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At least 883 records · Page 49Linked to original sources

USGS2015

Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover ( r 2 = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass ( r 2 = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.

Maryland↗

USGS2020

Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements

Surface soil temperature is the soil temperature from the surface to 10 cm in depth. Surface soil temperature plays a significant role in agricultural drought monitoring, ecosystem energy transfer modeling, and global carbon cycle evaluation. Studies have been proposed to estimate surface soil temperature, but surface soil temperature monitoring within forested areas still poses a significant challenge. In this study, we proposed a surface soil temperature retrieval method using combined satellite observations and in-situ measurements for the Great Dismal Swamp (GDS). The GDS is a U.S. protected area managed and protected by the U.S. Fish and Wildlife Service. It is located along the boundary of Virginia and North Carolina, with maple gum, Atlantic white cedar, and pine pocosin as the main forest cover types. Ground-based surface soil temperature measurements were collected for these forest types from May 2015 to April 2017. Both the Land Remote Sensing Satellite (Landsat) Thermal Infrared Sensor (TIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) carry two thermal infrared (TIR) channels. The TIR channels with similar corresponding wavelengths were first fused using an improved fusing model to generate high resolution TIR measurements. Then the enterprise algorithm was applied to calculate land surface temperature (LST) from the fused TIR bands. An improved soil temperature retrieval method was applied to generate surface soil temperature based on LST and vegetation index (VI) within the study area for the three forest types. In-situ measurements were used to build the surface soil temperature retrieval method, and results were then validated. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were integrated separately as VIs in the model to monitor surface soil temperature. The R 2 for retrieved surface soil temperature through satellite observations was 0.76, and the RMSE was 1.96 ℃ ">℃ ℃ when NDVI was integrated in the model; the R 2 was 0.78, and the RMSE was 1.85 ℃ ">℃ ℃ when EVI was used.

North Carolina, Virginia↗

USGS2022

Achieving sub-nanoTesla precision in multirotor UAV aeromagnetic surveys

An uncrewed aerial vehicle (UAV) multirotor aeromagnetic system using a 5-m sling load for a magnetic sensor system is described and characterized. Four magnetic surveys with identical flight lines were completed, at two nominal altitudes of 25 and 40 m. The surveys were used to assess the repeatability of data collected with the described UAV aeromagnetic system, and comparison with a ground survey was used to assess the precision. The 5-m sling is designed to reduce magnetic interference from the UAV. A magnetic compensation model was developed for this particular UAV aeromagnetic system. This custom compensation model reduces the noise in the collected data by a factor of five over the uncompensated data, and the 5-m sling further reduces the noise by an estimated factor of four over a similar system with a 3-m sling. The precision of the UAV aeromagnetic system was then estimated to be sub-nT, with 50% of the noise component <0.3 nT, and 90% <0.6 nT.

Journal of Applied Geophysics↗

USGS2004

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Journal of Arid Environments↗

USGS2008

Multiyear riparian evapotranspiration and groundwater use for a semiarid watershed

Riparian evapotranspiration (ET) is a major component of the surface and subsurface water balance for many semiarid watersheds. Measurement or model-based estimates of ET are often made on a local scale, but spatially distributed estimates are needed to determine ET over catchments. In this paper, we document the ET that was quantified over 3 years using eddy covariance for three riparian ecosystems along the Upper San Pedro River of southeastern Arizona, USA, and we use a water balance equation to determine annual groundwater use. Riparian evapotranspiration and groundwater use for the watershed were then determined by using a calibrated, empirical model that uses 16-day, 250-1000 m remote-sensing products for the years of 2001-2005. The inputs for the model were derived entirely from the NASA MODIS sensor and consisted of the Enhanced Vegetation Index and land surface temperature. The scaling model was validated using subsets of the entire dataset (omitting different sites or years) and its capable performance for well-watered sites (MAD=0.32 mm day-1, R2=0.93) gave us confidence in using it to determine ET over the watershed. Three years of eddy covariance data for the riparian sites reveal that ET and groundwater use increased as woody plant density increased. Groundwater use was less variable at the woodland site, which had the greatest density of phreatophytes. Annual riparian groundwater use within the watershed was nearly constant over the study period despite an on-going drought. For the San Pedro alone, the amounts determined in this paper are within the range of most recently reported values that were derived using an entirely different approach. However, because of our larger estimates for groundwater use for the main tributary of the San Pedro, the watershed totals were higher. The approach presented here can provide riparian ET and groundwater use amounts that reflect real natural variability in phreatophyte withdrawals and improve the accuracy of a watershed's water budget. ?? 2008 Elsevier Ltd. All rights reserved.

