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At least 685 records · Page 38Linked to original sources
USGS2009

Streamflow-Characteristic Estimation Methods for Unregulated Streams of Tennessee

Streamflow-characteristic estimation methods for unregulated rivers and streams of Tennessee were developed by the U.S. Geological Survey in cooperation with the Tennessee Department of Environment and Conservation. Streamflow estimates are provided for 1,224 stream sites. Streamflow characteristics include the 7-consecutive-day, 10-year recurrence-interval low flow, the 30-consecutive-day, 5-year recurrence-interval low flow, the mean annual and mean summer flows, and the 99.5-, 99-, 98-, 95-, 90-, 80-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent flow durations. Estimation methods include regional regression (RRE) equations and the region-of-influence (ROI) method. Both methods use zero-flow probability screening to estimate zero-flow quantiles. A low flow and flow duration (LFFD) computer program (TDECv301) performs zero-flow screening and calculation of nonzero-streamflow characteristics using the RRE equations and ROI method and provides quality measures including the 90-percent prediction interval and equivalent years of record. The U.S. Geological Survey StreamStats geographic information system automates the calculation of basin characteristics and streamflow characteristics. In addition, basin characteristics can be manually input to the stand-alone version of the computer program (TDECv301) to calculate streamflow characteristics in Tennessee. The RRE equations were computed using multivariable regression analysis. The two regions used for this study, the western part of the State (West) and the central and eastern part of the State (Central+East), are separated by the Tennessee River as it flows south to north from Hardin County to Stewart County. The West region uses data from 124 of the 1,224 streamflow sites, and the Central+East region uses data from 893 of the 1,224 streamflow sites. The study area also includes parts of the adjacent States of Georgia, North Carolina, Virginia, Alabama, Kentucky, and Mississippi. Total drainage area, a geology factor, a climate factor, and two soil factors were used as explanatory variables in the RRE equations. Average deleted-residual prediction errors for the West-region RRE equations were 18 and 123 percent for the 10-percent flow duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for RRE equations were 21 and 89 percent for the same respective flow quantiles in the Central+East region. The ROI method calculates unique multivariable regression equations for a site of interest using the flow and basin characteristics of 45 similar streamflow-data sites selected from the same region. These 45 sites are selected using a metric that measures similarity between the site of interest and the streamflow-data sites based on total drainage area, geology factor, and climate factor. The ROI method estimates streamflow characteristics using total drainage area, geology factor, and a soil factor as explanatory variables. Average deleted-residual prediction errors for the West-region ROI equations were 18 and 125 percent for the 10-percent duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for ROI equations were 20 and 85 percent for the same respective flow quantiles in the Central+East region. In general, when compared to the RRE equations, the ROI method performs similarly in the West region and reduces streamflow-characteristic prediction errors by an average of about 7 percent in the Central+East region of Tennessee.

Scientific Investigations Report↗
USGS2015

Spatially explicit spectral analysis of point clouds and geospatial data

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python , it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Computers & Geosciences↗
USGS1991

Simulation of vertical compaction in models of regional ground-water flow

A new computer program was developed to simulate vertical compaction in models of regional ground-water flow. The program accounts for ground-water storage changes and compaction in discontinuous interbeds or in extensive confining beds. The new program is a package for the U.S. Geological Survey modular finite-difference ground-water flow model. Several features of the program make it useful for application in shallow unconfined flow systems. Geostatic load can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress at the center of a model layer. Thickness of compressible sediments in an unconfined model layer can vary in proportion to saturated thickness. The new package was tested by comparison with an existing model of one-dimensional compaction.

Conference Paper↗
USGS1987

Simulation of flow in the Edwards Aquifer, San Antonio region, Texas, and refinement of storage and flow concepts

The Edwards aquifer is a complexly faulted, carbonate aquifer lying within the Balcones fault zone of south-central Texas. The aquifer is recharged mainly by streamflow losses in the outcrop area of the Edwards aquifer and is discharged by major springs located at considerable distances, as much as 150 mi, from the areas of recharge, and by wells. Groundwater flow within the Edwards aquifer of the San Antonio region was simulated to investigate concepts relating to the storage and flow characteristics. A general purpose, finite difference model, modified to provide the capability of representing barrier faults, was used to simulate groundwater flow and storage in the aquifer. The simulations investigated the effects of complex geologic structures and significant changes in transmissivity, anisotropy, and storage coefficient, with initial values based on concepts developed in previous studies. Results of the simulations confirmed the original estimates of transmissivity values (> 100 sq ft/sec) in the confined zone of the aquifer between San Antonio and Comal Springs. A storage coefficient of 0.05 in the unconfined zone of the aquifer produced the best simulation of water levels and springflow. A major interpretation resulting from the simulations is that two essentially independent areas of regional flow were identified in the west and central part of the study area. Flow from the two areas converges at Comal Springs. The directions of computed flux vectors reflected the presence of major barrier faults which locally deflect patterns of groundwater movement. The most noticeable deflection is the convergence of flow through the geologic structural opening, the Knippa gap, in eastern Uvalde County. A second significant interpretation is that groundwater flow in northeastern Bexar, Comal, and Hays Counties is diverted by barrier faults toward San Marcos Springs, a regional discharge point. (Lantz-PTT)

