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USGS2025

Methods for estimating selected low-flow statistics at gaged and ungaged stream sites in Massachusetts

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, Office of Water Resources, computed selected at-site streamflow statistics at U.S. Geological Survey streamgages in and near Massachusetts and developed regional regression equations for estimating selected streamflows at ungaged stream sites in Massachusetts. Two sets of regional regression equations were developed: (1) the “mainland” equations, for mainland Massachusetts excluding the area covered by the second set, and (2) the “southeastern” equations, for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and for Cape Cod. The regression equations and at-site statistics may be used by Federal, State, and local water managers in addressing water-resources issues relevant in Massachusetts. Regional regression analyses for the mainland equations were developed to estimate the following 27 streamflow statistics: 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent flow durations; monthly June, July, August, and September 90- and 50-percent flow durations; February, June, and August median of the monthly means; harmonic mean; and medians of the following annual low-flow frequency statistics: 7-day; 7-day, 2-year; 7-day, 10-year; 30-day, 2-year; and 30-day, 10-year. The analyses used 81 streamgages with minimal to no regulations in and near Massachusetts. The regression analyses determined that four basin characteristics—drainage area, combined hydrologic soils A and B, streamflow variability index, and annual mean temperature—were the only significant explanatory variables for the different mainland equations. Regional regression equations were developed for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and Cape Cod, because surface-water drainage areas and groundwater contributing areas do not always coincide in this area of the State. The regression analyses to estimate 10 flow durations from the 99th to 50th percentiles used 18 streamflow sites with some occasional minor regulations—because there are few unregulated streams in southeastern Massachusetts. The analyses determined that groundwater contributing area and storage (combined water bodies and wetlands) were the only significant explanatory variables in the southeastern equations.

Massachusetts↗
USGS2025

The 3D Elevation Program—Supporting the economy of Massachusetts

Introduction Massachusetts extends from the mountains of the Appalachian system in the west of the State to the sandy beaches and rocky shorelines of the Atlantic coast in the east. Inland topographic data support a wide range of important activities, including geologic mapping, transportation planning, forest and wildlife management, quantifying ecological services, water supply protection, commonwealth-wide infrastructure planning, local site planning, and flood-plain management. Nearshore bathymetry can be used to support coastal portions of the Commonwealth by addressing the combined threats of ocean warming, strong storm surge, and rising sea levels. The maintenance and (or) expansion of Massachusetts ports (for instance, Boston, New Bedford) and Cape Cod sediment management depends upon the accurate mapping of bathymetry and the frequent influx of sediment and redeposition. Critical applications that address the broad range of requirements depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Massachusetts. The status of available and in-progress 3DEP baseline lidar data in Massachusetts is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.23 million in new benefits annually to Massachusetts. The top 10 Massachusetts business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Massachusetts↗
USGS2024

Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee

The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.

Tennessee↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2026

Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach

Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.

Arizona, New Mexico↗
USGS2025

Ungulate migrations of the Western United States, volume 5

Many ungulates migrate between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. In 2018, the U.S. Department of the Interior established Secretarial Order 3362, which provided Federal support to expand existing research efforts to study ungulate populations and conserve their migrations by enhancing habitat quality for ungulates across the Western United States. In response to the order, the U.S. Geological Survey (USGS) created the Corridor Mapping Team, which is a collaboration among 11 State agencies, regional and Federal partners, and an expanding number of Tribal wildlife agencies. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States and publishes them in the USGS “Ungulate Migrations of the Western United States” report series. This report details migrations and seasonal ranges from 36 additional herds and includes 2 herd updates detailed in previous reports. The Corridor Mapping Team has mapped the migrations and seasonal ranges of 218 unique herds for the report series, including this report. The report series serves as a map-based inventory of the ungulate migrations across the Western United States for biologists, managers, policymakers, and conservation practitioners. Building on the previous report volumes in the series, volume 5 additionally describes some of the local and national initiatives that are incorporating the products, tools, and information from this growing USGS report series.

Navajo Nation↗
USGS2025

Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data

The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km 2 ) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m 2 ) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points ( n =870) during active mapping and accuracy assessment points ( n =216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones. The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m 2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.

