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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 37 records · Page 2Linked to original sources
USGS2001

Remote rainfall sensing for landslide hazard analysis

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

Open-File Report↗
USGS2017

The Volcano Disaster Assistance Program—Helping to save lives worldwide for more than 30 years

What do you do when a sleeping volcano roars back to life? For more than three decades, countries around the world have called upon the U.S. Geological Survey’s (USGS) Volcano Disaster Assistance Program (VDAP) to contribute expertise and equipment in times of crisis. Co-funded by the USGS and the U.S. Agency for International Development’s Office of U.S. Foreign Disaster Assistance (USAID/OFDA), VDAP has evolved and grown over the years, adding newly developed monitoring technologies, training and exchange programs, and eruption forecasting methodologies to greatly expand global capabilities that mitigate the impacts of volcanic hazards. These advances, in turn, strengthen the ability of the United States to respond to its own volcanic events. VDAP was formed in 1986 in response to the devastating volcanic mudflow triggered by an eruption of Nevado del Ruiz volcano in Colombia. The mudflow destroyed the city of Armero on the night of November 13, 1985, killing more than 25,000 people in the city and surrounding areas. Sadly, the tragedy was avoidable. Better education of the local population and clear communication between scientists and public officials could have allowed warnings to be received, understood, and acted upon prior to the disaster. VDAP strives to ensure that such a tragedy will never happen again. The program’s mission is to assist foreign partners, at their request, in volcano monitoring and empower them to take the lead in mitigating hazards at their country’s threatening volcanoes. Since 1986, team members have responded to over 70 major volcanic crises at more than 50 volcanoes and have strengthened response capacity in 12 countries. The VDAP team consists of approximately 20 geologists, geophysicists, and engineers, who are based out of the USGS Cascades Volcano Observatory in Vancouver, Washington. In 2016, VDAP was a finalist for the Samuel J. Heyman Service to America Medal for its work in improving volcano readiness and warning systems worldwide, helping countries to forecast eruptions, save lives, and reduce economic losses while enhancing America’s ability to respond to domestic volcanic events.

Fact Sheet↗
USGS2007

PAGER - Rapid Assessment of an Earthquake's Impact

PAGER (Prompt Assessment of Global Earthquakes for Response) is an automated system to rapidly assess the number of people and regions exposed to severe shaking by an earthquake, and inform emergency responders, government agencies, and the media to the scope of the potential disaster. PAGER monitors the U.S. Geological Survey?s near real-time U.S. and global earthquake detections and automatically identifies events that are of societal importance, well in advance of ground-truth or news accounts.

Fact Sheet↗
USGS2023

Flood warning toolset for the Sabinal River near Utopia, Texas

Introduction Floods are one of the most frequent and expensive natural disasters that occur across the United States. Rapid, high-water events that occur in local areas—flash floods—are especially difficult for emergency managers to predict and provide advance warning to the public, and insufficient data can hamper postflood recovery efforts. Central Texas is hilly, and it is known as a “flash flood alley” because of its high-intensity rains, shallow soils, and steep terrain, all of which combined can result in loss of life and property damage. For example, the flash flood event during July 2002 claimed 12 lives in central Texas, including 1 in the town of Utopia, which is on the east bank of the Sabinal River in a flash-flood-prone area along the Balcones Escarpment. During the flood event, the peak discharge recorded on July 5, 2002, at U.S. Geological Survey (USGS) streamgage 08198000 Sabinal River near Sabinal, Tex. (hereinafter referred to as the “Sabinal gage”), was 108,000 cubic feet per second (corresponding to a stream stage [also called gage height] of 33.74 feet). To put the 2002 flood into context, during a typical year the median daily discharge in the Sabinal River at the Sabinal gage is only about 23 cubic feet per second. In 2021, the USGS, in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, developed a flood warning toolset for the Sabinal River near Utopia. This study builds on earlier USGS flood work on the Medina River in Bandera County. The newly developed toolset consists of a newly installed USGS streamgage to collect continuous stream stage data (streamgage 08197970 Sabinal River at Utopia, Tex.; hereinafter referred to as the “Utopia gage”) 13 miles upstream from the Sabinal gage, a hydraulic model developed for the Sabinal River near Utopia, and an online library of digital flood-inundation maps referenced to the stream stage at the Utopia gage.

