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USGS2024

Projected sea-level rise and high tide flooding at Timucuan Ecological and Historic Preserve, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Timucuan Ecological and Historic Preserve, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗
USGS2024

Projected sea-level rise and high tide flooding at Biscayne National Park, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Biscayne National Park, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗
USGS2025

Mineral commodity summaries 2025

Introduction Each mineral commodity chapter of the 2025 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2024 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2025 are welcomed.

Mineral Commodity Summaries↗
USGS2026

Mineral commodity summaries 2026

Introduction Each mineral commodity chapter of the 2026 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2025 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the 2026 MCS are welcomed.

Mineral Commodity Summaries↗
USGS2026

Modeling legacy nitrogen transport under instantaneous, steady-state, and transient groundwater flow conditions

In hydrologic settings where groundwater discharge contributes substantially to surface waters, legacy nitrogen in groundwater can confound surface water nitrogen loads estimated exclusively from current terrestrial sources. Additionally, legacy nitrogen in groundwater can contribute to lagged responses to nitrogen management efforts. Some methods of estimating groundwater contributions to surface water nitrogen loads account for legacy nitrogen, while others do not. The resulting differences are rarely quantified. We used a numerical modeling framework to compare three methods of estimating time-varying annual groundwater nitrogen loads to surface water receptors on eastern Long Island, New York. The instantaneous load method used steady-state contributing areas and includes no temporal groundwater lag. The second method used numerical simulations of nitrogen loads under steady-state flow, which captures groundwater transport lags but omits the annual variability in transient hydrologic stresses. The third method numerically simulated both transient groundwater flow and nitrogen transport to explicitly capture the effects of legacy nitrogen in groundwater. Depending on antecedent nitrogen and hydrologic conditions, historical nitrogen loads estimated from the numerical simulations were sometimes similar (<10% difference) and other times substantially different (±100%) from the instantaneous load estimates. Additionally, simulated future surface water nitrogen loads responded asymptotically over several decades following reductions in terrestrial nitrogen sources, further highlighting the effect of groundwater transport lag times. The comparison of the three methods, quantification of historical interannual variability, and prediction of lagged responses to nitrogen source reductions provide important context for decision makers using estimated groundwater nitrogen loads to help evaluate nitrogen management efficacy.

New York↗
USGS2024

Projected sea-level rise and high tide flooding at San Juan National Historic Site, Puerto Rico

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at San Juan National Historic Site, Puerto Rico, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

San Juan National Historic Site↗
USGS2024

Projected sea-level rise and high tide flooding at Big Cypress National Preserve, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Big Cypress National Preserve, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗
USGS1997

Water-quality assessment of south-central Texas: Occurrence and distribution of volatile organic compounds in surface water and ground water, 1983-94, and implications for future monitoring

The study area of the South-Central Texas study unit of the National Water-Quality Assessment Program comprises the Edwards aquifer in the San Antonio region and its catchment area. The first phase of the assessment includes evaluation of existing water-quality data for surface water and ground water, including volatile organic compounds, to determine the scope of planned monitoring. Most analyses of volatile organic compounds in surface water are from the National Pollutant Discharge Elimination System sites in San Antonio, Texas. Nine volatile organic compounds were detected at the six sites. The three compounds with the most detections at National Pollutant Discharge Elimination System sites are 1,2,4-trimethylbenzene, toluene, and xylene. Analysis of volatile organic compounds in ground water was limited to Edwards aquifer wells. Twenty-eight volatile organic compounds were detected in samples from 89 wells. The five most commonly detected compounds in samples from wells, in descending order, are tetrachloroethene, trichloroethene, bromoform, chloroform, and dibromochloromethane. Detections of volatile organic compounds in surface water and ground water within the South-Central Texas study area are limited to site-specific sources associated with development; therefore, planned monitoring for possible detections of volatile organic compounds as part of the National Water-Quality Assessment Program will emphasize areas of expanding population and development. Monitoring of volatile organic compounds is planned at National Pollutant Discharge Elimination System sites, at basic fixed surface-water sites, and in the ground-water study-unit surveys.