Hawaii↗
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

Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa

This report presents the results of a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources to quantify sediment transport source contributions in the Medicine Creek drainage basin. Understanding relative source contributions provides valuable information for selecting the conservation practices that may be most effective in reducing sediment and sediment-associated nutrient transport in the Medicine Creek drainage basin and similar areas of the Lower Grand River drainage basin. Sediment samples were collected from potential contributing areas (source samples) and from fluvial-transported samples (target samples). Source sample types included streambanks, row crop fields, and a combined pastures and forests category. Samples were analyzed for particle size and quantity of carbon, nitrogen, stable isotopes of carbon and nitrogen, and 49 mineral elements as potential tracers. Results for the carbon stable isotope ratio of carbon-13/carbon-12 (δ 13 C) and concentrations of total carbon, total nitrogen, calcium, potassium, and copper were selected by discriminant function analysis as the best combination of multiple tracers to differentiate each source type. The discriminant function analysis poorly differentiated pastures and forests, so these source types were combined. The sources defined by the discriminant function analysis were then used in an unmixing model to apportion sources for each target sample. In the study area, transported sediment was predominantly bank sediment, with an overall average of 86.9 percent of suspended-sediment samples and depositional streambed samples attributed to bank material. Suspended-sediment samples from the mainstem of Medicine Creek were dominated by bank sediments (average of 95.8 percent), and depositional streambed samples from throughout the drainage basin had more variable source contributions with an average of 71.1 percent attributed to bank material. The relative importance of upland sources (row crop fields and the combined pastures and forests category) varied seasonally and with streamflow but was not related to land use or drainage basin size. Relative contributions from upland sources were greater in the summer through winter rather than spring and during lower streamflow, though this may be driven by the seasonality of streamflow. These results indicate management practices that reduce bank erosion could be effective strategies for managing the dominant source of sediment and sediment-associated phosphorus.

Iowa, Missouri↗
USGS2026

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports↗
USGS2025

Protected from Pterygoplichthys? Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River

Objective Nonnative fishes can modify ecosystems and harm economies when they are introduced to new environments. Climate change is likely to assist the spread and establishment of some nonnative fishes (e.g., warmwater species), but spatiotemporal gaps in water temperature monitoring and modeling may prevent ecologists and managers from forecasting thermal habitat suitability for these taxa. The purpose of this study was to develop a predictive model of winter water temperatures and thermal habitat suitability for two priority nonnative armored catfish, Vermiculated Sailfin Catfish Pterygoplichthys disjunctivus and Orinoco Sailfin Catfish P. multiradiatus , in the Suwannee River, Florida and Georgia. Methods Precipitation- and groundwater-corrected air–water temperature models were developed and evaluated using a model selection procedure to predict water temperatures at four sites in the Suwannee River. These models were chosen because they blend the simplicity of air–water temperature models with the accuracy of hydrometeorological models to create an efficient, economical, management-relevant approach for analyzing and forecasting water temperature. Results Most of the top-performing water temperature models (92%) had precipitation or groundwater corrections to air–water temperature formulations. Projected mean and maximum water temperatures increased as simulated climate change intensified. All four Suwannee River sites studied were projected to be thermally hospitable to the survival of Vermiculated Sailfin Catfish. Lower river sites, noticeably warmer than upper river sites, were conducive to the survival of Orinoco Sailfin Catfish throughout the winter months. The upper river sites were too cold for Orinoco Sailfin Catfish survival in some climate-change scenarios, but the Suwannee River has an abundance of constant-temperature springs that are likely hospitable to Vermiculated Sailfin Catfish and Orinoco Sailfin Catfish throughout the year. Conclusions The findings suggest that winter water temperatures will likely not be a barrier to the survival of Pterygoplichthys catfish in the Suwannee River, amplifying the importance of conservation and management approaches to inhibit their spread and establishment. If the Pterygoplichthys population remains small and isolated and decision makers are able to devote required staff time and resources to managing these species, removal and eradication at local if not broader scales may be reasonable goals. This study provides a water temperature modeling approach that can aid ecologists and managers in prioritizing sites to prevent the introduction, slow the dispersal, eradicate, and control Pterygoplichthys catfish and other nonnative fishes in the Suwannee River and beyond.

