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At least 811 records · Page 45Linked to original sources

A passive microwave snow depth algorithm with a proxy for snow metamorphism

Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002 John Wiley & Sons, Ltd.

Hydrological Processes↗

Wide-area estimates of evapotranspiration by red gum ( Eucalyptus camaldulensis ) and associated vegetation in the Murray-Darling River Basin, Australia

Floodplain red gum forests ( Eucalyptus camaldulensis plus associated grasses, reeds and sedges) are sites of high biodiversity in otherwise arid regions of southeastern Australia. They depend on periodic floods from rivers, but dams and diversions have reduced flood frequencies and volumes, leading to deterioration of trees and associated biota. There is a need to determine their water requirements so environmental flows can be administered to maintain or restore the forests. Their water requirements include the frequency and extent of overbank flooding, which recharges the floodplain soils with water, as well as the actual amount of water consumed in evapotranspiration (ET). We estimated the flooding requirements and ET for a 38&thinsp;134&thinsp;ha area of red gum forest fed by the Murrumbidgee River in Yanga National Park, New South Wales. ET was estimated by three methods: sap flux sensors placed in individual trees; a remote sensing method based on the Enhanced Vegetation Index from MODIS satellite imagery and a water balance method based on differences between river flows into and out of the forest. The methods gave comparable estimates yet covered different spatial and temporal scales. We estimated flood frequency and volume requirements by comparing Normalized Difference Vegetation Index values from Landsat images with flood history from 1995 to 2014, which included both wet periods and dry periods. ET during wet years is about 50% of potential ET but is much less in dry years because of the trees' ability to control stomatal conductance. Based on our analyses plus other studies, red gum trees at this location require environmental flows of 2000&thinsp;GL&thinsp;yr &minus;1 every other year, with peak flows of 20&thinsp;000&thinsp;ML&thinsp;d &minus;1 , to produce flooding sufficient to keep them in good condition. However, only about 120&ndash;200&thinsp;GL&thinsp;yr &minus;1 of river water is consumed in ET, with the remainder flowing out of the forest where it enters the Murray River system.

Murray-Darling River Basin↗

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↗

Evaluating a process-guided deep learning approach for predicting dissolved oxygen in streams

Dissolved oxygen (DO) is a critical water quality constituent that governs habitat suitability for aquatic biota, biogeochemical reactions and solubility of metals in streams. Recently introduced high-frequency sensors have increased our ability to measure DO, but we still lack the capacity to understand and predict DO concentrations at high spatial resolutions or in unmonitored locations. Machine learning (ML) has been a commonly used approach for modelling DO, however, conventional ML models have no representation of the limnological processes governing DO dynamics. Here we implement and evaluate two process-guided deep learning (PGDL) approaches for predicting daily minimum, mean and maximum DO concentrations in rivers from the Delaware River Basin, USA. In both cases, a multi-task approach was taken in which the PGDL models predicted stream metabolism and gas exchange rates in addition to the DO concentrations themselves. Our results showed that for these sites, the PGDL approaches did not improve upon baseline predictions in temporal and spatially similar holdout experiments. One of the approaches did, however, improve predictions when applied to spatially dissimilar sites. Although this particular PGDL approach did not improve predictive accuracy in most cases, our results suggest that process guidance, perhaps a more constrained approach, could benefit a data-driven DO model.

Hydrological Processes↗

Understanding the role of fog in forest hydrology: Stable isotopes as tools for determining input and partitioning of cloud water in montane forests