Texas↗
USGS1982

Triggering of large earthquakes by magma-chamber inflation, Izu Peninsula (Japan)

A close spatial and temporal association between three aseismic uplift episodes and subsequent large (M ≈ 7) earthquakes on the Izu Peninsula, Japan, suggests a causal relation. Quaternary geology, as well as studies by other workers, indicates a volcanic origin for the observed uplift, and we use a simple inflation model constrained by leveling data to compute the expected increments in normal and shear stress across faults that ruptured in the earthquakes. Using a Mohr-Coulomb criterion, we find that in two cases out of three, stress changes induced by inflation are in the correct sense to trigger failure. Although changes are no more than a few bars, they represent the equivalent of several decades to a century of secular stress buildup.

Izu Peninsula↗
USGS2022

A computer-aided approach for adapting stage-discharge ratings and characterizing uncertainties of streamflow data with discrete measurements

Relations between stage (water level) and discharge of streamflow through a natural channel are the result of time-varying processes, which are commonly described by time-varying stage-discharge ratings. Hydrographers with the U.S. Geological Survey successfully maintain the accuracy of streamflow data by manually applying time-tested approaches to adapt ratings to temporal changes in hydraulic conditions. The difficulty with the manual approach is that it is a subjective, time-consuming process that requires considerable skill and experience to implement. In addition, manual adjustments of ratings make quantification of resulting streamflow data uncertainties problematic. A computer-aided adaptive stage-discharge estimation approach is proposed to track sequential changes in the relation between stage and discharge at continuous-record streamgages. In this report, adaptations are based strictly on discrete measurement data that are then used to compute the magnitudes and uncertainties of streamflow. The approach entails the parameterization of a cubic regression spline (CRS) for the stage-discharge relation based on an existing rating or on a set of discrete measurements. A state-space model is then parameterized to track temporal changes in stage-discharge relations beginning with the initial CRS parameterization using discrete measurements. Finally, Kalman estimation is used with the state-space model to estimate the magnitude and uncertainty of flows. In a case study using data from streamgage U.S. Geological Survey 04122500 Marquette River at Scottville, Michigan, a five-parameter CRS model was estimated from data in an existing stage-discharge rating to provide an initial CRS parameter set for a state-space model. The initial CRS parameters were updated sequentially in a state-space model based on periodic discrete measurements of stage and discharge that spanned a 30-year period for this analysis. Additional analysis is needed to determine the timing of rapidly varying shifts more precisely in stage-discharge relations than the relatively infrequent discrete measurements currently enabled. Unit streamflow estimates based on flow in a local streamgaging network may provide a basis for adapting a stage-discharge rating at unit time intervals by augmenting discrete measurement data within the state-space model.

Michigan↗
USGS2000

Uncertainty estimation for resource assessment-an application to coal

The U.S. Geological Survey is conducting a national assessment of coal resources. As part of that assessment, a geostatistical procedure has been developed to estimate the uncertainty of coal resources for the historical categories of geological assurance: measured, indicated, inferred, and hypothetical coal. Data consist of spatially clustered coal thickness measurements from coal beds and/or zones that cover, in some cases, several thousand square kilometers. Our procedure involved trend removal, an examination of spatial correlation, computation of a sample semivariogram, and fitting a semivariogram model. This model provided standard deviations for the uncertainty estimates. The number of sample points (drill holes) in each historical category also was estimated. Measurement error in the thickness of the coal bed/zone was obtained from the fitted model or supplied exogenously. From this information approximate estimates of uncertainty on the historical categories were computed. We illustrate the methodology using drill hole data from the Harmon coal bed located in southwestern North Dakota. The methodology will be applied to approximately 50 coal data sets.