Florida, Georgia↗
USGS2026

Ungulate migrations of the Western United States, volume 6

This report, volume 6 in the “Ungulate Migrations of the Western United States” report series, showcases the migrations of 23 ungulate herds in the Western United States. The report series is produced by the Corridor Mapping Team (CMT). Led by the U.S. Geological Survey, the CMT is a collaboration among 11 State agencies, as well as regional and Federal partners, and an expanding number of Tribal wildlife agencies. The CMT was initiated in response to the U.S. Department of the Interior Secretarial Order 3362, which was signed in 2018 and provided Federal support to expand existing research efforts to study ungulate populations and conserve their migrations throughout the Western United States. Including this volume, the report series has detailed the migrations of 237 unique ungulate herds throughout the Western United States and continues to serve as a valuable resource to guide local and regional management, policy, and on-the-ground work necessary to maintain intact and functional ungulate migrations. This report highlights several guiding principles of the CMT that facilitate collaboration among the diverse set of partners and contribute to the program’s continued successes. Notably, raw global positioning system data are not shared among participating agencies and the U.S. Geological Survey, delineating migration corridors and seasonal ranges relies on empirical data, the CMT provides flexible approaches to participating State and Tribal partners, and regular CMT meetings create a framework for open communication among agency partners that supports transboundary mapping of migrations. The 237 ungulate migrations that have been included in the report series are an expanding inventory, which can help maintain ungulate migrations in perpetuity.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2026

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan↗
USGS2025

Status of water-level altitudes and long-term and short-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2024

Since the early 1900s, groundwater withdrawn from the primary aquifers that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers—has been an important source of water in the greater Houston area, Texas. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting the status of water-level altitudes and water-level changes in these aquifers in the greater Houston area. In this report, the Chicot and Evangeline aquifers are treated as a single aquifer for the purposes of providing annual assessments of regional-scale water-level altitudes and water-level changes over time. In 2024, shaded depictions of estimated water-level altitudes for the Chicot and Evangeline aquifers (undifferentiated) ranged from about 301 feet (ft) below the North American Vertical Datum of 1988 (NAVD 88) to about 184 ft above NAVD 88. The largest decline in water-level altitudes depicted by the 1977–2024 long-term water-level-change map was in south-central Montgomery County. In comparison, the 1990–2024 long-term water-level-change map depicts the largest declines in water-level altitudes in an area northwest of The Woodlands and in an area of northern Waller County. The largest rise in water-level altitudes for 1977–2024 is depicted in an area of east-central Harris County, whereas the largest rise in water-level altitudes for 1990–2024 is depicted in an area of central Harris County. The 5-year short-term water-level-change map depicts the largest declines in several parts of the study area, but these declines are concentrated primarily in northern Fort Bend County, southwestern Harris County, and south-central Montgomery County. The largest rise for 2019–24 is depicted at a well in northern Fort Bend County. The 1-year short-term water-level-change map depicts the largest declines at a well in northern Fort Bend County and a well in west-central Harris County. The largest rise for 2023–24 is depicted at a well in east-central Fort Bend County. In 2024, shaded depictions of estimated water-level altitudes for the Jasper aquifer ranged from about 255 ft below NAVD 88 to about 321 ft above NAVD 88. The 2000–24 long-term water-level-change map depicts the largest water-level decline in an area of central San Jacinto County; the largest rise is depicted in an area of central Grimes County. The 5-year short-term water-level-change map depicts the largest declines across parts of central and southern Montgomery County and at one well in north-central Harris County. The largest rise for 2019–24 is depicted at a well centered on the Montgomery-Grimes County line. The 1-year short-term water-level-change map depicts the largest declines at two wells in south-central Montgomery County and one well in northwestern Montgomery County on the west side of Lake Conroe. The largest rises during 2023–24 are depicted at one well in northwestern Montgomery County and one well in south-central Montgomery County.

