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At least 595 records · Page 33Linked to original sources
USGS2004

Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells

A neural network analysis of agrichemical occurrence in groundwater was conducted using data from a pilot study of 192 small-diameter drilled and driven wells and 115 dug and bored wells in Illinois, a regional reconnaissance network of 303 wells across 12 Midwestern states, and a study of 687 domestic wells across Iowa. Potential factors contributing to well contamination (e.g., depth to aquifer material, well depth, and distance to cropland) were investigated. These contributing factors were available in either numeric (actual or categorical) or descriptive (yes or no) format. A method was devised to use the numeric and descriptive values simultaneously. Training of the network was conducted using a standard backpropagation algorithm. Approximately 15% of the data was used for testing. Analysis indicated that training error was quite low for most data. Testing results indicated that it was possible to predict the contamination potential of a well with pesticides. However, predicting the actual level of contamination was more difficult. For pesticide occurrence in drilled and driven wells, the network predictions were good. The performance of the network was poorer for predicting nitrate occurrence in dug and bored wells. Although the data set for Iowa was large, the prediction ability of the trained network was poor, due to descriptive or categorical input parameters, compared with smaller data sets such as that for Illinois, which contained more numeric information.

Journal of Hydrologic Engineering↗
USGS2008

Coupled semivariogram uncertainty of hydrogeological and geophysical data on capture zone uncertainty analysis

This study investigates capture zone uncertainty that relates to the coupled semivariogram uncertainty of hydrogeological and geophysical data. Semivariogram uncertainty is represented by the uncertainty in structural parameters (range, sill, and nugget). We used the beta distribution function to derive the prior distributions of structural parameters. The probability distributions of structural parameters were further updated through the Bayesian approach with the Gaussian likelihood functions. Cokriging of noncollocated pumping test data and electrical resistivity data was conducted to better estimate hydraulic conductivity through autosemivariograms and pseudo-cross-semivariogram. Sensitivities of capture zone variability with respect to the spatial variability of hydraulic conductivity, porosity and aquifer thickness were analyzed using ANOVA. The proposed methodology was applied to the analysis of capture zone uncertainty at the Chicot aquifer in Southwestern Louisiana, where a regional groundwater flow model was developed. MODFLOW-MODPATH was adopted to delineate the capture zone. The ANOVA results showed that both capture zone area and compactness were sensitive to hydraulic conductivity variation. We concluded that the capture zone uncertainty due to the semivariogram uncertainty is much higher than that due to the kriging uncertainty for given semivariograms. In other words, the sole use of conditional variances of kriging may greatly underestimate the flow response uncertainty. Semivariogram uncertainty should also be taken into account in the uncertainty analysis. ?? 2008 ASCE.

Journal of Hydrologic Engineering↗
USGS2008

Low-Level detections of halogenated volatile organic compounds in groundwater: Use in vulnerability assessments

Concentrations of halogenated volatile organic compounds (VOCs) were determined by gas chromatography (GC) with an electron-capture detector (GC-ECD) and by gas chromatography with mass spectrometry (GC-MS) in 109 groundwater samples from five study areas in the United States. In each case, the untreated water sample was used for drinking-water purposes or was from a monitoring well in an area near a drinking-water source. The minimum detection levels (MDLs) for 25 VOCs that were identified in GC-ECD chromatograms, typically, were two to more than four orders of magnitude below the GC-MS MDLs. At least six halogenated VOCs were detected in all of the water samples analyzed by GC-ECD, although one or more VOCs were detected in only 43% of the water samples analyzed by GC-MS. In nearly all of the samples, VOC concentrations were very low and presented no known health risk. Most of the low-level VOC detections indicated post-1940s recharge, or mixtures of recharge that contained a fraction of post-1940s water. Concentrations of selected halogenated VOCs in groundwater from natural and anthropogenic atmospheric sources were estimated and used to recognize water samples that are being impacted by nonatmospheric sources. A classification is presented to perform vulnerability assessments at the scale of individual wells using the number of halogenated VOC detections and total dissolved VOC concentrations in samples of untreated drinking water. The low-level VOC detections are useful in vulnerability assessments, particularly for samples in which no VOCs are detected by GC-MS analysis.