Understanding the hydrology of tropical montane cloud forests (TMCF) has become essential as deforestation of mountain areas proceeds at an increased rate worldwide. Passive and active cloud‐water collectors, throughfall and stemflow collectors, visibility or droplet size measurements, and micrometeorological sensors are typically used to measure the fog water inputs to ecosystems. In addition, stable isotopes may be used as a natural tracer for fog and rain. Previous studies have shown that the isotopic signature of fog tends to be more enriched in the heavier isotopes 2 H and 18 O than that of rain, due to differences in condensation temperature and history. Differences between fog and rain isotopes are largest when rain is from synoptic‐scale storms, and fog or orographic cloud water is generated locally. Smaller isotopic differences have been observed between rain and fog on mountains with orographic clouds, but only a few studies have been conducted. Quantifying fog deposition using isotope methods is more difficult in forests receiving mixed precipitation, because of limitations in the ability of sampling equipment to separate fog from rain, and because fog and rain may, under some conditions, have similar isotopic composition. This article describes the various types of fog most relevant to montane cloud forests and the importance of fog water deposition in the hydrologic budget. A brief overview of isotope hydrology provides the background needed to understand isotope applications in cloud forests. A summary of previous work explains isotopic differences between rain and fog in different environments, and how monitoring the isotopic signature of surface water, soil water and tree xylem water can yield estimates of the contribution of fog water to streamflow, groundwater recharge and transpiration. Next, instrumentation to measure fog and rain, and methods to determine isotopic concentrations in plant and soil water are discussed. The article concludes with the identification of some of the more pressing research questions in this field and offers various suggestions for future research.

Hydrological Processes↗

Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil evaporation. Copyright ?? 2011 John Wiley & Sons, Ltd.

Hydrological Processes↗

Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling

In-stream sensors are increasingly deployed as part of ambient water quality-monitoring networks. Temporally dense data from these networks can be used to better understand the transport of constituents through streams, lakes or reservoirs. Data from existing, continuously recording in-stream flow and water quality monitoring stations were coupled with the two-dimensional hydrodynamic CE-QUAL-W2 model to assess the potential of altered reservoir outflow management to reduce sediment trapping in John Redmond Reservoir, located in east-central Kansas. Monitoring stations upstream and downstream from the reservoir were used to estimate 5.6 million metric tons of sediment transported to John Redmond Reservoir from 2007 through 2010, 88% of which was trapped within the reservoir. The two-dimensional model was used to estimate the residence time of 55 equal-volume releases from the reservoir; sediment trapping for these releases varied from 48% to 97%. Smaller trapping efficiencies were observed when the reservoir was maintained near the normal operating capacity (relative to higher flood pool levels) and when average residence times were relatively short. An idealized, alternative outflow management scenario was constructed, which minimized reservoir elevations and the length of time water was in the reservoir, while continuing to meet downstream flood control end points identified in the reservoir water control manual. The alternative scenario is projected to reduce sediment trapping in the reservoir by approximately 3%, preventing approximately 45 000 metric tons of sediment from being deposited within the reservoir annually. This article presents an approach to quantify the potential of reservoir management using existing in-stream data; actual management decisions need to consider the effects on other reservoir benefits, such as downstream flood control and aquatic life.

Hydrological Processes↗

Foreshocks during the nucleation of stick-slip instability

We report on laboratory experiments which investigate interactions between aseismic slip, stress changes, and seismicity on a critically stressed fault during the nucleation of stick-slip instability. We monitor quasi-static and dynamic changes in local shear stress and fault slip with arrays of gages deployed along a simulated strike-slip fault (2 m long and 0.4 m deep) in a saw cut sample of Sierra White granite. With 14 piezoelectric sensors, we simultaneously monitor seismic signals produced during the nucleation phase and subsequent dynamic rupture. We observe localized aseismic fault slip in an approximately meter-sized zone in the center of the fault, while the ends of the fault remain locked. Clusters of high-frequency foreshocks (M w ~ −6.5 to −5.0) can occur in this slowly slipping zone 5–50 ms prior to the initiation of dynamic rupture; their occurrence appears to be dependent on the rate at which local shear stress is applied to the fault. The meter-sized nucleation zone is generally consistent with theoretical estimates, but source radii of the foreshocks (2 to 70 mm) are 1 to 2 orders of magnitude smaller than the theoretical minimum length scale over which earthquake nucleation can occur. We propose that frictional stability and the transition between seismic and aseismic slip are modulated by local stressing rate and that fault sections, which would typically slip aseismically, may radiate seismic waves if they are rapidly stressed. Fault behavior of this type may provide physical insight into the mechanics of foreshocks, tremor, repeating earthquake sequences, and a minimum earthquake source dimension.