Texas↗
USGS1995

Evaluation of ground-water flow and hydrologic budget for Lake Five-O, a seepage lake in northwestern Florida

Temporal and spatial distributions of ground-water inflow to, and leakage from Lake Five-O, a softwater, seepage lake in northwestern Florida, were evaluated using hydrologic data and simulation models of the shallow ground-water system adjacent to the lake. The simulation models indicate that ground-water inflow to the lake and leakage from the lake to the ground-water system are the dominant components in the total inflow (precipitation plus ground-water inflow) and total outflow (evaporation plus leakage) budgets of Lake Five-O. Simlulated ground-water inflow and leakage were approximately 4 and 5 times larger than precipitation inputs and evaporative losses, respectively, during calendar years 1989-90. Exchanges of water between Lake Five-O and the ground-water system were consistently larger than atmospheric-lake exchanges. A consistent pattern of shallow ground-water inflow and deep leakage was also evident throughout the study period. The mean time of travel from ground-water that discharges at Lake Five-O (time from recharge at the water table to discharge at the lake) was estimated to be within a range of 3 to 6 years. Flow-path evaluations indicated that the intermediate confining unit probably has a negligible influence on the geochemistry of ground-water inflow to Lake Five-O. The hydrologic budgets and flow-path evaluations provide critical information for developing geochemical budgets for Lake Five-O and for improving the understanding of the relative importance of various processes that regulate the acid-neutralizing capacity of softwater seepage lakes in Florida.

Florida↗
USGS1996

Pesticides in surface water from three agricultural basins in south-central Georgia, 1993-97

Twenty-two of 43 pesticides analyzed were detected in 128 water samples collected from the Tucsawhatchee Creek, the Little River, and the Withlacoochee River. These streams drain agricultural basins in south-central Georgia and were sampled from March 1993 through June 1995. Herbicides were detected more frequently than insecticides. The most frequently detected herbicides were atrazine and metolachlor and the most frequently detected insecticide was carbaryl. Pesticide concentrations in the three streams were low and did not exceed U.S. Environmental Protection Agency drinking water standards. The maximum pesticide concentration was 2.6 mg/L (micrograms per liter) for propargite, a miticide detected in only one sample. The maximum concentrations of the remaining 21 pesticides were less than 0.25 mg/L. The median concentrations were equal to the method detection limit for all pesticides except atrazine (0.008 mg/L) and metolachlor (0.012 mg/L). The ratio of herbicide detections to nondetections was largest in the planting season, smaller in the harvest season and smallest in the fallow season for the three basins. The same pattern existed for the insecticide ratios in the Little River and the Withlacoochee River. Pairwise correlations between concentrations of atrazine and metolachlor, and four parameters (discharge, and concentrations of dissolved organic carbon, suspended organic carbon, and suspended sediment) were evaluated for each stream. The strongest correlations existed between metolachlor and mean daily discharge, and metolachlor and sediment in the Withlacoochee River. The only significant correlation for the Little River was between atrazine and suspended sediment.

Georgia↗
USGS1998

Continuous hydrologic simulation of runoff for the Middle Fork and South Fork of the Beargrass Creek basin in Jefferson County, Kentucky

The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.

