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Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California

Evidence of mineral alteration in a salt marsh subterranean estuary: Implications for carbon and trace element cycling

Subterranean estuaries (STE) in salt marshes are biogeochemically active zones where interactions between terrestrial groundwater and seawater drive complex cycling of carbon and trace elements, influenced by mineral dissolution. These systems, characterized by fine-grained organic-rich peat overlying permeable coastal aquifers, play a crucial role as a blue carbon sink, yet their geochemical dynamics remain poorly understood. We investigated dissolved trace elements, carbon, silica, and radium isotopes in a salt marsh STE (Sage Lot Pond, Waquoit Bay, MA) over seasonal and annual cycles. Our results reveal that groundwater and estuarine water circulation through marsh peat and aquifer sediments leads to enrichments of dissolved organic and inorganic carbon (DOC and DIC), Si, Ba, and Mn, with variable source/sink behavior of Fe and net removal of U. Submarine groundwater discharge dominated Ba fluxes, whereas pore water drainage from marsh peat acted as the main sink for U and source of Si. Fe cycling was variable, with terrestrial Fe largely removed as groundwater passed through the STE, consistent with Fe-sulfide and amorphous phase formation. Radium isotope ratios identified two distinct subsurface flow pathways, influenced by metal-oxide cycling and organic matter breakdown. Si production was decoupled from DIC, suggesting Si originates from mineral alteration, whereas DIC results from both mineral weathering and microbial respiration. Silicate mineral alteration, coupled with marsh pore water drainage, accounts for up to 16% of annual DIC exports (66 g C m −2 y −1 ), highlighting the importance of STEs in coastal carbon and trace element cycling, especially as marshes face environmental change.

Massachusetts

Utilizing hydrophones to detect streambed mobilization in the Wild and Scenic reach of the Rio Chama

This paper describes a study that deployed underwater acoustic sensors (hydrophones) to detect streambed mobilization in the Wild and Scenic reach of the Rio Chama, New Mexico. Fine sediment accumulation in the gravel‑cobble bed affects brown trout spawning habitat, and understanding incipient motion thresholds is essential for planning effective environmental flushing flows released from El Vado Dam. Two hydrophone stations were operated during 2021–2022, capturing audio data during a high‑flow pulse in late 2021. Acoustic processing techniques, including spectral analysis and threshold‑based impact detection, were used to identify sediment‑generated noise associated with coarse sediment transport. Results indicate detectable sediment mobilization during the high‑flow pulse, demonstrating hydrophones’ potential as a passive monitoring tool for environmental flow planning and sediment‑management decision support.

Conference Paper

Turbidite correlation for paleoseismology

Marine turbidite paleoseismology relies on the assumption of synchronous triggering of turbidity currents by earthquake shaking to infer rupture extent and recurrence. Such inference commonly depends on age dating and correlation of the physical stratigraphy of deposits carried by turbidity currents (i.e., turbidites) across great distances. Along the Cascadia subduction zone, which lies offshore the Pacific Northwest, USA, turbidite facies in core photographs, X-ray computed tomography images, and magnetic susceptibility (MS) data exhibit differences in character over relatively short distances, which implies that not all deposits can be correlated with confidence. Thus, subjective correlation based on expected similarity over great distances and weak age constraints does not independently support paleoseismic models. We present a new method for correlating turbidites along the Cascadia margin that can yield a more objective and repeatable stratigraphic framework to underpin earthquake recurrence. We use dynamic time warping to correlate MS logs and measure correlation coefficients of core pairs to evaluate correlation strength. We then compare these measures to a distribution of correlation coefficients of randomly generated turbidite sequences and find that only a small number of core pairs can be correlated more confidently than randomly stacked turbidites. This methodology promises a more robust correlation strategy for future stratigraphic studies.

Oregon, Washington

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş

Paleoseismology and paleogeodesy using coral microatolls

Establishing the rupture extent and slip distribution of individual paleo-earthquakes is vital for assessing fault behavior including the persistence of rupture segmentation, recurrence patterns, and similarity of successive events, key issues in both fault mechanics and hazard assessment. Techniques with high temporal and geodetic precision as well as a wide distribution of study sites are necessary to investigate past earthquakes in such detail. Coral microatoll growth is one of the best types of geologic record for paleoseismology and paleogeodesy given these needs, as it provides long, continuous, widely distributed records of centimeter-scale vertical tectonic motion with potentially annual-level temporal precision. This chapter describes the process of interpreting microatoll growth records to obtain time series of relative sea level, tectonic vertical deformation fields, and finally slip and coupling parameters on an underlying fault interface.