Journal of Geophysical Research B: Solid Earth↗

Field measurement of basal forces generated by erosive debris flows

It has been proposed that debris flows cut bedrock valleys in steeplands worldwide, but field measurements needed to constrain mechanistic models of this process remain sparse due to the difficulty of instrumenting natural flows. Here we present and analyze measurements made using an automated sensor network, erosion bolts, and a 15.24 cm by 15.24 cm force plate installed in the bedrock channel floor of a steep catchment. These measurements allow us to quantify the distribution of basal forces from natural debris‒flow events that incised bedrock. Over the 4 year monitoring period, 11 debris‒flow events scoured the bedrock channel floor. No clear water flows were observed. Measurements of erosion bolts at the beginning and end of the study indicated that the bedrock channel floor was lowered by 36 to 64 mm. The basal force during these erosive debris‒flow events had a large‒magnitude (up to 21 kN, which was approximately 50 times larger than the concurrent time‒averaged mean force), high‒frequency (greater than 1 Hz) fluctuating component. We interpret these fluctuations as flow particles impacting the bed. The resulting variability in force magnitude increased linearly with the time‒averaged mean basal force. Probability density functions of basal normal forces were consistent with a generalized Pareto distribution, rather than the exponential distribution that is commonly found in experimental and simulated monodispersed granular flows and which has a lower probability of large forces. When the bed sediment thickness covering the force plate was greater than ~ 20 times the median bed sediment grain size, no significant fluctuations about the time‒averaged mean force were measured, indicating that a thin layer of sediment (~ 5 cm in the monitored cases) can effectively shield the subjacent bed from erosive impacts. Coarse‒grained granular surges and water‒rich, intersurge flow had very similar basal force distributions despite differences in appearance and bulk‒flow density. These results demonstrate that debris flows can have strong control on rates of steepland evolution and contribute to a foundation needed for modeling debris‒flow incision stochastically.

Journal of Geophysical Research F: Earth Surface↗

Assessing satellite-derived start-of-season measures in the conterminous USA

National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now available to study many aspects of vegetation activity in this region. One feature, the onset of deciduous plant growth at the start of the spring season (SOS) is of special interest, as it appears to be crucial for accurate computation of several important biospheric processes, and a sensitive measure of the impacts of global change. In this study, satellite-derived SOS dates produced by the delayed moving average (DMA) and seasonal midpoint NDVI (SMN) methods, and modelled surface phenology (spring indices, SI) were compared at widespread deciduous forest and mixed woodland sites during 1990&ndash;93 and 1995&ndash;99, and these three measures were also matched to native species bud-break data collected at the Harvard Forest (Massachusetts) over the same time period. The results show that both SOS methods are doing a modestly accurate job of tracking the general pattern of surface phenology, but highlight the temporal limitations of biweekly satellite data. Specifically, at deciduous forest sites: (1) SMN SOS dates are close in time to SI first bloom dates (average bias of +0.74 days), whereas DMA SOS dates are considerably earlier (average bias of &minus;41.24 days) and also systematically earlier in late spring than in early spring; (2) SMN SOS tracks overall yearly trends in deciduous forests somewhat better than DMA SOS, but with larger average error (MAEs 8.64 days and 7.37 days respectively); and (3) error in both SOS techniques varies considerably by year. Copyright &copy; 2002 Royal Meteorological Society.

International Journal of Climatology↗

Sea-cave temperature measurements and amino acid geochronology of British Late Pleistocene Sea stands

