USGS Science⌕ Search

USGS · sir20245085

Suspended sediment and trace element transport in the Big River downstream from the Old Lead Belt in southeastern Missouri, 2018–21

Abstract

Lead Belt, an area of major lead mining from the 1860s until 1972 where more than 8.5 million tons of lead were mined. After active mining ceased, the effects of mining activities persisted in the Big River system because of large mine waste pile erosion, and floodplain sediment and streambank contamination along several tributaries and the main stem of the Big River. Lead-contaminated streambed and floodplain sediments extend more than 90 miles from the Old Lead Belt to the confluence of the Big River with the Meramec River. The waste piles and mine-waste contaminated streambed and floodplain sediments have been sources of high concentrations of several trace elements, primarily cadmium, lead, and zinc. The U.S. Environmental Protection Agency Region 7 has made several efforts to prevent further erosion of contaminated sediments into the Big River including the capping of major mine waste piles, reclaiming sediment deposits along the floodplains, and monitoring soil conditions of croplands and residential properties. A cooperative effort began in 2011 between the U.S. Geological Survey and the U.S. Environmental Protection Agency Region 7 to characterize suspended sediment quantity and quality in the Big River downstream from the Old Lead Belt as reclamation activities in the drainage basin progressed. The study was completed in two phases, and each phase included continuous stage, turbidity, and water temperature monitoring at the Big River below Bonne Terre, Missouri, streamgage and sampling station. Periodic suspended sediment samples also were collected manually (discrete samples) during base flow and selected stormflow events. Continuous streamflow, turbidity, and discrete suspended sediment data were used to develop regression models to compute daily suspended sediment concentrations and loads. During both phases, the discrete stormflow event samples were also evaluated to determine particle size distribution and concentrations of select trace elements. Phase one was completed from October 2011 through September 2013, and phase two, which is the primary focus of this report, was completed from October 2018 through September 2021. Phase two also included time-integrated suspended sediment samples collected using passive samplers. Discrete samples (collected during stormflow events) and passive samples were analyzed for concentrations of barium, cadmium, lead, and zinc in two sediment size fractions (when possible) to estimate trace element loads. Suspended sediment concentrations and loads and select trace element concentration results computed during phase one were compared to those computed during phase two to identify trends in the Big River Basin during the full study period. The concentrations of cadmium, lead, and zinc in nearly all discrete stormflow event suspended sediment samples and passive suspended sediment samples exceeded the threshold effect concentrations and the probable effect concentrations, which are two sediment quality guidelines. Most samples also exceeded the toxic effect threshold, the level at which sediment is considered to be heavily contaminated and problematic for sediment-dwelling organisms. Bulk cadmium concentrations (median of 7.90 milligrams per kilogram [mg/kg]) exceeded the toxic effect threshold (3.0 mg/kg) in 17 discrete stormflow event samples, and bulk lead concentrations (median of 1,070 mg/kg) exceeded the toxic effect threshold (170 mg/kg) in all 18 discrete stormflow event samples. Bulk zinc concentrations (median of 500 mg/kg) exceeded the toxic effect threshold (540 mg/kg) in eight discrete stormflow event samples. Bulk concentrations of these trace elements in passive suspended sediment samples were slightly greater, with concentrations of cadmium (median of 14.0 mg/kg) and lead (median of 1,860 mg/kg) exceeding the toxic effect threshold in all 18 samples. Bulk concentrations of zinc (median of 733 mg/kg) exceeded the toxic effect threshold in 15 passive samples. Compared to phase one (water years 2012–13), phase two (water years 2019–21) concentrations of lead and cadmium in the fine fraction of discrete suspended sediment samples collected at Big River below Bonne Terre were statistically similar; concentrations of barium and zinc were statistically smaller in samples collected during phase two (water years 2018–21). Sediment quality data from passive samples and daily mean suspended sediment loads from the regression model were used to calculate annual oads of barium, cadmium, lead, and zinc at the Bonne Terre streamgage. Water year 2019 had the largest loads of barium, cadmium, lead, and zinc (58.6, 1.43, 194, and 76.5 tons, respectively). The total loads of barium, cadmium, lead, and zinc for phase two (water years 2019–21) were 149, 4.00, 520, and 213 tons, respectively. Less than 5 percent of the total lead load calculated for the study period was transported when daily mean streamflow was less than 455 cubic feet per second, which is the approximate flow at which the passive samplers were inundated and began sampling. This highlights that most of the lead load is transported during stormflow events and the effectiveness of using passive samplers for ongoing monitoring of the Big River. Annual suspended sediment loads at the Bonne Terre streamgage computed using the regression model were 113,000 tons in water year 2019, 83,400 tons in water year 2020, and 96,500 tons in water year 2021. The event-based suspended sediment loads for the eight sampled stormflow events ranged from 45.3 to 32,500 tons. Although only a portion of all stormflow events during phase two were sampled, the loads accounted for during these eight stormflow events represented approximately 30.9 percent of the total suspended sediment load calculated for the study period, confirming that a large part of suspended sediments continue to be transported in the Big River during stormflow events. Event-based loads of barium, cadmium, lead, and zinc were greatest during the stormflow events sampled in January 2020 (event 4) and March 2021 (event 8). Event-based loads calculated for event 4 for barium, cadmium, lead, and zinc were 17.1, 0.206, 27.2, and 14.5 tons, respectively. During event 8, an estimated 15.6 tons of barium, 0.239 tons of cadmium, 34.0 tons of lead, and 13.6 tons of zinc were transported in suspended sediments. The continued high concentrations of lead in suspended sediments in the Big River, despite reclamation activities, is likely because of the continual transport from streambed and stream banks of lead-enriched sediment, which remain in the system from historical mining activities.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 37.29246138824874° to 38.3° latitude; -91.28892432173701° to -89.90464697798724° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kendra M. Markland, Camille E. Buckley. 2024-09-09. Suspended sediment and trace element transport in the Big River downstream from the Old Lead Belt in southeastern Missouri, 2018–21. https://doi.org/10.3133/sir20245085