Book chapter

Integration of rupture directivity models for the US National Seismic Hazard Model

Several rupture directivity models (DMs) have been developed in recent years to describe the near-source spatial variations in ground motion amplitudes related to propagation of rupture along the fault. We recently organized an effort towards incorporating these directivity effects into the USGS National Seismic Hazard Model (NSHM), by first evaluating the community's work and potential methods to implement directivity adjustments into probabilistic seismic hazard analysis (PSHA). Guided by this evaluation and comparison among the considered DMs, we selected an approach that can be readily implemented into the USGS hazard software, that provides an azimuthally varying adjustment to the median ground motion and its aleatory variability. This method allows assessment of the impact on hazard levels and provides a platform to test the DM amplification predictions using a generalized coordinate system, necessary for consistent calculation of source-to-site distance terms for complex ruptures. We give examples of the directivity-related impact on hazard, progressing from a simple, hypothetical rupture, to more complex fault systems, composed of multiple rupture segments and sources. The directivity adjustments were constrained to strike-slip faulting, where DMs have good agreement. We find that rupture directivity adjustments using a simple median and aleatory adjustment approach can impact hazard both from a site perspective and on a regional scale, increasing shaking off the end of the fault trace up to 30--40\% and potentially reducing it for sites along strike. Statewide hazard maps of California show that the change in shaking along major faults can be a factor to consider for assessing long-period (>ls) near-source effects within the USGS NSHM going forward, reaching up to 10--20\%. Finally, we suggest consideration of minimum parameter ranges and baseline requirements as future DMs are developed to minimize single approach adaptations, to enable more consistent application within both ground motion and hazard studies.

Earthquake Spectra

Cooling perspectives on the risk of pathogenic viruses from thawing permafrost

Climate change is inducing wide-scale permafrost thaw in the Arctic and subarctic, triggering concerns that long-dormant pathogens could reemerge from the thawing ground and initiate epidemics or pandemics. Viruses, as opposed to bacterial pathogens, garner particular interest because outbreaks cannot be controlled with antibiotics, though the effects can be mitigated by vaccines and newer antiviral drugs. To evaluate the potential hazards posed by viral pathogens emerging from thawing permafrost, we review information from a diverse range of disciplines. This includes efforts to recover infectious virus from human remains, studies on disease occurrence in polar animal populations, investigations into viral persistence and infectivity in permafrost, and assessments of human exposure to the enormous viral diversity present in the environment. Based on currently available knowledge, we conclude that the risk posed by viruses from thawing permafrost is no greater than viruses in other environments such as temperate soils and aquatic systems.

mSystems

Tringa flavipes (Lesser Yellowlegs) from separate breeding sites subdivides the Prairie Pothole Region in space and time during southbound migration

Some staging regions support multiple groups of the same migratory species, each of which may use the region differently. Characterizing the ways, in which separate groups use such regions can therefore help to identify vulnerabilities during this sensitive period of the annual cycle. The Prairie Pothole Region (PPR) is a massive wetland complex in the northern Great Plains of North America used by ∼11 million shorebirds during migration. The PPR has been heavily modified by agriculture and is experiencing varied effects of global climate change, threatening the health of the shorebirds that rely on it. Here, we used 6 seasons of southbound tracking data of Tringa flavipes (Lesser Yellowlegs)—a long-distance migratory shorebird species with an estimated population decline of 63% over the last 4 decades—from 9 sites across their breeding range to explore differences in migratory behavior within this important staging region. We found that 75% of tracked individuals used the region during southbound migration, and T. flavipes from different breeding sites detoured 110–875 km from their most direct migratory route to access the PPR. Individuals that arrived later stayed longer and made more stops within the region than those that arrived early. Individuals originating from different breeding sites also displayed spatial and temporal segregation within the region: T. flavipes from southwest and central Alaska relied heavily on the northwestern PPR, while those from Canada used the central and southeastern portions of the PPR. Finally, timing of use varied among groups, but the southeastern PPR became increasingly important over the course of the southbound migratory window, as other wetlands likely dried out. Our study highlights the portions of the PPR of critical importance to migrating T. flavipes and the diversity of ways, in which different groups from within the same species can use a single staging region.

