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USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗

USGS2026

Development of liquefaction-targeted design basis in U.S. seismic provisions

Seismic design criteria for new buildings in the United States have historically focused on life safety performance objectives through minimizing the potential for structural collapse. Development of design criteria to meet this performance objective has evolved over time, leading to the current, risk-targeted maximum considered earthquake (MCE R ) design basis. Corresponding MCE R seismic design loads incorporate the full range of probabilistic ground motion hazard information available from U.S. Geological Survey National Seismic Hazard Models, as well as a representation of the uncertainty in structural collapse capacity. Despite these considerable advances in structural design criteria, guidelines for geotechnical hazards such as liquefaction-induced damage, which continue to be based on uniform ground-shaking hazard (i.e., MCE ground motions), are not well-connected with risk-based, collapse prevention performance objectives. This study, undertaken as part of Building Seismic Safety Council efforts to update recommended seismic provisions through the National Earthquake Hazards Reduction Program, presents probabilistic, liquefaction-targeted design objectives and corresponding ground motion parameters, with a focus on improving consistency in first-level screening criteria for liquefaction hazard assessment. This study identifies a potential maximum acceptable annualized probability of liquefaction triggering ( P L,max ) of 2.5% in 50 years, above which liquefaction consequences and potential mitigation measures would be considered. The P L,max -based design basis is calibrated to effective probabilistic liquefaction hazard levels obtained in practice using current MCE peak ground accelerations, and could be implemented via a new liquefaction-targeted maximum considered earthquake (MCE L ) peak ground acceleration ( PGA L ). The proposed PGA L is derived from probabilistic liquefaction hazard curves and includes uncertainties inherent to liquefaction hazard modeling. The potential design effects of the proposed PGA L are demonstrated via comparison with current MCE PGA levels, effects on first-level liquefaction screening analyses, and improvements in the consistency of P L,max levels across the United States, and for a wide range of site conditions.

conterminous United States↗

USGS2025

ShakeAlert®—Communication, education, outreach and technical engagement strategic vision

Executive Summary In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert ® research and in 2012 the ShakeAlert demonstration system began testing ( Given and others, 2018 ). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States ( Jaiswal and others, 2015 ), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes. The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert. Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities. Focus Areas Technical engagement.— The objective of this focus area is to expand and broaden ShakeAlert technical engagement and implementation. External engagement.— This focus area targets engagement in long-term communication, education, and outreach planning, implementation, and evaluation. Internal engagement.— The purpose of this focus area is to build and sustain a robust infrastructure to optimize collaboration, information sharing, and project planning among the community of stakeholders charged with implementing ShakeAlert CEO&TE. Priorities The enumeration of the five priorities listed below does not suggest priority ranking. Public safety, preparedness, and resilience; Technical implementation and engagement; Consistent messaging and communication; Integration with other Federal and State earthquake hazards products; and Educational resources development and dissemination. This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages. The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.

Circular↗

USGS1999

Comparison of two approaches for determining ground-water discharge and pumpage in the lower Arkansas River Basin, Colorado, 1997-98

In March 1994, the Colorado Division of Water Resources (CDWR) adopted “Rules Governing the Measurement of Tributary Ground Water Diversions Located in the Arkansas River Basin” (Office of the State Engineer, 1994); these initial rules were amended in February 1996 (Office of the State Engineer, 1996). The amended rules require users of wells that divert tributary ground water to annually report the water pumped monthly by each well. The rules allow a well owner to report the pumpage measured by a totalizing flowmeter (TFM) or pumpage determined from electrical power data and a power conversion coefficient (PCC) (Hurr and Litke, 1989). Opinions by representatives of the State of Kansas, presented before the Special Master hearing a court case [State of Kansas v. State of Colorado, No. 105 Original (1996)] concerning post-Compact well pumping, stated that the PCC approach does not provide the same level of accuracy and reliability as a TFM when used to determine pumpage. In 1997, the U.S. Geological Survey (USGS), in cooperation with the CDWR, began a 2-year study to compare ground-water pumpage estimates made using the TFM and the PCC approaches. The study area was along the Arkansas River between Pueblo, Colorado, and the Colorado-Kansas State line (fig. 1). The two approaches for estimating ground-water discharge and pumpage were compared for more than 100 wells completed in the alluvial aquifer of the Arkansas River Basin. The TFM approach uses an inline flowmeter to directly measure instantaneous discharge and the total volume of water pumped at a well. The PCC approach uses electrical power consumption records and a power conversion coefficient to estimate the pumpage at ground-water wells. This executive summary describes the results of the comparison of the two approaches. Specifically, (1) the differences in instantaneous discharge measured with three portable flowmeters and measured with an inline TFM are evaluated, and the statistical differences in paired instantaneous discharge between the two approaches are determined; (2) short- and long-term variations in the PCC’s are presented; (3) differences in pumpage between the two approaches are evaluated, and the statistical differences in pumpage between the two approaches are determined; (4) potential sources of discrepancy between pumpage estimates are discussed; and (5) differences in total network pumpage using the two approaches are presented. During the irrigation seasons of 1997 and 1998, instantaneous discharge and electrical power demand were measured at randomly selected wells to determine PCC’s. At more than 100 wells, the PCC’s determined during the 1998 season were applied to total electrical power consumption data that was recorded between the initial and final readings at each network well site in 1998 to estimate total ground-water pumpage. At each site, an inline TFM was installed in a full-flowing, acceptable test section of pipe on the discharge side of the pump where the measurement of discharge was made. Measurements of instantaneous ground-water discharge also were made using three different types of portable flowmeters. The average velocity multiplied by the cross-sectional area of the discharge pipe was used to compute the discharge in gallons per minute. Whenever possible, discharge measurements were made at each network site using all three types of portable flowmeters.

Colorado↗

USGS2024

The importance of nodal plane orientation diversity for earthquake focal mechanism stress inversions

Inversions of earthquake focal mechanisms are among the most accessible and reliable methods for determining crustal stress. However, the use of this method varies widely, and assumptions that underpin it are often violated, potentially compromising stress estimates. We investigate the consequences of violating the little-studied assumption that the focal mechanisms have diverse orientations. Our approach is to employ data-informed synthetic mechanisms, with nodal plane orientations defined by recent earthquake lineaments in the Midland Basin, western Texas, and rakes consistent with slip in the mapped stress field. Using both the traditional stress inversion method that assumes constant shear stress magnitudes on the causative faults as well as a recently published variable shear stress method, we show that low fault plane diversity can cause maximum horizontal stress ( S Hmax ) orientation and relative principal stress magnitude (faulting regime) estimates to differ markedly from the true values. This problem is compounded for catalogs with even modest amounts of noise (≤15°) or few (e.g., 20) mechanisms. Significantly, traditional approaches for quantifying uncertainty such as the bootstrap can severely underestimate the true uncertainty under these circumstances. To remedy this, we provide simple tools to quantify nodal plane orientation diversity and stress inversion reliability.

Geological Society of London Special Publications↗

USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗

USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗

USGS2017