, SPAtially Referenced Regression On Watershed attributes (SPARROW) models developed to describe long-term (2000–14) mean-annual streamflow, total nitrogen (TN), total phosphorus (TP), and suspended-sediment (SS) transport in streams of the Midwestern part of the United States (the Mississippi River, Great Lakes, and Red River of the North Basins) are described. The nutrient and suspended-sediment models have a base year of 2012, which means they were developed based on source inputs and management practices similar to those existing during or near 2012 and average hydrological conditions detrended to 2012 (2000–14), whereas the streamflow model has base years of 2000–14, which means it was developed based on the average input precipitation minus actual evapotranspiration from 2000 to 2014. In developing the models, several updates and improvements were made to the data inputs and statistical approaches used to calibrate/develop the models from those used in the previous 2002 SPARROW models. The 2012 SPARROW models were constructed using a higher resolution stream network, which resulted in a mean catchment size of 2.7 square kilometers compared to 480 square kilometers in the 2002 models; more detailed and updated wastewater treatment plant contribution estimates; inputs from background phosphorus sources that were not included in the 2002 model; and more accurate loads for calibration that were computed using a modified Beale ratio-estimator technique whenever no trend in load was determined. Statistical approaches were added to compensate for the unequal effect of each monitoring site during the calibration process by adjusting for the fraction of the basin included in other upstream monitored sites (nested share) and thinning the calibration sites if a negative statistical correlation between nearby sites was determined. Results from 2012 SPARROW models describe how much of each water, TN, TP, and SS source was delivered to the stream network, and the major landscape factors that affected their delivery. Atmospheric deposition and natural (background) sources of TN and TP, respectively, were the dominant sources in anthropogenically unaffected areas (especially in the Rocky Mountains and north-central areas of the Midwest), whereas fertilizers, manure, and fixation were dominant sources in agricultural areas, especially in the Corn Belt and near the Mississippi River. Urban sources of TN and TP were typically localized, but they were still important for some large areas, especially the Lake Erie Basin. All of the land-to-water delivery variables in the nutrient and sediment SPARROW models, such as runoff, soil erodibility, basin slope, and the amount of tile drains, are commonly included in process-driven models. In the SPARROW TN and TP models, best management practices (BMPs) reduced the delivery of these nutrients to streams. Long-term mean-annual flows and nutrient and sediment loads were simulated in streams throughout the Midwest. The simulated flows from the SPARROW flow model were used in the SPARROW TN, TP, and SS models to help describe nutrient and sediment transport from the watershed and through the stream network. Outputs from the TN, TP, and SS models describe loads and yields of these constituents throughout the Midwest, and from major drainage basins throughout the Midwest. Highest TN, TP, and SS yields and delivered yields were from the Lake Erie, Ohio River, Upper Mississippi River, and Lower Mississippi River Basins, whereas lowest yields were spread over most other areas. Losses during downstream delivery resulted in part of the TN, TP, and SS that reach the stream network not reaching the downstream receiving bodies: 14, 15, and 28 percent of the TN, TP, and SS, respectively, are lost during delivery to the Great Lakes and 19, 23, and 52 percent of the TN, TP, and SS, respectively, are lost during delivery to the Gulf of Mexico. The largest losses of nutrients and sediments during transport were in the Missouri and Arkansas River Basins. Information from these SPARROW models can help guide nutrient and sediment reduction strategies throughout the Midwest. Model results provide information on what may be the most appropriate general type of actions to reduce total loading by describing the relative importance of each source, and where to most efficiently place the efforts to reduce loading by describing the distribution of nutrient and sediment loading. By implementing management efforts addressing the major sources of the loads in areas contributing the highest loads, it may be possible to reduce nutrient loading throughout the Mississippi River Basin and thus reduce the size of the hypoxic zone in the Gulf of Mexico; reduce nutrient loading into lakes, and thus reduce the occurrence of harmful algal blooms; and reduce sediment losses, and thus improve the benthic habitat in streams and rivers throughout the Midwest.

