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USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗

USGS2026

Temperate wetlands lose climate-cooling capacity under warming

Temperate inland wetlands have long been viewed as climate regulators, with sustained CO₂ sequestration offsetting continuous CH₄ emissions over centennial–millennial timescales. However, the net climatic effect of these opposing fluxes remains uncertain under anthropogenic warming as they differ in both magnitude and atmospheric lifetime. We combine 19,000 CH₄ chamber measurements from 202 temperate inland wetlands with carbon burial rates from 16 dated sediment cores in North America’s Prairie Pothole Region to estimate greenhouse gas dynamics over two centuries. Here we show that CH₄ emissions rise by ~1.39 kg CH₄ ha⁻¹ yr⁻¹ over the historical period and are projected to approach 950 kg CH₄ ha⁻¹ yr⁻¹ under high-forcing scenarios by 2100, while CO₂ sequestration is expected to decline by ~0.3 kg CO₂ ha⁻¹ yr⁻¹, driving a shift toward persistent net CO₂-equivalent source behaviour and a weakening of the long-term cooling effect that wetlands have provided under natural conditions.

Prairie Pothole Region↗

USGS2025

An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi

The U.S. Geological Survey has developed a high-resolution inset groundwater-flow model in the Mississippi Delta as part of an interdisciplinary collaboration coordinated by the Mississippi Alluvial Plain project to provide a tool that stakeholders can use to support water-resource management decisions. Groundwater withdrawals from the Mississippi River Valley alluvial (MRVA) aquifer have been vital to support agricultural production in the region, but substantial groundwater-level declines near Shellmound, Mississippi, have caused concerns for long-term sustainability of the aquifer. To better understand the subsurface and try to mitigate the long-term groundwater-level declines, stakeholders have undertaken actions including a Groundwater Transfer and Injection Pilot (GTIP) project using a riverbank filtration-based managed aquifer recharge approach. The pilot project consisted of extracting groundwater near the Tallahatchie River and reinjecting it into the aquifer 3 kilometers west where water levels have substantially declined. A high-resolution airborne electromagnetic (AEM) survey was also completed to collect electrical resistivity data to support the GTIP project and the development of the groundwater model. The inset groundwater-flow model was developed to (1) integrate the AEM data into the optimal layering configuration of the MRVA aquifer that the available observation data can support through calibration, and (2) assess the potential effect of the GTIP project on the groundwater levels. The AEM data were processed into three different layering configurations leading to the development of model A (18 layers), model B (16 layers), and model C (8 layers), all at a 100- x 100-meter cell spatial resolution using the U.S. Geological Survey modular finite-difference flow model 6 code with Newton-Raphson formulation. The model development process integrated recent advances in modeling, such as the incorporation of AEM data, the use of outputs from the soil-water-balance (SWB) model, and the Aquaculture and Irrigation Water-Use Model, and was facilitated by robust automation using the open-source python packages Modflow-setup and SFRmaker. Using Parameter Estimation ++ Iterative Ensemble Smoother, the three numerical groundwater-flow models (models A, B, and C) were calibrated against a set of observations, which included aquifer groundwater levels, streamflows, stream stage, and aquifer transmissivity. Results indicate that the detailed representation of MRVA aquifer layers in model A produced the best calibrated model by history matching, and the integration of data representing surficial connectivity played a key role in improving groundwater recharge and enhancing the ability of the model to match groundwater levels in the cone of depression. A forecast model simulated the managed aquifer recharge approach, and the results indicated that, given average irrigation and recharge conditions (2010–15), the GTIP project has the potential to induce groundwater-level increases of as much as 3 meters around the injection site, but a sustained increase would require repetition in subsequent years of water transfer at 2022 rates or above.

Mississippi↗

USGS2025

PEST++IES how many iterations & realizations, finding the point of diminishing returns

PEST++IES (White 2018; White et al. 2020) is widely used in the groundwater modeling community for its ability to perform computationally efficient history matching and uncertainty analysis in a highly parameterized context. One primary advantage of using an iterative ensemble smoother is that the number of model runs required per iteration depends on the number of realizations in an ensemble, not the number of parameters in each realization. However, this raises the question: what is the optimal number of realizations and iterations to use for any one model before the point of diminishing returns? Using a modified version of the Freyberg model (Freyberg 1988; Hunt et al. 2020), different parameter and observation scenarios were evaluated for four iterations and ensembles of 10, 25, 50, 100, 250, 500, 1000, and 2000 realizations. To match observations, PEST++IES altered hydraulic conductivity ( k ), both globally across the model and locally at three different pilot point densities, as well as global recharge (via a single multiplier), global river conductance, and individual well flow rates. Risk-based well capture zone results (Fienen et al. 2022a) and estimated hydraulic conductivity fields from each scenario were quantitatively and qualitatively compared against the “truth” model and its outputs. Across the cases examined, ensemble sizes of 100 to 250 realizations and two PEST++IES iterations were generally sufficient to achieve good results.

