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At least 955 records · Page 53Linked to original sources

USGS2016

Mapping site index and volume increment from forest inventory, Landsat, and ecological variables in Tahoe National Forest, California, USA

High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by ( i ) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, ( ii ) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and ( iii ) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R 2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R 2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m 3 ·ha −1 ·year −1 . Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.

Canadian Journal of Forest Research↗

USGS2024

Variability in weather and site properties affect fuel and fire behavior following fuel treatments in semiarid sagebrush-steppe.

Fuel-treatments targeting shrubs and fire-prone exotic annual grasses (EAGs) are increasingly used to mitigate increased wildfire risks in arid and semiarid environments, and understanding their response to natural factors is needed for effective landscape management. Using field-data collected over four years from fuel-break treatments in semiarid sagebrush-steppe, we asked 1) how the outcomes of EAG and sagebrush fuel treatments varied with site biophysical properties, climate, and weather, and 2) how predictions of fire behavior using the Fuel Characteristic Classification System fire model related to land-management objectives of maintaining fire behavior expected of low-load, dry-climate grasslands. Generalized linear mixed effect modeling with build-up model selection was used to determine best-fit models, and marginal effects plots to assess responses for each fuel type. EAG cover decreased as antecedent-fall precipitation increased and increased as antecedent-spring temperatures and surface soil clay contents increased. Herbicides targeting EAGs were less effective where pre-treatment EAG cover was >40 % and antecedent spring temperatures were >9.5 °C. Sagebrush cover was inversely related to soil clay content, especially where clay contents were >17 %. Predicted fire behavior exceeded management objectives under 1) average fire weather conditions when EAG or sagebrush cover was >50 % or >26 %, respectively, or 2) extreme fire weather conditions when EAG or sagebrush cover was >10 % or >8 %, respectively. Consideration of the strong effects of natural variability in site properties and antecedent weather can help in justifying, planning and implementing fuel-treatments.

Idaho, Oregon↗

USGS2024

Climate and weather drivers in southern California Santa Ana Wind and non-Santa Wind fires

Background. Autumn and winter Santa Ana Winds (SAW) are responsible for the largest and most destructive wildfires in southern California. Aims. 1) To contrast fires ignited on SAW days vs non-SAW days, 2) evaluate the predictive ability of the Canadian Fire Weather Index (CFWI) for these two fire types, and 3) determine climate and weather factors responsible for the largest wildfires. Methods. Cal Fire FRAP fire data were coupled with hourly climate data from 4 stations, and with regional indices of SAW wind speed, and with seasonal drought from the Palmer Drought Severity Index. Key results. Fires on non-SAW days were more numerous and burned more area, and were significant May to October. CFWI indices were tied to fire occurrence and size for both non-SAW and SAW days, and in the days following ignition. Multiple regression models for months with greatest area burned explained up to a quarter of variation in area burned. Conclusions. The drivers of fire size differ between non-SAW and SAW fires. The best predictor of fire size for non-SAW fires was drought during the prior five years, followed by current-year vapor pressure deficit. For SAW fires, wind speed followed by drought were most important.

California↗

USGS2024

Simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

Journal of Hydrology↗

USGS2012

Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska

Thermokarst lakes and peat-accumulating drained lake basins cover a substantial portion of Arctic lowland landscapes, yet the role of thermokarst lake drainage and ensuing peat formation in landscape-scale carbon (C) budgets remains understudied. Here we use measurements of terrestrial peat thickness, bulk density, organic matter content, and basal radiocarbon age from permafrost cores, soil pits, and exposures in vegetated, drained lake basins to characterize regional lake drainage chronology, C accumulation rates, and the role of thermokarst-lake cycling in carbon dynamics throughout the Holocene on the northern Seward Peninsula, Alaska. Most detectable lake drainage events occurred within the last 4,000 years with the highest drainage frequency during the medieval climate anomaly. Peat accumulation rates were highest in young (50–500 years) drained lake basins (35.2 g C m −2 yr −1 ) and decreased exponentially with time since drainage to 9 g C m −2 yr −1 in the oldest basins. Spatial analyses of terrestrial peat depth, basal peat radiocarbon ages, basin geomorphology, and satellite-derived land surface properties (Normalized Difference Vegetation Index (NDVI); Minimum Noise Fraction (MNF)) from Landsat satellite data revealed significant relationships between peat thickness and mean basin NDVI or MNF. By upscaling observed relationships, we infer that drained thermokarst lake basins, covering 391 km 2 (76%) of the 515 km 2 study region, store 6.4–6.6 Tg organic C in drained lake basin terrestrial peat. Peat accumulation in drained lake basins likely serves to offset greenhouse gas release from thermokarst-impacted landscapes and should be incorporated in landscape-scale C budgets.