Scientific Investigations Report↗

USGS2021

Simulation of groundwater budgets and travel times for watersheds on the north shore of Long Island Sound, with implications for nitrogen-transport studies

Aquatic systems in and around the Long Island Sound (LIS) provide a variety of ecological and economic benefits, but in some areas of the LIS, aquatic ecosystems have become degraded by excess nitrogen. A substantial fraction of the nitrogen inputs to the LIS are transported through the groundwater-flow system. Because groundwater travel times in surficial aquifers can exceed 100 years, multiyear lags are introduced between inputs at the water table in recharge areas and discharge to inland or coastal receiving waters. The U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection and the U.S. Environmental Protection Agency’s Long Island Sound Study, developed a steady-state groundwater model of the watersheds draining from the northern shore of the LIS for the purpose of calculating groundwater budgets and travel times to coastal waters. The model was developed by using the MODFLOW–NWT software and existing spatial data on aquifers, river networks, land-surface altitudes, land cover, groundwater recharge, and water use. Coastal waters were delineated on the basis of the National Wetland Inventory; all non-coastal waters were collectively termed “inland waters.” A coarse-resolution model was calibrated by using the PEST++ software, long-term records of water levels in 65 wells, stream altitudes from 477 streams, base-flow records for 14 streamgages that are relatively unaffected by withdrawals, and error metrics based on incorrectly simulated flooding and incorrectly simulated dry streams. The calibrated values were used in a fine-resolution model in which the mean absolute residuals were 4.5 meters for groundwater levels, 1.3 meters for stream altitudes, and 7,200 cubic meters per day (2.9 cubic feet per second) for base flow. About 89 percent of the terrestrial cells were correctly simulated with the water table below land surface, and nearly 90 percent of the cells representing streams were correctly simulated as having the water table above the stream bottom. Together, these metrics suggest that this model is robust for simulating regional-scale groundwater patterns. Simulated groundwater budgets were compiled for the entire study area, for each HUC12 (Hydrologic Unit Code no. 12) watershed and its adjacent coastal waters, if applicable, within the study area, and for 14 coastal-embayment watersheds. Most groundwater (90.6 percent of inflows) discharged to inland waters, with smaller fractions to coastal waters (7.0 percent) and well withdrawals (2.4 percent). When computed for HUC12 watersheds with coastal discharge, the portions of groundwater discharging to coastal waters ranged from 0.02 to 66 percent of groundwater outflows, with a median of 13 percent. Within priority-embayment watersheds, the portions of groundwater discharging to coastal waters ranged from 2 to 56 percent, with a median of 15 percent. Groundwater travel times also were simulated for the entire study area, for each HUC12 watershed and its adjacent coastal waters, if applicable, within the study area and for 14 priority coastal embayments. Within the entire study area, the median groundwater travel time was 1.9 years, with an interquartile range of 0.1 to 5.9 years. Sensitivity analysis of groundwater travel times within a subbasin in the study area indicates that the travel times are a function of the grid resolution, with coarser grids resulting in shorter median travel times. Travel times for groundwater discharging to coastal waters were similar to travel times for groundwater discharging to inland waters, with a median of 1.9 years. Median travel times for the HUC12 watersheds ranged from 0.9 to 53.5 years, with a median of 1.8 years. Among HUC12 watersheds that include coastal areas, travel times for groundwater discharging to coastal waters ranged from less than 1 to 61.6 years, with a median of 2.8 years. The HUC12 watersheds with the longest simulated travel times were in the urban area near New York City where the model performance is less accurate. Median travel times for groundwater discharging to coastal waters within the priority-embayment watersheds ranged from less than 1 to 18.6 years, with a median of 2.3 years. A more focused analysis was conducted for the Niantic River watershed to demonstrate the applicability of the regional model to local-scale nitrogen-transport analyses by using nitrogen-input and -attenuation rates from literature sources. Nitrogen inputs were estimated by using land-cover-based loading factors, and attenuation was estimated by using attenuation factors based on geologic zones and soil properties. Based on this analysis, groundwater transports an estimated 22,000 kilograms of nitrogen per year (2.9 kilograms of nitrogen per hectare per year) to streams, rivers, and coastal waters within the Niantic River watershed. Approximately 36 percent of discharging nitrogen is from atmospheric-deposition sources, 38 percent is from fertilizers, and 26 percent is from septic systems. Most of the groundwater-transported nitrogen (88 percent) discharges first to streams and rivers, with only 12 percent discharging directly to coastal waters. Travel times for groundwater-transported nitrogen ranged from less than 1 day to more than 100 years, with a median of 1.6 years.