Mathematical Geology↗
USGS1976

The national coal-resources data system of the U.S. geological survey

The National Coal Resources Data System (NCRDS) was designed by the U.S. Geological Survey (USGS) to meet the increasing demands for rapid retrieval of information on coal location, quantity, quality, and accessibility. An interactive conversational query system devised by the USGS retrieves information from the data bank through a standard computer terminal. The system is being developed in two phases. Phase I, which currently is available on a limited basis, contains published areal resource and chemical data. The primary objective of this phase is to retrieve, calculate, and tabulate coal-resource data by area on a local, regional, or national scale. Factors available for retrieval include: state, county, quadrangle, township, coal field, coal bed, formation, geologic age, source and reliability of data, and coal-bed rank, thickness, overburden, and tonnage, or any combinations of variables. In addition, the chemical data items include individual values for proximate and ultimate analyses, BTU value, and several other physical and chemical tests. Information will be validated and deleted or updated as needed. Phase II is being developed to store, retrieve, and manipulate basic point source coal data (e.g., field observations, drill-hole logs), including geodetic location; bed thickness; depth of burial; moisture; ash; sulfur; major-, minor-, and trace-element content; heat value; and characteristics of overburden, roof rocks, and floor rocks. The computer system may be used to generate interactively structure-contour or isoline maps of the physical and chemical characteristics of a coal bed or to calculate coal resources. ?? 1976.

Computers & Geosciences↗
USGS2012

Methods for determining magnitude and frequency of floods in California, based on data through water year 2006

Methods for estimating the magnitude and frequency of floods in California that are not substantially affected by regulation or diversions have been updated. Annual peak-flow data through water year 2006 were analyzed for 771 streamflow-gaging stations (streamgages) in California having 10 or more years of data. Flood-frequency estimates were computed for the streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Low-outlier and historic information were incorporated into the flood-frequency analysis, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low outliers. Special methods for fitting the distribution were developed for streamgages in the desert region in southeastern California. Additionally, basin characteristics for the streamgages were computed by using a geographical information system. Regional regression analysis, using generalized least squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins in California that are outside of the southeastern desert region. Flood-frequency estimates and basin characteristics for 630 streamgages were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for the area of California outside of the desert region. The final regional regression equations are functions of drainage area and mean annual precipitation for four of the five regions. In one region, the Sierra Nevada region, the final equations are functions of drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression equations in all five regions range from 42.7 to 161.9 percent. For the desert region of California, an analysis of 33 streamgages was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the log-Pearson Type III distribution. The regional estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final regional regression equations are functions of drainage area. Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent. Annual peak-flow data through water year 2006 were analyzed for eight streamgages in California having 10 or more years of data considered to be affected by urbanization. Flood-frequency estimates were computed for the urban streamgages by fitting a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Regression analysis could not be used to develop flood-frequency estimation equations for urban streams because of the limited number of sites. Flood-frequency estimates for the eight urban sites were graphically compared to flood-frequency estimates for 630 non-urban sites. The regression equations developed from this study will be incorporated into the U.S. Geological Survey (USGS) StreamStats program. The StreamStats program is a Web-based application that provides streamflow statistics and basin characteristics for USGS streamgages and ungaged sites of interest. StreamStats can also compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in California.

California↗
USGS2017

Computing spatial correlation of ground motion intensities for ShakeMap

Modeling the spatial correlation of ground motion residuals, caused by coherent contributions from source, path, and site, can provide valuable loss and hazard information, as well as a more realistic depiction of ground motion intensities. The U.S. Geological Survey (USGS) software package, ShakeMap, utilizes a deterministic empirical approach to estimate median ground shaking in conjunction with observed seismic data. ShakeMap-based shaking estimates are used in concert with loss estimation algorithms to estimate fatalities and economic losses after significant seismic events around the globe. Incorporating the spatial correlation of ground motion residuals has been shown to improve seismic loss estimates. In particular, Park, Bazzuro, and Baker (Applications of Statistics and Probability in Civil Engineering, 2007) investigated computing spatially correlated random fields of residuals. However, for large scale ShakeMap grids, computational requirements of the method are prohibitive. In this work, a memory efficient algorithm is developed to compute the random fields and implemented using the ShakeMap framework. This new, iterative parallel algorithm is based on decay properties of an associated ground motion correlation function and is shown to significantly reduce computational requirements associated with adding spatial variability to the ShakeMap g round motion estimates. Further, we demonstrate and quantify the impact of adding peak ground motion spatial variability on resulting earthquake loss estimates.

