USGS Science⌕ Search

SEARCH · USGS Science

Results for “Remote Sensing”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81Linked to original sources
USGS2015

Effect of permafrost thaw on the dynamics of lakes recharged by ice-jam floods: case study in Yukon Flats, Alaska

Large river floods are a key water source for many lakes in fluvial periglacial settings. Where permeable sediments occur, the distribution of permafrost may play an important role in the routing of floodwaters across a floodplain. This relationship is explored for lakes in the discontinuous permafrost of Yukon Flats, interior Alaska, using an analysis that integrates satellite-derived gradients in water surface elevation, knowledge of hydrogeology, and hydrologic modeling. We observed gradients in water surface elevation between neighboring lakes ranging from 0.001 to 0.004. These high gradients, despite a ubiquitous layer of continuous shallow gravel across the flats, are consistent with limited groundwater flow across lake basins resulting from the presence of permafrost. Permafrost impedes the propagation of floodwaters in the shallow subsurface and constrains transmission to “fill-and-spill” over topographic depressions (surface sills), as we observed for the Twelvemile-Buddy Lake pair following a May 2013 ice-jam flood on the Yukon River. Model results indicate that permafrost table deepening of 1–11 m in gravel, depending on watershed geometry and subsurface properties, could shift important routing of floodwater to lakes from overland flow (fill-and-spill) to shallow groundwater flow (“fill-and-seep”). Such a shift is possible in the next several hundred years of ground surface warming, and may bring about more synchronous water level changes between neighboring lakes following large flood events. This relationship offers a potentially useful tool, well-suited to remote sensing, for identifying long-term changes in shallow groundwater flow resulting from thawing of permafrost.

Alaska↗
USGS2017

High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA

Technological improvements in remote sensing and geographic information systems have demonstrated the abundance of artificially constructed water bodies across the landscape. Although research has shown the ubiquity of small ponds globally, and in the southeastern United States in particular, their cumulative impact in terms of evaporative alteration is less well quantified. The objectives of this study are to examine the hydrologic and evaporative importance of small artificial water bodies in the Upper Oconee watershed in the northern Georgia Piedmont, USA, by mapping their locations and modelling these small reservoirs using the Soil Water Assessment Tool. Comparative Soil Water Assessment Tool models were run with and without the inclusion of small reservoir surface area and volume. The models used meteorological inputs from 1990–2013 to represent years with drought, high precipitation, and moderate precipitation for both the calibration and evaluation periods. Statistical comparison of streamflow indicated that the calibration methodology produced results where the default model simulation without reservoirs fit observed flows more closely than the modified model with small reservoirs included (e.g., Nash–Sutcliffe efficiency of 0.72 vs. 0.64, r 2 of 0.73 vs. 0.66, and percent bias of 11.4 vs. 21.6). In addition, Penman–Monteith, Hargreaves, and Priestley–Taylor evapotranspiration equations were used to estimate actual evaporation from 2,219 small water bodies identified throughout the 1,936.8 km 2 watershed. Depending on the evaporation equation used, water bodies evaporated an average of 0.03–0.036 km 3 /year for the period 2003–2013. Using Penman–Monteith further, if the reservoirs were not considered and average actual evapotranspiration rates from the rest of the basin were applied, only 0.016 km 3 of water would have left the basin as a result of evapotranspiration. This finding suggests construction of small reservoirs increased evaporation by an average of 0.017 km 3 per year (approximately 46,500 m 3 /day). As the construction of small reservoirs continues and high resolution image data used to map these water bodies becomes increasingly available, watershed models that evolve to address the cumulative impacts of small water bodies on evaporation and other hydrologic processes will have greater potential to benefit the water resource management community.