Connecticut, New York, Rhode Island↗

USGS2005

UCODE_2005 and six other computer codes for universal sensitivity analysis, calibration, and uncertainty evaluation constructed using the JUPITER API

This report documents the computer codes UCODE_2005 and six post-processors. Together the codes can be used with existing process models to perform sensitivity analysis, data needs assessment, calibration, prediction, and uncertainty analysis. Any process model or set of models can be used; the only requirements are that models have numerical (ASCII or text only) input and output files, that the numbers in these files have sufficient significant digits, that all required models can be run from a single batch file or script, and that simulated values are continuous functions of the parameter values. Process models can include pre-processors and post-processors as well as one or more models related to the processes of interest (physical, chemical, and so on), making UCODE_2005 extremely powerful. An estimated parameter can be a quantity that appears in the input files of the process model(s), or a quantity used in an equation that produces a value that appears in the input files. In the latter situation, the equation is user-defined. UCODE_2005 can compare observations and simulated equivalents. The simulated equivalents can be any simulated value written in the process-model output files or can be calculated from simulated values with user-defined equations. The quantities can be model results, or dependent variables. For example, for ground-water models they can be heads, flows, concentrations, and so on. Prior, or direct, information on estimated parameters also can be considered. Statistics are calculated to quantify the comparison of observations and simulated equivalents, including a weighted least-squares objective function. In addition, UCODE_2005 can be used fruitfully in model calibration through its sensitivity analysis capabilities and its ability to estimate parameter values that result in the best possible fit to the observations. Parameters are estimated using nonlinear regression: a weighted least-squares objective function is minimized with respect to the parameter values using a modified Gauss-Newton method or a double-dogleg technique. Sensitivities needed for the method can be read from files produced by process models that can calculate sensitivities, such as MODFLOW-2000, or can be calculated by UCODE_2005 using a more general, but less accurate, forward- or central-difference perturbation technique. Problems resulting from inaccurate sensitivities and solutions related to the perturbation techniques are discussed in the report. Statistics are calculated and printed for use in (1) diagnosing inadequate data and identifying parameters that probably cannot be estimated; (2) evaluating estimated parameter values; and (3) evaluating how well the model represents the simulated processes. Results from UCODE_2005 and codes RESIDUAL_ANALYSIS and RESIDUAL_ANALYSIS_ADV can be used to evaluate how accurately the model represents the processes it simulates. Results from LINEAR_UNCERTAINTY can be used to quantify the uncertainty of model simulated values if the model is sufficiently linear. Results from MODEL_LINEARITY and MODEL_LINEARITY_ADV can be used to evaluate model linearity and, thereby, the accuracy of the LINEAR_UNCERTAINTY results. UCODE_2005 can also be used to calculate nonlinear confidence and predictions intervals, which quantify the uncertainty of model simulated values when the model is not linear. CORFAC_PLUS can be used to produce factors that allow intervals to account for model intrinsic nonlinearity and small-scale variations in system characteristics that are not explicitly accounted for in the model or the observation weighting. The six post-processing programs are independent of UCODE_2005 and can use the results of other programs that produce the required data-exchange files. UCODE_2005 and the other six codes are intended for use on any computer operating system. The programs consist of algorithms programmed in Fortran 90/95, which efficiently performs numerical calculations. The model runs required to obtain perturbation sensitivities can be performed using multiple processors. The programs are constructed in a modular fashion using JUPITER API conventions and modules. For example, the data-exchange files and input blocks are JUPITER API conventions and many of those used by UCODE_2005 are read or written by JUPITER API modules. UCODE-2005 includes capabilities likely to be required by many applications (programs) constructed using the JUPITER API, and can be used as a starting point for such programs.

Techniques and Methods↗

USGS2006

GoPhast: A graphical user interface for PHAST

GoPhast is a graphical user interface (GUI) for the USGS model PHAST. PHAST simulates multicomponent, reactive solute transport in three-dimensional, saturated, ground-water flow systems. PHAST can model both equilibrium and kinetic geochemical reactions. PHAST is derived from HST3D (flow and transport) and PHREEQC (geochemical calculations). The flow and transport calculations are restricted to constant fluid density and constant temperature. The complexity of the input required by PHAST makes manual construction of its input files tedious and error-prone. GoPhast streamlines the creation of the input file and helps reduce errors. GoPhast allows the user to define the spatial input for the PHAST flow and transport data file by drawing points, lines, or polygons on top, front, and side views of the model domain. These objects can have up to two associated formulas that define their extent perpendicular to the view plane, allowing the objects to be three-dimensional. Formulas are also used to specify the values of spatial data (data sets) both globally and for individual objects. Objects can be used to specify the values of data sets independent of the spatial and temporal discretization of the model. Thus, the grid and simulation periods for the model can be changed without respecifying spatial data pertaining to the hydrogeologic framework and boundary conditions. This report describes the operation of GoPhast and demonstrates its use with examples. GoPhast runs on Windows 2000, Windows XP, and Linux operating systems.