Computers & Geosciences↗
USGS2021

A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek‐Hayward‐Calaveras Fault System, California

The Hayward fault in California's San Francisco Bay area produces large earthquakes, with the last occurring in 1868. We examine how physics‐based dynamic rupture modeling can be used to numerically simulate large earthquakes on not only the Hayward fault, but also its connected companions to the north and south, the Rodgers Creek and Calaveras faults. Equipped with a wealth of images of this fault system, including those of its 3D geology and 3D geometry, in addition to inferences about its interseismic creep‐rate pattern and rock‐friction behavior, we use a finite‐element computer code to perform 3D dynamic earthquake rupture simulations. We find that the rock properties affect the locations and amount of slip produced in our simulated large earthquakes. Crucial factors that control rupture behavior in our modeling are the earthquake nucleation locations, the fault geometry, and the data that reveal where the fault system is creeping or locked. Our findings suggest that large Rodgers Creek‐Hayward‐Calaveras‐Northern Calaveras (RC‐H‐C‐NC) fault‐system earthquakes may result from dynamic rupture that starts in a locked part of the fault system, but is then stopped by the creeping parts, leading to high‐magnitude‐6 earthquakes; or, from dynamic rupture that starts in a locked part of the fault system, then cascades through some of the creeping parts, leading to magnitude‐7 earthquakes.

California↗
USGS2012

Science in support of the Deepwater Horizon response

This introduction to the Special Feature presents the context for science during the Deepwater Horizon oil spill response, summarizes how scientific knowledge was integrated across disciplines and statutory responsibilities, identifies areas where scientific information was accurate and where it was not, and considers lessons learned and recommendations for future research and response. Scientific information was integrated within and across federal and state agencies, with input from nongovernmental scientists, across a diverse portfolio of needs—stopping the flow of oil, estimating the amount of oil, capturing and recovering the oil, tracking and forecasting surface oil, protecting coastal and oceanic wildlife and habitat, managing fisheries, and protecting the safety of seafood. Disciplines involved included atmospheric, oceanographic, biogeochemical, ecological, health, biological, and chemical sciences, physics, geology, and mechanical and chemical engineering. Platforms ranged from satellites and planes to ships, buoys, gliders, and remotely operated vehicles to laboratories and computer simulations. The unprecedented response effort depended directly on intense and extensive scientific and engineering data, information, and advice. Many valuable lessons were learned that should be applied to future events.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS1955

The Sudbury [Ontario] aeromagnetic map as a test of interpretation methods

The method of interpretation of aeromagnetic maps described by Vacquier, Steenland, Henderson, and Zietz (1951) is applied to several anomalies on the aeromagnetic map of part of Sudbury, Ontario. The resulting average computed depths deviate from the known depths by less than 10 percent. The aeromagnetic map is described and compared with the known surface geology.

Ontario↗
USGS2003

MODFLOW-2000 ground-water model-user guide to the Subsidence and Aquifer-System Compaction (SUB) Package

This report documents a computer program, the Subsidence and Aquifer-System Compaction (SUB) Package, to simulate aquifer-system compaction and land subsidence using the U.S. Geological Survey modular finite-difference ground-water flow model, MODFLOW-2000. The SUB Package simulates elastic (recoverable) compaction and expansion, and inelastic (permanent) compaction of compressible fine-grained beds (interbeds) within the aquifers. The deformation of the interbeds is caused by head or pore-pressure changes, and thus by changes in effective stress, within the interbeds. If the stress is less than the preconsolidation stress of the sediments, the deformation is elastic; if the stress is greater than the preconsolidation stress, the deformation is inelastic. The propagation of head changes within the interbeds is defined by a transient, one-dimensional (vertical) diffusion equation. This equation accounts for delayed release of water from storage or uptake of water into storage in the interbeds. Properties that control the timing of the storage changes are vertical hydraulic diffusivity and interbed thickness. The SUB Package supersedes the Interbed Storage Package (IBS1) for MODFLOW, which assumes that water is released from or taken into storage with changes in head in the aquifer within a single model time step and, therefore, can be reasonably used to simulate only thin interbeds. The SUB Package relaxes this assumption and can be used to simulate time-dependent drainage and compaction of thick interbeds and confining units. The time-dependent drainage can be turned off, in which case the SUB Package gives results identical to those from IBS1. Three sample problems illustrate the usefulness of the SUB Package. One sample problem verifies that the package works correctly. This sample problem simulates the drainage of a thick interbed in response to a step change in head in the adjacent aquifer and closely matches the analytical solution. A second sample problem illustrates the effects of seasonally varying discharge and recharge to an aquifer system with a thick interbed. A third sample problem simulates a multilayered regional ground-water basin. Model input files for the third sample problem are included in the appendix.

