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At least 379 records · Page 21Linked to original sources
USGS2024

Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States. This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States. Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Iowa, Illinois, Michigan, Missouri, Minnesota, Mon↗
USGS2022

Hawaiian forest bird conservation strategies for minimizing the risk of extinction: biological and biocultural considerations

The iconic forest birds of Hawai‘i are facing a conservation crisis. Across the Hawaiian Islands, native forest birds have been experiencing population declines that have accelerated in the last one to two decades. While habitat loss, invasive species, and non-native predators have negatively affected forest bird species for hundreds of years, and continue to do so, introduced diseases, particularly avian malaria, are the greatest threat to forest birds today. Further, climate change has increased temperatures in the high-elevation forests, facilitating the spread of disease into areas that were once largely disease-free. Rapid population declines have now (2022) pushed four Hawaiian honeycreeper species to the brink of extinction: the endangered ‘akikiki ( Oreomystis bairdi ) and ‘akeke‘e ( Loxops caeruleirostris ) on Kaua‘i Island, and kiwikiu ( Pseudonestor xanthophrys ) and ‘ākohekohe ( Palmeria dolei ) on Maui Island. The biologists that study these birds strongly agree that without a rapid conservation response to the threat of increasing disease mortality there is a high probability these species will go extinct in the coming decade. To help evaluate alternative conservation strategies for minimizing the risk of extinction, we convened diverse groups of experts with broad experience in Hawai‘i forest birds and ecosystems, as well as the management approaches being considered, to assess the probability of success of alternative management actions. In addition to assessing this crisis from a biological perspective, we convened a group of Native Hawaiian participants that have a strong connection to the forest birds, forests, and the integration of their culture in natural and biocultural resource management. They give voice to the significance of forest birds to Native Hawaiians and provide their perspectives on alternative management actions. Broadly, the three alternative management actions being considered to prevent the extinction of forest birds from the increasing threat of disease are (1) landscape-level mosquito control through the Wolbachia incompatible insect technique, (2) captive care, and (3) conservation translocations. The two key components of the problem of preventing extinction in these four bird species is time and risk. For each species, very few individuals remain, and they are all in danger of imminent extinction. Each management action takes time to implement, which might exceed the actual time to extinction. Additionally, each of these conservation actions has potential benefits and inherent risks, as well as substantial uncertainty in terms of being successful. Native Hawaiian perspectives and considerations also vary across the conservation actions. The expert evaluations summarized in this report provide a broad assessment of conservation strategies that could be undertaken to prevent the extinction of ‘akikiki, ‘akeke‘e, kiwikiu, and ‘ākohekohe. While this report does not recommend specific actions, the information is intended to support decision-makers as they assess which, if any, conservation strategies to pursue.

Hawaii↗
USGS2023

Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast

Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands. Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area. Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington. Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t. Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.

California, Oregon, Washington↗
USGS2013

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

Conservation Biology↗
USGS2025

Characterizing projected future droughts for south Florida (2056–2095)

Balance anomalies, defined as the deviation of monthly precipitation minus reference evapotranspiration from their long-term monthly historical means (1950–2005), were computed for regions in south Florida and temporally averaged over 6- and 12-month timescales to identify meteorological drought events during a historical (1950–2005) and future (2056–2095) period of interest for 40 CMIP5 general circulation models (GCM) and scenario combinations downscaled by the Multivariate Adaptive Constructed Analogs method. Under the assumption of stomatal resistance ( r s ) remaining constant at the historical standard value (70 s/m), 81% of models project declines in monthly balance anomalies in the future compared to historical, with multimodel ensemble mean declines of 3.7 in/year under RCP4.5 and 8.7 in/year under RCP8.5. Drought events were identified from the downscaled model projections, their characteristics (duration and intensity) extracted, and their historical joint distributions validated against those derived from historical observational datasets. The future joint distributions of drought characteristics were compared across models using hierarchical clustering. A climate model summary plot and table were developed based on these methods to guide climate model selection for hydrologic modeling in support of water-supply planning at the South Florida Water Management District (SFWMD). The model summary plot for the entire SFWMD shows that 35% of GCM/training-dataset combinations have historical joint distributions of drought characteristics that are significantly different at the 10% level from those derived from observational gridded data, whereas 39% of GCM/scenario/training-dataset combinations have future joint distributions that are significantly different from historical. A sensitivity analysis was performed assuming r s increasing with increasing CO 2 .