Georgia↗
USGS2020

Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data

Upper Klamath Lake (UKL) is the source of the Klamath river that flows through southern Oregon and northern California. The UKL basin is home to two endangered species and provides water for 81,000+ ha (200,000+ acres) of irrigation on the United States Bureau of Reclamation (USBR) Klamath Project located downstream of the UKL basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water right calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance (SSEBop) model with gridded precipitation and USGS station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for five base years (2004, 2006, 2008-2010) and four target years (2013-2016) over irrigated areas above UKL. Our results indicated that the impact of the curtailment program over the June to September time-period was highest during 2013 and declined in each of the following years. The total on-field water savings were approximately 60 hm3 in 2013 and 2014, 44 hm3 in 2015, and 32 hm3 in 2016. The instream water flow change or extra water available (EWA) were found at 92, 68, 45, and 26 hm3 respectively for 2013, 2014, 2015 and 2016. Most water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting EWA from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. This study presents the use of Landsat-based ETa and other remote sensing datasets for evaluating water-related impacts of the irrigation curtailment program.

Upper Klamath Lake Basin↗
USGS2020

Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data

Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well‐suited for long‐term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep‐rooted, non‐native tamarisk shrubs ( Tamarix sp.). After the introduction of the tamarisk beetle ( Diorhabda sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape‐scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000–2009) and after (2010–2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% ( p < .001), while ET decreased 26% from the pre‐ to post‐beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 ( r 2 = .71; p = .009). Tamarisk greenness (a proxy for health) was significantly affected by Diorhabda but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period.

New Mexico↗
USGS2020

Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta

Hydrological and bioclimatic processes that lead to drought may stress plants and wildlife, restructure plant community type and architecture, increase monotypic stands and bare soils, facilitate the invasion of non‐native plant species and accelerate soil erosion. Our study focuses on the impact of a paucity of Colorado River surface flows from the United States (U.S.) to Mexico. We measured change in riparian plant greenness and water use over the past two decades using remotely sensed measurements of vegetation index (VI), evapotranspiration (ET), and a new annualized Phenology Assessment Metric (PAM) for ET. We measure these long‐term (2000‐2019) metrics and their short‐term (2014‐2019) response to an environmental, pulse flow in 2014, as prescribed under Minute 319 of the 1944 Water Treaty between the two nations. In subsequent years, small directed flows were provided to restoration areas under Minute 323. We use 250 m MODIS and 30 m Landsat imagery to evaluate three vegetation indices (NDVI, EVI, EVI2). We select EVI2 to parameterize an optical‐based ET algorithm and test the relationship between ET from Landsat and MODIS by regression approaches. Our analyses show significant decreases in VIs and ET for both the 20‐year and post‐pulse 5‐year periods. Over the last 20 years, EVI Landsat declined 34% (30% by EVI MODIS ) and ET Landsat‐EVI declined 38% (27% by ET MODIS‐EVI ), overall ca. 1.61 mmd ‐1 or 476 mmyr ‐1 drop in ET. Over the 5 years since the 2014 pulse flow, EVI Landsat declined 20% (13% by EVI MODIS ) and ET Landsat‐EVI declined 23% (4% by ET MODIS‐EVI ) with a 0.77 mmd ‐1 or a 209 mmyr ‐1 5‐year drop in ET. Data and change maps show the pulse flow contributed enough water to slow the rate of loss, but only for the very short‐term (1‐2 years). These findings are critically important as they suggest further deterioration of biodiversity, wildlife habitat and key ecosystem services due to anthropogenic diversions of water in the U.S. and Mexico and from land clearing, fires, and plant‐related drought which affect hydrological processes.