Texas↗
USGS2023

A conceptual framework for estimation of initial emergency food and water resource requirements in disasters

Many households lack the necessary food and water supplies to sustain themselves for more than three days during a disaster. Community vulnerability assessments can be used to identify households with more pressing needs for emergency food and water resources. It is critical that these assessments include the interaction between physical impacts to lifeline infrastructure and the social vulnerabilities of food and water insecurity to prioritize, allocate, and distribute emergency resources. In this paper, we review and synthesize relevant literature to propose a new multidisciplinary conceptual framework of community vulnerability assessment for estimating initial emergency food and water resource requirements in a developed country. Using the framework as a guide, we illustrate its practical application through a simplified, deterministic model of initial resource requirements in disaster response, and offer a quantitative, comprehensive description of its application within the geophysical hazard context of the “ShakeOut” scenario—a major M w 7.8 earthquake on California's San Andreas fault , occurring within the Los Angeles Basin, CA (USA) region. Model results estimate that 999,027 households (2,947,130 residents) will require initial emergency food and water resource requirements. Estimates include about 6 million meals and 9 million liters of water, concentrated in Lancaster-Palmdale, El Monte-Baldwin Park, East Los Angeles-Downey in Los Angeles County, the Coachella Valley (Riverside County), and in populated areas of San Bernardino County. A sensitivity analysis of social vulnerability interactions with utility service outages investigates the influence of food insecurity on the amplification of resource needs. This study establishes fundamental knowledge at the nexus of natural hazards, critical infrastructure disruptions, and social vulnerability by providing initial estimates of emergency resource demand while advancing the understanding of social inequity in emergency resource access.

International Journal of Disaster Risk Reduction↗
USGS2022

Long-term ocean observing for international capacity development around tsunami early warning

The 2004 magnitude (M) 9.1 Sumatra-Andaman Islands earthquake in the Indian Ocean triggered the deadliest tsunami ever, killing more than 230,000 people. In response, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) established three additional Intergovernmental Coordination Groups (ICGs) for the Tsunami and Other Coastal Hazards Early Warning System: for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS), for the Indian Ocean, and for the Northeastern Atlantic, Mediterranean, and Connected Seas. Along with the ICG for the Pacific Ocean, which was established in 1965, one of the goals of the new ICGs was to improve earthquake and tsunami monitoring and early warning. This need was further demonstrated by the 2011 Great East Japan (Tōhoku-oki) earthquake and tsunami, which killed more than 20,000 people, and other destructive tsunamis that occurred in the Solomon Islands, Samoa, Tonga, Chile, Indonesia, and Peru. In response to the call to action by the UN Decade of Ocean Science for Sustainable Development (2021–2030), as well as the desired safe ocean outcome (von Hillebrandt-Andrade et al., 2021), the Intergovernmental Oceanographic Commission (IOC) of UNESCO approved the Ocean Decade Tsunami Programme in June 2021. One of its goals is to develop the capability to issue actionable alerts for tsunamis from all sources with minimum uncertainty within 10 minutes (Angove et al., 2019). While laudable, this goal presents complexities. Currently, warning depends on quick detection as well as the location and initial magnitude estimates of an earthquake that may generate a tsunami. Other factors that affect tsunamis, such as the faulting mechanism (how the faults slide past each other) and areal extent of the earthquake, currently take at least 20–30 minutes to forecast and are still subject to large uncertainties. Hence, agencies charged with tsunami early warning need to broadcast public alerts within minutes after an earthquake occurs but may struggle to meet this 10-minute goal without further technological advances, some of which are outlined in this article. To reduce loss of life through adequate tsunami warning requires global ocean-based seismic, sea level, and geodetic initiatives to detect high-impact earthquakes and tsunamis, combined with sufficient communication and education so that people know how to respond when they receive alerts and warnings. The United Nations International Strategy for Disaster Reduction defines an early warning system as “a set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities, and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss” (UNISDR, 2012). In short, a successful early warning system requires technology coupled with human factors (Kelman and Glantz, 2014). In this article, we explore case studies from Japan and Canada, where scientists are leading the way in incorporating ocean observing capabilities in their early warning systems. We also explore advancements and challenges in the Caribbean, an area with a complex tectonic environment that would benefit greatly from increased global ocean observing capabilities. We also explore physical and social science interventions necessary to reduce loss of life.