Journal of Hydrologic Engineering↗
USGS2009

Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

Journal of Hydrologic Engineering↗
USGS2010

Discussion of "Natural hydrograph of the Missouri River near Sioux City and the least tern and piping plover" by Donald G. Jorgensen

The author analyzed stream-flow data from a single gauging station to predict preengineering flooding frequency for "sandbar islands adjacent to stream gauge on the Missouri River at Sioux City." He predicted dates that sandbars would be exposed and discussed his results relative to reproduction by least terns (Sternula antillarum) and piping plovers (Charadrius melodus). His analysis predicted sandbar inundation during nesting and concluded that "successful migrations of age-zero juveniles leading to recruitment would not have resulted from the use of the sandbar islands for attempted reproduction most years in the Sioux City area." We argue that the author (1) overlooked published historical records of breeding terns and plovers on the Missouri River and nearby systems, (2) inaccurately portrayed inundation for Missouri River sandbars and the importance of high flows for forming sandbars, and (3) underestimated these species' ability to withstand periodic reproductive failures. We conclude that the data do not support the author's contention that the preengineered Missouri River was "unfriendly" to terns and plovers.

Iowa↗
USGS2013

Generalized additive regression models of discharge and mean velocity associated with direct-runoff conditions in Texas: Utility of the U.S. Geological Survey discharge measurement database

A database containing more than 17,700 discharge values and ancillary hydraulic properties was assembled from summaries of discharge measurement records for 424 U.S. Geological Survey streamflow-gauging stations (stream gauges) in Texas. Each discharge exceeds the 90th-percentile daily mean streamflow as determined by period-of-record, stream-gauge-specific, flow-duration curves. Each discharge therefore is assumed to represent discharge measurement made during direct-runoff conditions. The hydraulic properties of each discharge measurement included concomitant cross-sectional flow area, water-surface top width, and reported mean velocity. Systematic and statewide investigation of these data in pursuit of regional models for the estimation of discharge and mean velocity has not been previously attempted. Generalized additive regression modeling is used to develop readily implemented procedures by end-users for estimation of discharge and mean velocity from select predictor variables at ungauged stream locations. The discharge model uses predictor variables of cross-sectional flow area, top width, stream location, mean annual precipitation, and a generalized terrain and climate index (OmegaEM) derived for a previous flood-frequency regionalization study. The mean velocity model uses predictor variables of discharge, top width, stream location, mean annual precipitation, and OmegaEM. The discharge model has an adjusted R-squared value of about 0.95 and a residual standard error (RSE) of about 0.22 base-10 logarithm (cubic meters per second); the mean velocity model has an adjusted R-squared value of about 0.67 and an RSE of about 0.063 fifth root (meters per second). Example applications and computations using both regression models are provided. - See more at: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000635#sthash.jhGyPxgZ.dpuf

Journal of Hydrologic Engineering↗
USGS2013

Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment

The increase in runoff from urbanization is well known; one extreme example comes from a 13 hectare residential neighborhood in southeast Arizona where runoff was 27 times greater than an adjacent grassland watershed over a forty‐month period from 2005 to 2008. Rainfall‐runoff modeling using the newly‐described KINEROS2 urban element and tension infiltrometer measurements indicate that 17±14 percent of this increase in runoff is due to a 53 percent decrease in the saturated hydraulic conductivity of constructed pervious areas, as compared to the undeveloped grassland. Directly connected impervious areas, primarily streets and driveways, cause 56 percent of the increase in runoff, and indirectly connected impervious areas, primarily rooftops and sidewalks, and a decrease in canopy interception account for the remaining 27 percent increase. Tension infiltrometer measurements show that saturated hydraulic conductivity (K s ) is about double in the grassland watershed than in the urban watershed, 6.2 ± 3.5mm/hr and 2.9 ± 1.6mm/hr, respectively. K s in the urban watershed identified from calibrating the rainfall‐runoff model to measured runoff is 9.5 ± 2.8 mm/hr—higher than what was measured but much lower than the 26 mm/hr value indicated by a soil‐texture based KINEROS2 parameter look‐up table. A new component of the KINEROS2 modeling framework, the urban element, forms the basis for the model by simulating a contiguous row of houses and the adjoining street as a series of pervious and impervious overland flow planes. Tests using different levels of discretization found that watershed geometry can be represented in a simplified manner, although more detailed discretization led to better model performance.