Colorado River delta↗
USGS2021

Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado

Loch Vale watershed was instrumented in 1983 with initial support from the National Acid Precipitation Assessment Program to ask whether ecosystems of Rocky Mountain National Park (RMNP) were affected by acidic atmospheric deposition. Research and monitoring activities were expanded in 1991 by the U.S. Geological Survey Water, Energy, and Biogeochemical Budgets program to understand the processes, and their interactions, controlling water, energy, and biogeochemical fluxes. With help from many collaborators we have characterized trends and patterns in atmospheric deposition, climate, and hydrology, including glaciers and other ice features. Instead of acidic deposition, we documented high atmospheric inputs of reactive nitrogen (Nr), and have studied the ecological consequences in soils, surface water, and vegetation. Using paleolimnology, we documented the onset of human-caused change to lake primary producers ca. 1950 in response to increased Nr deposition and warming. Our results provided the basis for the Colorado Nitrogen Deposition Reduction Plan, a state policy that aims to reduce Nr emissions to protect resources in RMNP by 2032. Carbon cycle research revealed mountain wetlands now release more carbon than they store, and respiration and methane flux occurs even during winter through deep snow packs. Trend analyses found export of Nr to be closely tied to atmospheric inputs, but can lag in response to drought. Current research explores consequences of the combination of warming, changes in precipitation dynamics, and atmospheric deposition of Nr and dust on stream and lake CO 2 dynamics, lake biology and trophic state, and soil carbon composition. Dramatic increases in park visitors have prompted studies on the effects of recreational use on water quality. New tools such as remote sensing and high frequency instream water quality sensors are being applied to lake and stream studies. Monitoring, combined with experiments, models, and spatial comparisons is an essential foundation for science-based resource management.

Colorado↗
USGS2008

Ground-based thermography of fluvial systems at low and high discharge reveals potential complex thermal heterogeneity driven by flow variation and bioroughness

Temperature is a primary physical and biogeochemical variable in aquatic systems. Field‐based measurement of temperature at discrete sampling points has revealed temperature variability in fluvial systems, but traditional techniques do not readily allow for synoptic sampling schemes that can address temperature‐related questions with broad, yet detailed, coverage. We present results of thermal infrared imaging at different stream discharge (base flow and peak flood) conditions using a handheld IR camera. Remotely sensed temperatures compare well with those measured with a digital thermometer. The thermal images show that periphyton, wood, and sandbars induce significant thermal heterogeneity during low stages. Moreover, the images indicate temperature variability within the periphyton community and within the partially submerged bars. The thermal heterogeneity was diminished during flood inundation, when the areas of more slowly moving water to the side of the stream differed in their temperature. The results have consequences for thermally sensitive hydroecological processes and implications for models of those processes, especially those that assume an effective stream temperature. Copyright © 2008 John Wiley & Sons, Ltd.

Hydrological Processes↗
USGS2025

Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management

Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.

Hydrological Processes↗
USGS2026

Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States

In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.

Arizona↗
USGS2026

Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems

Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and secondary datasets and 11 repositories and argues how better integration and accessibility of hydrological data can improve research. The paper distinguishes between datasets where streamflow was the primary data collection objective and those where it was secondary. This distinction highlights opportunities to consider data from efforts peripheral to hydrology but is still useful for understanding hydrologic conditions. The analysis reveals that out of about 118 000 active and inactive stream observation sites, about 6.6% and 25% are located on first- and second-order streams, respectively. This indicates a substantial data gap for headwater systems, which account for over 77% of stream length in CONUS. Federal agencies manage 72% of hydrologic monitoring sites across all stream orders, but only 34% of these are in headwater systems. Academic institutions operate about 2% of sites, with almost half (48%) in headwater systems, focusing on ecosystem research. State agencies also operate about 2% of sites, primarily on larger systems, with 19% on headwaters. Additionally, 23% of sites are managed by multiple agencies. Spatial patterns further reveal pronounced disparities among physiographic regions. Eastern and coastal provinces show relatively dense monitoring, while central and western regions show sparse coverage. These gaps reflect historical priorities, logistical constraints, funding limitations, and the high cost of continuous instrumentation. To address biases in monitoring networks, data collection could be enhanced with low-cost monitoring, community science, and remote sensing technologies. This study also notes the benefits of long-term monitoring and prioritizing retention of streamgages with longer records.

conterminous United States↗
USGS2006

Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov&ndash;Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa.