Groundwater↗

USGS2026

Groundwater spatial variability within an atoll island: Assessing shallow aquifer heterogeneity with geophysical and physicochemical measurements

This study examines the spatial variability of shallow groundwater on Dhigelaabadhoo Island using electromagnetic induction surveys, groundwater monitoring, and sediment analyses. The research reveals how variations in island morphology—such as differences in elevation, reef flat width, and sediment composition—affect the spatial distribution of groundwater lenses and the overall aquifer dynamics. Saltwater intrusion is especially pronounced in low elevated areas, with narrow reef flat plate and areas where higher hydraulic conductivity—driven by the presence of coarser sediments—is observed, whereas regions characterized by finer sediments, higher elevation, and wider reef flat plates tend to support more symmetric and less saline groundwater lenses. The geophysical investigations reveal that tidal oscillations alter groundwater movement by markedly changing water levels and conductivity, thereby underscoring the critical need to account for temporal dynamics in atoll coastal aquifer systems and the importance of integrating tidal dynamics into the aquifer zone. The findings highlight the significant role of intrinsic morphological and external hydrodynamic factors in shaping groundwater distribution on atoll islands, offering critical insights for sustainable freshwater resource management.

Dhigelaabadhoo Island↗

USGS2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience↗

USGS2026

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular↗

USGS2025

Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho

The U.S. Geological Survey (USGS)—in cooperation with the U.S. Department of Energy (DOE) for the Naval Reactors Laboratory Field Office that supports operations for the Naval Reactors Facility (NRF) located at the Idaho National Laboratory (INL)—drilled and constructed well NRF-17 (formerly borehole USGS 151) and well NRF-18 (formerly borehole USGS 152) for stratigraphic framework analyses and water-quality monitoring at the Idaho National Laboratory (INL) near the NRF, in southeastern Idaho. Borehole USGS 151 was continuously cored from about 48 to 1,070 feet (ft) below land surface (BLS); rotary drilled from approximately 1,070 to 1,720 ft BLS; and re-drilled to complete construction as a monitor well NRF-17, completed to 461 ft BLS. Borehole USGS 152 was continuously cored from approximately 19 to 1,259 ft BLS; rotary drilled from approximately 1,259 to 1,630 ft BLS; and re-drilled to complete construction as a monitor well NRF-18, completed to 450 ft BLS. Geophysical data were examined with photographed core material to record lithologic descriptions and to suggest zones where groundwater flow was anticipated. Basalt flows varied from highly fractured to dense, with high-to-low vesiculation. Well NRF-17 generally was constructed in mostly dense basalt (greater than 75 percent), and well NRF-18 was constructed in primarily fractured and (or) vesicular basalt. In well NRF-17, the well capacity is directly affected by the limited amount of fractured basalt, which serves as the primary pathway for groundwater. This effect was observed during the pumping test conducted after the well's final construction. Single-well aquifer tests were done at wells NRF-17 and NRF-18 to provide estimates of transmissivity and hydraulic conductivity after final well construction and initial well development. Estimated values of transmissivity and hydraulic conductivity for well NRF-17 were 8.81 feet squared per day (ft 2 /d) and 1.04×10 -2 feet per day (ft/d), respectively. Estimated values of transmissivity and hydraulic conductivity for well NRF-18 were 4.77×10 3 ft 2 /d and 5.61 ft/d, respectively. The NRF-17 pump test resulted in 19.41 ft of measured drawdown at a sustained average pumping rate of 3.3 gallons per minute (gal/min). The NRF-18 pump test resulted in 0.55 ft of measured drawdown at a sustained average pumping rate of 31.0 gal/min. Water-quality samples collected from the two wells were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for select inorganic constituents showed concentrations consistent with signatures from tributary valley groundwater with influences from ephemeral surface-water recharge from the Big Lost River. Water-quality samples analyzed for stable isotopes of oxygen and hydrogen are consistent with signatures from tributary valley groundwater and surface-water recharge inputs to the aquifer. No measured water-quality results were greater than their respective maximum contaminant levels for public drinking-water supplies. Inorganic and nutrient water-quality results for well NRF-17 and well NRF-18 suggest the groundwater in this area is potentially affected by industrial wastewater disposal.