Techniques and Methods↗

USGS2008

User Guide and Documentation for Five MODFLOW Ground-Water Modeling Utility Programs

This report documents five utility programs designed for use in conjunction with ground-water flow models developed with the U.S. Geological Survey's MODFLOW ground-water modeling program. One program extracts calculated flow values from one model for use as input to another model. The other four programs extract model input or output arrays from one model and make them available in a form that can be used to generate an ArcGIS raster data set. The resulting raster data sets may be useful for visual display of the data or for further geographic data processing. The utility program GRID2GRIDFLOW reads a MODFLOW binary output file of cell-by-cell flow terms for one (source) model grid and converts the flow values to input flow values for a different (target) model grid. The spatial and temporal discretization of the two models may differ. The four other utilities extract selected 2-dimensional data arrays in MODFLOW input and output files and write them to text files that can be imported into an ArcGIS geographic information system raster format. These four utilities require that the model cells be square and aligned with the projected coordinate system in which the model grid is defined. The four raster-conversion utilities are * CBC2RASTER, which extracts selected stress-package flow data from a MODFLOW binary output file of cell-by-cell flows; * DIS2RASTER, which extracts cell-elevation data from a MODFLOW Discretization file; * MFBIN2RASTER, which extracts array data from a MODFLOW binary output file of head or drawdown; and * MULT2RASTER, which extracts array data from a MODFLOW Multiplier file.

Techniques and Methods↗

USGS2012

User guide for MODPATH version 6—A particle-tracking model for MODFLOW

MODPATH is a particle-tracking post-processing model that computes three-dimensional flow paths using output from groundwater flow simulations based on MODFLOW, the U.S. Geological Survey (USGS) finite-difference groundwater flow model. This report documents MODPATH version 6. Previous versions were documented in USGS Open-File Reports 89-381 and 94-464. The program uses a semianalytical particle-tracking scheme that allows an analytical expression of a particle's flow path to be obtained within each finite-difference grid cell. A particle's path is computed by tracking the particle from one cell to the next until it reaches a boundary, an internal sink/source, or satisfies another termination criterion. Data input to MODPATH consists of a combination of MODFLOW input data files, MODFLOW head and flow output files, and other input files specific to MODPATH. Output from MODPATH consists of several output files, including a number of particle coordinate output files intended to serve as input data for other programs that process, analyze, and display the results in various ways. MODPATH is written in FORTRAN and can be compiled by any FORTRAN compiler that fully supports FORTRAN-2003 or by most commercially available FORTRAN-95 compilers that support the major FORTRAN-2003 language extensions.

Techniques and Methods↗

USGS2017

Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System

A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.

Techniques and Methods↗

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↗

USGS2003

Residence times and nitrate transport in ground water discharging to streams in the Chesapeake Bay Watershed