Florida↗
USGS2013

A landscape-based assessment of climate change vulnerability for all native Hawaiian plants

In Hawaiʽi and elsewhere, research efforts have focused on two main approaches to determine the potential impacts of climate change on individual species: estimating species vulnerabilities and projecting responses of species to expected changes. We integrated these approaches by defining vulnerability as the inability of species to exhibit any of the responses necessary for persistence under climate change (i.e., tolerate projected changes, endure in microrefugia, or migrate to new climate-compatible areas, but excluding evolutionary adaptation). To operationalize this response-based definition of species vulnerability within a landscape-based analysis, we used current and future climate envelopes for each species to define zones across the landscape: the toleration zone; the microrefugia zone; and the migration zone. Using these response zones we calculated a diverse set of factors related to habitat area, quality, and distribution for each species, including the amount of habitat protection and fragmentation and areas projected to be lost to sea-level rise. We then calculated the probabilities of each species exhibiting these responses using a Bayesian network model and determined the overall climate change vulnerability of each species by using a vulnerability index. As a first iteration of a response-based species vulnerability assessment (VA), our landscape-based analysis effectively integrates species-distribution models into a Bayesian network-based VA that can be updated with improved models and data for more refined analyses in the future. Our results show that the species most vulnerable to climate change also tend to be species of conservation concern due to non-climatic threats (e.g., competition and predation from invasive species, land-use change). Also, many of Hawaiʽi’s taxa that are most vulnerable to climate change share characteristics with species that in the past were found to be at risk of extinction due to non-climatic threats (e.g., archipelago endemism, single-island endemism). Of particular concern are the numerous species that have no compatible-climate areas remaining by the year 2100. Species primarily associated with dry forests have higher vulnerability scores than species from any other habitat type. When examined at taxonomic levels above species, low vulnerabilities are concentrated in families and genera of generalists (e.g., ferns or sedges) and typically associated with mid-elevation wet habitats. Our results replicate findings from other regions that link higher species vulnerability with decreasing range size. This species VA is possibly the largest in scope ever conducted in the United States with over 1000 species considered, 319 of which are listed as endangered or threatened under the U.S. Endangered Species Act, filling a critical knowledge gap for resource managers in the region. The information in this assessment can help prioritize species for special conservation actions, guide the management of conservation areas, inform the selection of research and monitoring priorities, and support adaptive management planning and implementation.

Hawai'i↗
USGS2021

Evaluating fish rescue as a drought adaptation strategy using a life cycle modeling approach for imperiled coho salmon

Projected intensification of drought as a result of climate change may reduce the capacity of streams to rear fish, exacerbating the challenge of recovering salmonid populations listed under the Endangered Species Act. Without management intervention, some stocks will likely go extinct as stream drying and fragmentation reduce juvenile survival to unsustainable levels. To offset drought‐related mortality, fish rescue programs have proliferated, whereby juvenile salmonids are captured and transferred to off‐site rearing facilities. However, the efficacy of this potential conservation tool remains poorly understood. We developed a life cycle model to examine the implications of fish rescue on the abundance of Coho Salmon Oncorhynchus kisutch across serial life stages. The simulation model examines scenarios with varying quantities of rescued fish, time in captivity, drought severity, and reduced smolt‐to‐adult return rates. Our results indicate that fish rescue can increase the abundance of adults and lower extinction risk, particularly for fish held in captivity for a full year. However, fish rescue can also decrease the abundance of adults and increase extinction risk if fish are held only for summer and there is limited winter habitat. We found that when fish rescue did increase returns, it functioned more like a stock enhancement program than a drought mitigation tool and it would likely lead to consecutive generations of captive rearing, which has been shown to have negative effects on fitness. We translated our model into an R Shiny application ( https://shiny.wdfw‐fish.us/CohoPopulationDynamics/ ) that allows users to explore how fish rescue affects Coho Salmon population dynamics through customized parameterization of the model to represent different systems or different assumptions about the effects of fish rescue.

