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HILARRI Version 2 is a database of links between major datasets of operational hydropower dams and powerplants (National Inventory of Dams (2021), Global Reservoir and Dam Database (GRanD v1.3), Existing Hydropower Assets (EHA 2022), and inland water bodies (NHDPlusV2 river network, NHD water bodies, NHD Watershed Boundary Dataset, HydroLAKES).
We used entropy and wavelet techniques to identify temporal variability in geochemical constituents and their controls along three transects within a contaminated floodplain system near Rifle CO. The objectives of this study were to: (1) identify hot moments of conservative and redox sensitive species as short time-periods with disproportionally high levels of concentration, and (ii) associate the transport and/or biogeochemical factors controlling this temporal variability. This data package includes tables from Arora et al. 2016a: Identifying geochemical hot moments and their controls on a contaminated river floodplain system using wavelet and entropy approaches, Environmental modelling & software, 85, 27-41. In particular, files include sampling frequency for geochemical data at the Rifle site, and results of entropy analysis.
This file contains data used to calculate subsurface flow and transport at the Pumphouse Lower Montane (PLM) hillslope transect. Information includes locations, weather data, hydraulic conductivities, hydraulic head profiles, soil water profiles, depths to the water table, specific conductance (SC) and dissolved organic carbon (DOC) in pore waters, water isotopic composition, calculated subsurface fluxes, calculated subsurface transport concentrations for SC and DOC, East River discharge and SC, transect soil particle-size distributions, and moisture characteristic curves.
This dataset contains snow water, precipitation, and discharge data collected from the East River watershed. This provides insight as to how the watershed works as a system and responds to hydrological perturbations.
Groundwater contributions to streams, or baseflow, represents a mix of numerous flow paths through the subsurface of varying ages that are important to understanding system hydrologic lag and solute export. To better constrain numerical estimates of baseflow age, we used a novel experiment from Sanford et al. (2015) based on stream water concentrations of environmental gases (SF6, N2 and Ar) and an assumed Weibull distribution for a Colorado (CO) River headwater basin, Copper Creek (24 km2). The data package contains steam data collected over a 12-hour period on August 27, 2017 and the finite difference approximation for the mass balance approach.
This data package contains sample collection metadata for soil cores from the East River Watershed in Colorado used in biogeochemical analyses by the Watershed Function SFA. Soil cores were collected seasonally during autumn, winter, snowmelt, and spring at a predominately montane meadow, high altitude field site. Information provided for each soil core sample assigned an International Geo Sample Number (IGSN) includes: sample name, IGSN, material, description, collection method, core depth, location, field program, collectors, and date. The full list of 53 IGSN's is listed in the Methods section. There is also a complete core sample list and metadata for the set of baseline data.
This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.
Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.
Electronic waste (e-waste) has caused a severe worldwide pollution problem. Despite increasing isolation of degradative microorganisms from e-waste contaminated environments, the mechanisms underlying their adaptive evolution in such habitats remain unclear. Sphingomonads generally have xenobiotic-degrading ability and may play important roles in bioremediation. Sphingobium hydrophobicum C1 T , characterized with superior cell surface hydrophobicity, was recently isolated from e-waste contaminated river sediment. To dissect the mechanisms driving its adaptive evolution, we evaluated its stress resistance, sequenced its genome and performed comparative genomic analysis with 19 other Sphingobium strains. Strain C1 T can feed on several kinds of e-waste-derived xenobiotics, exhibits a great resistance to heavy metals and possesses a high colonization ability. It harbors abundant genes involved in environmental adaptation, some of which are intrinsic prior to experiencing e-waste contamination. The extensive genomic variations between strain C1 T and other Sphingobium strains, numerous C1 T -unique genes, massive mobile elements and frequent genome rearrangements reflect a high genome plasticity. Positive selection, gene duplication, and especially horizontal gene transfer drive the adaptive evolution of strain C1 T . Moreover, presence of type IV secretion systems may allow strain C1 T to be a source of beneficial genes for surrounding microorganisms. This study provides new insights into the adaptive evolution of sphingomonads, and potentially guides bioremediation strategies.