International Journal of Climatology↗
USGS2011

Habitat suitability and nest survival of white-headed woodpeckers in unburned forests of Oregon

We evaluated habitat suitability and nest survival of breeding white-headed woodpeckers ( Picoides albolarvatus ) in unburned forests of central Oregon, USA. Daily nest-survival rate was positively related to maximum daily temperature during the nest interval and to density of large-diameter trees surrounding the nest tree. We developed a niche-based habitat suitability model (partitioned Mahalanobis distance) for nesting white-headed woodpeckers using remotely sensed data. Along with low elevation, high density of large trees, and low slope, our habitat suitability model suggested that interspersion–juxtaposition of low- and high-canopy cover ponderosa pine ( Pinus ponderosa ) patches was important for nest-site suitability. Cross-validation suggested the model performed adequately for management planning at a scale >1 ha. Evaluation of mapped habitat suitability index (HSI) suggested that the maximum predictive gain (HSI = 0.36), where the number of nest locations are maximized in the smallest proportion of the modeled landscape, provided an objective initial threshold for identification of suitable habitat. However, managers can choose the threshold HSI most appropriate for their purposes (e.g., locating regions of low–moderate suitability that have potential for habitat restoration). Consequently, our habitat suitability model may be useful for managing dry coniferous forests for white-headed woodpeckers in central Oregon; however, model validation is necessary before our model could be applied to other locations.

Journal of Wildlife Management↗
USGS2019

Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community

Most wildlife professionals are engaged in 1 or both of 2 basic endeavors: science and management. These endeavors are a focus of many other disciplines, leading to widespread sharing of general methodologies. Wildlife professionals have appropriately borrowed and assimilated many methods developed primarily in other disciplines but have also led the development of one class of quantitative methods, those that confront and incorporate uncertainty. Uncertainty arises in counts of focal entities, for which wildlife professionals have developed effective methods to deal with the common problems of nondetection and misclassification. These methods have been borrowed by disciplines as varied as paleobiology, medicine, human epidemiology, industrial quality control, military target acquisition, remote sensing, and human census. Uncertainty also arises in the modeling of those counts, specifically the observation and ecological processes that generated them. Wildlife professionals recognized the fundamental importance of model selection and rapidly assimilated methods for selecting the most appropriate model for a given data set. These methods for dealing with uncertainty inherent to counting and modeling are critical to the conduct of science and management. Wildlife professionals have developed additional methods for incorporating uncertainty in the accumulation of knowledge and the development of optimal decisions in an environment of learning. In some cases, professionals in other disciplines are using methods developed and popularized in the wildlife profession, but there is much potential for greater use. In this essay, I describe these areas of wildlife leadership, document their assimilation by other disciplines, and emphasize the potential for more interdisciplinary use of these methods.

Journal of Wildlife Management↗
USGS2023

Multi-scale effects of land cover, weather, and fire on Columbian sharp-tailed grouse

Columbian sharp-tailed grouse ( Tympanuchus phasianellus columbianus ) are endemic to grassland and shrub-steppe ecosystems of western North America, yet their distribution has contracted to <10% of their historical range. Primary threats to Columbian sharp-tailed grouse include loss of native habitat and conversion to agriculture, reductions in habitat once provided by the Conservation Reserve Program (CRP), wildfire, and drought conditions, yet population-level consequences of these threats and their spatio-temporal scales of effect are poorly understood. We evaluated multi-scale effects of land cover, weather, and fire histories on patterns of abundance and productivity for Columbian sharp-tailed grouse populations during 1995–2020 in Idaho, USA, using mixed-effects generalized regression and remotely sensed data. We demonstrated negative effects of fire, tree encroachment, and bare ground, positive effects of spring and summer precipitation and cover of shrubs and perennial forbs and grasses, and positive effects of CRP on grouse abundance that changed in magnitude with cover of perennials and shrubs near leks (i.e., strongest effects when average cover of shrubs and perennial forbs and grasses were less abundant). We also demonstrated per capita recruitment of Columbian sharp-tailed grouse is positively associated with late-summer greenness. Our results show that several suspected threats have measurable, population-level impacts to Columbian sharp-tailed grouse within Idaho. Moreover, our results suggest ongoing changes occurring within the core range of Columbian sharp-tailed grouse, including loss of CRP cover to tilled agriculture and changes to wildfire and precipitation dynamics are likely to have negative effects on populations.