Kentucky↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2026

Status and understanding of groundwater quality in the San Joaquin Valley Kern County subbasin domestic-supply aquifer study unit, 2022—California GAMA Priority Basin Project

The quality of water accessed by domestic wells (here referred to as domestic groundwater resources) in the San Joaquin Valley Kern County subbasin (basin number 5-022.14) was assessed as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project (GAMA-PBP), in cooperation with the California State Water Resources Control Board. Kern County is at the southern end of the San Joaquin Valley in California, and about 30,000 residents are estimated to use privately owned domestic wells for drinking water. Domestic wells typically draw from shallower parts of the aquifer system than public-supply wells and can be more vulnerable to effects from surface activities. Kern County is host to a highly productive agricultural industry, with Bakersfield as the main urban center. The Kern River runs through Bakersfield from the southern Sierra Nevada and intersects the Kern Water Bank, one of the largest groundwater banking operations in California, at the Kern River Intertie. The section of the Kern River running through the Kern Water Bank is dry most years. Kern County also encompasses some of the most productive oil and gas basins in California, with extensive underground and surface disposal of oil-field wastewater. This study was based on data collected from 33 sites sampled by the U.S. Geological Survey for the GAMA-PBP in 2022. To provide context for the water quality assessment, measured concentrations were compared to regulatory and non-regulatory health-based and aesthetic benchmarks. A grid-based method was used to estimate the proportions of the groundwater resources used for domestic-supply wells that have water-quality constituents below (low relative concentration), approaching (moderate relative concentration), or above (high relative concentration) benchmark concentrations. At least one measured constituent with a regulatory benchmark was categorized as having a high relative concentration in 72 percent of the aquifer area used for domestic groundwater resources. Inorganic constituents were detected at high concentrations in 45 percent of the domestic groundwater resources, and the constituents detected above regulatory benchmarks were arsenic, nitrate, and uranium. At least one organic constituent was detected at high concentrations in 41 percent of the domestic groundwater resources, and the constituents exceeding regulatory benchmarks were the fumigants 1,2,3-trichloropropane (1,2,3-TCP), 1,2-dibromo-3-chloropropane (dibromochloropropane [DBCP]), 1,2-dibromoethane (EDB), and the per-and polyfluoroalkyl substance (PFAS) perfluorooctanesulfonate. The disinfection by-product chloroform, the fumigant 1,2-dichloropropane, the herbicides atrazine and hexazinone, and the herbicide degradates 2-chloro-6-ethylamino-4-amino-s-triazine, 2-chloro-4,6-diamino-s-triazine, 4-hydroxychlorothalonil, and metolachlor sulfonic acid were detected in more than 10 percent of domestic groundwater resources, but concentrations did not exceed regulatory benchmarks. Land use, groundwater age (fraction of modern water and mean age), and geochemical environment (oxic or anoxic conditions, pH, alkalinity) were associated with the distribution of high relative concentrations of inorganic and organic constituents. Young, oxygenated water is recharged along the Kern River and adjacent recharge ponds, or as irrigation water in the agricultural areas. High concentrations of nitrate and volatile organic compounds occurred in the oxic water in urban and agricultural areas. The fumigants 1,2,3-TCP, DBCP, and EDB were reported throughout the agricultural areas, whereas chloroform, tetrachloroethene, and PFAS were associated with urban land use. High uranium concentrations were associated with young, modern groundwater in agricultural areas with low pH and high bicarbonate. Total dissolved solids increased with distance from the Kern River, as the contributions of fresh, oxic water decreased. High concentrations of arsenic were present in older anoxic or alkaline groundwater away from areas of recharge. Overall, groundwater age, redox conditions, and the source of recharge as a result of different land uses contribute to large aquifer-scale portions of domestic groundwater resources that exceed health-based benchmarks for nitrate, uranium, and fumigant concentrations.