Oceanography↗
USGS2009

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter↗
USGS2016

Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics

Distance metrics play significant roles in spatial modeling tasks, such as flood inundation (Tucker and Hancock 2010), stream extraction (Stanislawski et al. 2015), power line routing (Kiessling et al. 2003) and analysis of surface pollutants such as nitrogen (Harms et al. 2009). Avalanche risk is based on slope, aspect, and curvature, all directly computed from distance metrics (Gutiérrez 2012). Distance metrics anchor variogram analysis, kernel estimation, and spatial interpolation (Cressie 1993). Several approaches are employed to measure distance. Planar metrics measure straight line distance between two points (“as the crow flies”) and are simple and intuitive, but suffer from uncertainties. Planar metrics assume that Digital Elevation Model (DEM) pixels are rigid and flat, as tiny facets of ceramic tile approximating a continuous terrain surface. In truth, terrain can bend, twist and undulate within each pixel. Work with Light Detection and Ranging (lidar) data or High Resolution Topography to achieve precise measurements present challenges, as filtering can eliminate or distort significant features (Passalacqua et al. 2015). The current availability of lidar data is far from comprehensive in developed nations, and non-existent in many rural and undeveloped regions. Notwithstanding computational advances, distance estimation on DEMs has never been systematically assessed, due to assumptions that improvements are so small that surface adjustment is unwarranted. For individual pixels inaccuracies may be small, but additive effects can propagate dramatically, especially in regional models (e.g., disaster evacuation) or global models (e.g., sea level rise) where pixels span dozens to hundreds of kilometers (Usery et al 2003). Such models are increasingly common, lending compelling reasons to understand shortcomings in the use of planar distance metrics. Researchers have studied curvature-based terrain modeling. Jenny et al. (2011) use curvature to generate hierarchical terrain models. Schneider (2001) creates a ‘plausibility’ metric for DEM-extracted structure lines. d’Oleire- Oltmanns et al. (2014) adopt object-based image processing as an alternative to working with DEMs; acknowledging the pre-processing involved in converting terrain into an object model is computationally intensive, and likely infeasible for some applications. This paper compares planar distance with surface adjusted distance, evolving from distance “as the crow flies” to distance “as the horse runs”. Several methods are compared for DEMs spanning a range of resolutions for the study area and validated against a 3 meter (m) lidar data benchmark. Error magnitudes vary with pixel size and with the method of surface adjustment. The rate of error increase may also vary with landscape type (terrain roughness, precipitation regimes and land settlement patterns). Cross-scale analysis for a single study area is reported here. Additional areas will be presented at the conference.

Conference Paper↗
USGS2025

Simulating human behavior under earthquake early warning

Earthquakes are a rapid-onset hazard where advance planning and learning plays a key role in mitigating injuries and death to individuals. Recent advances in earthquake detection have resulted in the development of earthquake early warning (EEW) systems. These systems can provide advance warning to predetermined geographic regions that an earthquake is in progress, which may result in individuals receiving warning seconds before significant shaking is felt at their location. This additional time could allow individuals to take more effective protective actions during the immediate disaster. To demonstrate this, we created an agent-based simulation of a basic apartment that allowed us to randomly and repeatedly simulate an individual receiving and responding to an EEW message. The results of our preliminary simulation show that, in our study environment, earthquake early warning alerts have the potential to allow for sufficient time for individuals to take protective actions.

Washington↗
USGS2025

Special issue "Effects of surface geology on seismic motion (ESG): General state-of-research"

To understand and predict the behaviors of strong ground motions incurred during devastating earthquakes, studies focused on the “effects of surface geology (ESG) on seismic motions” (following tradition, herein contracted as: “ESG”) have progressed steadily in the last three decades. These ESG studies typically involve in situ measurements of the wavefield and commonly apply both analytical and computational approaches. Concurrently, improvements in ESG related research can be readily attributed to the proliferation of openly accessible strong motion data, as well as advances in computational power. Nevertheless, there remain significant shortfalls in our understanding of the epistemic and aleatory uncertainties associated with the ESG as demonstrated by phenomena from recent deadly earthquake-related site effects. Thus, investigations toward addressing these deficiencies should be underscored in future earthquake related disaster mitigation efforts. This special issue of Earth, Planets, and Space (EPS) is dedicated to the ongoing efforts by the International Association of Seismology and Physics of the Earth’s Interior (IASPEI) and the International Association of Earthquake Engineering (IAEE) that champion activities promoting studies related to the ESG.