Idaho↗

USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗

USGS2025

Footprints of past mining in Alaska (USA) derived from high-resolution satellite imagery

Mapping the land area used for mining in the past is essential for guiding the remediation of affected landscapes and assessing the resource potential of related waste products. Despite significant recent progress delineating footprints of active and inactive mining globally, the known inventory of such mine lands remains incomplete. Here, I describe a new map dataset of footprints of land surface disturbance and waste at sites of past mining in Alaska (USA) based on visual interpretation of satellite imagery. This dataset maps 6–14 times the area of previous regional and global mine footprint maps in Alaska and is the first in the region to explicitly delineate mine waste landforms (e.g., tailings piles). The data are publicly available from the U.S. Geological Survey under a “no rights reserved” Creative Commons (CC0) license agreement.

Alaska↗

USGS2026

Thermal detectability of subsurface water ice on Mars: A comparative analysis for the Subsurface Water Ice Mapping (SWIM) Project

We have developed a new global map of shallow ground ice distribution, SWIM23, based on Mars Global Surveyor Thermal Emission Spectrometer data and made systematic comparisons between this new map and two similar, previously developed data products. We have explored the origin of differences between the three ice maps by detailing technical and procedural differences in their development, by making global pixel-by-pixel comparisons, and by carrying out a series of one-dimensional thermal simulations to explore fundamental physical limitations of thermal ice-detection techniques. These efforts and the production of a composite thermal ice-consistency map supported integration of multiple geophysical data products relevant to ice detection in the upper meter of the Martian regolith into the larger Mars Subsurface Water Ice Mapping project. Our work also highlights fundamental physical limitations to thermal ice detection as a technique, particularly the rapid fall-off in ice detection sensitivity at depths >30 cm, which produces maximum uncertainty in the presence and depth of ice within regions preferred for potential human landing sites. A future Mars orbiter mission designed to detect ice and support crewed landing site selection in the midlatitude region should give payload priority to an instrument capable of probing the 1–5 m depth range (i.e., a high-frequency radar), over a next-generation thermal spectrometer, which is unlikely to offer clarity on ice table depths or lateral continuity of the ice table in the locations of highest interest.

Planetary Science Journal↗

USGS2025

Analysis of the potential effects of Uzbekistan’s mineral endowment on the critical mineral supply of tungsten

Tungsten appears on the 2018 and 2022 U.S. Geological Survey critical mineral lists in part because of a very high global production concentration in China, which produces almost 83 percent of the world’s mined tungsten. Using known parameters and values from other tungsten mining operations, we created hypothetical scenarios in which three tungsten deposits in Uzbekistan are considered for development. Our results show that all three deposits are likely to be economically viable to develop under 2024 market conditions. If the three studied tungsten deposits were put into production, Uzbekistan could become the third-leading tungsten-producing country in the world and increase world output of tungsten by 2.7 percent. Putting these tungsten deposits in Uzbekistan into production could slightly reduce the tungsten global market concentration, therefore reducing the supply disruption potential for tungsten.

Open-File Report↗

USGS2026

Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm 3 ) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot-wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

California↗

USGS2025

Zircon as a pathfinder to REE mineralization

Carbonatites and alkaline silicate rocks are major primary sources of the rare earth elements (REE) and other critical metals, such as Nb. Despite the economic significance of these rocks, their formation and the processes of REE enrichment are poorly understood. Here, statistical analysis of a global dataset demonstrates that zircon geochemistry is a powerful recorder of REE metallogenesis and a potential pathfinder for REE deposits. Zircons from REE and Nb fertile intrusions lack Eu anomalies and have elevated Gd/Yb and Th/Yb, indicating they crystallised from magmas that originated from deep, oxidised and enriched mantle sources. Complexes with Nb enrichment have low U/Nb, reflecting an enriched mantle source, whereas high U/Nb in REE-only fertile intrusions suggest a subduction-metasomatised mantle source. Machine learning models demonstrate high accuracy in classifying zircon from barren and fertile deposits. Classification of detrital zircons shows that REE-enriched deposits correlate with supercontinent assembly, whereas Nb fertile complexes are associated with supercontinent breakup. This approach offers a new, mineral to global scale, petrologic and exploration tool that enhances understanding of REE metallogenesis.

