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At least 1,099 records · Page 61Linked to original sources
USGS2026

Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering

A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.

Wind Energy↗
USGS2026

Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals

Using Alaskan lake sediment oxygen isotope records (δ 18 O), which trace the δ 18 O of precipitation, we establish that abrupt atmospheric shifts occurred during the last deglacial period in the North Pacific-Arctic. The robust lake δ 18 O chronologies confidently correlate Younger-Dryas (YD) atmospheric adjustments in Alaska with Greenland ice-core records and their seasonal sensitivity are consistent with cooling during winter. In contrast, abrupt δ 18 O decreases during the late Holocene observed in our records, of similar magnitude as the YD, are best explained by atmospheric modes involving long-distance transport of sub-tropical Pacific moisture. Our sediment cores are among the most reliably dated records yet produced in the circum-Arctic and show that similar decreases in δ 18 O of winter precipitation during the YD and late Holocene were driven by different atmospheric teleconnections. These results underscore major roles for seasonality and atmospheric patterns in the conceptual understanding of global scale climate oscillations, both past and future.

Alaska↗
USGS2026

Abiotic and biotic controls of non-native perennial plant success in drylands

Drivers of non-native plant success in drylands are poorly understood. Here we identify functional differences between dryland native and non-native perennial plants and assess how biotic, abiotic and anthropogenic factors shape the success of the latter. On the basis of plant community and functional trait data from 98 sites across 25 countries, we report a total of 41 non-native plant species at 31 sites. Non-natives tend towards faster growth strategies than natives. Non-native plant richness is higher at sites with greater grazing pressure and under environmental conditions associated with higher soil fertility, decomposition and fungal richness—conditions that tend to occur in less arid regions—and lower where native plant and herbivore richness are greater. Non-native plant cover correlates positively with grazing pressure and negatively with native plant richness. Taken together, our results suggest that non-native plant success in drylands is facilitated when high grazing pressure coincides with elevated resource availability. Such context-dependence of non-native plant success and linkages with native plant and herbivore diversity highlight the need for managing grazing and conserving biodiversity across the world’s drylands.

Nature Ecology and Evolution↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2026

Mineral commodity summaries 2026

Introduction Each mineral commodity chapter of the 2026 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2025 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the 2026 MCS are welcomed.

Mineral Commodity Summaries↗
USGS2026

James Buttle Review: A synthesis of riparian plant water use over two decades in North American drylands

Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.

Arizona, California, Colorado, Idaho, Nevada, New ↗
USGS2026

Thiaminase I activity is high in grass and silver carp, but negligible in bighead and black carp

Bighead carp ( Hypophthalmichthys nobilis ), black carp ( Mylopharyngodon piceus ), grass carp ( Ctenopharyngodon idella ), and silver carp ( H. molitrix ) have spurred wide concern of potential ecosystem disruption as they threaten to invade the Laurentian Great Lakes. Besides competition for resources, carp may also have disadvantageous nutrition for predators. One biochemical aspect to consider in carp is production of the enzyme thiaminase that cleaves thiamine (vitamin B 1 ), making it unavailable to most vertebrates. The function of thiaminase within prey fishes is unclear, but roughly half of all fishes tested have measurable thiaminase activity. Predators consuming large volumes of prey with high thiaminase activity can develop thiamine deficiency, ultimately leading to offspring mortality. Three invasive carp (black carp, grass carp, and bighead carp) have no published thiaminase data. We tested juvenile (<160 mm standard length) black carp (n = 38), bighead carp (n = 7), grass carp (n = 50), and silver carp (n = 50) for thiaminase activity. All four species had measurable activity; however, grass carp had statistically higher thiaminase activity (p < 0.001; median = 61 nmol/g/min) than the other three species. Silver carp had the second highest thiaminase activity (14 nmol/g/min). Bighead (2.7 nmol/g/min) and black (2.2 nmol/g/min) carp had the lowest thiaminase activity; activities were often near detection limits. Predators with diets heavily composed of grass carp or silver carp may experience thiamine deficiency, though seasonal variation in carp size and other food source availability may determine potential effects of invasive carp predation in Great Lakes food webs.