Idaho↗
USGS2020

Drivers and projections of ice phenology in mountain lakes in the western United States

Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km 2 ) more than larger lakes (> 2–10 km 2 ). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively.

California, Idaho, Oregon, Washington↗
USGS2025

Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae

Measurements of chlorophyll concentration reported by fluorometers (fChl) are used in environmental research and monitoring, as inputs to models, and in the interpretation of remote sensing data. Researchers and managers benefit from understanding how to interpret and ensure the accuracy of fChl data collected by in situ fluorometers. Although fChl values produced by different manufacturers are often in agreement with discrete laboratory-derived Chlorophyll a (Chl a ) concentration measurements, there are instances in which results significantly differ. Further, when measuring fChl side by side, different fluorometers may report values that differ significantly from each other, despite passing calibration checks prior to deployment. We compared environmental conditions and phytoplankton species composition associated with instances in which fChl measurements from three different fluorometers (EXO2 Total Algae Smart Sensor, YSI Inc./Xylem Inc., Yellow Springs, Ohio; FluoroProbe III, bbe Moldaenke GmbH, Kiel, Germany; WETStar, Sea-Bird Scientific, Bellevue, Washington) were significantly different from laboratory-derived Chl a concentrations. Results indicated that elevated primary productivity, as indicated by high pH, dissolved oxygen, and the ratio of Chl a to phaeophytin, were correlated with underestimated fChl values recorded by each sensor. After removing outliers, we determined unique correction guidance for each of the three sensors and demonstrated that after applying correction formulae, fChl measurements produced by each sensor became directly comparable.

California↗
USGS2026

Demonstration, validation, and application of hyperspectral microscopy for the collection of cyanobacterial spectral signatures

Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins. Algal community composition can be monitored and analyzed by acquiring hyperspectral images that provide information on various photosynthetic and accessory pigments. Validated, traceable measurements are needed to compare data collected by different hyperspectral instruments. In this proof-of-concept study, we detail the development and validation of a custom hyperspectral microscopy imaging system and assess whether this technology can differentiate between cyanobacteria genera based on differences in their reflectance characteristics. As not all cyanobacteria produce toxins, the ability to distinguish among taxa could be used to identify potential toxin-producers and guide field sampling and further research. Spectral characterization of these taxa contributes to remote sensing efforts to characterize and identify cyanobacterial genera at larger spatial scales.

Oregon↗
USGS2026

MusselFinder: Automated dreissenid mussel density estimation via robotic benthic imaging

Despite the widespread need to map the abundance of invasive quagga and zebr mussels ( Dreissena spp.) in lakes and reservoirs worldwide, current methods remain limited by data collection and analysis bottlenecks. Autonomous underwater vehicles (AUVs) combined with machine learning (ML) offer a scalable remote sensing approach for estimating mussel density (individuals m −2 ) across large spatial domains and a range of habitats that are difficult to sample with current techniques. We present MusselFinder: a deep neural network (DNN)-based pipeline that detects and enumerates live mussels in AUV-collected benthic images. MusselFinder estimates live mussel percent cover and density in nadir monocular images captured at known altitudes above the lakebed. In images of suitable clarity, MusselFinder achieved strong pixel-level localization (mussel-class Intersection over Union [IoU] > 0.76) and density prediction (log-density R 2 = 0.79–0.95) over a variety of bottom types. AUV-based image acquisition is more than three orders of magnitude faster than physical sampling by divers or ponar grabs, and DNN-based analysis can proceed at rates comparable to image acquisition. We used MusselFinder to analyze over 50,000 spatially referenced images at a spawning reef in Lake Michigan, representing a shift from small-scale, diver-collected datasets to large-scale monitoring in unconstrained environments. The method can be adapted to new imaging conditions using a modest training set and a user-friendly point-labeling technique, supporting broader-scale monitoring of one of the world's most invasive invertebrates.

Illinois, Michigan↗