Journal of Arid Environments↗

USGS2012

A simple method for estimating basin-scale groundwater discharge by vegetation in the basin and range province of Arizona using remote sensing information and geographic information systems

Groundwater is a vital water resource in the arid to semi-arid southwestern United States. Accurate accounting of inflows to and outflows from the groundwater system is necessary to effectively manage this shared resource, including the important outflow component of groundwater discharge by vegetation. A simple method for estimating basin-scale groundwater discharge by vegetation is presented that uses remote sensing data from satellites, geographic information systems (GIS) land cover and stream location information, and a regression equation developed within the Southern Arizona study area relating the Enhanced Vegetation Index from the MODIS sensors on the Terra satellite to measured evapotranspiration. Results computed for 16-day composited satellite passes over the study area during the 2000 through 2007 time period demonstrate a sinusoidal pattern of annual groundwater discharge by vegetation with median values ranging from around 0.3 mm per day in the cooler winter months to around 1.5 mm per day during summer. Maximum estimated annual volume of groundwater discharge by vegetation was between 1.4 and 1.9 billion m 3 per year with an annual average of 1.6 billion m 3 . A simplified accounting of the contribution of precipitation to vegetation greenness was developed whereby monthly precipitation data were subtracted from computed vegetation discharge values, resulting in estimates of minimum groundwater discharge by vegetation. Basin-scale estimates of minimum and maximum groundwater discharge by vegetation produced by this simple method are useful bounding values for groundwater budgets and groundwater flow models, and the method may be applicable to other areas with similar vegetation types.

Arizona↗

USGS2015

Wide-area ratios of evapotranspiration to precipitation in monsoon-dependent semiarid vegetation communities

Evapotranspiration (ET) and the ratio of ET to precipitation (PPT) are important factors in the water budget of semiarid rangelands and are in part determined by the dominant plant communities. Our goal was to see if landscape changes such as tree or shrub encroachment and replacement of native grasses by invasive grasses impacted ET and ET/PPT and therefore watershed hydrology in this biome. We determined ET and ET/PPT for shrublands, grasslands and mesquite savannas in southern Arizona at five moisture flux towers and determined the environmental factors controlling ET in each plant community. We then scaled ET over areas of 4–36 km 2 , representing homogeneous patches of each plant community, using the Enhanced Vegetation Index (EVI) from MODIS sensors on the Terra satellite. Over wide areas, estimated ET/PPT projected from MODIS EVI ranged from 0.71 for a sparsely-vegetated shrub site to 1.00 for grasslands and mesquite savannas. The results did not support hypotheses that encroachment of mesquites into grasslands or that replacement of native grasses with introduced Eragrostis lehmanniana (lehmann lovegrass) have increased rangeland ET.

Arizona↗

USGS2014

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Through the use of statistically derived correction factors or choosing field methods that better correlate with the imagery, vegetation heights from HR DSMs could be a valuable technique for broad-scale rangeland monitoring needs.

California;Nevada↗

USGS2017

Benefits of the fire mitigation ecosystem service in the Great Dismal Swamp National Wildlife Refuge, Virginia, USA

The Great Dismal Swamp (GDS) National Wildlife Refuge delivers multiple ecosystem services, including air quality and human health via fire mitigation. Our analysis estimates benefits of this service through its potential to reduce catastrophic wildfire related impacts on the health of nearby human populations. We used a combination of high-frequency satellite data, ground sensors, and air quality indices to determine periods of public exposure to dense emissions from a wildfire within the GDS. We examined emergency department (ED) visitation in seven Virginia counties during these periods, applied measures of cumulative Relative Risk to derive the effects of wildfire smoke exposure on ED visitation rates, and estimated economic losses using regional Cost of Illness values established within the US Environmental Protection Agency BenMAP framework. Our results estimated the value of one avoided catastrophic wildfire in the refuge to be \$3.69 million (2015 USD), or \$306 per hectare of burn. Reducing the frequency or severity of extensive, deep burning peatland wildfire events has additional benefits not included in this estimate, including avoided costs related to fire suppression during a burn, carbon dioxide emissions, impacts to wildlife, and negative outcomes associated with recreation and regional tourism. We suggest the societal value of the public health benefits alone provides a significant incentive for refuge mangers to implement strategies that will reduce the severity of catastrophic wildfires.