North American Journal of Fisheries Management↗
USGS2016

Cheatgrass percent cover change: Comparing recent estimates to climate change − Driven predictions in the Northern Great Basin

Cheatgrass ( Bromus tectorum L.) is a highly invasive species in the Northern Great Basin that helps decrease fire return intervals. Fire fragments the shrub steppe and reduces its capacity to provide forage for livestock and wildlife and habitat critical to sagebrush obligates. Of particular interest is the greater sage grouse ( Centrocercus urophasianus ), an obligate whose populations have declined so severely due, in part, to increases in cheatgrass and fires that it was considered for inclusion as an endangered species. Remote sensing technologies and satellite archives help scientists monitor terrestrial vegetation globally, including cheatgrass in the Northern Great Basin. Along with geospatial analysis and advanced spatial modeling, these data and technologies can identify areas susceptible to increased cheatgrass cover and compare these with greater sage grouse priority areas for conservation (PAC). Future climate models forecast a warmer and wetter climate for the Northern Great Basin, which likely will force changing cheatgrass dynamics. Therefore, we examine potential climate-caused changes to cheatgrass. Our results indicate that future cheatgrass percent cover will remain stable over more than 80% of the study area when compared with recent estimates, and higher overall cheatgrass cover will occur with slightly more spatial variability. The land area projected to increase or decrease in cheatgrass cover equals 18% and 1%, respectively, making an increase in fire disturbances in greater sage grouse habitat likely. Relative susceptibility measures, created by integrating cheatgrass percent cover and temporal standard deviation datasets, show that potential increases in future cheatgrass cover match future projections. This discovery indicates that some greater sage grouse PACs for conservation could be at heightened risk of fire disturbance. Multiple factors will affect future cheatgrass cover including changes in precipitation timing and totals and increases in freeze-thaw cycles. Understanding these effects can help direct land management, guide scientific research, and influence policy.

Idaho, Montana, Nevada, Oregon, Utah, Washington, ↗
USGS2018

Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation

Changes in land-use practices and the extirpation (local extinction) of beaver populations in the early 20th century during European settlement are believed to have resulted in many changes in how streams in the Western United States function. Some of the negative changes that have resulted include stream channelization, soil erosion, changing vegetation, water turbidity, and a loss of overland flow. Efforts to restore streams and reduce soil erosion by water have included reintroductions of beaver, incorporating Native American traditional knowledge of dry-land farming techniques, and the installation of rigid check-dams. Many of these efforts have been successful in improving both intermittent and perennial stream function. Therefore, stakeholders in the Southern Rockies Landscape Conservation Cooperative (SRLCC) have identified a need to prioritize streams within their region of interest for the installation of check-dams to continue restoration and conservation efforts and to improve sediment catchment. Using Natural Resource Conservation Service soil databases, topographic features derived from digital elevation models, stream networks, and regional climatic patterns, I developed a ranking system for watershed potential erosion rates and suitability for check-dam placement across the SRLCC. This ranking system serves as a first step for land managers to prioritize areas for check-dam installation based on relatively static factors (soil properties, topography, and hydrology) that can contribute to rates of soil erosion by water and the stability of check-dams. Many other relatively dynamic factors over time can contribute to rates of soil erosion by water, such as recent wildfire events, changes in weather patterns and extreme climate events, and changing land-use such as grazing, logging, mining, development, and cultivation. These factors that influence vegetative and biological soil crusts cover are also important elements to the potential erosion of soil by water. Because of this, SRLCC stakeholders might consider further evaluation of the watersheds identified here as high ranking. Final watershed prioritization among the high-ranking watersheds identified here should include current knowledge of land-use and land-cover estimates to identify areas at risk for soil erosion or degree of existing erosion problems.