Journal of Great Lakes Research↗
USGS2026

Increasing density from population recovery does not explain elevated partial brood loss in a threatened cooperative breeder

Partial brood loss in Dryobates borealis (Red-cockaded Woodpecker), a federally threatened cooperative breeder in the USA, was not associated with increases in population density. Across three populations—Sandhills, North Carolina; Marine Corps Base Camp Lejeune, North Carolina; and Eglin Air Force Base, Florida—we documented no support for density-dependent effects on either early or late partial brood loss. Using long-term nest monitoring data, we evaluated multiple metrics of group size and group density in relation to brood loss at early (egg-to-nestling up to 6–10 days when banded) and late (banding-to-fledgling up to 38–40 days) stages. Reproductive outcomes did not vary with density within populations, indicating that the recent rise in partial brood loss, particularly late in the nestling period, was not driven by increasing density. While both density and partial brood loss have increased over time, these trends appear to be decoupled, highlighting the need to investigate other potential drivers of partial brood loss. Cooperative breeding can buffer reproductive output from density-related pressures through shared parental care, but as densities increase due to conservation-driven population recovery, cooperative breeders may face new or shifting constraints. Variation in reproductive outcomes may be more closely tied to site-specific factors or density-independent pressures such as weather, predation, or habitat quality. As D. borealis populations continue to grow under ongoing recovery efforts, understanding the mechanisms behind partial brood loss remains critical for refining conservation strategies. Our results add to growing evidence that density-dependent effects on reproduction are not universal; increasing density, though a conservation success, does not necessarily lead to reduced productivity or increased brood loss.

Florida, North Carolina↗
USGS2026

Estimating the magnitude and frequency of floods at ungaged locations on urban streams in Tennessee and parts of Alabama, Georgia, Mississippi, North Carolina, and South Carolina, using data through the 2022 water year

In 2024, the U.S. Geological Survey, in cooperation with the Tennessee Department of Transportation, updated the methods for predicting the magnitude and frequency of floods at ungaged locations on streams in urban areas in Tennessee. The study area included 136 streamgages in urban areas in Tennessee, Mississippi, Alabama, Georgia, South Carolina, and North Carolina that had at least 10 percent developed imperviousness in their basins as indicated by data from the 2011 National Land Cover Database. Regression equations were developed to predict streamflows corresponding to the 50-​, 20-​, 10-​, 4-​, 2-​, 1-​, 0.5-​, and 0.2-​percent annual exceedance probabilities (AEPs) and were incorporated into the StreamStats application. In generalized least-​squares regression, the base-​10 logarithm of drainage area, the percentages of the streamgage basins in developed land use, and the percentages of the streamgage basins in the Piedmont and Ridge and Valley Level 3 ecoregions were statistically significant in explaining the variability in annual peak streamflows in the study area. Drainage areas ranged from 0.164 to 93.4 square miles, the percentage of the streamgage basins in developed land use ranged from 26 to 100 percent, and the percentage of the streamgage basins in Piedmont and Ridge and Valley Level 3 ecoregions ranged from 0 to 100 percent. Pseudo R-​squared values for the regression equations ranged from 0.86, or 86 percent, for the 50-​ and 20-​percent AEPs (2-​ and 5-​year floods) to 0.71, or 71 percent, for the 0.2-​percent AEP (500-​year flood). The average variance of prediction (in log base-​10 units) ranged from 0.023 for the 20-​ and 10-​percent AEPs to 0.05 for the 0.2-​percent AEP. The average variance of prediction can be reported as a percentage of the predicted value, known as the standard error of prediction, which ranged from 35.8 percent for the 20-​percent AEP (5-​year flood) to 55.4 percent for the 0.2-​percent AEP (500-​year flood). Methods are presented for estimating annual peak streamflows for gaged locations, ungaged locations on gaged streams, and locations on ungaged streams.

Alabama, Georgia, Mississippi, North Carolina, Sou↗
USGS2026

A fresh perspective - Advancing fish immunotoxicology in a complex world

Understanding how environmental changes affect the health of organisms and ecosystems is complex, but recent interdisciplinary advances and the recognition of immune function as a dynamic mediator offer exciting progress. Environmental immunotoxicology in teleost fishes is evolving beyond cataloguing stressors towards a mechanistic, integrative framework that leverages omics, in vivo tracking and cross-disciplinary modelling. However, knowledge gaps in immune mechanisms, toxicokinetics and multi-stressor interactions remain. The present work highlights these gaps, advocating for immune function as both a mechanistic lens and an integrative health indicator. Such a framework can improve predictive risk assessments, management strategies and our understanding of contaminant effects on resilience, disease susceptibility and population viability. While challenges remain, the field is poised for significant growth through collaborative innovation and advancing technology.