Texas↗
USGS2025

Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019

Cyanobacterial harmful algal blooms (CyanoHABs) have become increasingly common, threatening the security of water resources globally. The U.S. Geological Survey conducted high-resolution nearshore mapping surveys using boat-mounted multiparameter sondes and nitrate sensors during the summer and fall of 2019 on Owasco Lake and Seneca Lake, two lakes with documented CyanoHABs in the Finger Lakes region of New York State. Discrete sensor measurements and water-quality samples were collected at fixed points along survey routes and continuous data were generated at open-water monitoring platforms. This investigation examined whether water-quality information from nearshore surveys was representative of open-water conditions and if nearshore surveys could be used to identify areas with localized nearshore CyanoHABs and potential sources of nutrients not captured by tributary sampling. In addition to comparisons across methods, nearshore concentrations of nitrate and chlorophyll were evaluated relative to tributary outlets, cyanobacterial abundance and biovolume at discrete locations, and the locations of near-surface CyanoHABs that were designated as “confirmed with high toxins” by the New York State Department of Environmental Conservation. Nitrate and chlorophyll concentrations were comparable across methods for each lake, although concentration ranges were typically higher for nearshore mapping datasets than for nearshore discrete datasets. Nearshore surveys indicated areas of nitrate enrichment that varied temporally in both lakes. Orthophosphate was not routinely detected. Across methods, median chlorophyll concentrations were higher for the summer survey than for the fall survey in Owasco Lake. Nearshore chlorophyll concentrations varied more temporally in Owasco Lake than in Seneca Lake. Phytoplankton and cyanobacterial abundance and biovolume were about five times higher in Owasco Lake than in Seneca Lake. Cyanobacteria dominated the phytoplankton community in most samples, and Microcystis comprised the bulk of the cyanobacterial biovolume. The most abundant potential cyanotoxin-producing (specifically microcystins) genera were Microcystis , Synechococcus , Aphanocapsa , and Pseudanabaena . The cyanobacterial community composition was comparable between open-water monitoring platforms and nearshore samples. Microcystins were detected in seven survey samples from Owasco Lake, in one survey sample from Seneca Lake, and in one sample each from the open-water monitoring platforms on Owasco and Seneca Lakes that were collected about 7 days before the fall surveys. Microcystin detections were not consistently associated with high cyanobacterial cell counts or cyanotoxin-producing genera. Results from nearshore surveys were comparable to open-water monitoring platforms and discrete nearshore observations in the absence of nearshore or open-water CyanoHABs in these systems during the study. Patterns of nearshore concentrations of nitrate and chlorophyll from nearshore surveys may aid in the identification of areas with localized nitrate loading and shifts in phytoplankton abundance and community composition.

New York↗
USGS2025

“Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams

“Leaky weirs” are rock structures installed in dryland streams, which are anchored into exposed bedrock, loosely cemented, and designed to allow water to slowly pass through. They are being tested at a ranch in southeastern Arizona, USA, to restore and conserve the historic range and desert wetlands. Data are collected to assess how leaky weirs impact surface water, subsurface water, and groundwater recharge—including stream discharge, timing, and depth of infiltration, and groundwater elevations. Three adjacent watersheds, two with outlets just below leaky weirs and one with leaky weirs farther upstream, were instrumented with water-level loggers, wildlife cameras, and crest stage instruments with temperature sensors in the soil. As most groundwater recharge is assumed to be focused along the mountain fronts in this region, mountain-block recharge is also evaluated to differentiate between the two using isotope analyses. Finally, a single, late-season flood event is scrutinized to consider the leaky weir effect on all monitored components in the water budget. Results indicated groundwater flow is primarily from the mountains to the east via older, regional mountain-block recharge. However, the development of shallow alluvial aquifers is supported by the leaky weirs, that slow flows, capture permeable sediments, and allow infiltration, thus enhancing mountain-front recharge. In turn, these new pockets of water help support the restoration of historic wetlands. Sediment accumulates where leaky weirs are installed, reducing flashy peak flows, and resulting in a series of infiltration ponds along the channel that support vegetation during growing seasons and recharge the shallow aquifer during non-growing seasons.

Arizona↗
USGS2026

Evaluating harvest liberalization strategies on population dynamics of southern latitude temperate-breeding Canada geese

The recovery of the Canada goose ( Branta canadensis ) is one of North America's greatest conservation success stories. Today, continental abundance of temperate-breeding Canada geese (those breeding in southern Canada and lower 48 states in the United States) greatly exceeds historical levels. As a result of increased abundance, human–goose conflicts have also increased, ranging from private and agricultural property damage to human health concerns. Managers have primarily attempted to lower Canada goose populations using hunter harvest via liberalized hunting regulations (increased bag limits and total hunting days). To evaluate the effectiveness of harvest strategies for temperate-breeding Canada geese, managers need a better understanding of how liberalized hunting regulations affect population dynamics. We estimated survival and harvest probabilities, abundance, and recovery distribution of temperate-breeding Canada geese banded in Arkansas, USA, during 2005–2020. We found that adult harvest probabilities declined overall during the study and adult survival probabilities increased. Annual abundances of juvenile geese (≤1 year old) declined during the study, whereas there was no detectable trend in abundance of the adult population over time. Most Canada geese breeding in Arkansas were shot in Arkansas, indicating potential for population dynamics to be influenced largely by state-specific harvest regulations. However, our results suggest that harvest liberalization as a management tool may have limited capacity to further influence population dynamics of Canada geese. Declines in productivity and recruitment likely had a greater influence on the similar observed declines in juvenile and adult abundances, respectively, during our study. More research is needed to better understand the ecological mechanism affecting the population dynamics of Canada geese in both urban and rural environments.

Arkansas↗