Open-File Report↗
USGS2015

Preliminary peak stage and streamflow data at selected USGS streamgaging stations for the South Carolina flood of October 2015

Heavy rainfall occurred across South Carolina during October 1–5, 2015, as a result of an upper atmospheric low-pressure system that funneled tropical moisture from Hurricane Joaquin into the State. The storm caused major flooding from the central to the coastal areas of South Carolina. Almost 27 inches of rain fell near Mount Pleasant in Charleston County during this period. U.S. Geological Survey streamgages recorded peaks of record at 17 locations, and 15 other locations had peaks that ranked in the top 5 for the period of record. During the October 2015 flood event, U.S. Geological Survey personnel made about 140 streamflow measurements at 86 locations to verify, update, or extend existing rating curves, which are used to compute streamflow from monitored river stage.

South Carolina↗
USGS1986

Distributed information system (water fact sheet)

During 1982-85, the Water Resources Division (WRD) of the U.S. Geological Survey (USGS) installed over 70 large minicomputers in offices across the country to support its mission in the science of hydrology. These computers are connected by a communications network that allows information to be shared among computers in each office. The computers and network together are known as the Distributed Information System (DIS). The computers are accessed through the use of more than 1500 terminals and minicomputers. The WRD has three fundamentally different needs for computing: data management; hydrologic analysis; and administration. Data management accounts for 50% of the computational workload of WRD because hydrologic data are collected in all 50 states, Puerto Rico, and the Pacific trust territories. Hydrologic analysis consists of 40% of the computational workload of WRD. Cost accounting, payroll, personnel records, and planning for WRD programs occupies an estimated 10% of the computer workload. The DIS communications network is shown on a map. (Lantz-PTT)

Open-File Report↗
USGS2009

Geomorphology and river dynamics of the lower Copper River, Alaska

Located in south-central Alaska, the Copper River drains an area of more than 24,000 square miles. The average annual flow of the river near its mouth is 63,600 cubic feet per second, but is highly variable between winter and summer. In the winter, flow averages approximately 11,700 cubic feet per second, and in the summer, due to snowmelt, rainfall, and glacial melt, flow averages approximately 113,000 cubic feet per second, an order of magnitude higher. About 15 miles upstream of its mouth, the Copper River flows past the face of Childs Glacier and enters a large, broad, delta. The Copper River Highway traverses this flood plain, and in 2008, 11 bridges were located along this section of the highway. The bridges cross several parts of the Copper River and in recent years, the changing course of the river has seriously damaged some of the bridges. Analysis of aerial photography from 1991, 1996, 2002, 2006, and 2007 indicates the eastward migration of a channel of the Copper River that has resulted in damage to the Copper River Highway near Mile 43.5. Migration of another channel in the flood plain has resulted in damage to the approach of Bridge 339. As a verification of channel change, flow measurements were made at bridges along the Copper River Highway in 2005–07. Analysis of the flow measurements indicate that the total flow of the Copper River has shifted from approximately 50 percent passing through the bridges at Mile 27, near the western edge of the flood plain, and 50 percent passing through the bridges at Mile 36–37 to approximately 5 percent passing through the bridges at Mile 27 and 95 percent through the bridges at Mile 36–37 during average flow periods. The U.S. Geological Survey’s Multi-Dimensional Surface-Water Modeling System was used to simulate water-surface elevation and velocity, and to compute bed shear stress at two areas where the Copper River is affecting the Copper River Highway. After calibration, the model was used to examine the effects that betterments, such as guide banks or bridge extensions, would have on flow conditions and to provide sound conceptual information that could help decide if a proposed betterment will work or determine potential problems that need to be addressed for a particular betterment. The ability of the model to simulate these hydraulic conditions was constrained by the accuracy and level of channel geometry detail, which is constantly changing in the lower Copper River.

Scientific Investigations Report↗
USGS1974

Digital-model study of ground-water hydrology, Columbia Basin Irrigation Project Area, Washington

Since 1952 water diverted from the Columbia River at Grand Coulee Dam has been used to irrigate parts of the Columbia Basin Irrigation Project area in eastern Washington, and as a result ground-water levels generally have risen in the area. The rapid increases in ground-water inflow, outflow, and storage from irrigation have created a need for a better understanding of the ground-water system before and after the start of irrigation to establish guidelines necessary for management of the area's ground-water resource. Data and information from previous geologic and hydrologic studies were used as a basis for quantitative analyses of ground-water inflow and outflow by means of digital computer models representing three major areas--Quincy Basin, Pasco Basin, and Royal Slope.

Washington↗