Predicting boundary layer clouds is important for the accurate modeling of pollutant dispersion. Higher resolution mesoscale models would be expected to produce better forecasts of cloud properties that affect dispersion. Using ceilometer observations, we assess the skill of two operational mesoscale models (RAMS and WRF) to forecast cloud base altitude and cloud fraction at the Savannah River Site in the southeastern US during the springtime. Verifications were performed at small spatial and temporal scales necessary for dispersion modeling. Both models were unreliable with a 50% (RAMS) and a 46% (WRF) rate of predicting clouds observed by the ceilometer which led to low cloud fraction predictions. Results indicated that WRF better predicted daytime cloud bases from convection that occurred frequently later in the period and RAMS better predicted nighttime cloud bases. Using root mean squared error (RMSE) to score the forecast periods also highlighted this diurnal dichotomy, with WRF scores better during the day and RAMS scores better at night. Analysis of forecast errors revealed divergent model cloud base biases—WRF low and RAMS high. A hybrid solution which weighs more heavily the RAMS nighttime forecasts and WRF daytime forecasts will likely provide the best prediction of cloud properties for dispersion.
A largely understudied microbially mediated mercury (Hg) bioremediative pathway includes the volatilization of Hg 2+ to Hg 0 . Therefore, studies on Hg resistant bacteria (HgR), isolated from historically long-term contaminated environments, can serve as models to understand mechanisms underpinning Hg cycling. Towards this end, a mercury resistant bacterial strain, identified as Stenotrophomonas sp., strain MA5, was isolated from Mill Branch on the Savannah River Site (SRS); an Hg-impacted ecosystem. Minimum inhibitory concentration (MIC) analysis showed Hg resistance of up to 20 µg/mL by MA5 with 95% of cells retaining viability. Microcosm studies showed that the strain depleted more than 90% of spiked Hg 2+ within the first 24 h of growth and the detection of volatilized mercury indicated that the strain was able to reduce Hg 2+ to Hg 0 . To understand molecular mechanisms of Hg volatilization, a draft whole genome sequence was obtained, annotated and analyzed, which revealed the presence of a transposon-derived mer operon (merRTPADE) in MA5, known to transport and reduce Hg 2+ into Hg 0 . Based on the whole genome sequence of strain MA5, qRT-PCR assays were designed on merRTPADE, we found a ~40-fold higher transcription of mer T, P, A, D and E when cells were exposed to 5 µg/mL Hg 2+ . Interestingly, strain MA5 increased cellular size as a function of increasing Hg concentrations, which is likely an evolutionary response mechanism to cope with Hg stress. Moreover, metal contaminated environments are shown to co-select for antibiotic resistance. When MA5 was screened for antibiotic resistance, broad resistance against penicillin, streptomycin, tetracycline, ampicillin, rifampicin, and erythromycin was found; this correlated with the presence of multiple gene determinants for antibiotic resistance within the whole genome sequence of MA5. Overall, this study provides an in-depth understanding of the underpinnings of Stenotrophomonas-mercury interactions that facilitate cellular survival in a contaminated soil habitat.
