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At least 955 records · Page 53Linked to original sources
USGS2026

Evaluation of turbidity corrections for EXO fluorescent dissolved organic matter (fDOM) sensors

Executive Summary The use of field-deployable fluorescence sensors to better understand dissolved organic matter concentrations and composition has grown immensely in recent years. Applications of these sensors to critical monitoring efforts have also grown, encompassing post-fire monitoring, wastewater tracking, and use as a proxy for various contaminants. Despite the growth, it is well known that these sensors require corrections for temperature (Watras and others, 2011) and are subject to many light-field interferences caused by both scattering and absorbance due to dissolved and particulate substances (Downing and others, 2012; Lee and others, 2015; Booth and others, 2023). The most common fluorescence sensors used by the U.S. Geological Survey (USGS) include those targeting fluorescent dissolved organic matter (fDOM) and chlorophylls. Because fDOM sensors primarily measure fluorescence in the dissolved to colloidal phases, corrections to the interferences caused by particulates can be made relatively easily. By the end of 2024, the USGS had 69 fDOM sensors deployed within official water quality monitoring networks included on the USGS National Water Dashboard ( https://dashboard.waterdata.usgs.gov/app/nwd/en/ ) and numerous others used in surveys and research applications across the Nation. Although temperature corrections are widely applicable across sensor models, interference corrections can be model specific due to differences in design specifications across manufacturers and models (Booth and others, 2023). The corrections are also potentially subject to changes in manufacturing within a specific sensor model. Recently, USGS staff obtained information regarding possible changes in the manufacturing of its most widely-used fDOM sensor model, raising concerns about data consistency and quality in the USGS fDOM sensor networks. Furthermore, changes in turbidity sensors since the corrections guidance was performed may also affect the performance of the corrections. The turbidity sensor used in the original experiments (Downing and others, 2012) was determined to have a signal output approximately 1.3 times higher than the output of the turbidity sensor currently used in an extensive field comparison study (Messner and others, 2023). With these changes, it is imperative that the corrections be reevaluated to maintain data consistency and continuity across the USGS. In this study, we evaluated turbidity corrections for fDOM sensors over a range of serial numbers covering manufacturing dates 2015 through 2022 and turbidity serial numbers covering the range 2013 through 2022. The goal was to determine whether reported changes in the manufacturing process of the fDOM and turbidity sensors affected the correction approach developed by Downing and others (2012) such that additional guidance would be required to address this manufacturing change. To evaluate, we repeated a laboratory-based test similar to that performed by Downing and others (2012) in which a series of tank experiments with multiple sensors were deployed in a suspension of Elliot Silt Loam (ESL). High turbidities of the ESL suspension were maintained throughout the tank by turbulent recirculation using submersible pumps. Particulates were removed using a recirculated line equipped with a capsule filter (0.45 micron). Measurements were collected throughout the filtration until turbidities reached approximately 5 formazin nephelometric units (FNU; data available in Baxter and others, 2023). Each experimental run included a mixture of unique sensor combinations to account for variability imposed by the turbidity and temperature sensors. The fDOM correction factor was calculated for each combination of fDOM and turbidity sensors included in the test. We observed no systematic change in fDOM correction coefficients across serial numbers representing manufacturing years 2015 through 2022. However, the results highlighted questions raised about the corrections for high-turbidity samples, as noted in USGS Techniques and Methods (Booth and others, 2023). Applying the inverse of the commonly-used fDOM ratio with a quadratic fit performed better than the exponential fits when correcting fDOM data for turbidity in the ESL laboratory filtration test and generated a simple scale factor correction equation. This approach also served as a better indicator of data quality than the exponential fit approach. Similar to fDOM, more rigorous quality assurance measures may be necessary to evaluate turbidity sensor calibrations and performance. Sensors exceeding a certain age may need to be replaced despite passing quality assurance checks during calibration. Further testing of the turbidity corrections for different sediment and water types is warranted to better understand the variations in the fits and correctable ranges of turbidity in different systems.

