Geology topics

Research about East River

Source-linked reports with geographic coverage including East River.

5 recordsLinked to original sources

USGS2025

Evaluating uncertainties with sample-collection method and source selection in sediment fingerprinting: an example from a Great Lakes tributary

Purpose Identifying suspended-sediment (SS) sources, seasonal variability, and phosphorus (P) transported with SS is critical information for basin managers, although there may be concerns about comparability between flow-integrated SS samples used for sediment fingerprinting and discrete samples used for concentrations and loads in basins where SS is mostly silt + clay and(or) one land-use predominates. Objectives were to determine if (1) sample-collection method and (2) source consideration influenced apportionment of the largest SS source. Methods Concurrent-replicate, SS samples were collected during 2022 from the East River, Wisconsin using an automated sampler, commonly used for water-quality sampling, and passive samplers, frequently used for SS fingerprinting. Samples were evaluated for differences in physical and chemical characteristics that may affect source apportionment. Considered sources included three upland land-use (cropland, forest, and roads), two in-channel (streambank and streambed sediment), and one that connects uplands to the stream channel (gullies). Source apportionment used established methods in the SedSAT tool. Source scenarios included land-use + streambank (4src), 4src + gully, 4src + streambed, and 4src + gully + streambed (6src). Results There were no statistically significant differences in median grain size, organic carbon, or sediment-bound P as a function of collection method. In-channel sources were the largest proportional SS source, regardless of season, hydrologic condition, collection method, or source scenario. Source verification highlighted which source fingerprints were most accurately defined and implications for SS target apportionment. Conclusion Varying the source scenarios for sediment fingerprinting indicated that improved management of hydrologic connectivity between upland land use and the stream channel has the potential to mitigate SS loads.

Wisconsin↗

USGS2025

Changing dynamic phosphorus forms from field to stream during surface runoff events

The risk of water quality impairment from agricultural runoff depends on nutrient source, transport, and bioavailability. Phosphorus (P) spirals between dissolved and particulate forms as it is transported with suspended sediment (SS) from agricultural fields, through the stream network, to receiving water bodies. This dynamic sorption-desorption influences bioavailability. We quantified P form and abundance in samples collected during surface-runoff events from a farm field in the East River Basin, Wisconsin and compared them to those in stream water collected from the East River. We sampled five events between late March 2022 and June 2023. During most events, P in surface runoff was mainly in dissolved form, with particulate P sorbed to fine clay, the most abundant particle fraction transported from the field, whereas P in stream water was mainly in particulate form and sorbed to silt, even though fine clay was the most abundant particle fraction in the stream during events. Overall capacity for P sorption to SS in the stream varied among events. Total P and SS concentrations were lower during summer baseflow conditions and smaller surface runoff events; however, what SS was present was more P enriched. This shift in P form from field to stream indicates a potential for sorbing dissolved P to SS during transport through the stream network, which changes the bioavailability of P exported downstream with less bioavailable P as dissolved P binds to SS.

Wisconsin↗

USGS2022

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

Colorado↗

USGS2020

Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado)

Manganese (Mn) plays a critical role in river-water quality because Mn-oxides serve as sorption sites for contaminant metals. The aim of this study is to understand the seasonal cycling of Mn in an alpine streambed that experiences large spring snowmelt events and the potential responses to changes in snowmelt timing and magnitude. To address this goal, annual variations in river-water/groundwater interaction and Mn (aq) transport were measured and modeled in the bed of East River, Colorado, USA. In observations and numerical models, oxygenated river water containing dissolved organic carbon (DOC) mixes with groundwater rich in Mn (aq) in the streambed. The mixing depth increases during spring snowmelt when river discharge increases, leading to a greater DOC supply to the hyporheic zone and net respiration of Mn-oxides, despite an enhanced supply of oxygen. As groundwater upwelling resumes during the subsequent baseflow period, Mn (aq) -rich groundwater mixes with oxygenated river water, resulting in net accumulation of Mn-oxides until the bed freezes in winter. To explore potential responses of Mn transport to different climate-induced hydrological regimes, three hydrograph scenarios were numerically modeled (historic, low-snow, and storm) for the Rocky Mountain region. In a warming climate, Mn (aq) export to the river decreases, and Mn (aq) oxidation is favored in the upper streambed sediments over more of the year. One important implication is that the streambed may have an increased sorption capacity for metals over more of the year, leading to potential changes in river-water quality.

Colorado↗

USGS2018

Airborne geophysical characterizationof geologic structure in a mountain headwater system, upper East River, Colorado

Geologic controls on groundwater flow, particularly in tectonically and topographically complex mountainous terrain, can be difficult to quantify without a detailed understanding of the regional subsurface geologic structure. This structure can influence the magnitude of groundwater flow through the mountain block, which in turn impacts groundwater composition and the flux of metals and nutrients to the near - surface ecosystem. In support of several ongoing studies in the upper East River and surrounding w atersheds in central Colorado, regional - scale airborne electromagnetic, magnetic, and radiometric survey s were conducted in late 2017 . These data give a view of the geologic structure underlying the region that is unprecedented in both resolution and spa tial coverage.

Colorado↗