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1. Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

   https://doi.org/10.5061/dryad.8sf7m0cpx  

   Hussain, Mir Zaman ; Hamilton, Stephen ; Robertson, G. Philip ; Basso, Bruno ( January 2021 , Dryad)

   Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α = 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 

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2. From on high: Geochemistry of alpine springs, Niwot Ridge, Colorado Front Range, USA

   https://doi.org/10.1002/hyp.13436  

   Fields, Jordan F. ; Dethier, David P. ( May 2019 , Hydrological Processes)

   Snowmelt‐fed springs and small (0.5 km²) upland catchments in alpine areas of the western United States contribute significantly to the quantity and inorganic chemistry of water delivered to downstream basins but have not been studied extensively. Mineral weathering, transit time, and hydrologic mixing control the solute chemistry of waters that drain the upland zone of Niwot Ridge, Colorado Front Range, and adjacent areas in the granitic core of the Southern Rocky Mountains. Water in 37 springs sampled in this study flows in generally short steep paths (~0.3 km) through shallow regolith with mean transit times (MTT) of weeks to months, producing solutions dominated by Si, Ca²⁺, Na⁺, and HCO₃⁻, locally SO₄²⁻. Rock type is a significant control on spring, surface, and shallow groundwater chemistry, and plagioclase (oligoclase) is the major source of dissolved Na⁺and Si. Concentrations of Ca²⁺exceed stoichiometric predictions of oligoclase weathering by ~3.5×; excess Ca²⁺likely represents weathering of aeolian material, vein calcite, or trace minerals. Concentrations of base cations and Si increase slowly with estimated MTT of 0.2 years for Niwot Ridge spring waters, and several years for shallow groundwater sampled by wells. Chemical weathering of silicate minerals is slow with estimated rates of ~2.0 and 0.2 pmol·m⁻²·s⁻¹for oligoclase and microcline, respectively; the most mineralized spring waters are saturated only with respect to kaolinite and montmorillonite. More than 50% of the dissolved base cations + Si measured in Boulder Creek at Orodell (~25 km downstream) accumulate before water emerges from alpine springs on Niwot Ridge. Warming global temperatures are shifting more high‐elevation precipitation to rain, potentially changing run‐off patterns, transit time, and solute loads. Acquisition of solutes by alpine waters thus has implications far beyond small upland catchments.

    

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3. Groundwater–Stream Connectivity Mediates Metal(loid) Geochemistry in the Hyporheic Zone of Streams Impacted by Historic Mining and Acid Rock Drainage

   https://doi.org/10.3389/frwa.2020.600409  

   Hoagland, Beth ; Navarre-Sitchler, Alexis ; Cowie, Rory ; Singha, Kamini ( December 2020 , Frontiers in Water)

   null (Ed.)

   High concentrations of trace metal(loid)s exported from abandoned mine wastes and acid rock drainage pose a risk to the health of aquatic ecosystems. To determine if and when the hyporheic zone mediates metal(loid) export, we investigated the relationship between streamflow, groundwater–stream connectivity, and subsurface metal(loid) concentrations in two ~1-km stream reaches within the Bonita Peak Mining District, a US Environmental Protection Agency Superfund site located near Silverton, Colorado, USA. The hyporheic zones of reaches in two streams—Mineral Creek and Cement Creek—were characterized using a combination of salt-tracer injection tests, transient-storage modeling, and geochemical sampling of the shallow streambed (<0.7 m). Based on these data, we present two conceptual models for subsurface metal(loid) behavior in the hyporheic zones, including (1) well-connected systems characterized by strong hyporheic mixing of infiltrating stream water and upwelling groundwater and (2) poorly connected systems delineated by physical barriers that limit hyporheic mixing. The comparatively large hyporheic zone and high hydraulic conductivities of Mineral Creek created a connected stream–groundwater system, where mixing of oxygen-rich stream water and metal-rich groundwater facilitated the precipitation of metal colloids in the shallow subsurface. In Cement Creek, the precipitation of iron oxides at depth (~0.4 m) created a low-hydraulic-conductivity barrier between surface water and groundwater. Cemented iron oxides were an important regulator of metal(loid) concentrations in this poorly connected stream–groundwater system due to the formation of strong redox gradients induced by a relatively small hyporheic zone and high fluid residence times. A comparison of conceptual models to stream concentration–discharge relationships exhibited a clear link between geochemical processes occurring within the hyporheic zone of the well-connected system and export of particulate Al, Cu, Fe, and Mn, while the poorly connected system did not have a notable influence on metal concentration–discharge trends. Mineral Creek is an example of a hyporheic system that serves as a natural dissolved metal(loid) sink, whereas poorly connected systems such as Cement Creek may require a combination of subsurface remediation of sediments and mitigation of upstream, iron-rich mine drainages to reduce metal export. 