‘Calibrating’ amino acid ratios with uranium-series dates requires an accurate knowledge of current mean annual temperatures (CMATs) over the region studied. To measure these, test-tube sized ‘diffusion sensors’ were emplaced for 1 year (in 1984, 1985 and 1986), both outside and inside Minchin Hole sea-cave in South Wales and Belle Hougue sea-cave in Jersey, both of which have yielded Oxygen Isotope Substage 5e uranium-series ages on speleothems. Our outside temperatures agreed with meteorological ones. Our inside temperatures were over 1°C lower. To allow for this, a mean of ‘empirical’, ‘linear’ and ‘parabolic’ epimerisation calculations suggests that ratios from molluscs inside the caves should be multiplied by over 1.1 for comparison with outside ratios. This raises Bowen et al .'s ‘Pennard’ stage ratios from inside Minchin (and Bacon) Hole up towards the ‘Unnamed’ stage ratios outside, and suggests that the Unnamed sites are also from Oxygen Isotope Substage 5e, as proposed by Proctor and Smart. The same conclusion is reached more strongly by comparisons with the ratios and temperatures inside Belle Hougue to the south, and at Eemian (assumed 5e) sites in The Netherlands, Germany and Denmark to the east. The Pennard ratios from outside sites may provide further evidence for global sea stands close to the present level later in Oxygen Isotope Stage 5.

Journal of Quaternary Science↗

Seasonal survival of adult female mottled ducks

The mottled duck ( Anas fulgivula ) is a non-migratory duck dependent on coastal habitats to meet all of its life cycle requirements in the Western Gulf Coast (WGC) of Texas and Louisiana, USA. This population of mottled ducks has experienced a moderate decline during the past 2 decades. Adult survival has been identified as an important factor influencing population demography. Previous work based on band-recovery data has provided only annual estimates of survival. We assessed seasonal patterns of female mottled duck survival from 2009 to 2012 using individuals marked with satellite platform transmitter terminals (PTTs). We used temperature and movement sensors within each PTT to indicate potential mortality events. We estimated cumulative weekly survival and ranked factors influential in patterns of mortality using known-fate modeling in Program MARK. Models included 4 predictors: week; hunting and non-hunting periods; biological periods defined as breeding, brooding, molt, and pairing; and mass at time of capture. Models containing hunt periods, during and outside the mottled duck season, comprised essentially 100% of model weights where both legal and illegal harvest had a negative influence on mottled duck survival. Survival rates were low during 2009–2011 (12–38% annual rate of survival), when compared with the long-term banding average of 53% annual survival. During 2011, survival of female mottled ducks was the lowest annual rate (12%) ever documented and coincided with extreme drought. Management actions maximizing the availability of wetlands and associated upland habitats during hunting seasons and drought conditions may increase adult female mottled duck survival.

Texas↗

Mammalian mesocarnivore visitation at tortoise burrows in a wind farm

There is little information on predator–prey interactions in wind energy landscapes in North America, especially among terrestrial vertebrates. Here, we evaluated how proximity to roads and wind turbines affect mesocarnivore visitation with desert tortoises ( Gopherus agassizii ) and their burrows in a wind energy landscape. In 2013, we placed motion-sensor cameras facing the entrances of 46 active desert tortoise burrows in a 5.2-km 2 wind energy facility near Palm Springs, California, USA. Cameras recorded images of 35 species of reptiles, mammals, and birds. Counts for 4 species of mesocarnivores at desert tortoise burrows increased closer to dirt roads, and decreased closer to wind turbines. Our results suggest that anthropogenic infrastructure associated with wind energy facilities could influence the general behavior of mammalian predators and their prey. Further investigation of proximate mechanisms that underlie road and wind turbine effects (i.e., ground vibrations, sound emission, and traffic volume) and on wind energy facility spatial designs (i.e., road and wind turbine configuration) could prove useful for better understanding wildlife responses to wind energy development. © 2017 The Wildlife Society.

California↗

The metabolic regimes of flowing waters

The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of photosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classifying and modeling the current and future metabolic regimes of flowing waters.