Arizona↗
USGS2014

Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database

A database containing more than 16,300 discharge values and ancillary hydraulic attributes was assembled from summaries of discharge measurement records for 391 USGS streamflow-gauging stations (streamgauges) in Texas. Each discharge is between the 40th- and 60th-percentile daily mean streamflow as determined by period-of-record, streamgauge-specific, flow-duration curves. Each discharge therefore is assumed to represent a discharge measurement made for near-median streamflow conditions, and such conditions are conceptualized as representative of midrange to baseflow conditions in much of the state. The hydraulic attributes of each discharge measurement included concomitant cross-section flow area, water-surface top width, and reported mean velocity. Two regression equations are presented: (1) an expression for discharge and (2) an expression for mean velocity, both as functions of selected hydraulic attributes and watershed characteristics. Specifically, the discharge equation uses cross-sectional area, water-surface top width, contributing drainage area of the watershed, and mean annual precipitation of the location; the equation has an adjusted R-squared of approximately 0.95 and residual standard error of approximately 0.23 base-10 logarithm (cubic meters per second). The mean velocity equation uses discharge, water-surface top width, contributing drainage area, and mean annual precipitation; the equation has an adjusted R-squared of approximately 0.50 and residual standard error of approximately 0.087 third root (meters per second). Residual plots from both equations indicate that reliable estimates of discharge and mean velocity at ungauged stream sites are possible. Further, the relation between contributing drainage area and main-channel slope (a measure of whole-watershed slope) is depicted to aid analyst judgment of equation applicability for ungauged sites. Example applications and computations are provided and discussed within a real-world, discharge-measurement scenario, and an illustration of the development of a preliminary stage-discharge relation using the discharge equation is given.

Texas↗
USGS2014

Impact of climate variability on runoff in the north-central United States

Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.

Iowa, Kansas, Minnesota, Missouri, Nebraska, North↗
USGS2014

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

Georgia↗
USGS2017

Salinity influences on aboveground and belowground net primary productivity in tidal wetlands

Tidal freshwater wetlands are one of the most vulnerable ecosystems to climate change and rising sea levels. However salinification within these systems is poorly understood, therefore, productivity (litterfall, woody biomass, and fine roots) were investigated on three forested tidal wetlands [(1) freshwater, (2) moderately saline, and (3) heavily salt-impacted] and a marsh along the Waccamaw and Turkey Creek in South Carolina. Mean aboveground (litterfall and woody biomass) production on the freshwater, moderately saline, heavily salt-impacted, and marsh, respectively, was 1,061, 492, 79, and 0     g   m − 2   year − 1 versus belowground (fine roots) 860, 490, 620, and 2,128     g   m − 2   year − 1 . Litterfall and woody biomass displayed an inverse relationship with salinity. Shifts in productivity across saline sites is of concern because sea level is predicted to continue rising. Results from the research reported in this paper provide baseline data upon which coupled hydrologic/wetland models can be created to quantify future changes in tidal forest functions.

South Carolina↗
USGS2020

Comparing discharge computation methods in the Great Lakes connecting channels

Records of discharge for the connecting channels within the Great Lakes Basin are important to national governments of Canada and the United States and the various water management agencies and users in the basin. For more than 100 years, the official discharge records for the St. Clair and Detroit Rivers, two connecting channels within the Great Lakes Basin, have been computed using various stage-fall-discharge (SFQ) methods. However, as a result of technological advancements, newer methods have recently been considered for discharge computations. In this study, three discharge computation methods were compared: two SFQ methods and the index-velocity discharge (IVQ) method. Although the two SFQ methods have significantly different assumptions and use different data from the index-velocity method, the differences between the computed discharges derived from the methods are small, especially as the time step approaches monthly discharge values. Statistical analyses of discharge measurements and discharges computed using each of these methods indicate that there is no substantive difference in the discharges computed using the three methods. However, the IVQ method provides distinct advantages over the SFQ methods, including increased temporal resolution of computed discharge (minutes versus daily) and the ability to account for changes caused by aquatic vegetation and ice. Based on the results of the comparisons described herein, the IVQ discharge computation method is the most appropriate method for discharge computation in the St. Clair and Detroit Rivers. Updated SFQ equations for the St. Clair and Detroit Rivers, also presented herein, can be used to compute discharge during periods of missing or invalid IVQ record.