Open-File Report↗
USGS2026

Who needs closure? Estimating abundance with a Markovian availability model for geographically open removal sampling

Removal sampling is an important method for estimating abundance, but nearly all removal models assume closure during sampling. Yet, closure may be difficult to assume, evaluate, or enforce in many settings. To address situations where populations are geographically open between each removal sample, we incorporated a Markovian availability process into an N-mixture model framework. This model relates local abundance available for sampling to a superpopulation through recruitment of new individuals to the sampling area. To test the model, we (1) conducted parameter identifiability analysis, (2) fit the model to removal data generated from a random walk movement model, and (3) analyzed a case study of empirical removal data. Parameters were increasingly identifiable as capture probability exceeded 0.25 and removal samples increased from 3 to 6. Abundance estimates were unbiased when parameters were identifiable, except for scenarios that simulated a behavioral response to sampling. For our case study, the model estimated negligible recruitment for benthic-oriented fishes, indicating closure, but we found evidence against closure for juvenile Chinook salmon, a highly mobile species. Our removal model allows researchers to formally test closure assumptions, to estimate the degree of closure, and to estimate abundance without bias when closure is violated.

California↗
USGS2026

Fragmentation as a population rate-changer: A field experiment

Experimental and observational studies of effects of fragmentation on biodiversity and population dynamics have produced mixed results, with some reviews concluding strong evidence of negative effects and others concluding small positive effects. In addition, many factors (e.g., interspecific interactions, edge effects, nutrient cycling) have been identified as potential explanations underlying the various results. We carried out a population-level fragmentation study on meadow voles, focusing on changes in vital rates caused by reduced movements in experimental 2-patch systems. We developed predictions of fragmentation effects by decomposing rates of apparent survival and recruitment (parameters directly estimated using capture–recapture models) into components that do and do not include movement. Fragmentation was predicted to reduce movement rates, and reduced movement was predicted to increase apparent survival rates, decrease immigration rates, and slightly increase population growth rates. We found evidence of increased adult and juvenile apparent survival and adult population growth rate on fragmented grids, whereas results for recruitment were ambiguous and did not support our predictions. The recruitment results led to the hypothesis that immigration into suitable habitat may not be reduced by fragmentation as much as permanent emigration from that habitat. A focus on effects of reduced movement on vital rates should be a reasonable starting point for investigations of fragmentation effects. This focus suggests that explanations underlying fragmentation effects will require additional effort devoted to isolating movement components of vital rates.

Ecology↗
USGS2026

Measuring storm waves and water levels from a fixed structure with a rapidly deployable oceanographic radar

A new oceanographic radar instrument package was developed by the U.S. Geological Survey (USGS) to measure storm waves and water levels in the nearshore, capable of being deployed rapidly and transmitting data in near real-time. To test the performance and accuracy of the sensor, multiple years of data were collected over various hydrodynamic conditions and compared to long-term monitoring data collected at the U.S. Army Corps of Engineers (USACE) Field Research Facility in Duck, North Carolina, USA. The oceanographic radars were highly reliable, with less than 1% of the record being erroneous spikes or missing data points. At the end of the pier, the radar was highly accurate, with nearly perfect agreement in water level ( r 2 = 0.997) compared to a nearby National Oceanic and Atmospheric Administration (NOAA) tide gauge, and good agreement in significant wave height ( r 2 = 0.98) and peak wave period ( r 2 = 0.65) compared to a nearby USACE sensor. This work demonstrates the potential of the USGS radar for rapid response storm deployments and collecting reliable and accurate hydrodynamic measurements in the nearshore for validating coastal impact models.