North Carolina, Virginia↗

USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗

USGS2013

Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support

The invasive variety of Phragmites australis (common reed) forms dense stands that can cause negative impacts on coastal Great Lakes wetlands including habitat degradation and reduced biological diversity. Early treatment is key to controlling Phragmites, therefore a map of the current distribution is needed. ALOS PALSAR imagery was used to produce the ﬁrst basin-wide distribution map showing the extent of large, dense invasive Phragmites-dominated habitats in wetlands and other coastal ecosystems along the U.S. shore of the Great Lakes. PALSAR is a satellite imaging radar sensor that is sensitive to differences in plant biomass and inundation patterns, allowing for the detection and delineation of these tall (up to 5 m), high density, high biomass invasive Phragmites stands. Classiﬁcation was based on multi-season ALOS PALSAR L-band (23 cm wavelength) HH and HV polarization data. Seasonal (spring, summer, and fall) datasets were used to improve discrimination of Phragmites by taking advantage of phenological changes in vegetation and inundation patterns over the seasons. Extensive ﬁeld collections of training and randomly selected validation data were conducted in 2010–2011 to aid in mapping and for accuracy assessments. Overall basin-wide map accuracy was 87%, with 86% producer's accuracy and 43% user's accuracy for invasive Phragmites. The invasive Phragmites maps are being used to identify major environmental drivers of this invader's distribution, to assess areas vulnerable to new invasion, and to provide information to regional stakeholders through a decision support tool.

Lake Erie;Lake Huron;Lake Michigan;Lake Ontario;La↗

USGS2023

Lake Erie hypoxia spatial and temporal dynamics present challenges for assessing progress toward water quality goals

Seasonal hypolimnetic hypoxia has been documented in Lake Erie’s central basin since the 1950s. Ship-based surveys to monitor hypoxia have been conducted since the 1980s, but they occur at a relatively low frequency and focus on the deeper areas of the central basin. To better document the seasonal development of stratification and the consequent occurrence of hypoxia, we deployed eight moorings, in both nearshore-shallow areas and offshore-deep areas of the central basin, equipped with temperature and oxygen sensors at multiple depths, that recorded temperature and oxygen concentrations every 10 minutes. Results from 2017-2019 reveal that hypoxia occurs as early as July in the shallower areas west of, and around the southern perimeter of the central basin, but does not occur until August or September in the deeper central basin. Hypoxia is intermittent in the shallower perimeter areas; whereas in the deeper areas, hypoxia can persist into October, often progressing to anoxia. The intra and interannual differences in the spatial and temporal extent of hypoxia indicate that an extensive monitoring program will be necessary to more accurately assess progress toward reducing the extent of hypoxia pursuant to the lake ecosystem objectives of the 2012 Great Lakes Water Quality Agreement.

Michigan, New York, Ohio, Pennsylvania↗

USGS2024

On the survival and habitat use of hatchery-reared cisco (Coregonus artedi) in Lake Erie

Cisco ( Coregonus artedi ) have been extirpated from Lake Erie in North America since the 1960s, but they once supported one of the largest Laurentian Great Lakes fisheries. Numerous potential impediments to rehabilitation have been identified, including summer habitat refugia and predation. We used acoustic telemetry to investigate the thermal habitat use and survival of hatchery-reared adult cisco in Lake Erie. Fish were experimentally released (n = 50 per site) offshore at Dunkirk, New York, in the eastern basin and Huron, Ohio, in the central basin. Cisco in both basins found suitable summer oxythermal habitat in the metalimnion, suggesting that coldwater habitat availability is likely not an impediment for reestablishment. However, track end dates or predation dates were distributed across only four months with the last detection at 155 days. Predation sensors combined with temperature values during digestion indicated different potential predators: lake trout ( Salvelinus namaycush ) for the Dunkirk group and walleye ( Sander vitreus ) for the Huron group. Additionally, digestion temperatures of two tags indicated bird predation was also important, likely underestimated and suggested substantial use of the epilimnion by tagged fish. The results highlight the need for additional studies to address stocking optimization questions in support of future reintroduction experiments and related cisco conservation efforts.