One of the major water-quality problems in the Chesapeake Bay is an overabundance of nutrients from the streams and rivers that discharge to the Bay. Some of these nutrients are from nonpoint sources such as atmospheric deposition, agricultural manure and fertilizer, and septic systems. The effects of efforts to control nonpoint sources, however, can be difficult to quantify because of the lag time between changes at the land surface and the response in the base-flow (ground water) component of streams. To help resource managers understand the lag time between implementation of management practices and subsequent response in the nutrient concentrations in the base-flow component of streamflow, a study of ground-water discharge, residence time, and nitrate transport in springs throughout the Chesapeake Bay Watershed and in four smaller watersheds in selected hydrogeomorphic regions (HGMRs) was conducted. The four watersheds were in the Coastal Plain Uplands, Piedmont crystalline, Valley and Ridge carbonate, and Valley and Ridge siliciclastic HGMRs. A study of springs to estimate an apparent age of the ground water was based on analyses for concentrations of chlorofluorocarbons in water samples collected from 48 springs in the Chesapeake Bay Watershed. Results of the analysis indicate that median age for all the samples was 10 years, with the 25th percentile having an age of 7 years and the 75th percentile having an age of 13 years. Although the number of samples collected in each HGMR was limited, there did not appear to be distinct differences in the ages between the HGMRs. The ranges were similar between the major HGMRs above the Fall Line (modern to about 50 years), with only two HGMRs of small geographic extent (Piedmont carbonate and Mesozoic Lowland) having ranges of modern to about 10 years. The median values of all the HGMRs ranged from 7 to 11 years. Not enough samples were collected in the Coastal Plain for comparison. Spring samples showed slightly younger water under wet conditions than under dry conditions. The apparent age of water from wells, springs, and other ground-water discharge points in the four targeted watersheds was modern to 60 years, which was similar to the apparent ages from the spring study. In the Pocomoke River Watershed in the Coastal Plain Uplands HGMR, the apparent age of ground-water samples ranged from 0 to 60 years; the ages in the vicinity of the streams ranged from 0 to 23 years. The apparent ages of ground water in the Polecat Creek Watershed in the Piedmont crystalline HGMR ranged from 2 to 30 years. The apparent ages of water from wells in the Muddy Creek Watershed in the Valley and Ridge carbonate HGMR ranged from 10 to 20 years (except for a single sample that was 45 years). The ages in the East Mahantango Creek Watershed in the Valley and Ridge siliciclastic HGMR ranged from 0 to 50 years. The distribution in apparent age of water from wells in the targeted watersheds, however, generally is older than that for water from the springs. The median age of water from wells in the Muddy Creek Watershed, for example, was 15 years, compared to 11 years for the water from the springs in that watershed, and less than 10 years for water from all springs in the spring study. The similarity in the ranges in apparent age of water from the wells and from the springs shows that the samples from the targeted watersheds and springs have bracketed the range of apparent ages that would be expected in the shallow ground-water-flow systems throughout the Chesapeake Bay Watershed. The apparent age of water from individual wells does not necessarily represent the entire distribution of ages of the discharging ground water, and it is this distribution of ages that affects the response of nutrient concentrations in stream base flow. Nutrient-reduction scenarios were modeled for two watersheds for which the distribution of apparent ground-water ages was available, the East Mahantango Creek Watershed in the Valley and Ridge siliciclastic HGMR and the Locust Grove Watershed in the Coastal Plain Uplands HGMR. A nutrient-reduction scenario was created for East Mahantango Creek, where the average residence time was determined to be approximately 10 years on the basis of the output of particle tracking from a ground-water-ﬂow model. This scenario showed decreases of nearly 50 percent in base-ﬂow concentrations of nitrate in streams within the ﬁrst year after the reduction in nitrogen input; smaller reductions in nitrate concentration occurred in each subsequent year. A second scenario for that same watershed, in which the same 10-year average residence time was assumed and an exponential model was used for analysis, showed that a 50-percent reduction in base-ﬂow concentrations of nitrate could take up to 5 years. For the Locust Grove Watershed, in which an average residence time of 32 years was assumed, simulation with the exponential model showed that it may take more than 20 years to achieve a 50-percent reduction in base-ﬂow concentra-tions of nitrate. Although it was not possible to construct such scenarios for all watersheds, these examples show the range of possible responses to changes in nutrient inputs in two very different types of watersheds. Findings from this study include information on factors that affect ground-water age, spatial distribution of ages, and nitrogen transport. In the East Mahantango Creek Watershed and the Polecat Creek Watershed, the residence time varied spatially depending on the position of the ﬂow path, and temporally depending on the recharge conditions. Generally, ground water in areas near the stream had short residence times and the water in upland areas had longer residence times. Water traveling through deep layers had longer residence times than water traveling through shallow layers, and residence times were faster under high recharge conditions than low recharge conditions. Ground water in the Pocomoke Watershed exhibits a similar pattern: younger water discharges to small order streams in headwater basins and older water discharges to larger streams near the basin outlet. Factors affecting nitrogen transport in ground water include spatial and temporal variation in input sources, ground-water age, and aquifer processes that lead to denitriﬁcation. Spatial and temporal variations in nitrogen sources affect all the watersheds. Tributaries with higher inputs of nitrogen have higher concentrations in stream base ﬂow. Areas where nitrogen application rates have increased over time show an age-nitrate relation in ground-water samples. The age-nitrate relation can be affected by denitriﬁcation, which occurs in Pocomoke and East Mahantango Creeks but is not evident in Polecat and Muddy Creeks. In East Mahantango Creek, the level of denitriﬁcation is signiﬁcant in water with residence times greater than 20 years, but because this is a small component of overall ground-water discharge to a stream, it may not remove a signiﬁcant quantity of nitrogen from the system. Denitriﬁcation in Pocomoke Creek is signiﬁcant and appears to affect mostly older water discharging to streams. Therefore, if most of the nitrogen entering these two streams is associated with the discharge of younger ground water, denitriﬁcation may not greatly affect the overall nitrogen delivery to these streams. Other ﬁndings of this study show that nitrate in ground water discharging along preferential ﬂow paths may not be affected by natural processes, such as denitriﬁcation or uptake by riparian vegetation. Seeps to swales and ditches beneath the north uplands at Polecat Creek indicate a shallow water table and discharge of young ground water whereas the absence of such seeps on the south side indicates a deep water table and a lack of young ground water. Similarly, discharge at the base of the slope and to the valley wetland south of the creek but not north of the creek indicates a different role for the riparian forest on the two sides of the creek. In many of the systems where water discharges at the base of slopes to wetlands, ditches have been dug to drain the valley. Such drainage circumvents possible removal of nitrate by riparian vegetation. Because ground-water residence times do not appear directly related to the HGMRs, the targeting of management practices will achieve the most rapid response in water quality if directed at 1) watersheds with large agricultural sources of nitrate, 2) areas with the shortest ground-water-ﬂow paths and 3) areas not affected by signiﬁcant denitriﬁcation. The fastest response in stream base-ﬂow concentrations of nitrogen to implementation of management practices would be to implement practices in those areas with the highest loads rather than attempt to target practices on the basis of HGMR stratiﬁcation. Overall ﬁndings of the study indicate that 1) ground-water contributions to nitrogen in streamﬂow are signiﬁcant, 2) some response to management practices should be evident in base-ﬂow concentrations of nitrogen and loads within 1 to 5 years in watersheds with the shortest average residence times, but response time may be closer to 20 years in watersheds with longer average ground-water residence times, 3) the majority of the response in ground-water discharge to any changes in management practices will be distributed over a 10-year time period even in the watersheds with the fastest response times, and 4) given that half the streamﬂow is from ground-water discharge and the other half is runoff or soil water, about 90 percent of total water being discharged to a stream will be less than about a decade old; therefore, full implementation of nutrient reductions may result in improved streamwater quality in about a decade. In the more-likely scenario of gradual source reduction, the reduction in concentrations of nitrate in streams and aquifers would take longer than the examples shown here.