Alaska↗

USGS2015

New insight into California’s drought through open data

Historically unprecedented drought in California has brought water issues to the forefront of the nation’s attention. Crucial investigations that concern water policy, management, and research, in turn, require extensive information about the quality and quantity of California’s water. Unfortunately, key sources of pertinent data are unevenly distributed and frequently hard to find. Thankfully, the vital importance of integrating water data across federal, state, and tribal, academic, and private entities, has recently been recognized and addressed through federal initiatives such as the Climate Data Initiative of President Obama’s Climate Action Plan and the Advisory Committee on Water Information’s Open Water Data Initiative . Here, we demonstrate an application of integrated open water data, visualized and made available online using open source software, for the purpose of exploring the impact of the current California drought. Our collaborative approach and technical tools enabled a rapid, distributed development process. Many positive outcomes have resulted: the application received recognition within and outside of the Federal Government, inspired others to visualize open water data, spurred new collaborations for our group, and strengthened the collaborative relationships within the team of developers. In this article, we describe the technical tools and collaborative process that enabled the success of the application.

BayGEO Journal↗

USGS2007

Ecological observations on the colonial ascidian Didemnum sp. in a New England tide pool habitat

The colonial ascidian Didemnum sp. has colonized northwestern Atlantic coastal habitats from southern Long Island, New York, to Eastport, Maine. It is also present in offshore habitats of the Georges Bank fishing grounds. It threatens to alter fisheries habitats and shellfish aquacultures. Observations in a tide pool at Sandwich, MA from December 2003 to February 2006 show that Didemnum sp. tolerates water temperatures ranging from ≤ 1 to > 24 °C, with daily changes of up to 11 °C. It attaches to pebbles, cobbles, and boulders, and it overgrows other tunicates, seaweeds, sponges, and bivalves. From May to mid July, colonies appear as small patches on the bottoms of rocks. Colonies grow rapidly from July to September, with some growth into December, and they range in color from pink to pale yellow to pale orange. Colony health declines from October through April, presumably in response to changes in water temperatures, and this degenerative process is manifested by color changes, by the appearance of small dark brown spots that represent clumps of fecal pellets in the colony, by scavenging by periwinkles, and by a peeling-away of colonies from the sides of cobbles and boulders. At Sandwich, colonies died that were exposed to air at low tide. The species does not exhibit this seasonal cycle of growth and decline in subtidal habitats (40–65 m) on the Georges Bank fishing grounds where the daily climate is relatively stable and annual water temperatures range from 4 to 15 °C. Experiments in the tide pool with small colony fragments (5 to 9 cm 2 ) show they re-attach and grow rapidly by asexual budding, increasing in size 6- to 11-fold in the first 15 days. Didemnum sp. at Sandwich has no known predators except for common periwinkles ( Littorina littorea ) that graze on degenerating colonies in the October to April time period and whenever colonies are stressed by desiccation. The tendencies of the ascidian (1) to attach to firm substrates, (2) to rapidly overgrow other species, (3) to tolerate a wide temperature range, (4) to be free from predation, and (5) to spread by colony fragmentation combine to make it a potential threat to benthic marine habitats and aquacultures. Didemnum sp. is known to overgrow mussels, oysters, and sea scallops, and it likely envelops other bivalves too.