California↗
USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗
USGS1992

Public water-supply systems and water use in Tennessee, 1988

This report summarizes the results of a study conducted by the U.S. Geological Survey, in cooperation with the Tennessee Department of Environment and Conservation (TDEC), Division of Water Supply in 1988. Data gathered during an inventory by the TDEC were collated to determine water use, supply sources, population served, and design and storage capacities of the systems. The inventory was limited to systems that were active on June 30, 1988. Results of a survey of the systems conducted by the Tennessee Department of Health and Environment during 1988 were a primary source of data for this report. Data from computer and manual files maintained by the Tennessee Department of Health and Environment and the U.S. Geological Survey also were used. The Division of Water Supply, TDEC, surveyed 541 public water-supply systems. These systems served 81 percent of the population of the State, or 3.95 million people. The gross per capita use statewide for public-supplied water was 179 gallons per day. Total water withdrawals for public supply increased about 39 percent from 510 million gallons per day (Mgal/d) in 1980, to 708 Mgalld in 1988. During the same period, the population increased about 7 percent. Surface-water withdrawals accounted for 63 percent (446 Mgal/d) of the total water withdrawn in the State. All of these withdrawals occurred in the Tennessee (56 percent or 249 Mgal/d) and the Ohio (44 percent or 197 Mgalld) hydrologic regions. Ground water supplied 262 Mgal/d or 37 percent of the total water withdrawn by public-supply systems statewide. Of that amount, 79 percent, or 208 Mgalld, was used in western Tennessee.

Tennessee↗
USGS1995

Methods for estimating the magnitude and frequency of peak discharges of rural, unregulated streams in Virginia

Methods are presented for estimating the peak discharges of rural, unregulated streams in Virginia. A Pearson Type III distribution is fitted to the logarithms of the unregulated annual peak-discharge records from 363 stream-gaging stations in Virginia to estimate the peak discharge at these stations for recurrence intervals of 2 to 500 years. Peak-discharge characteristics for 284 unregulated stations are divided into eight regions based on physiographic province, and regressed on basin characteristics, including drainage area, main channel length, main channel slope, mean basin elevation, percentage of forest cover, mean annual precipitation, and maximum rainfall intensity. Regression equations for each region are computed by use of the generalized least-squares method, which accounts for spatial and temporal correlation between nearby gaging stations. This regression technique weights the significance of each station to the regional equation based on the length of records collected at each cation, the correlation between annual peak discharges among the stations, and the standard deviation of the annual peak discharge for each station. Drainage area proved to be the only significant explanatory variable in four regions, while other regions have as many as three significant variables. Standard errors of the regression equations range from 30 to 80 percent. Alternate equations using drainage area only are provided for the five regions with more than one significant explanatory variable. Methods and sample computations are provided to estimate peak discharges at gaged and engaged sites in Virginia for recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, and to adjust the regression estimates for sites on gaged streams where nearby gaging-station records are available.

Virginia↗
USGS2025

Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration

Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.

Colorado↗
USGS2024

Beyond the wedge: Impact of tidal streams on salinization of groundwater in a coastal aquifer stressed by pumping and sea-level rise

Saltwater intrusion (SWI) is a well-studied phenomenon that threatens the freshwater supplies of coastal communities around the world. The development and advancement of numerical models has led to improved assessment of the risk of salinization. However, these studies often fail to include the impact of surface waters as potential sources of aquifer salinity and how they may impact SWI. Based on field-collected data, we developed a regional, variable-density groundwater model using SEAWAT for east Dover, Delaware. In this location, major users of groundwater from the surficial aquifer are the City of Dover and irrigation for agriculture. Our model includes salinized marshland and tidal streams, along with irrigation and municipal pumping wells. Model scenarios were run for 100 years and included changes in pumping rates and sea-level rise (SLR). We examined how these drivers of SWI affect the extent and location of salinization in the surficial aquifer by evaluating differences in chloride concentration near surface waters and the subsurface freshwater-saltwater interface. We found the presence of the marsh inverts the typical freshwater-saltwater wedge interface and that the edge of the interface did not migrate farther inland. Additionally, we found that tidal streams are the dominant pathways of SWI at our site with salinization from streams being exacerbated by SLR. Our results also show that spatial distribution of pumping affects both the magnitude and extent of salinization, with an increase in concentrated pumping leading to more intensive salinization than a more widely distributed increase of the same total pumping volume.

Delaware↗