Alaska, Manitoba, Northwest Territories, Ontario,

Updating the crustal fault model for the 2023 National Seismic Hazard Model for Alaska

We present the crustal fault model for Alaska, based on geologic observations, as a primary input for the 2023 revision of the U.S. Geological Survey National Seismic Hazard Model. We update the 2013 Alaska Quaternary fault and fold database to produce a simplified model of 105 fault sections and four fault zone polygons with basic geologic parameters including slip sense and rate. Significant updates include the following: (1) a slip rate of ∼53 mm/year on the Queen Charlotte Fault indicating it accommodates all of the plate boundary motion; (2) quantified slip rates on megathrust splay faults in the southern Prince William Sound region and near Kodiak Island; (3) improved details of structures in the Chugach-St. Elias orogen; (4) revision of the Castle Mountain Fault from right-lateral slip to a predominantly reverse fault; (5) improved Interior Alaska tectonic models that clarify relationships between the Denali, Totschunda, and thrust faults on both sides of the Alaska Range; (6) identified large earthquake sources in the eastern Brooks Range; and (7) omission of the Chatham Strait section of the Denali Fault. The fault model underscores that the collision of the Yakutat microplate is the dominant driver of active crustal faulting in most of Alaska.

Alaska, Yukon

3D Converted wave reverse time migration imaging

We describe a newly developed method for recovering high-resolution images of seismic discontinuities, such as subducting slabs, in 3D. Our method makes use of converted S → P or P → S waves observed by dense arrays of seismometers to infer the locations and relative strengths of seismic discontinuities at depth in a target region. Observed direct and converted waves are backpropagated to their times of origin. The time-reversed wavefield is then separated into its constituent P and S components via the Helmholtz decomposition, and those separated wavefields are used to compute imaging functions that characterize the locations and relative strengths of seismic discontinuities. Imaging functions may be designed to use either S → P or P → S waves, so that users can target those arrivals expected to be most dominant in a given dataset. We have previously demonstrated the efficacy of our method in two dimensions, and we now present a 3D implementation of our technique which addresses the significant computational challenges posed by the size of volumetric wavefield data in three dimensions. Through a series of synthetic examples, we demonstrate that our method is capable of recovering the fine scale structure of a subducting slab given realistic station coverage and earthquake sources. We investigate optimal seismic station geometries for our technique and explore image interpretability in regions with poor data coverage. We find that linear station geometries yield more optimal, interpretable imaging functions than collections of small arrays can. We also show that our method can successfully recover bothS → P or P → S images when realistic shear earthquake sources are used, and we explore the additional computational challenges presented by the high frequency content of S waves. Our results demonstrate the potential for our technique to recover high-resolution information about subducting slabs in real-world regions, given that relatively sparse seismic arrays with only approximately 100 stations are capable of recovering interpretable imaging functions from just a few realistic earthquake sources for multiple discontinuities at significant depth in an area of approximately 400~sq~km.

Seismica

An optimized network for phosphorus load monitoring for Lake Okeechobee, Florida

Phosphorus load data were evaluated for Lake Okeechobee, Florida, for water years 1982 through 1991. Standard errors for load estimates were computed from available phosphorus concentration and daily discharge data. Components of error were associated with uncertainty in concentration and discharge data and were calculated for existing conditions and for 6 alternative load-monitoring scenarios for each of 48 distinct inflows. Benefit-cost ratios were computed for each alternative monitoring scenario at each site by dividing estimated reductions in load uncertainty by the 5-year average costs of each scenario in 1992 dollars. Absolute and marginal benefit-cost ratios were compared in an iterative optimization scheme to determine the most cost-effective combination of discharge and concentration monitoring scenarios for the lake. If the current (1992) discharge-monitoring network around the lake is maintained, the water-quality sampling at each inflow site twice each year is continued, and the nature of loading remains the same, the standard error of computed mean-annual load is estimated at about 98 metric tons per year compared to an absolute loading rate (inflows and outflows) of 530 metric tons per year. This produces a relative uncertainty of nearly 20 percent. The standard error in load can be reduced to about 20 metric tons per year (4 percent) by adopting an optimized set of monitoring alternatives at a cost of an additional $200,000 per year. The final optimized network prescribes changes to improve both concentration and discharge monitoring. These changes include the addition of intensive sampling with automatic samplers at 11 sites, the initiation of event-based sampling by observers at another 5 sites, the continuation of periodic sampling 12 times per year at 1 site, the installation of acoustic velocity meters to improve discharge gaging at 9 sites, and the improvement of a discharge rating at 1 site.