FEBS Letters↗
USGS2026

Seasonal variation in wild pig (Sus scrofa) diet revealed by DNA metabarcoding

Invasive species within North America, particularly wild pigs ( Sus scrofa ), pose a serious threat to native ecosystems through both direct and indirect impacts. Wild pigs are a large-bodied omnivorous species native to Eurasia and introduced to North America. Using DNA metabarcoding of fecal samples, we investigated the diet of wild pigs at a bottomland hardwood forest ecosystem within Felsenthal National Wildlife Refuge in southern Arkansas. We found that the wild pig diet was diverse and included at least 74 plant families and 106 genera, dominated by plant matter with Fagaceae (oaks and hickories), Poaceae (grasses), and Asteraceae (asters, sunflowers, and daisies) comprising over 50% of total dietary detections. Hard mast was a primary food source in fall and winter, while herbaceous vegetation peaked in spring. We documented DNA from 23 species of vertebrates in wild pig fecal samples, including mammals, birds, fish, frogs, and turtles. Vertebrate matter was most frequently detected in autumn. Vertebrate consumption constituted ~17% of wild pig diet by relative read abundance. Our results highlighted the potential long-term ecological consequences of wild pig foraging behaviors, particularly competition for critical food resources with native wildlife and impact on forest regeneration through the consumption of mast. Understanding dietary dynamics is crucial for managing wild pig populations and mitigating impacts on vulnerable ecosystems and wildlife.

Arkansas↗
USGS2026

Geochronologic data reveal Late Pleistocene to Holocene debris-flow history and wildfire association within Whiskeytown National Recreation Area, Klamath Mountains, northern California

Understanding the local to regional history of extreme events such as debris flows and floods provides context to plan for and mitigate these hazards to life, property, and infrastructure. The Klamath Mountains of northwestern California have experienced both debris flows and devastating wildfires. Whiskeytown National Recreation Area (WHIS) is at the heart of this range and has a wealth of debris flow–related landforms. Gaining an understanding of prehistoric flows and their relationship with fire or other potential triggers can help mitigate future problems. Optically stimulated luminescence and radiocarbon analyses from sediment and entrained organics in undisturbed facies, including beneath partially buried boulders, establishes a chronology of paleo-events in WHIS. The levee deposits indicate a repetition of debris flows during the latest Holocene, every 125–150 years, since 850 yr. Larger flows occurred, with a record elucidated from debris-flow deposits along Clear Creek, with Middle Holocene ages, ca. 2600 to 5500 yr, most of which have sufficient concentrations of charcoal to indicate origins as postfire debris flows. Deposits at higher elevations show events from the latest Pleistocene ca. 13,000 yr. This geochronology indicates that these are not singular events but are relatively common and inherent to the geomorphic processes shaping this landscape.

California↗
USGS2026

Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland

The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.

California↗
USGS2026

Wetland characteristics influence dabbling duckling habitat use and movements

The availability of inundated wetlands, near upland nesting habitats, during the brood-rearing period is critical to dabbling duck brood survival and population recruitment. Yet, in some breeding areas, wetland habitats often are drained or dry out during the waterfowl breeding season, which can limit the habitat available for ducklings. In a brackish marsh (Suisun Marsh, California, USA), we evaluated the specific types of wetlands selected by ducklings and quantified the habitat variables that affected wetland selection by dabbling duck hens and their broods from 2016 to 2019. Anas platyrhynchos (Mallard) and Mareca strepera (Gadwall) broods selected semi-permanent wetlands (flooded in the fall and winter and remained inundated until at least August 1) and avoided permanent wetlands (inundated year-round). Mareca strepera broods also selected summer flooded seasonal wetlands (flooded in the spring and summer and remained inundated through August). Anas platyrhynchos and M. strepera broods demonstrated selection for intermediate to larger sized wetlands, wetlands with lower salinity concentrations, and wetlands with intermediate levels of vegetation cover. Ducklings of both species moved rapidly away from the nest during the first week after hatch (mean distance from the nest for 5-day old ducklings: 0.8–1.4 km for the 4 study years), after which ducklings exhibited limited additional movement away from the nest (14-day old ducklings: 1.0–1.6 km among the 4 study years). Increasing the availability of semi-permanent wetlands and summer-flooded seasonal wetlands within 1.4 km of upland nesting sites could decrease the distance ducklings would need to travel to reach preferred wetland types. Decreased travel distance may reduce risk of duckling depredation and improve both duckling survival rates and population recruitment.