Indiana, Michigan, Minnesota, New York, Ohio, Onta↗
USGS2021

Performance of bedload sediment transport formulas applied to the Lower Minnesota River

Despite limitations in reproducing complex bedload sediment transport processes in rivers, formulas have been preferred over collection and analysis of field data due to the high cost and time-consuming nature of bedload discharge measurements. However, the performance of such formulas depends on the hydraulic and sedimentological conditions they attempt to describe. The availability of field measurements provides a unique opportunity to test bedload transport formulas to better guide formula selection. Hydraulic parameters and bedload discharge data from the Lower Minnesota River and two of its tributaries were used to evaluate nine bedload transport formulas using three different indices. The bedload data for the different sites were collected by the United States Geological Survey (USGS) from 2011 through 2014, with bed material varying from very coarse to medium sand. The formulas calculated higher bedload rates than were measured due to a combination of site-specific physical characteristics, including the presence of bed forms (dunes), and sampling uncertainties. Because of the lack of reproducibility of the tested formulas, five power functions, based on the relation between the specific unit power (independent hydraulic variable) and the USGS measured data (dependent variable), were derived as provisional equations to estimate the bedload discharge on the Lower Minnesota River and tributaries.

Minnesota↗
USGS2022

On the role of climate in monthly baseflow changes across the continental United States

Baseflow is the portion of streamflow that comes from groundwater and subsurface sources. Although baseflow is essential for sustaining streams during low flow and drought periods, we have little information about how and why it has changed over large regions of the continental United States. The objective of this study was to evaluate how changes in the climate system have affected observed monthly baseflow records at 3,283 USGS gauges over the last 30 years (1989–2019). We developed a statistical modeling framework to determine the relationship between monthly baseflow and monthly climate predictors (i.e., precipitation, temperature, and antecedent wetness). Overall, we found that baseflow trends and the factors influencing them vary by region and month. In the US Northeast, increases were detected earlier in the year (February and March) and in the summer (May and June), and were likely due to increasing precipitation, warmer temperature, and subsequent changes in snowmelt. Increasing baseflow in the US Pacific Northwest and Midwest were associated with increases in precipitation and antecedent wetness throughout the year. Decreasing trends were located in the US Southeast and Southwest. Baseflow trends in the US Southeast were only detected in March, possibly as a result of decreased precipitation during the spring. On the other hand, decreases in baseflow in the Central Southwestern United States occurred throughout the year. These trends were associated with a lack of precipitation and increases in temperature. Finally, we examined the relationship between monthly baseflow trends and changes in total water storage using monthly Gravity Recovery and Climate Experiment mascon products from the Jet Propulsion Laboratory. In this study, trends in total water storage were strongly associated with baseflow trends across the United States. The spatial and temporal variability in baseflow response to climate reported here can aid water managers in adapting to future climate change.

continental United States↗
USGS2019

Turbidity current observations in a large reservoir following a major wildfire

Turbidity currents are generated when denser river water plunges and flows along the bottom of a lake, reservoir, or ocean. The plunging and downstream movement are driven by density differences due to temperature and/or suspended sediment, and currents have been observed to move slowly over long distances. This study presents observations of multiple turbidity currents in a large reservoir in California, United States, during runoff events following a major wildfire in the upstream watershed. Several aspects of the currents are documented and discussed, including the conditions leading to plunging, the vertical and longitudinal structure of turbidity within the currents, the velocity of the currents, and the development of a muddy lake upstream from an old submerged dam in the reservoir.

California↗
USGS2025

Validation of gridded precipitation datasets for flood-typing in select conterminous U.S. basins