Fractional calculus-based differential equations were found by previous studies to be promising tools in simulating local-scale anomalous diffusion for pollutants transport in natural geological media (geomedia), but efficient models are still needed for simulating anomalous transport over a broad spectrum of scales. This study proposed a hierarchical framework of fractional advection-dispersion equations (FADEs) for modeling pollutants moving in the river corridor at a full spectrum of scales. Applications showed that the fixed-index FADE could model bed sediment and manganese transport in streams at the geomorphologic unit scale, whereas the variable-index FADE well fitted bedload snapshots at the reach scale with spatially varying indices. Further analyses revealed that the selection of the FADEs depended on the scale, type of the geomedium (i.e., riverbed, aquifer, or soil), and the type of available observation dataset (i.e., the tracer snapshot or breakthrough curve (BTC)). When the pollutant BTC was used, a single-index FADE with scale-dependent parameters could fit the data by upscaling anomalous transport without mapping the sub-grid, intermediate multi-index anomalous diffusion. Pollutant transport in geomedia, therefore, may exhibit complex anomalous scaling in space (and/or time), and the identification of the FADE’s index for the reach-scale anomalous transport, which links the geomorphologic unit and watershed scales, is the core for reliable applications of fractional calculus in hydrology.
We describe a potentially new species of a platinum cupride–stannide mineral (PCSM) of composition Pt(Cu 0.67 Sn 0.33 ). It occurs in a placer deposit in the River Bolshoy Khailyk, southern Krasnoyarskiy kray, Russia. A synthetic equivalent of PCSM was obtained and characterized. The PCSM occurs as anhedral or subhedral grains up to 15 μm × 30 μm in association with various platinum-group minerals, Rh–Co-rich pentlandite and magnetite, all hosted by a placer grain of Cu–Au–Pt alloy. Synchrotron micro-Laue diffraction studies indicate that the PCSM mineral is tetragonal and belongs to the inferred space-group P4/mmm (#123). Its unit-cell parameters are a = 2.838 (3) Å, c = 3.650 (4) Å, and V = 29.40 (10) Å 3 , and Z = 1. The c:a ratio calculated from the unit-cell parameters is 1.286. These characteristics are in good agreement with those obtained for specimens of synthetic Pt(Cu 0.67 Sn 0.33 ). A review on related minerals and unnamed phases is provided to outline compositional variations and extents of solid solutions in the relevant systems PtNi–PtFe–PtCu, PdCu–PdHg–PdAu, PdHg–PtHg, and AuCu–PtCu. The PCSM-bearing mineralization appears to be related genetically with an ophiolitic source-rock of the Aktovrakskiy complex of the western Sayans. The unnamed phase likely crystallized from microvolumes of a highly fractionated melt rich in Cu and Sn.
Examination of a fly ash derived from the combustion of a low-S, subbituminous Powder River Basin coal by Scanning Electron Microscopy (SEM) and High-resolution Transmission Electron Microscopy (HRTEM), both supplemented by Energy-dispersive X-ray spectroscopy (EDS), showed that the fly ashes were dominated by amorphous phases, Ca-rich plagioclase feldspars, Mg-rich phases, complex Ca-Mg-Al-Si-Ti-Fe grains, and trace amounts of REE-rich particles. Many of the particles were rimmed by a Ca-S, possibly a sulfate. HRTEM-EDS examination of a REE-rich particle proved it to be a mix of light- and heavy-rare earth minerals mixed with amorphous phases.
Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA’s Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983–2018) reduced SD from 61–96%, TN from 34–55%, TP from 9–48%, and BD from 53–99%, and raised DO from 4–10% with respect to No-RBZ in the three watersheds. The late century’s (2070–2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28–94% and BD from 69–93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ.
In this paper, we examine the filamentous cyanobacterial strain NILCB16 and describe it as a new species within the genus Pegethrix. The original population was sampled from a mat growing in an irrigation canal in the Nile River, Egypt. Initially classified under Plectonema or Planktolyngbya, the strain is a potential producer of the toxins microcystin and β-N-Methylamino-L-Alanine (BMAA). Additionally, we reviewed the taxonomic relationships between the Oculatellales genera. To describe the new species, we conducted a polyphasic study, encompassing 16S rRNA gene phylogenetic analyses performed using both Maximum Likelihood and Bayesian methods, sequence identity (p-distance) analysis, 16S-23S ITS secondary structures, and morphological and habitat comparisons. The phylogenetic analysis revealed that strain NILCB16 clustered within the Pegethrix clade with strong phylogenetic support, but in a distinct position from other species in the genus. The strain shared a maximum 16S rRNA gene identity of 97.3% with P. qiandaoensis and 96.1% with the type species, P. bostrychoides. Morphologically, NILCB16 can be differentiated from other species in the genus by its lack of false branching. Our phylogenetic analyses also show that Pegethrix, Cartusia, Elainella, and Maricoleus are clustered with strong phylogenetic support. They exhibit high 16S rRNA gene identity and are morphologically indistinguishable, suggesting they could potentially be merged into a single genus in the future.