Chesapeake Bay watershed↗

USGS2003

Probability of detecting elevated concentrations of nitrate in ground water in a six-county area of south-central Idaho

A probability map constructed for this study identified several areas in a six-county region of south-central Idaho with high probabilities of detecting elevated concentrations (greater than 2 milligrams per liter) of nitrate. An increasing proportion of Idaho’s ground water being used for drinking water and large increases in the inputs of nitrogen to ground water in Cassia, Gooding, Jerome, Lincoln, Minidoka, and Twin Falls Counties have prompted concerns about the quality of the resource. The probability map was constructed to assist regulatory and resource agencies in managing land use and protecting water resources. To construct the probability map, hydrogeologic and anthropogenic data were integrated with ground-water quality data in a geographic information system. The resulting data set contained land use, geology, precipitation, soil characteristics, depth to ground water, nitrogen input, and ground-water velocity information for each of the 1,365 samples collected from 1991 to 2001. Logistic regression analysis was used to determine the most statistically significant variables related to the detection of elevated nitrate concentrations. The resulting multivariate probability model showed that ground-water velocity, nitrogen input, precipitation, soil drainage, land use, and depth to ground water were significantly correlated with elevated nitrate concentrations. A subset of the water-quality data set was used to verify these results. Linear regression of the percentage of predicted probabilities of elevated nitrate concentrations and the actual percentage of elevated nitrate concentrations with the model data set and the verification data set both showed good correlations: r-squared values were 0.96 and 0.97, respectively. Statistical comparisons of both data sets showed that ground-water samples containing elevated nitrate concentrations had significantly higher probabilities of detection (p < 0.001) than samples without elevated nitrate concentrations. On the basis of these results, a map identifying the probability of detecting elevated nitrate concentrations was constructed. High-probability areas on the map coincided with regions of agricultural land use and high nitrogen input, except in southern Gooding County and western Jerome County. In these areas, high ground-water velocities representing a predominance of regional ground water resulted in a low probability of detecting elevated nitrate concentrations. Areas of poor prediction tended to be congregated along the transition zone between high and low ground-water velocities in Jerome and Gooding Counties, indicating a mix of regional and recently recharged ground water.

Idaho↗