North Carolina↗
USGS2026

Climate-driven waterline variability along the North American West Coast

Sandy coasts are highly dynamic environments shaped by a myriad of hydro-sedimentary processes operating across various spatio-temporal scales. From seasonal to centennial timescales, sandy beach dynamics are strongly influenced by climate variability expressed in various forms, including seasonal cycles, climate modes (e.g., El Niño Southern Oscillation (ENSO)), and global warming. Satellite-based methods enable the observation of coastlines with unprecedented spatial and temporal coverage. However, over the past decade, as these methods have matured, coastal change studies have predominantly focused on long-term trends rather than on climate-driven cycles of shoreline change. In this study, we utilize a large dataset of monthly-sampled time series of waterline positions along the Pacific Coast of the United States and Baja California, Mexico. From these time series, we derived information on long-term trends and seasonal cycles of waterline change. Our analysis reveals clear contrasts in seasonal patterns of waterline variability across the study area, with greater amplitudes observed at higher latitudes. A shift in the dominant dynamics is evident in Southern Baja California, where shoreline variability is more influenced by intertropical dynamics and sea-level anomalies than by wave energy modulation, which dominates further north. ENSO is found to induce contrasting responses of the waterline along the study area. During El Niño events, shoreline retreat is observed in subtropical regions, while La Niña winters drive waterline retreat in higher latitudes, with southern regions either remaining stable or advancing.

Baja California, California, Oregon, Washington↗
USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗
USGS2026

Comparison of nonlethal techniques as indicators of lipid content in Lake Whitefish

Objective Energetic reserves are important indicators of the relative health of fish and fish populations. Body condition indices that relate fish weight to length are commonly used as quick, noninvasive methods for approximating lipid content and condition. A microwave meter (i.e., fat meter or energy meter) is a noninvasive method found to be more accurate in some species. The objective of this study was to evaluate the suitability of nonlethal techniques for estimating muscle lipid content in Lake Whitefish Coregonus clupeaformis . Methods We compared the sensitivity of three nonlethal indicators of lipid content to laboratory-extracted muscle lipid content in Lake Whitefish, including readings from a handheld microwave meter at several positions, Fulton’s condition factor, and relative weight. Results We found significant, positive relationships between lipid content and each estimation method, except relative weight, with weak to moderate correlations. The microwave meter was moderately correlated to lipid content when positioned anterior to the dorsal fin above the lateral line ( r 2 = 0.50), while other positions and combinations of positions had weaker correlations ( r 2 range = 0.27–0.45). Correlation was only slightly improved by including additional model variables (i.e., length and weight). Fulton’s condition factor was weakly correlated with lipid content ( r 2 = 0.19), while relative weight was not significantly correlated with lipid content. Conclusion The microwave meter provides an improvement to muscle lipid estimation compared with length–weight body condition indices; however, microwave meter readings alone do not constitute a reliable predictive measure for true muscle lipid content under the conditions tested here. We hypothesize that the low strength of correlation may be due to low muscle lipid content or the presence of thick scales in Lake Whitefish. Further investigation is needed to understand the mechanisms negatively affecting the predictive performance of the microwave meter in Lake Whitefish and other species.

Michigan↗
USGS2026

From understanding to action: Integrating new and old methodologies to manage marine infectious disease

Marine diseases can have far-reaching effects on population, community and ecosystem health; however, our ability to track, predict and manage these diseases has, historically, been poor. As a result, the fields of disease ecology and epidemiology have developed at a slower pace for marine than terrestrial systems [ 1 ]. New methodologies, including genomic tools for diagnostics [ 2 , 3 ], transcriptomic tools for measuring host and pathogen responses to infection (e.g. [ 4 , 5 ]), regional oceanic modelling systems that estimate environmental conditions influencing pathogen dispersal and disease progression [ 6 ], artificial intelligence methods for quantifying pathology from images (e.g. [ 7 ]) and advanced disease modelling techniques [ 8 , 9 ] are precipitating a rapid increase in our understanding of marine pathosystems. In 2016, these efforts led to the first special issue of Philosophical Transactions of the Royal Society B ( Marine diseases, volume 371, issue 1689) focused entirely on marine disease ecology and evolution, and in 2020, the first book, Marine disease ecology, was devoted to this topic [ 10 ]. This special issue, focused on marine disease management , is being published a decade after the first Philosophical Transactions special issue on marine diseases. The shift to a management focus reflects an urgent need for management strategies to address high-impact diseases and the rapid methodological advances that have resulted. The papers included in this issue demonstrate the value of combining classical approaches (e.g. routine disease surveillance, reductionistic pathogen challenge trials, rapid throughput diagnostics) with cutting-edge technologies (e.g. high-resolution oceanographic models, Bayesian models, replicated transcriptomic studies) to identify drivers of disease, quantify impacts and suggest management strategies.