Limnology and Oceanography↗

Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes

Although seasonal patterns of ecosystem productivity have been extensively described and analyzed with respect to their primary forcings in terrestrial and marine systems, comparatively little is known about these same processes in rivers. However, it is now possible to perform a large‐scale synthesis on the patterns and drivers of river productivity regimes because of the recent sensor advances allowing for near‐continuous estimates of river productivity. Here, we explore a dataset of 47 U.S. rivers to examine whether there are characteristic river productivity regimes. We use classification approaches to develop a typology of productivity regimes and then use these regimes to examine differences with respect to potential controls of productivity. We identified two distinct metabolic regimes, which we named Summer Peak and Spring Peak Rivers, within our dataset. These regimes meaningfully differed in both the timing and magnitude of productivity and were robust to different approaches to classification. We also found that several variables, including watershed area and characteristics of water temperature or discharge, were able to predict the class membership of these regimes with modest accuracy. Our results support the presence of characteristic metabolic regimes and suggests that these regimes may have common sets of environmental controls. We present classification as one approach to begin exploring the productivity regimes of rivers. The strength of our approach is that it fully leverages these newly available high‐frequency productivity estimates to create classes that can be used to draw inferences about how the controls of river productivity differ between or within systems.

Limnology and Oceanography↗

A novel boat-based field application of a high-frequency conductometric ammonium analyzer to characterize spatial variation in aquatic ecosystems

Documenting dissolved inorganic nitrogen (DIN) concentration and form at appropriate temporal and spatial scales is key to understanding aquatic ecosystem health, particularly as DIN fuels primary productivity. In addition to point and non-point source nutrient inputs, factors such as hydrology, geomorphology, temperature, light, and biogeochemical transformations influence nutrient dynamics in surface waters, allowing for the formation of steep spatial gradients and patchiness. Documenting nutrient variability is also necessary to identify sources, quantify transformation rates, and understand drivers. Due to logistical and cost constraints, it is often unfeasible to measure concentrations of nutrients in surface waters using discrete sampling followed by laboratory analysis at a resolution high enough to identify steep spatial gradients and patchiness. Because of these constraints, data generated from discrete sampling are limited in space and time, often missing key variabilities. Recent advancements of in situ nitrate plus nitrite (NO3- and NO2-) sensor technology has enabled highly temporally and spatially resolved NO3- concentration measurements in aquatic ecosystems. However, comparable information about ammonium (NH4+) concentrations remains unavailable. To address this need, U.S. Geological Survey collaborated with Timberline Instruments to modify their commercially available benchtop TL-2800 ammonia analyzer to collect high-frequency continuous (1 unique sample measurement per second) NH4+ concentration measurements at a micromolar (0.5 µM) resolution in flow-through mode while receiving water pumped from a moving boat. Although the utility of this method is described for spatial surveys, we anticipate that it would be adaptable to installation at a fixed station for continuous monitoring of NH4+ concentration.

California↗

Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska

Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6 m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes.

Alaska↗

Linking suspended sediment conditions to hyporheic dissolved oxygen and fine sediment deposition in salmonid spawning habitat below an irrigation dam, Park County, Wyoming

Dams are essential for water resources management but impose notable effects on fluvial sediment transport and downstream river morphology by reducing or altering the timing of sediment loads. We explored the relationship between dam sediment management and downstream sediment dynamics in the context of riverine fisheries management. We quantified the effects of dam sediment management operations on downstream salmonid spawning habitat during two fall water-level drawdown periods: an experimental drawdown leading to sediment release or a typical slower drawdown intended to minimize release of sediment. The experimental drawdown increased deposited fine sediment and decreased hyporheic dissolved oxygen levels. However, the typical drawdown did not increase fine sediment deposition or decrease hyporheic dissolved oxygen. We quantify the immediate impacts of dam operations using a number of water column and substrate metrics, and demonstrate the potential for sediment flushing operations to have short-term seasonally persistent effects on salmonid spawning habitat. Common surrogates of suspended sediment concentration (i.e. turbidity) were poor indicators of salmonid spawning habitat, especially when sand was the dominant grain size. Instead, measures of suspended sediment concentration such as acoustic backscatter sensors and depth-integrated samples, combined with discharge, appear to be better suited for monitoring and inferring the impacts of dam operations involving sediment releases on salmonid spawning habitat. We demonstrate the importance of understanding sediment particle sizes, monitoring relevant water column conditions in real-time, and provide options for effectively monitoring the downstream impact of dam operations. This work can help managers balance dam sediment management operations with ecological priorities.

Wyoming↗