Earth, Planets and Space↗
USGS2016

The 2014 annual report for the Hawaiian Volcano Observatory

Introduction This report summarizes team activities and findings of the Hawaiian Volcano Observatory during the year 2014 in geology, geodesy, seismicity, and gas geochemistry. The eruption of Pu‘u ‘Ō‘ō continued into its 32nd year with flows active to the northeast of the vent. One of them, the June 27th lava flow, named for the date in 2014 that the flow started, advanced far and fast enough to threaten the town of Pāhoa and Highway 130 in the Puna District of the Island of Hawai‘i. In response, the alert level for Kīlauea was elevated from WATCH to WARNING on September 4, followed by the declaration of a State Disaster on September 5 and a National Disaster on November 3. During 2014, renewed inflation and increased seismicity was detected beneath the summit and upper west flank of Mauna Loa. Although above background, the frequency and magnitude of the earthquakes remained at such low levels that, by year’s end, the four-tier alert level code for Mauna Loa remained at its lowest level—NORMAL. These changes were discussed in several Volcano Watch articles. Hualālai, Haleakalā, Mauna Kea, and Lo‘īhi showed no signs of unrest during the year.

Scientific Investigations Report↗
USGS2018

Landsat benefiting society for fifty years

Since 1972, data acquired by the Landsat series of satellites have become integral to land management for both government and the private sector, providing scientists and decision makers with key information about agricultural productivity, ice sheet dynamics, urban growth, forest monitoring, natural resource management, water quality, and supporting disaster response. Landsat 9 continues the mission of unrivaled space-based Earth observation and will lead the Landsat program into its second half century of Earth imagery provided to users, worldwide, at no charge. More than 8 million Landsat scenes held in the USGS archive to date are used in conjunction with advanced geographic information systems, image processing software, and cloud computing capabilities to enable Landsat users to study changes on the Earth’s surface across continental regions and extended time periods. The Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2) instruments onboard Landsat 9 —which replicate the technologically-advanced instruments introduced onboard Landsat 8—allow for the collection of continuous high-quality data required for advancing Earth applications, including our ability to map surface temperature and surface water quality. Landsat 9 will build on the Landsat legacy, achieving a half-century record of global Earth observations.

Report↗
USGS2013

Exploring Hawaiian volcanism

In 1912 the Hawaiian Volcano Observatory (HVO) was established by Massachusetts Institute of Technology professor Thomas A. Jaggar Jr. on the island of Hawaii. Driven by the devastation he observed while investigating the volcanic disasters of 1902 at Montagne Pelée in the Caribbean, Jaggar conducted a worldwide search and decided that Hawai‘i provided an excellent natural laboratory for systematic study of earthquake and volcano processes toward better understanding of seismic and volcanic hazards. In the 100 years since HVO’s founding, surveillance and investigation of Hawaiian volcanoes have spurred advances in volcano and seismic monitoring techniques, extended scientists’ understanding of eruptive activity and processes, and contributed to development of global theories about hot spots and mantle plumes.

Hawai'i↗
USGS2008

Development of the U.S. Geological Survey's PAGER system (Prompt Assessment of Global Earthquakes for Response)