Open-File Report↗
USGS2022

Integrating urban planning and water management through green infrastructure in the United States-Mexico border

Creating sustainable, resilient, and livable cities calls for integrative approaches and collaborative practices across temporal and spatial scales. However, practicability is challenged by institutional, social, and technical complexities and the need to build collective understanding of integrated approaches. Rapid urbanization along the United States-Mexico border, fueled by industrialization, trade, and migration, has resulted in cities confronted with recurrent flooding risk, extended drought, water pollution, habitat destruction and systemic vulnerabilities. The international border, which separates natural and built ecosystems, is both a challenge and an opportunity, making a unique social and institutional setting ideal for testing the integration of urban planning and water management. Our research focuses on fusing multi-functional and multi-scalar green infrastructure to restore ecosystem services through a strategic binational planning process. This paper describes this planning process, including the development and application of both a land suitability analysis and a hydrological model to optimally site green infrastructure in the Nogales, Arizona, United States—Nogales, Sonora, Mexico, cross border region. We draw lessons from this process and stakeholder feedback focused on the potential for urban green infrastructure, to allow for adaptation and even transformation in the face of current and future challenges such as limited resources, underdeveloped governance, bordering, and climate change. In sum, a cross border network of green infrastructure can provide a backbone to connect this transboundary watershed while providing both hydrological and social benefits.

Frontiers in Water↗
USGS2019

An integrated framework for ecological drought across riverscapes of North America

Climate change is increasing the severity and extent of extreme droughts events, posing a critical threat to freshwater ecosystems, particularly with increasing human demands for diminishing water supplies. Despite the importance of drought as a significant driver of ecological and evolutionary dynamics, current understanding of drought consequences for freshwater biodiversity is very limited. We describe key barriers that hinder integrative drought research and monitoring across riverscapes. The primary constraint limiting understanding of ecological drought is an existing monitoring framework focused on human water consumption and flood risk in mainstem rivers. This approach is misaligned with escalating needs for research and data collection that illuminate exposure, sensitivity, and adaptive capacity (i.e., vulnerability) of biota to drought across entire riverscapes. We present a hierarchical framework for integrated ecological drought monitoring and research that addresses drought vulnerability across riverscapes, and describe how this approach can directly inform natural-resource management.

BioScience↗
USGS2024

Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. This work is part of that reexamination. The stationarity assumption is a concern because flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done to assess potential nonstationarity in peak flows in the north-central United States. This report summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Scientific Investigations Report↗
USGS2008

Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

Journal of Flood Risk Management↗
USGS2009

Proceedings of the Second All-USGS Modeling Conference, February 11-14, 2008: Painting the Big Picture

The Second USGS Modeling Conference was held February 11-14, 2008, in Orange Beach, Ala. Participants at the conference came from all U.S. Geological Survey (USGS) regions and represented all four science discipline - Biology, Geography, Geology, and Water. Representatives from other Department of the Interior (DOI) agencies and partners from the academic community also participated. The conference, which was focused on 'painting the big picture', emphasized the following themes: Integrated Landscape Monitoring, Global Climate Change, Ecosystem Modeling, and Hazards and Risks. The conference centered on providing a forum for modelers to meet, exchange information on current approaches, identify specific opportunities to share existing models and develop more linked and integrated models to address complex science questions, and increase collaboration across disciplines and with other organizations. Abstracts for the 31 oral presentations and more than 60 posters presented at the conference are included here. The conference also featured a field trip to review scientific modeling issues along the Gulf of Mexico. The field trip included visits to Mississippi Sandhill Crane National Wildlife Refuge, Grand Bay National Estuarine Research Reserve, the 5 Rivers Delta Resource Center, and Bon Secour National Wildlife Refuge. On behalf of all the participants of the Second All-USGS Modeling Conference, the conference organizing committee expresses our sincere appreciation for the support of field trip oganizers and leaders, including the managers from the various Reserves and Refuges. The organizing committee for the conference included Jenifer Bracewell, Sally Brady, Jacoby Carter, Thomas Casadevall, Linda Gundersen, Tom Gunther, Heather Henkel, Lauren Hay, Pat Jellison, K. Bruce Jones, Kenneth Odom, and Mark Wildhaber.

