299 (2017) 54–75

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Geomorphology

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Legacy , lead, and zinc storage in channel and floodplain deposits of the Big River, Old Lead Belt District, , USA

Robert T. Pavlowsky a,⁎, Scott A. Lecce b,MarcR.Owenc, Derek J. Martin d a Department of Geography, Geology, and Planning, Missouri State University, Springfield, MO 65804, USA b Department of Geography, Planning and Environment, East Carolina University, NC 27858, USA c Ozarks Environmental and Water Resources Institute, Missouri State University, Springfield, MO 65804, USA d Department of Geography and Planning, Appalachian State University, Boone, NC 28608, USA article info abstract

Article history: The Old Lead Belt of southeastern Missouri was one of the leading producers of Pb ore for more than a century Received 4 March 2017 (1869–1972). Large quantities of contaminated mine waste have been, and continue to be, supplied to local Received in revised form 17 August 2017 streams. This study assessed the magnitude and spatial distribution of mining-contaminated legacy sediment Accepted 17 August 2017 stored in channel and floodplain deposits of the Big River in the Ozark Highlands of southeastern Missouri. Available online 27 September 2017 Although metal concentrations decline downstream from the mine sources, the channel and floodplain are contaminated above background levels with Pb and Zn along its entire 171-km length below Keywords: fl N −1 N −1 Legacy sediment the mine sources. Mean concentrations in oodplain cores 2000 mg kg for Pb and 1000 mg kg for Zn Mining contamination extend 40–50 km downstream from the mining area in association with the supply of fine particles Fluvial storage that were easily dispersed downstream in the . Mean concentrations in channel bed and bar Ozark Highlands sediments ranging from 1400 to 1700 mg kg−1 for Pb extend 30 km below the mines, while Zn concentrations of 1000–3000 mg kg−1 extend 20 km downstream. Coarse dolomite fragments in the 2–16 mm channel sediment fraction provide significant storage of Pb and Zn, representing 13–20% of the bulk sediment storage mass in the channel and can contain concentrations of N4000 mg kg−1 forPbandN1000 mg kg−1 for Zn. These coarse tailings have been transported a maximum distance of only about 30 km from the source over a period of 120 years for an average of about 250 m/y. About 37% of the Pb and 9% of the Zn that was originally released to the watershed in tailings wastes is still stored in the Big River. A total of ~157 million Mg of contaminated sediment is stored along the Big River, with 92% of it located in floodplain deposits that are typically contaminated to depths of 1.5–3.5 m. These contaminated sediments store a total of 188,549 Mg of Pb and 34,299 Mg of Zn, of which 98% of the Pb and 95% of the Zn are stored in floodplain deposits. Most of the metal mass in channel deposits is stored near the mines, with 72% of the Pb and 78% of the Zn occurring in the 25 km of channel proximal to the mine source. Although environmental assessments of streams contaminated by mines often focus on evaluating metal concentrations in the geochem- ically active fine sediment fractions, about 60% of the Pb stored in channels is associated with coarse dolomite tailings fragments deposited in channels within 25 km of the mines. The magnitude and basinwide distribution of Pb and Zn storage in legacy floodplain sediments ensures that remobilization by bank erosion will be a continuing problem for far into the future. © 2017 Elsevier B.V. All rights reserved.

1. Introduction and population (Kondolf, 1997; Wilkinson and McElroy, 2007; Hoffmann et al., 2010; UNESCO, 2011). Moreover, significant costs are In 1864, George Perkins Marsh explained how forest clearing and often attributed to human-induced soil erosion and resulting impacts soil erosion produced flooding, channel change, and on sedimentation in river channels and on floodplains, including along rivers and coasts in the Old World and North America, even quot- long-term sediment storage that can degrade watershed functions ing Pliny the Elder who reported similar observations in the first century (Walling, 1983, 1999; Slaymaker, 2003; de Vente et al., 2007). In A.D. (Lowenthal, 1965). Now widely acknowledged, human activities North America alone, physical, chemical, and biological damage from are responsible for modifying the geomorphic characteristics of river sediment problems may currently exceed $24 billion annually systems worldwide, often with negative consequences for the economy (Osterkamp et al., 1998; dollars adjusted for inflation). Legacy sediment is a recognized cause of geomorphic and water quality problems in ⁎ Corresponding author. watersheds; it is generated by widespread and/or intensive episodes E-mail address: [email protected] (R.T. Pavlowsky). of anthropogenic disturbances such as initial settlement and land