Massachusetts↗

USGS2003

Actual evapotranspiration and deficit: Biologically meaningful correlates of vegetation distribution across spatial scales

Correlative approaches to understanding the climatic controls of vegetation distribution have exhibited at least two important weaknesses: they have been conceptually divorced across spatial scales, and their climatic parameters have not necessarily represented aspects of climate of broad physiological importance to plants. Using examples from the literature and from the Sierra Nevada of California, I argue that two water balance parameters—actual evapotranspiration (AET) and deficit (D)—are biologically meaningful, are well correlated with the distribution of vegetation types, and exhibit these qualities over several orders of magnitude of spatial scale (continental to local). I reach four additional conclusions. (1) Some pairs of climatic parameters presently in use are functionally similar to AET and D; however, AET and D may be easier to interpret biologically. (2) Several well-known climatic parameters are biologically less meaningful or less important than AET and D, and consequently are poorer correlates of the distribution of vegetation types. Of particular interest, AET is a much better correlate of the distributions of coniferous and deciduous forests than minimum temperature. (3) The effects of evaporative demand and water availability on a site's water balance are intrinsically different. For example, the ‘dry’ experienced by plants on sunward slopes (high evaporative demand) is not comparable to the ‘dry’ experienced by plants on soils with low water-holding capacities (low water availability), and these differences are reflected in vegetation patterns. (4) Many traditional topographic moisture scalars—those that additively combine measures related to evaporative demand and water availability—are not necessarily meaningful for describing site conditions as sensed by plants; the same holds for measured soil moisture. However, using AET and D in place of moisture scalars and measured soil moisture can solve these problems.

Journal of Biogeography↗

USGS2013

Emerging methods for the study of coastal ecosystem landscape structure and change

Coastal landscapes are heterogeneous, dynamic, and evolve over a range of time scales due to intertwined climatic, geologic, hydrologic, biologic, and meteorological processes, and are also heavily impacted by human development, commercial activities, and resource extraction. A diversity of complex coastal systems around the globe, spanning glaciated shorelines to tropical atolls, wetlands, and barrier islands are responding to multiple human and natural drivers. Interdisciplinary research based on remote-sensing observations linked to process studies and models is required to understand coastal ecosystem landscape structure and change. Moreover, new techniques for coastal mapping and monitoring are increasingly serving the needs of policy-makers and resource managers across local, regional, and national scales. Emerging remote-sensing methods associated with a diversity of instruments and platforms are a key enabling element of integrated coastal ecosystem studies. These investigations require both targeted and synoptic mapping, and involve the monitoring of formative processes such as hydrodynamics, sediment transport, erosion, accretion, flooding, habitat modification, land-cover change, and biogeochemical fluxes.

International Journal of Remote Sensing↗

USGS2007

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Journal of Applied Ecology↗

USGS2008

Trends in abundance of collared lemmings near Cape Churchill, Manitoba, Canada

Regular, multiannual cycles observed in the population abundance of small mammals in many arctic and subarctic ecosystems have stimulated substantial research, particularly among population ecologists. Hypotheses of mechanisms generating regular cycles include predator-prey interactions, limitation of food resources, and migration or dispersal, as well as abiotic factors such as cyclic climatic variation and environmental stochasticity. In 2004 and 2005, we used indirect methods to estimate trends in population size of Richardson's collared lemmings (Dicrostonyx richardsoni) retrospectively, and evaluated the extent of synchrony between lemming populations at 2 coastal tundra study areas separated by approximately 60 km near Cape Churchill, Manitoba, Canada. We collected scars on willow plants (Salix) resulting from lemming feeding. Ages of scars ranged from 0 to 13 years at both study areas. Scar-age frequency appeared cyclic and we used nonlinear Poisson regression to model the observed scar-age frequency. Lemming populations cycled with 2.8-year periodicity and the phase of the cycle was synchronous between the 2 study areas. We suggest that our approach could be applied in multiple settings and may provide the most efficient way to gather data on small mammals across both space and time in a diversity of landscapes. ?? 2008 American Society of Mammalogists.

Journal of Mammalogy↗

USGS2016

Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana

Study region Eastern and central Montana. Study focus Fish in Northern Great Plains streams tolerate extreme conditions including heat, cold, floods, and drought; however changes in streamflow associated with long-term climate change may render some prairie streams uninhabitable for current fish species. To better understand future hydrology of these prairie streams, the Precipitation-Runoff Modeling System model and output from the RegCM3 Regional Climate model were used to simulate streamflow for seven watersheds in eastern and central Montana, for a baseline period (water years 1982–1999) and three future periods: water years 2021–2038 (2030 period), 2046–2063 (2055 period), and 2071–2088 (2080 period). New hydrological insights for the region Projected changes in mean annual and mean monthly streamflow vary by the RegCM3 model selected, by watershed, and by future period. Mean annual streamflows for all future periods are projected to increase (11–21%) for two of the four central Montana watersheds: Middle Musselshell River and Cottonwood Creek. Mean annual streamflows for all future periods are projected to decrease (changes of −24 to −75%) for Redwater River watershed in eastern Montana. Mean annual streamflows are projected to increase slightly (2–15%) for the 2030 period and decrease (changes of −16 to −44%) for the 2080 period for the four remaining watersheds.