Philosophical Transactions of the Royal Society, S↗
USGS2026

Region-specific understanding of virus transmission to support salmonid health at hatcheries in three regions of the Pacific Northwest, North America

Juvenile salmonid mortality due to infectious haematopoietic necrosis virus (IHNV) can be a major burden on fish hatcheries. We consider possible IHNV transmission routes and specialist–generalist patterns across three regions in the Pacific Northwest of North America: Coastal Washington and Oregon (CWO), Lower Columbia River Basin (LCRB) and Snake River Basin (SRB) to obtain multi-region inference about IHNV transmission and specialization. While individual regions have been studied previously, our consideration of three regions to identify consistent trends or localized patterns is novel. The most consistent patterns we found were that most exposure to IHNV was from migrating adult salmonids and that the IHNV lineage MD specialized in steelhead and rainbow trout. Our results were consistent with LCRB being a source of IHNV and the SRB and CWO being sinks. Results specific to particular regions include the role of local geography on exposure and influence of hatchery complexes on transmission, which highlights the need to understand local hatchery operations before disease ecology can be understood and suitable hatchery management can be planned. Results demonstrate the need for spatially and temporally explicit quantitative approaches to understand disease dynamics and inform management.

Oregon, Washington↗
USGS2026

Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes

Understanding how climatic variables impact host-pathogen relationships in temperature-sensitive ectothermic host organisms is crucial under global change. Few studies have explored how temperature gradients generate inter-individual variation in epidemiological traits like host susceptibility or pathogen replication. Here, we develop a mathematical model to explore a novel hypothesis: stochastic within-host dynamics and simulated thermal mismatches between host and pathogen traits generate predictable variation in infection outcomes among hosts and across thermal gradients. Our model demonstrates that varying trait thermal optima in host immunity and pathogen replication, and stochastic within-host processes produced variation in infection outcomes. Variability was low when temperatures strongly favored host or pathogen traits, but high and diverse when their performance was similar across a broad thermal range. In contrast, when trait performance was equal across all temperatures (no mismatch) variability remained low at all temperatures. Further, the magnitude of variation, quantified by entropy, exhibited predictable patterns depending on host-pathogen thermal mismatches. We conclude that interactions between trait thermal mismatches and within-host stochasticity provide a theoretical framework to improve ectotherm disease models under climate change, providing a valuable tool for exploring the impacts of environmental change on epizootic or epidemic dynamics, particularly in vulnerable marine ecosystems.

Philosophical Transactions of the Royal Society, S↗
USGS2026

The impacts of co-circulating pathogens in Pacific herring depend on interactions between viral life-cycle traits and transmission parameters, highlighting interdependencies between pathogen epizootics

The average host susceptibility decreases as the epizootic progresses because easily infected hosts are first removed from the population. While host susceptibility is pathogen-specific, it is likely that host susceptibility is correlated between different pathogens, so that co-circulating pathogens may have reciprocal impacts on their epidemics. However, despite well-documented examples of concomitant infections in marine hosts, reciprocal epizootic effects have not been documented in wild marine organisms. We quantify reciprocal impacts between viral haemorrhagic septicaemia and viral erythrocytic necrosis in Pacific herring ( Clupea pallasii ) using field and laboratory work. We show that the causative viruses for both diseases circulate through herring populations and that infection with one pathogen has negative impacts on the epizootic and infection characteristics of the other pathogen, suggesting positive correlations in the susceptibility to infection between pathogens. We then use simulations of a two-strain pathogen model to show that the impact of the correlation is modulated by transmission parameters, such as the incubation period and the initial transmission rate. Our work shows that co-occurring epizootics pose a management challenge because single-pathogen management actions may amplify the epizootics of the non-targeted pathogen. This study provides a framework to evaluate the consequences of reciprocal epizootic impacts through field, experimental and modelling work.