Florida

Quality of groundwater used for domestic supply in the eastern Sacramento Valley and adjacent foothills, California

Summary More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the eastern Sacramento Valley and adjacent foothills where more than 25,000 residents are estimated to use privately owned domestic wells. Study results show that inorganic and organic constituents in groundwater were present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 8 and 3 percent, respectively, of the aquifer area used for domestic drinking-water supply (herein, “domestic groundwater resources”; fig. 1). The only inorganic constituent detected above regulatory benchmarks was arsenic. The only organic constituent exceeding regulatory benchmarks was the fumigant 1,2,3-trichloropropane (1,2,3-TCP). Three additional organic constituents—the disinfection by-product chloroform, the gasoline oxygenate methyl tert -butyl ether (MTBE), and the solvent tetrachloroethene (PCE)—were detected at low concentrations below one-tenth of regulatory benchmarks in 34, 10, and 10 percent of domestic groundwater resources, respectively. Total dissolved solids (TDS), iron, and manganese exceeded non-regulatory aesthetic guidelines for drinking water in 5, 10, and 26 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFASs) were detected in 29 percent of domestic groundwater resources,with 5 percent exceeding the recently enacted (April 2024) U.S. Environmental Protection Agency MCLs. Total coliform and enterococci bacteria were detected in 13 and 8 percent of domestic groundwater resources, respectively. Redox sensitive constituents in this study included arsenic, manganese, nitrate, and iron. In the lower elevation portions of the eastern Sacramento Valley study area, reducing conditions in groundwater aquifers promote elevated arsenic, iron, and manganese, and conversely lower concentrations of nitrate. The presence of the volatile organic compound (VOC) 1,2,3-TCP was related to its past history in select agricultural land uses (on orchards or vineyards) in the Sacramento Valley; however, unlike in the San Joaquin Valley where orchards and vineyards are more common, its detection frequency was low (only detected in one well in this study). Chloroform was frequently detected in this study at low levels. Chloroform is a disinfection byproduct commonly found in domestic wells treated by shock chlorination. The solvent PCE is among the most frequently detected VOCs in groundwater, which is primarily related to its long history of use and its persistence in groundwater in oxic conditions. The gasoline oxygenate MTBE was a contaminant introduced to groundwater through atmospheric exchange when it was used as a fuel additive to decrease smog inducing emissions from vehicles. Its occurrence in groundwater at low levels is expected and makes it a potentially useful tracer of relatively recent recharge water being withdrawn from wells. The PFASs are anthropogenic chemicals with hundreds of uses, and they have been incorporated into many different products, processes, and applications worldwide. Like MTBE, the occurrence of PFASs in groundwater may be in part due to atmospheric exchange, but there are several other pathways that contribute PFASs to the environment.

California

The U.S. Geological Survey 2025 Puerto Rico and U.S. Virgin Islands time-independent earthquake rupture forecast

We present the 2025 U.S. Geological Survey Puerto Rico and U.S. Virgin Islands (PRVI) time‐independent earthquake rupture forecast (ERF), developed for the 2025 update to the National Seismic Hazard Model (NSHM) for PRVI. The updated ERF improves upon a prior model from 2003, including an expanded fault inventory with slip‐rate estimates, updated seismicity catalogs, and refined subduction zone geometries and deformation models. It applies the fault‐system inversion methodology to solve for rates of ruptures on modeled faults, adapted from the 2023 NSHM (NSHM23) for the western United States, including the first application of the inversion to model rates on a U.S. subduction interface. Off‐fault and intraslab seismicity are constrained by observed seismicity and use updated methods developed for NSHM23. Uncertainties in model components are substantial, and the ERF represents epistemic uncertainties through a comprehensive logic tree consisting of 1.7 billion logic‐tree branches combined across all sources.