Lake Erie↗

USGS2024

Influences of meteorological conditions, runoff, and bathymetry on summer thermal regime of a Great Lakes estuary

To better understand the primary drivers of the thermal regime in a Great Lakes estuary, and their implications for local biota, water temperature variations in the Milwaukee Estuary of Lake Michigan were studied between July and October of 2019 using a network of 25 sensors at 18 locations. Like Lake Michigan, the estuary was thermally stratified July to October, and historically dredged channels with water depths greater than 6 m allowed for the free movement of cold lake water into the estuary. However, temperatures in the estuary fluctuated rapidly both spatially and temporally, reflecting lake temperature fluctuations driven by changing meteorological conditions. Lake-driven upwelling and downwelling events influenced water temperature more than tributary contributions. Periodic upwelling and downwelling events caused temperature changes by up to 15 °C in less than 24 h. Nearshore upwelling events occasionally allowed cold, hypolimnetic lake water to reach tributary portions of the estuary beyond dredged areas, while downwelling events disrupted thermal stratification and caused the deep, dredged portions of the estuary to exceed 20 °C. Thermal impacts from these events were especially noticeable in transition zones between dredged and not dredged channels less than 2 m deep. The warming effects from downwelling persisted longer inside the estuary – up to two weeks – than cooling effects from upwelling, which typically lasted a few days. The predominantly lake-driven, rapid summer water temperature fluctuations observed in the Milwaukee Estuary serve as an important consideration in habitat restoration activities happening in Great Lakes estuaries.

Wisconsin↗

USGS2008

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Journal of Hydrology↗

USGS2014

Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling

Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.

Journal of Hydrology↗

USGS2024

Groundwater-Surface water interactions research: Past trends and future directions

Interactions between groundwater and surface water sustain groundwater-dependent ecosystems and regulate river temperature and biogeochemical cycles, amongst many other processes. These interactions occur in freshwater environments including rivers, springs, lakes, and wetlands, and in coastal environments via tidal pumping, submarine groundwater discharge, and seawater intrusion. Here, we explore groundwater-surface water interactions research using bibliometric analyses of titles, abstracts, and keywords from 20,275 journal papers published between 1970 and 2023 extracted from Scopus. Analyses show that research into groundwater-surface water interactions is highly multi-disciplinary, with growing contributions from the social and biological sciences. The number of groundwater-surface water interactions papers is rapidly increasing with over 1200 papers published per year since 2020. Drawing on our data-driven approach and expert knowledge, we synthesise current research trends and identify critical future research directions. Despite the thousands of papers on groundwater-surface water interactions, important processes are still difficult to quantify or predict at meaningful spatial scales to inform water-resources management. We see benefits in future groundwater-surface water interactions research focusing on: (1) using new technologies including internet-of-things-based sensors, uncrewed vehicles, and remote-sensing approaches for data collection to inform groundwater-surface water interactions at large scales, (2) seeking approaches to upscale site-specific findings to better inform management, and (3) continuing the movement towards multi-disciplinary investigations to better inform the understanding of groundwater-surface water interactions and processes that will enable better management outcomes.

Journal of Hydrology↗

USGS2008

Broadband seismic measurements of degassing activity associated with lava effusion at Popocatépetl Volcano, Mexico

From November 1999 through July 2000, a broadband seismic experiment was carried out at Popocatépetl Volcano to record seismic activity over a wide period range (0.04–100 s). We present an overview of the seismicity recorded during this experiment and discuss results of analyses of long-period (LP) and very-long-period (VLP) seismic signals recorded at stations nearest to the crater over a four-month interval December 1999–March 2000. Three families of LP signals (Types-I, II, and III) are identified based on distinctive waveform features observed periods shorter than 1 s, periods longer than 15 s, and within the period range 0.5–2.5 s. Type-I LP events have impulsive first arrivals and exhibit a characteristic harmonic wave train with dominant periods in the 1.4–1.9 s range during the first 10 s of signal. These events are also associated with a remarkable VLP wavelet with period near 30 s. Type-II LP events represent pairs of events occurring in rapid succession and whose signatures are superimposed. These are typically marked by slowly emergent first arrivals and by a characteristic VLP wave train with dominant period near 30 s, made of two successive wavelets whose shapes are quasi-identical to those of the VLP wavelets associated with Type-I events. Type-III LP events represent the most energetic signals observed during our experiment. These have an emergent first arrival and display a harmonic signature with dominant period near 1.1 s. They are dominated by periods in the 0.25–0.35 s band and contain no significant energy at periods longer than 15 s. Hypocentral locations of the three types of LP events obtained from phase picks point to shallow seismic sources clustered at depths shallower than 2 km below the crater floor. Observed variations in volcanic eruptive activity correlate with defined LP families. Most of the observed seismicity consists of Type-I events that occur in association with 1–3-min-long degassing bursts (“exhalations”). Eruptive activity increased in intensity in February, coinciding with an increasing occurrence of Type-II LP events. Type-III events were first observed at the end of February and during March, in coincidence with the formation of a new lava dome. Vulcanian eruptions occurred in April and May. These events typically exhibit broadband signatures extending over the full period range of the sensors and lasting 30–80 min.

Popocatepetl Volcano↗