Gridded precipitation datasets are required for flood-typing historical annual peak streamflow events in basins across the Conterminous United States. Selected gridded precipitation datasets were validated over the period 1981–2013 through comparisons with gage data from the NOAA Global Historical Climatology Network daily (GHCNd). The ability of each gridded dataset to capture the spatiotemporal characteristics of daily precipitation, including multi-day extremes over six selected regions, was assessed using the Kling-Gupta Efficiency metric and its component statistics. Overall, the Parameter-elevation Regression on Independent Slopes Model and Livneh-unsplit were found to best match the spatiotemporal variability of the GHCNd precipitation data, including extremes. The Analysis of Record for Calibration was found to be the third best-performing dataset in most regions except in the western U.S. The performance of reanalysis datasets evaluated appears to be poor compared to gage-based datasets. The reanalysis datasets might not be able to skillfully capture precipitation amounts at the correct location and time. Gage- and radar-based datasets were found to have relatively small biases (within +/-10% on an annual basis), while reanalysis datasets were found to have larger positive apparent biases, especially in winter and spring in most regions. It is possible that the apparent overestimation of winter and spring precipitation in the reanalysis datasets might reflect snow undercatch at gages especially in the central U.S. An overall deterioration of performance for correlation and/or variability was also observed for the summer season compared to other seasons in the reanalysis datasets. Various precipitation datasets might need to be used for flood-typing during different periods from the late 19th century to present. Datasets from different sources have different biases and errors and might have to be homogenized using downscaling and bias-adjustment methods. Alternatively, precipitation thresholds used in some flood-typing schemes might have to be adjusted as a function of time.

conterminous United States↗
USGS2000

Snow crystal imaging using scanning electron microscopy: III. Glacier ice, snow and biota

Low-temperature scanning electron microscopy (SEM) was used to observe metamorphosed snow, glacial firn, and glacial ice obtained from South Cascade Glacier in Washington State, USA. Biotic samples consisting of algae ( Chlamydomonas nivalis ) and ice worms (a species of oligochaetes) were also collected and imaged. In the field, the snow and biological samples were mounted on copper plates, cooled in liquid nitrogen, and stored in dry shipping containers which maintain a temperature of-196°C. The firn and glacier ice samples were obtained by extracting horizontal ice cores, 8 mm in diameter, at different levels from larger standard glaciological (vertical) ice cores 7.5 cm in diameter. These samples were cooled in liquid nitrogen and placed in cryotubes, were stored in the same dry shipping container, and sent to the SEM facility. In the laboratory, the samples were sputter coated with platinum and imaged by a low-temperature SEM. To image the firn and glacier ice samples, the cores were fractured in liquid nitrogen, attached to a specimen holder, and then imaged. While light microscope images of snow and ice are difficult to interpret because of internal reflection and refraction, the SEM images provide a clear and unique view of the surface of the samples because they are generated from electrons emitted or reflected only from the surface of the sample. In addition, the SEM has a great depth of field with a wide range of magnifying capabilities. The resulting images clearly show the individual grains of the seasonal snowpack and the bonding between the snow grains. Images of firn show individual ice crystals, the bonding between the crystals, and connected air spaces. Images of glacier ice show a crystal structure on a scale of 1–2 mm which is considerably smaller than the expected crystal size. Microscopic air bubbles, less than 15 μm in diameter, clearly marked the boundaries between these crystal-like features. The life forms associated with the glacier were easily imaged and studied. The low-temperature SEM sample collecting and handling methods proved to be operable in the field; the SEM analysis is applicable to glaciological studies and reveals details unattainable by conventional light microscopic methods.

Washington↗
USGS2000

Origin of the Colorado River experimental flood in Grand Canyon

The Colorado River is one of the most highly regulated and extensively utilized rivers in the world. Total reservoir storage is approximately four times the mean annual runoff of −17 × 10 9 m 3 year −1 . Reservoir storage and regulation have decreased annual peak discharges and hydroelectric power generation has increased daily flow variability. In recent years, the incidental impacts of this development have become apparent especially along the Colorado River through Grand Canyon National Park downstream from Glen Canyon Dam and caused widespread concern. Since the completion of Glen Canyon Dam, the number and size of sand bars, which are used by recreational river runners and form the habitat for native fishes, have decreased substantially. Following an extensive hydrological and geomorphic investigation, an experimental flood release from the Glen Canyon Dam was proposed to determine whether sand bars would be rebuilt by a relatively brief period of flow substantially greater than the normal operating regime. This proposed release, however, was constrained by the Law of the River, the body of law developed over 70 years to control and distribute Colorado River water, the needs of hydropower users and those dependent upon hydropower revenues, and the physical constraints of the dam itself. A compromise was reached following often difficult negotiations and an experimental flood to rebuild sand bars was released in 1996. This flood, and the process by which it came about, gives hope to resolving the difficult and pervasive problem of allocation of water resources among competing interests.

Arizona↗