Weather data are the key forces that drive hydrological processes so that their accuracy in watershed modeling is fundamentally important. For large-scale watershed modeling, weather data are either generated by using interpolation methods or derived from assimilated datasets. In the present study, we compared model performances of the Soil and Water Assessment Tool (SWAT), as driven by interpolation weather data, and NASA North American Land Data Assimilation System Phase Two (NLDAS2) weather dataset in the Upper Mississippi River Basin (UMRB). The SWAT model fed with different weather datasets were used to simulate monthly stream flow at 11 United States Geological Survey (USGS) monitoring stations in the UMRB. Model performances were evaluated based on three metrics: coefficient of determination (R 2 ), Nash–Sutcliffe coefficient (NS), and percent bias (P bias ). The results show that, after calibration, the SWAT model compared well at all monitoring stations for monthly stream flow using different weather datasets indicating that the SWAT model can adequately produce long-term water yield in UMRB. The results also show that using NLDAS2 weather dataset can improve SWAT prediction of monthly stream flow with less prediction uncertainty in the UMRB. We concluded that NLDAS2 dataset could be used by the SWAT model for large-scale watersheds like UMRB as a surrogate of the interpolation weather data. Further analyses results show that NLDAS2 daily solar radiation data was about 2.5 MJ m -2 higher than the interpolation data. As such, the SWAT model driven by NLDAS2 dataset tended to underestimate stream flow in the UMRB due to the overestimation in evapotranspiration in uncalibrated conditions. Thus, the implication of overestimated solar radiation by NLDAS2 dataset should be considered before using NLDAS2 dataset to drive the hydrological model.
Abstract. An extreme warming event near the North Pole, with 2 m temperature rising above 0 °C, was observed in late December 2015. This specific event has been attributed to cyclones and their associated moisture intrusions. However, little is known about the characteristics and drivers of similar events in the historical record. Here, using data from European Centre for Medium-Range Weather Forecasts Reanalysis, version 5 (ERA5), we study these winter extreme warming events with 2 m temperature over a grid point above 0 °C over the high Arctic (poleward of 80° N) that occurred during 1980–2021. In ERA5, such wintertime extreme warming events can only be found over the Atlantic sector. They occur rarely over many grid points, with a total absence during some winters. Furthermore, even when occurring, they tend to be short-lived, with the majority of the events lasting for less than a day. By examining their surface energy budget, we found that these events transition with increasing latitude from a regime dominated by turbulent heat flux into the one dominated by downward longwave radiation. Positive sea level pressure anomalies which resemble blocking over northern Eurasia are identified as a key ingredient in driving these events, as they can effectively deflect the eastward propagating cyclones poleward, leading to intense moisture and heat intrusions into the high Arctic. Using an atmospheric river (AR) detection algorithm, the roles of ARs in contributing to the occurrence of these extreme warming events defined at the grid-point scale are explicitly quantified. The importance of ARs in inducing these events increases with latitude. Poleward of about 83° N, 100 % of these events occurred under AR conditions, corroborating that ARs were essential in contributing to the occurrence of these events. Over the past 4 decades, both the frequency, duration, and magnitude of these events have been increasing significantly. As the Arctic continues to warm, these events are likely to increase in both frequency, duration, and magnitude, with great implications for the local sea ice, hydrological cycle, and ecosystem.