Geochemical Perspectives Letters↗

USGS2026

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

conterminous United States↗

USGS2025

Shallow geologic framework of the Mississippi Sound and the potential for sediment resources

The Mississippi Sound, an estuarine environment located between the mainland and barrier islands bordering the northern Gulf of America (formerly the Gulf of Mexico), serves as a vital ecosystem for the States of Mississippi and Alabama. Spanning approximately 100 kilometers from east to west and covering 1,400 square kilometers, the sound is home to marine industry and ports, and its shallow and brackish waters sustain a diverse array of marine life. Barrier islands along the southern edge of the sound separate the microtidal estuary from the Gulf of America. This protection from gulf wave action mediates current flow within the sound, resulting in predominantly fine-grained sediment deposition along the seafloor. This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, provides insight on fluvial and tidal processes spanning the past 5,000 years. The report synthesizes existing research to provide a comprehensive overview of the sound geology, from Pleistocene origins to present-day morphology, and utilizes high-resolution single channel seismic profiles and sediment data to identify and map sedimentary deposits and morphologic features at and below the seafloor. Despite its ecological significance, the Mississippi Sound faces environmental challenges, including water-quality issues, habitat degradation, storm-induced erosion, and the ongoing threats of sea-level rise and environmental changes. This study uses the present-day understanding of the sound's geology to inform coastal management decisions, hazard assessment, and potential mineral resources.

Louisiana, Mississippi↗

USGS2026

Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed

Study region The Russian River watershed, situated in coastal, northern California, experiences hydrologic extremes, including periodic droughts and flooding. Water managers are working to maintain sustainable water supplies and environmental flows, while mitigating flood risks. Study focus This paper introduces an integrated hydrology and river operations model for the Russian River watershed. This model is distinct from models in previous studies because it represents surface-groundwater interactions and uses climate forcings to estimate dynamic water use demands that are superimposed onto both reservoir operations and water supply constraints. The model was used to examine three historical (1990–2015) and eight future (2016–2099) water use and climate change scenarios. New hydrological insights for the region The direct connection between streams and aquifers facilitated both annual aquifer replenishment by high winter streamflows and streamflow depletion by groundwater wells (19 % of pumped groundwater in alluvial aquifers from stream leakage) during critical low flow periods. Simulated streamflow changes included 59 % longer and 54 % more severe streamflow droughts, 26 % lower seasonal low streamflows, and up to 125 % higher peak streamflows, averaged over future climate and water use scenarios, suggesting increased future flood and water availability risks. Results showed the importance of reservoir operations for mitigating the impacts of increased hydroclimatic volatility, despite a decrease in reservoir reliability at Lake Mendocino, suggesting that reservoir management may be used to decrease future risks.

California↗

USGS2025

Climate change and future water availability in the United States

The steady rise in global temperature as a result of human activity is causing changes in Earth’s water cycle. The balance of water stored within and moving between vapor, liquid, and frozen states in the water cycle is shifting, with consequences for water availability that include increases in drought, fire weather, flooding, and heavy precipitation, as well as cryosphere decline and sea-level rise. In this chapter of the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, we provide an overview of climate-change observations and projections from Earth-system model simulations that relate to future water availability, from global and national climate assessments and from the published literature. Effects of climate change on primary water-cycle components are discussed in context of how global-scale hydroclimate drivers influence regional processes within the United States. Understanding the major climate drivers impacting the water cycle is crucial to predicting future changes in water availability and developing adaptation strategies to ensure human and ecosystem water supplies. First, we provide background information on the water cycle, the climate-model ensemble simulations developed to produce projections based on warming scenarios, and attribution and certainty levels. Tipping points, self-reinforcing feedbacks, cascading effects, and compound extremes are introduced. The framework of climatic impact drivers (CIDs) outlined in the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) is used to show primary drivers of physical change to the water cycle and to understand and predict changes in future water availability. Specific climate-change related observations and projections are discussed for water cycle components of precipitation, evapotranspiration, soil moisture, streamflow, lakes and wetlands, ice and snow, and groundwater, as well as their implications for future water availability for humans and ecosystems. The chapter concludes with a synthesis discussion of three examples of complex regional-scale hydroclimate processes that influence water availability for populations in the United States, including (1) mountain and coastal precipitation, (2) aridification and drought, and (3) the influence of forest-cover change on terrestrial water-vapor recycling.

Professional Paper↗