Washington↗
USGS2026

Decadal-scale characteristics of natural and anthropogenic dune morphology along North Carolina Barrier Islands (SE Atlantic Coast)

Dunes offer protection to coastal communities from storms, yet quantitative research characterizing human influences on dune systems across decades and 10–100 km spatial scales constitutes a known data gap. This study analyzed a multidecadal archive of dune crest elevations and positions to map mesoscale spatiotemporal trends in foredune morphology across the barrier island coastline of North Carolina, SE Atlantic coast. Results are summarized within four categories of coastline representing a range of coastal management intensities, integrating beach width and dune lateral accommodation space to assess the comparative influence of differing intensities of anthropogenic intervention on dune morphology. These categories account for the presence of structures, roads, and alongshore connectivity to anthropogenic sediment sources (beach nourishment). These categories show distinct dune and beach system characteristics. Dunes are largest in the areas with the longest legacy of coastal management. As categories decrease in development intensity, dune and beach system characteristics generally depart from the large, static dunes and narrow beaches consistent with hold-the-line management. Where small or transgressive dunes exist on heavily developed coasts, they coincide with relatively strong hydrodynamic forcing or sediment-limiting geology. There is evidence of indirect coastal management influence on undeveloped barrier islands with alongshore connectivity to developed barriers. While this analysis was conducted at the mesoscale, the results provide researchers with the framework to make insights at smaller scales than those demonstrated in this study.

North Carolina↗
USGS2026

Landsat 8–9 geometric and radiometric calibration and characterization

The U.S. Geological Survey Earth Resources Observation and Science Cal/Val (Calibration and Validation) Center of Excellence is a global leader in improving the accuracy, precision, and quality of remote-sensing data. Calibration is the process of quantitatively defining a system’s response to known and controlled signal inputs. Validation is the process of assessing, by independent means, the quality of the calibrated data products derived from system outputs. The Landsat Cal/Val team, comanaged by the Earth Resources Observation and Science Cal/Val Center of Excellence and the National Aeronautics and Space Administration Landsat Science Project, continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level, ensuring its reliability for scientific research. Landsat data quality is often referred to as the “gold standard” and gives other civil and commercial satellite programs a trusted reference point for measuring their own data quality. The Landsat program started more than 50 years ago. Since then, Landsat missions have gone through multiple technological advances, which, together with improved calibration and validation techniques, have led to higher data quality over time. The Cal/Val team also maintains consistency in data calibration across the multiple generations of sensors, which is vital to many scientists for time-series analysis.