California↗
USGS2026

Ensemble methods for history matching and uncertainty quantification with a watershed model

History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and qualitatively compare the results and performance to the stepwise history matching approach. In the latter approach, subsets of parameters and observations were sequentially calibrated to a diverse range of observations to mitigate non-uniqueness and local minima. In iES, localization simulates the same causal connections between parameters and observations without the need (and computational cost) of sequential history matching steps. iES uses a weighted sum-of-squared-errors objective function which allows differential weighting of multiple data sources. Formal adoption of range observation also pushes results to within ranges of observation values rather than discrete values. Overall, the ensemble approach performs similarly to the stepwise approach. Both approaches performed poorly for the cutout representing a snowmelt-dominated watershed, indicating a structural issue in the process representation of the model. The main advantage of iES is quantification of uncertainty in both the history matching and the predictions of interest.

Journal of the American Water Resources Associatio↗
USGS2026

Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave

Chinook salmon population declines span their geographic range with climate hypothesized as a major driver. Concerns of warming freshwater temperatures in their northern range gained urgency during 2019 when a heatwave coincided with premature mortality. This study examined heat stress during the 2019 heatwave compared to subsequent years and described water temperatures in western Alaska to understand the degree to which freshwater temperatures may be a stressor. Heat stress was prevalent among Chinook salmon captured in the 2019 heatwave (Kuskokwim tributaries: 90% in Kwethluk and 63% Takotna river), and variable in subsequent years (∼8% to 60% across Kuskokwim tributaries and Norton Sound rivers). A review of water temperature data indicated that potentially stressful temperatures (≥18 °C) were most common and prolonged in the Yukon River, moderately common and prolonged in the Kuskokwim River, and relatively rare in the Norton Sound region. Water temperatures in 2019 broke several records for overall maximum and frequency of temperatures ≥ 18 °C. Migration water temperatures and heat stress in northern Pacific salmon habitats vary more widely than previously recognized (up to 25 °C).

Alaska↗
USGS2026

Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23

The U.S. Geological Survey, in cooperation with the City of Brownsville, Texas, configured and calibrated a set of hydrologic models for a 217-square-mile study area in Cameron County in south Texas during 2022–23. The models were used for estimating runoff and quantities of water diverted from the Rio Grande/Rio Bravo del Norte (hereinafter referred to as the “Rio Grande”) to maintain water-surface elevations in the canals and resacas (former distributary channels cut off from the main channel of the Rio Grande). Resacas provide habitat to aquatic species and help reduce the effects of flooding. Because of the large size of the study area and diversity of hydrologic conditions, the study area was divided into 11 watersheds, and separate hydrologic models were developed for 9 of the watersheds. Six of the nine modeled watersheds are drained mostly by canals (canal watersheds), and three of the modeled watersheds drain to resacas (resaca watersheds). The Hydrological Simulation Program—FORTRAN was selected for modeling the study area watersheds because it is flexible in simulating a wide variety of watershed conditions. The models were calibrated with streamflow data collected during 2022–23. The calibrated models were used to simulate water budgets (streamflow, evapotranspiration, water-storage volumes, and water diversions and withdrawals) during 2022–23. Model simulations showed that the resaca watersheds required more diversions from the Rio Grande and released less runoff than did the canal watersheds. Management practices maintaining resaca water levels constrained their runoff.

Texas↗
USGS2026

Flood-inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026

Digital flood-inundation maps for a 2.7-mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water-surface profiles were computed for the stream reach by using a one-dimensional, steady-state, step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00-foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water-surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile. The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood-mitigation strategies and to define flood-hazard areas to help protect life and property, to coordinate flood-response activities such as evacuations and road closures, and to aid post-flood recovery efforts.

Puerto Rico↗