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4. Strontium isotope dynamics reveal streamflow contributions from shallow flow paths during snowmelt in a montane watershed, Provo River, Utah, USA

   https://doi.org/10.1002/hyp.14458  

   Hale, Colin A. ; Carling, Gregory T. ; Nelson, Stephen T. ; Fernandez, Diego P. ; Brooks, Paul D. ; Rey, Kevin A. ; Tingey, David G. ; Packer, Brian N. ; Aanderud, Zachary T. ( January 2022 , Hydrological Processes)

   Quantifying the routing of snowmelt to surface water is critical for predicting the impacts of atmospheric deposition and changing land use on water quality in montane catchments. To investigate solute sources and streamflow in the montane Provo River watershed (Utah, USA), we used time‐series⁸⁷Sr/⁸⁶Sr ratios sampled at three sites (Soapstone, Woodland and Hailstone) across a gradient of bedrock types. Soils are influenced by aeolian dust contributions, with distinct⁸⁷Sr/⁸⁶Sr ratios relative to siliciclastic bedrock, providing an opportunity to investigate shallow versus deeper flow paths for controlling water chemistry. At the most upstream site (Soapstone), Sr concentrations averaged ~17 μg/L with minimal dilution during snowmelt suggesting subsurface flow paths dominated streamflow. However, a decrease in⁸⁷Sr/⁸⁶Sr ratios from ~0.717 during baseflow to as low as ~0.713 during snowmelt indicated the activation of shallow flow paths through dust‐derived soils. In contrast, downstream sites receiving water inputs from Sr‐rich carbonate bedrock (Woodland and Hailstone) exhibited strong dilution of Sr from ~120 to 20 μg/L and an increase in⁸⁷Sr/⁸⁶Sr ratios from ~0.7095 to ~0.712 during snowmelt. A three‐component mixing model using⁸⁷Sr/⁸⁶Sr ratios and Sr concentrations at Soapstone showed water inputs were dominated by direct snowmelt and flushed soil water during runoff and groundwater during baseflow. At Woodland and Hailstone, a two‐component mixing model showed that the river was a mixture of groundwater and up to 75% upstream channel water during snowmelt. Our findings highlight the importance of flushed soil water for controlling stream water discharge and chemistry during snowmelt, with the signal from the upstream site propagating downstream in a nested catchment. Further, aeolian dust contributes to the solute chemistry of montane streams with potential impacts on water quality along shallow flow paths. Potential contaminants in these surface soils (e.g., Pb deposition in dust) may have significant impacts on water quality during snowmelt runoff.

    

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5. Causes and Characteristics of Electrical Resistivity Variability in Shallow (<4 m) Soils in Taylor Valley, East Antarctica

   https://doi.org/10.1029/2022JF006696  

   Gutterman, W. S. ; Doran, P. T. ; Virginia, R. A. ; Barrett, J. E. ; Myers, K. F. ; Tulaczyk, S. M. ; Foley, N. T. ; Mikucki, J. A. ; Dugan, H. A. ; Grombacher, D. J. ; et al ( February 2023 , Journal of Geophysical Research: Earth Surface)

   Airborne electromagnetic surveys collected in December 2011 and November 2018 and three soil sampling transects were used to analyze the spatial heterogeneity of shallow (<4 m) soil properties in lower Taylor Valley (TV), East Antarctica. Soil resistivities from 2011 to 2018 ranged from ∼33 Ωm to ∼3,500 Ωm with 200 Ωm assigned as an upper boundary for brine‐saturated sediments. Elevations below ∼50 m above sea level (masl) typically exhibit the lowest resistivities with resistivity increasing at high elevations on steeper slopes. Soil water content was empirically estimated from electrical resistivities using Archie's Law and range from ∼<1% to ∼68% by volume. An increase in silt‐ and clay‐sized particles at low elevations increases soil porosity but decreases hydraulic conductivity, promoting greater residence times of soil water at low elevations near Lake Fryxell. Soil resistivity variability between 2011 and 2018 shows soils at different stages of soil freeze‐thaw cycles, which are caused predominantly by solar warming of soils as opposed to air temperature. This study furthers the understanding of the hydrogeologic structure of the shallow subsurface in TV and identifies locations of soils that are potentially prone to greater rates of thaw and resulting ecosystem homogenization of soil properties from projected increases in hydrological connectivity across the region over the coming decades.

    

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