Scientific Investigations Report↗
USGS2024

Arsenic and other geogenic contaminants in global groundwater

Geogenic groundwater contaminants (GGCs) affect drinking-water availability and safety, with up to 60% of groundwater sources in some regions contaminated by more than recommended concentrations. As a result, an estimated 300–500 million people are at risk of severe health impacts and premature mortality. In this Review, we discuss the sources, occurrences and cycling of arsenic, fluoride, selenium and uranium, which are GGCs with widespread distribution and/or high toxicity. The global distribution of GGCs is controlled by basin geology and tectonics, with GGC enrichment in both orogenic systems and cratonic basement rocks. This regional distribution is broadly influenced by climate, geomorphology and hydrogeochemical evolution along groundwater flow paths. GGC distribution is locally heterogeneous and affected by in situ lithology, groundwater flow and water–rock interactions. Local biogeochemical cycling also determines GGC concentrations, as arsenic, selenium and uranium mobilizations are strongly redox-dependent. Increasing groundwater extraction and land-use changes are likely to modify GGC distribution and extent, potentially exacerbating human exposure to GGCs, but the net impact of these activities is unknown. Integration of science, policy, community involvement programmes and technological interventions is needed to manage GGC-enriched groundwater and ensure equitable access to clean water.

Nature Reviews Earth & Environment↗
USGS2010

A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

Greenhouse gas emissions have significantly altered global climate, and will continue to do so in the future. Increases in the frequency, duration, and/or severity of drought and heat stress associated with climate change could fundamentally alter the composition, structure, and biogeography of forests in many regions. Of particular concern are potential increases in tree mortality associated with climate-induced physiological stress and interactions with other climate-mediated processes such as insect outbreaks and wildfire. Despite this risk, existing projections of tree mortality are based on models that lack functionally realistic mortality mechanisms, and there has been no attempt to track observations of climate-driven tree mortality globally. Here we present the first global assessment of recent tree mortality attributed to drought and heat stress. Although episodic mortality occurs in the absence of climate change, studies compiled here suggest that at least some of the world's forested ecosystems already may be responding to climate change and raise concern that forests may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, even in environments that are not normally considered water-limited. This further suggests risks to ecosystem services, including the loss of sequestered forest carbon and associated atmospheric feedbacks. Our review also identifies key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasizes the need for a globally coordinated observation system. Overall, our review reveals the potential for amplified tree mortality due to drought and heat in forests worldwide.

Forest Ecology and Management↗
USGS2025

Evaluating a simulation-based wildfire burn probability map for the conterminous US

Background Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography and ignition locations, and BP maps are key components of wildfire risk assessments. Aims Few studies have compared BP maps with real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous US based on the large fire simulation model FSim. Methods We compared BP with observed wildfires from 2016 to 2022 across 128 regions representing similar fire regimes (‘pyromes’). We evaluated the distribution of burned areas across BP values, and compared burned area distributions among fire size classes. Key results Across all pyromes, mean BP was moderately correlated with observed burned area. An average of 71% of burned area occurred in higher-BP classes, vs 79% expected. BP underpredicted burned area in the Mountain West, especially for extremely large fires. Conclusions The FSim BP map was useful for estimating subsequent wildfire hazard, but may have underestimated burned areas where input data did not reflect recent climate change, vegetation change or human ignition patterns. Implications Our evaluations indicate that caution is needed when relying on simulation-based BP maps to inform management decisions. Our results also highlight potential opportunities to improve model estimates.

Conterminous United States↗
USGS2022

An introduction to current climate projections and their use in climate impacts research

Using climate projections to evaluate future climate impacts and their associated risks requires a background knowledge of the nature of climate change, use of climate models to develop future projections, and knowledge of how to address climate scenario uncertainty. This chapter provides an overview of climate and climate change, some of the foundational climate science that underlies current climate change assessments, and a brief introduction to climate models and climate scenario uncertainty. Global projections of temperature and precipitation changes from the recent Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) and a brief comparison to the prior assessment (AR5) are provided. The main sources of uncertainty in these projections include climate variability, climate model differences and treatment of scientific knowledge gaps, and greenhouse gas (GHG) emissions. When projections are downscaled to local resolution, downscaling is an additional source of uncertainty. These uncertainties can be incorporated in assessments of climate impacts by choosing a range of scenarios that directly address the sources of uncertainty. Evaluating the likelihood of a given climate impact on animal health or management strategies requires consideration of the main sources of climate projection uncertainties. Adaptation requires consideration of global-to-regional contexts of climate changes and impacts, but also adaptive capacity.

Book chapter↗