Puerto Rico, U.S. Virgin Islands

Trace elements in some rocks and slag from the Yemen Arab Republic and their bearing on the iron ore near Sa'dah

Thirty-seven samples of rocks, saprolite, laterite, gossan, and slag were collected in the Yemen Arab Republic during June-July 1975 when field work was conducted to refine an interpretation of the regional geology made from LANDSAT-1 images by M. J. Grolier. These samples we reanalyzed in the laboratories of the U. S. Geological Survey, and the results were interpreted for use in programs of economic development as a guide for the evaluation of mineral resources in the Yemen Arab Republic. The work was undertaken as part of the program of the U. S. Agency for International Development with the cooperation of the Mineral and Petroleum Authority, Ministry of Economy, Yemen Arab Republic.

Open-File Report

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California

Stream habitat characteristics at selected sites in the Georgia-Florida coastal plain

Habitat characterization is part of a multidisciplinary approach to water-quality assessment implemented by the National Water-Quality Assessment Program. Habitat data were collected in the Georgia-Florida Coastal Plain study unit at 24 sites during 1993-95. Data were collected for habitat characteristics at three spatial scales: basin, segment, and reach. Basin data include physiography, land resource provinces, and land use, providing a description of the environmental setting at each site. Segment data include length, gradient, and sinuosity. A Kendall correlation analysis performed on segment characteristics and the log-of-basin area showed a correlation between segment gradient and the log-of-basin area and a correlation between sinuosity and segment length. Reach data consist of field-collected measurements of both instream and riparian habitats. Sand and detritus were the most common channel-bed substrates among the sampled sites. Measurements of channel width, water depth, and bank width and height were used to create cross-sectional profiles of each sampled area. Elevations of selected durations plotted on cross sections illustrated the percentage of time that the banks were inundated at each site. Sites were divided into two groups based on duration of bank inundation (less than or equal to 1 percent and greater than 1 percent). Bank woody vegetation was also sampled and a clustering algorithm known as Two-Way INdicator SPecies ANalysis (TWINSPAN) was used to analyze these data. TWINSPAN divided the sites into two groups based on their vegetation composition. A statistical comparison of the two types of site groups (duration of bank inundation and vegetation) was performed. The significant association between these groups was consistent with the hypothesis that inundation frequency affected riparian vegetation.

Florida, Georgia

Technique for estimating magnitude and frequency of peak flows in Maryland

A convenient and reliable technique for estimating flood magnitudes is required for effective flood-plain management and for the efficient design of bridges, culverts, embankments, and flood-protection structures. Methods are presented for estimating peak-flow magnitudes of selected frequencies, ranging from 2 to 500 years, for all nontidal drainage basins in Maryland. The methods were developed by generalized least-squares regression techniques using data from 219 gaged basins in and near Maryland. The State is divided into five hydrologic regions: the Appalachian Plateaus and Allegheny Ridges region, the Blue Ridge and Great Valley region, the Piedmont region, the Western Coastal Plain region, and the Eastern Coastal Plain region. These regions correspond to the physiographic provinces of the State, with the exceptions that (1) the Coastal Plain Province is divided into two hydrologic regions, and (2) there is no distinct hydrologic region corresponding to the Valley and Ridge Province as it is divided into its constituent Allegheny Ridges and Great Valley subdivisions. Sets of equations for calculating peak discharges based on physical basin characteristics are provided for each of the regions. Based on the peak-flow equations, methods for estimating peak flows are presented for ungaged and gaged streams in Maryland. The methods and equations are supported by generalized least-squares analysis of basin and flood-frequency characteristics data from 219 drainage basins in and near Maryland. estimates for each of the five regions are calculated using combinations of the fol-lowing basin characteristics: drainage area, forest cover, basin relief, carbonate rock coverage, storage, and runoff-curve number. Drainage area contributes to the estimate in all five study regions. Carbonate rock coverage is used only in the Blue Ridge and Great Valley region. Storage and runoff-curve number are used solely in the Eastern Coastal Plain region. All other basin characteristics are used in two or more regions. Standard errors of estimate for the regression equations range from 19 to 31 percent in the Appalachian Plateaus and Allegheny Ridges region, 34 to 47 percent in the Blue Ridge and Great Valley region, 33 to 48 percent in the Piedmont region, 45 to 64 percent in the Western Coastal Plain region, and 36 to 42 percent in the Eastern Coastal Plain region.

Maryland