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evaluating the number of realizations (train-test splits) necessary to ensure robust estimates of conventional hydrothermal resource favorability using Monte Carlo cross-validation, the Great Basin, Western USA

Supervised machine learning approaches used to produce favorability maps in resource assessments commonly partition an input dataset into training and testing subsets (that is, through train-test splits). However, if a single split is not representative of underlying resource conditions, the resulting favorability map may be biased, particularly with sparse or heterogeneous datasets. To mitigate the potential for unrepresentative favorability maps, recent works by U.S. Geological Survey researchers have used Monte Carlo cross-validation to implement a large number ( n) of randomized train-test splits to produce n realizations. The realizations are then aggregated using cell-wise median predictions to produce the resulting final favorability map, recognizing that the median will remove extreme values that might have been estimated from a comparatively few unrepresentative realizations. Theoretically, the median prediction at every cell converges to a single estimate as n approaches infinity, and the question addressed herein is: How many realizations are necessary to get a robust estimate (that is, an estimate unaffected by additional realizations)? Therefore, convergence metrics are described to identify the number of train-test splits and realizations needed to make a reliable map using the data and supervised machine learning workflow for conventional hydrothermal resource assessment of the Great Basin of the Western United States. For this study, robust prediction occurs with n approximately equal to 600 realizations, and smaller ensembles (for example, n is approximately equal to 200 or even 100) may be suitable during preliminary or exploratory analyses. Although the resulting threshold numbers will vary depending on the data and modeling approach used, the convergence metrics proposed and applied herein are applicable to other supervised machine learning studies that use Monte Carlo cross-validation.

Scientific Investigations Report↗

Groundwater budget for the Portneuf River Basin, southeastern Idaho

The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, developed the first groundwater budget for the upper Portneuf River Basin in southeastern Idaho, a tributary of the Snake River. A groundwater budget for the Portneuf River Basin supports water resource and administrative management decisions within the basin and for downstream users of the eastern Snake River Plain aquifer. The analysis quantifies inflows, outflows, and residuals for an aquifer system defined by the Idaho Department of Water Resources under three recent precipitation conditions: an average year (2016), a dry year (2021), and a wet year (2023). The budget was calculated for the basin and for two subbasins delineated by the U.S. Geological Survey streamgage Portneuf River at Topaz, Idaho (13073000): the above Topaz subbasin, which includes the Portneuf-Gem valley, and the below Topaz subbasin, which includes Marsh Valley. Aquifer inflows include mountain-front recharge; areal recharge; recharge from applied water, including recharge from irrigation, canal seepage, and effluent returns; groundwater flow into the basin; and reservoir seepage. Outflows include groundwater pumping for agricultural, municipal, and domestic uses; subsurface outflow through the Portneuf gap; and discharge to streams as base flow. Estimated annual inflows for the full basin ranged from 116,880 acre-feet in 2021 to 154,880 acre-feet in 2023, and outflows ranged from 132,190 acre-feet in 2016 to 158,490 acre-feet in 2023. Basinwide residuals, the change in storage plus uncertainty, were −2,410 acre-feet in 2016, −18,410 acre-feet in 2021, and −3,610 acre-feet in 2023, and each subbasin had a mixture of negative and positive residuals. These basinwide results, interpreted as change in storage plus water-budget uncertainty, indicate minor net losses that increase with dry conditions, consistent with well depth-to-water measurements indicating gradual multi-decadal declines. Patterns in subbasin residuals are driven by irrigation practices and surface-water management; for example, the above Topaz subbasin relies more on groundwater for irrigation, resulting in more negative residuals during dry years. In contrast, the below Topaz subbasin depends more on surface water, producing positive residuals during dry years because of irrigation losses and canal seepage. The analyses for both subbasins indicate decades-long groundwater declines, which agree with the overall negative residuals calculated. The largest sources of uncertainty include climate inputs (precipitation and evapotranspiration) and poorly constrained components such as groundwater inflow and tributary stream infiltration. These findings provide insight into how climatic variables and irrigation practices affect groundwater inflows and outflows within the Portneuf River Basin.

Idaho↗

World minerals outlook—Antimony, copper, graphite, niobium, potash, silicon, silver, and tungsten through 2030

Demand for mineral commodities continues to increase owing to rapid technological advancements and global economic growth. To support this increase in demand, information about current and near-term supplies of these mineral commodities is essential. Such data help evaluate the health and stability of global supply chains and protect against potential supply risks. Current production and production capacity data coupled with information regarding near-term expected changes (such as facility closures, planned expansions, or the completion of new mineral production projects) can provide insight into expected future market developments and expected available supply of mineral commodities. This report within the “World Minerals Outlook” series analyzes data for antimony, copper, natural graphite, niobium, potash, silicon metal, silver, and tungsten—eight mineral commodities listed in the 2025 List of Critical Minerals. World production data from 2019 through 2025, as well as estimated world capacity data from 2023 through 2025 were analyzed. Using these data, near-term (2026–2030) expected world capacities were estimated. For antimony, copper, niobium, silicon metal, silver, and tungsten, modest increases in production capacity of 4 to 10 percent were expected between 2025 and 2030, whereas capacities for natural graphite and potash were expected to increase by about 18 to 20 percent.

Scientific Investigations Report↗