Montana↗

USGS2007

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m 2 . A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km 2 . The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

Minnesota↗

USGS2023

Wildfire-induced shifts in groundwater discharge to streams identified with paired air and stream water temperature analyses

Within the western United States, increasingly severe and frequent wildfires may alter the magnitude, timing, and quality of water exported from burned areas by streams. Post-fire hydrologic studies often focus on peak stream flow responses to shifts in runoff generation or on annual streamflow yield response to changes in evapotranspiration following fire. However, the magnitude and duration of wildfire effects on groundwater recharge, changes in subsurface routing, and consequences for stream low flows sourced predominately by baseflow are poorly understood. Here, we demonstrate an approach using the amplitude and phase of paired annual air and stream water temperature signals to broadly identify changes in watershed subsurface flow contributions after fire. Watersheds were classified using pre-fire temperature data, as having air-coupled (i.e., reduced apparent groundwater signature), deep groundwater, or shallow groundwater stream temperature signals. Changes in pre- and post-fire paired air and stream water temperature metrics were compared for locations (n = 17) spanning a large range of physiographic and climatic conditions across the western United States. Pre- and post-fire comparisons were computed by quantile using bootstrapped confidence intervals (ci = 95), as well as in aggregate using Kruskal-Wallis and post-hoc Dunn tests. Statistical comparisons of pre- and post-fire temperature metrics suggest that overall, watersheds classified as having minimal groundwater influence are the most likely to experience fire-induced subsurface hydrologic change. More specifically, watersheds classified as having air-coupled or shallow groundwater signals experienced increases in the magnitude of groundwater discharge, with more stable annual thermal regimes post-fire that are less-coupled to ambient air temperature. These findings form the basis of a conceptual framework for watershed resistance to subsurface hydrologic change following fire that can be broadly applied as a first approximation for water management, impacts on aquatic habitat, and post-wildfire response planning.

California, Idaho, Oregon, Washington↗

USGS2023

Climate change and the global redistribution of biodiversity: Substantial variation in empirical support for expected range shifts

Background Among the most widely predicted climate change-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution to track their climate niches. A series of commonly articulated hypotheses have emerged in the scientific literature suggesting species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to rising temperatures associated with climate change. Yet, many species are not demonstrating range shifts consistent with these expectations. Here, we evaluate the impact of anthropogenic climate change (specifically, changes in temperature and precipitation) on species’ ranges, and assess whether expected range shifts are supported by the body of empirical evidence. Methods We conducted a Systematic Review, searching online databases and search engines in English. Studies were screened in a two-stage process (title/abstract review, followed by full-text review) to evaluate whether they met a list of eligibility criteria. Data coding, extraction, and study validity assessment was completed by a team of trained reviewers and each entry was validated by at least one secondary reviewer. We used logistic regression models to assess whether the direction of shift supported common range-shift expectations (i.e., shifts to higher latitudes and elevations, and deeper depths). We also estimated the magnitude of shifts for the subset of available range-shift data expressed in distance per time (i.e., km/decade). We accounted for methodological attributes at the study level as potential sources of variation. This allowed us to answer two questions: (1) are most species shifting in the direction we expect (i.e., each observation is assessed as support/fail to support our expectation); and (2) what is the average speed of range shifts? Review findings We found that less than half of all range-shift observations (46.60%) documented shifts towards higher latitudes, higher elevations, and greater marine depths, demonstrating significant variation in the empirical evidence for general range shift expectations. For the subset of studies looking at range shift rates, we found that species demonstrated significant average shifts towards higher latitudes (average = 11.8 km/dec) and higher elevations (average = 9 m/dec), although we failed to find significant evidence for shifts to greater marine depths. We found that methodological factors in individual range-shift studies had a significant impact on the reported direction and magnitude of shifts. Finally, we identified important variation across dimensions of range shifts (e.g., greater support for latitude and elevation shifts than depth), parameters (e.g., leading edge shifts faster than trailing edge for latitude), and taxonomic groups (e.g., faster latitudinal shifts for insects than plants). Conclusions Despite growing evidence that species are shifting their ranges in response to climate change, substantial variation exists in the extent to which definitively empirical observations confirm these expectations. Even though on average, rates of shift show significant movement to higher elevations and latitudes for many taxa, most species are not shifting in expected directions. Variation across dimensions and parameters of range shifts, as well as differences across taxonomic groups and variation driven by methodological factors, should be considered when assessing overall confidence in range-shift hypotheses. In order for managers to effectively plan for species redistribution, we need to better account for and predict which species will shift and by how much. The dataset produced for this analysis can be used for future research to explore additional hypotheses to better understand species range shifts.