Fact Sheet↗
USGS2026

Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2024 breeding season

The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets ( Recurvirostra americana ), black-necked stilts ( Himantopus mexicanus ), and Forster’s terns ( Sterna forsteri ). These three species have relied largely on former commercial salt ponds in south San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring as much as 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt-pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt-pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project will maintain some pond habitat for wildlife and provide enhancements such as the construction of new islands for nesting. The South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained. In this report, we provide results of waterbird nest monitoring in south San Francisco Bay during the 2024 breeding season and present these results in the context of annual nest monitoring in south San Francisco Bay since 2005. Overall, Forster’s tern nest abundance in 2024 (1,808 nests) was the highest recorded between 2005 and 2024, and it maintained the high abundance first observed in 2022 (1,727 nests), which reversed the historically low abundance observed during 2015–17. In contrast, nest abundance remained at or near 20-year lows for American avocets (222 nests) and black-necked stilts (126 nests) in 2024, but both species had small increases in their nesting population sizes compared to 2022. In 2024, there were only 3 Forster’s tern, 5 American avocet, and 3 black-necked stilt major colony nesting sites, which is down from the annual averages of 6.6, 12.4, and 6.6 observed during 2005–09. Nest success (73 percent for American avocets, 54 percent for black-necked stilt, and 64 percent for Forster’s terns) increased compared to 2022 (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) and during 2005–10 (37 percent for American avocets, 24 percent for black-necked stilt, and 61 percent for Forster’s terns). Nest success in 2024 was above (American avocets and black-necked stilts) or slightly below (Forster’s terns) baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success was lower for American avocets (86 percent) and Forster’s terns (86 percent) and similar for black-necked stilts (96 percent) than the values observed during 2005–10. Average clutch sizes for American avocets (3.87 eggs), black-necked stilts (3.88 eggs), and Forster’s terns (2.73 eggs) were greater than what was observed in 2022 and during 2005–10. Average nest-initiation dates in 2024 were substantially earlier among all three species (April 19 for American avocets, April 25 for black-necked stilts, and May 12 for Forster’s terns) than in 2022 (May 4 for American avocets, May 13 for black-necked stilts, and May 20 for Forster’s terns) and during 2005–10 (May 15 for American avocets, May 3 for black-necked stilts, and May 30 for Forster’s terns). Finally, the enhanced managed ponds with newly constructed islands (Ponds A16 and SF2) supported 52 percent of American avocet nests, 47 percent of black-necked stilt nests, and 94 percent of all the Forster’s tern nests recorded in south San Francisco Bay in 2024.

California↗
USGS2026

Floods of June 2024 in northwestern Iowa

Following a heavy, multiday rainfall event that took place between June 20 and June 22, 2024, widespread flooding occurred in parts of northwestern Iowa. Ten U.S. Geological Survey (USGS) streamgages with periods of record ranging from 56 to 99 years in length experienced new peaks of record, three of which were more than double the previous peak-of-record: 06483500 (Rock River near Rock Valley, Iowa), 06605850 (Little Sioux River at Linn Grove, Iowa), and 06606600 (Little Sioux River at Correctionville, Iowa). A Presidential declaration of a major disaster for the State of Iowa was approved on June 24, 2024, and the cost of the flooding is estimated at over $310 million. The severity of this flooding prompted the USGS, in cooperation with the Iowa Department of Transportation, to summarize the meteorological and hydrological conditions preceding the flooding, compile estimates of the magnitude of peak flows resulting from the flooding, and update estimates of peak-flow frequency for selected USGS streamgages. Of the 33 streamgages analyzed, a peak streamflow occurred that corresponded to an annual exceedance probability of less than 4 percent at 13 streamgages, an annual exceedance probability of less than 1 percent at 6 streamgages, and an annual exceedance probability of less than 0.2 percent at 1 streamgage.

Iowa↗
USGS2026

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River↗
USGS2026

Measurements of wave runup on an atoll island using LiDAR

Coral atoll islands are highly susceptible to flooding and overwash due to their low-lying nature and the impacts of climate change. This study presents the first long-term, high-resolution field dataset of wave runup on a coral atoll island, collected over 6 weeks using a shore-mounted LiDAR scanner. The LiDAR data captured swash dynamics on a steep coral rubble beach fronted by a conglomerate platform. Results demonstrate the limitations of depth-based swash extraction methods, particularly for thin swash events, where depth thresholds lead to significant underprediction. Further analyses show that low-frequency oscillations (infragravity and very-low-frequency bands) and high-frequency components (transitional bores) dominate the spectra on the reef platform and are reflected in the swash signal. The displayed swash spectra highlight the critical role of low-frequency oscillations in extreme runup events, emphasizing their contribution to island flooding and overwash.

Conference Paper↗