The Prompt Assessment of Global Earthquakes for Response (PAGER) System plays a primary alerting role for global earthquake disasters as part of the U.S. Geological Survey’s (USGS) response protocol. We provide an overview of the PAGER system, both of its current capabilities and our ongoing research and development. PAGER monitors the USGS’s near real-time U.S. and global earthquake origins and automatically identifies events that are of societal importance, well in advance of ground-truth or news accounts. Current PAGER notifications and Web pages estimate the population exposed to each seismic intensity level. In addition to being a useful indicator of potential impact, PAGER’s intensity/exposure display provides a new standard in the dissemination of rapid earthquake information. We are currently developing and testing a more comprehensive alert system that will include casualty estimates. This is motivated by the idea that an estimated range of possible number of deaths will aid in decisions regarding humanitarian response. Underlying the PAGER exposure and loss models are global earthquake ShakeMap shaking estimates, constrained as quickly as possible by finite-fault modeling and observed ground motions and intensities, when available. Loss modeling is being developed comprehensively with a suite of candidate models that range from fully empirical to largely analytical approaches. Which of these models is most appropriate for use in a particular earthquake depends on how much is known about local building stocks and their vulnerabilities. A first-order country-specific global building inventory has been developed, as have corresponding vulnerability functions. For calibrating PAGER loss models, we have systematically generated an Atlas of 5,000 ShakeMaps for significant global earthquakes during the last 36 years. For many of these, auxiliary earthquake source and shaking intensity data are also available. Refinements to the loss models are ongoing. Fundamental to such an alert system, we are also developing computational and communications infrastructure for rapid and robust operations and worldwide notifications. PAGER’s methodologies and datasets are being developed in an open environment to support other loss estimation efforts and provide avenues for outside collaboration and critique.

Conference Paper↗
USGS2019

Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security

On a planet with more than 7 billion people, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the US Agency for International Development's Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model and predict food insecurity. Here we provide an overview of FEWS NET's DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET's monitoring system, it draws from many disciplines - remote sensing, climate prediction, agro-climatic monitoring, and hydrologic modeling. Here we describe FEWS NET's multi-agency multi-disciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Mid-season droughts are monitored using multiple cutting-edge earth observing systems. Crop and hydrologic models can translate these observations into impacts. This information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Bulletin of the American Meteorological Society↗
USGS1984

Forecasting eruptions in the Circum-Pacific

Many important advances have been made in the last few years in the techniques and approaches to forecasting volcanic eruptions. Yet some of the most dangerous volcanoes are in countries unable to provide either the equipment or the skills to monitor them and to warn endangered residents. This review of the many scientific, technical, social and even political factory involved in volcano forecasting will be of value to other scientists concerned with monitoring and coping with natural hazards and disasters.

Episodes, Journal of International Geoscience↗
USGS2025

Harnessing geospatial artificial intelligence and deep learning for landslide inventory mapping: Advances, challenges, and emerging directions

Recent advancements in artificial intelligence (AI) and deep learning enable more accurate, scalable, and automated mapping. This paper provides a comprehensive review of the applications of AI, particularly deep learning, in landslide inventory mapping. In addition to examining commonly used data sources and model architectures, we explore innovative strategies such as feature enhancement and fusion, attention-boosted techniques, and advanced learning approaches, including active learning and transfer learning, to enhance model adaptability and predictability. We also highlight the remaining challenges and potential research directions, including the estimation of more diverse variables in landslide mapping, multimodal data alignment, modeling regional variability and replicability, as well as issues related to data misinterpretation and model explainability. This review aims to serve as a useful resource for researchers and practitioners, promoting the integration of deep learning into landslide research and disaster management.

Remote Sensing↗
USGS2012

Flood-inundation maps for the Suncook River in Epsom, Pembroke, Allenstown, and Chichester, New Hampshire

Digital flood-inundation maps for a 16.5-mile reach of the Suncook River in Epsom, Pembroke, Allenstown, and Chichester, N.H., from the confluence with the Merrimack River to U.S. Geological Survey (USGS) Suncook River streamgage 01089500 at Depot Road in North Chichester, N.H., were created by the USGS in cooperation with the New Hampshire Department of Homeland Security and Emergency Management. The inundation maps presented in this report depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Suncook River at North Chichester, N.H. (station 01089500). The current conditions at the USGS streamgage may be obtained on the Internet (http://waterdata.usgs.gov/nh/nwis/uv/?site_no=01089500&PARAmeter_cd=00065,00060). The National Weather Service forecasts flood hydrographs at many places that are often collocated with USGS streamgages. Forecasted peak-stage information is available on the Internet at the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) flood-warning system site (http://water.weather.gov/ahps/) and may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. These maps along with real-time stream stage data from the USGS Suncook River streamgage (station 01089500) and forecasted stream stage from the NWS will provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations, road closures, disaster declarations, and post-flood recovery. The maps, along with current stream-stage data from the USGS Suncook River streamgage and forecasted stream-stage data from the NWS, can be accessed at the USGS Flood Inundation Mapping Science Web site http://water.usgs.gov/osw/flood_inundation/.

New Hampshire↗