Journal of Environmental Evidence↗

USGS2002

Historical changes in lake ice-out dates as indicators of climate change in New England, 1850-2000

Various studies have shown that changes over time in spring ice-out dates can be used as indicators of climate change. Ice-out dates from 29 lakes in New England (USA) with 64 to 163 years of record were assembled and analysed for this study. Ice-out dates have become significantly earlier in New England since the 1800s. Changes in ice-out dates between 1850 and 2000 were 9 days and 16 days in the northern/mountainous and southern regions of New England respectively. The changes in the ice-out data over time were very consistent within each of the two regions of New England, and more consistent than four air-temperature records in each region. The ice-out dates of the two regions had a different response to changes in air temperature. The inferred late winter-early spring air-temperature warming in both regions of New England since 1850, based on linear regression analysis, was about 1.5 ??C. Published in 2002 by John Wiley & Sons, Ltd.

International Journal of Climatology↗

USGS2024

Twentieth century extreme precipitation detected in a high-resolution, coastal lake-sediment record from California

California faces increasing economic and societal risks from extreme precipitation and flooding associated with atmospheric rivers (ARs) under projected twenty-first century climate warming. Lake sediments can retain signals of past extreme precipitation events, allowing reconstructions beyond the period of instrumental records. Here, we calibrate AR-related extreme precipitation from the last century to proxy data from lake sediments collected in the latitudinal zone of the highest frequency landfall for modern ARs in California. Excursions in erosional proxy data (Ti/Al) are positively and significantly correlated (r median = 0.45, p median = 0.04) with modern records of integrated vapor transport (IVT, kg m −1 s −1 ), a key metric of AR intensity, using correlations that incorporate age-model uncertainty. Despite the land-use change near the study site, the data suggest intense and long-lasting AR storms are identifiable in this sedimentary record. These results allow conservative inferences concerning past extreme hydrology at this site.

California↗

USGS2026

Reservoir releases and land cover interact to drive event-scale nitrate export in a large agricultural basin

Understanding the drivers of nitrate export in rivers is critical for developing effective nutrient management strategies. However, few studies have explored event-scale drivers of export in large river basins with human modifications like reservoirs. Here, we analyzed nitrate concentration-discharge (C-Q) relationships from 215 events at the outlet of the Kansas River Basin, USA (155,690 km 2 ) from 2014 to 2022 to (1) characterize event-scale nitrate export behaviors in a large agricultural basin, and (2) determine how different event characteristics are linked to these behaviors. We found that C-Q behaviors varied greatly, with 60% of events producing nitrate enrichment (n = 130) and 40% of events producing nitrate dilution (n = 85). These behaviors were correlated with complex spatial interlinkages between climate and land cover: across most of the basin, nitrate enrichment was correlated with drier antecedent conditions, but in wetter areas with higher proportions of urban and forested land cover, enrichment was more strongly correlated with precipitation magnitude/intensity. This difference in hydroclimatic controls on nitrate export might be related to differential distributions of nitrate sources within these land covers. Upstream of major reservoirs, however, neither variable was strongly correlated with C-Q behavior, suggesting that nitrate attenuation within reservoirs decouples event-scale concentration signals in upstream waters from those downstream. Reservoir outflows had variable impacts on C-Q behavior, reflecting reservoir-specific variations in nitrate attenuation efficiency. Together, these results identify specific complex interactions between hydroclimate, land cover, reservoir positioning, and individual reservoir properties that control event-scale nitrate export from large basins.

Colorado, Kansas, Nebraska↗