https://doi.org/10.1016/j.geomorph.2017.08.042 0169-555X/© 2017 Elsevier B.V. All rights reserved. R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 55 clearing, expansion of row crop and timber agriculture, grazing, and breaches (Mosby et al., 2009). A decade or two after cessation of mining (James, 2013). Legacy sediment commonly occurs in river activities, several studies confirmed the degree of metal contamination valleys as post-settlement on floodplains or colluvium along in channel sediments in the Big River near the mining sites in St. slope margins and contains some properties of human origin such as Francois County, Missouri (Schmitt and Finger, 1982; Davies and industrial and mining wastes or disturbed soil texture and mineralogy. Wixson, 1987; Smith and Schumacher, 1991, 1993) and the potential Although legacy was not yet used to describe historical alluvial influence on aquatic life (Gale et al., 2002, 2004). Designated as deposits, geomorphological studies of legacy sediments and related Superfund sites, the major tailings piles and slime ponds in the district watershed processes generally began in North America in the 1970s, were stabilized between 1994 and 2016 by U.S. Environmental Protec- most notably in the upper Midwest and southeastern Piedmont regions tion Agency-Region 7 (USEPA, 2017a)(Fig. 4). However, large volumes of the USA (Knox, 1972; Trimble, 1974, 1983; Magilligan, 1985; Jacobson of metal-contaminated sediment are still stored in bed and bar deposits and Coleman, 1986; Phillips, 1991; , 1994; Bettis and Mandel, within the main channel below mining sites (MDNR, 2001, 2003). These 2002; Wilkinson and McElroy, 2007; Walter and Merritts, 2008). mining sediments pose a long-term environmental risk the deposits are These works were based on earlier efforts to understand relationships available for reworking, downstream transport, and geochemical re- between soil erosion and stream channel and floodplain sedimentation lease of toxic metals to the river system (Alesandrini, 2014). Moreover, (e.g., Happ et al., 1940; Wolman, 1967). However, G.K. Gilbert's (1917) the contribution of contaminated legacy deposits on floodplains to total classic study of hydraulic in the Sierra Nevada of California contaminant storage along the Big River has not yet been evaluated. and its influence on excessive sediment loads in rivers downstream was Presently, major concerns persist over the longer-term effects of one of the first to quantify the fluvial response to episodic inputs of sediment contamination and excess mining sediment load on geomor- legacy sediment and to develop a watershed-scale sediment budget phic processes, ecological impacts (including freshwater fish and (James, 1989, 2010; James and Lecce, 2013). Gilbert's work showed endangered mussels), the community economy, and human health in that the production, transport, and storage of legacy sediment is a non- the Big River watershed (Murray, 1926; MDNR, 2007b; Roberts et al., equilibrium process, characterized by temporal lags and intermittent 2009; Hinck et al., 2012; Alesandrini, 2014). Understanding the movement of sediment through the system (James et al., 2017). geomorphic dimensions and contaminant distribution of metal storage Alluvial floodplains can function as important storage locations for in the Big River is paramount to addressing these problems. Previous legacy sediment and for associated metal contaminants in watersheds studies identified elevated Pb and Zn concentrations in present-day affected by mining (Davies and Lewin, 1974; Macklin, 1985; Knox, channel sediments of the Big River (Schmitt and Finger, 1982; Smith 1987; Bradley, 1989; Moore and Luoma, 1990). In some cases, the and Schumacher, 1991, 1993; Gale et al., 2002, 2004; Roberts et al., volume of mining sediment can overwhelm the river and exceed its 2009); however, the magnitude and spatial distribution of contaminated ability to transport the imposed load, causing manifest changes in sediment in active channel and floodplain deposits at the reach and channel morphology (James, 1989; Knighton, 1989). On the other segment scales have not been quantified. Besides the environmental hand, sediment discharges from mining sites may originate from a problems posed by historical mining (Mosby et al., 2009; Alesandrini, limited number of mine sources within a watershed and therefore 2014), an examination of the interconnections among the mining only interfere with geomorphic processes locally. Importantly, mining history, contaminated sediment patterns, and storage volumes of sediment inputs composed of mill tailings from mineral processing channel and legacy floodplain deposits offers the opportunity to better can contaminate channel and floodplain deposits with metals such as understand where and how sediment storages form and change over lead (Pb) and zinc (Zn) for distances of several hundred kilometers time (Ottesen et al., 1989; Graf, 1994, 1996; Walling et al., 2003; downstream and to concentrations exceeding 5000 mg kg−1 (Ritcey, Macklin et al., 2006). Further, more information is needed overall to 1989; Horowitz, 1991; Miller and Orbock Miller, 2007). During the understand how sediment contaminant budgets can be used to interpret period of mining, N40% of the tailings introduced into a river system fluvial processes and alluvial history in medium- to large-sized water- may become stored in floodplain deposits (Jeffery et al., 1988; Marron, sheds (Meade, 1982; Slaymaker, 2003; Hoffmann et al., 2010). 1989, 1992). However, after mine closure, subsequent remobilization The purpose of this paper, therefore, is to assess the magnitude and of stored mining sediment by bank erosion and weathering can spatial distribution of mining-contaminated sediment stored in the continue to contaminate the river for centuries (Ongley, 1987; main channel and adjacent floodplain of the Big River. In particular, Leenaers, 1989; Coulthard and Macklin, 2003; Lecce and Pavlowsky, we focus on quantifying downstream trends in reach-scale bed and 1997; Lecce et al., 2008). Indeed, Hudson-Edwards et al. (1999) showed bar storage, developing relationships for contaminated that floodplains contain a 2000-year record of mining contamination in channel deposits and floodplain soils, and comparing downstream northeast England. Consequently, geochemical profiles in mining- storage trends for coarse and fine sediment fractions. Previous efforts contaminated floodplains can be used as a stratigraphic tracer to more to understand contaminated sediment and metal storage in the water- precisely identify and date legacy deposits (Macklin, 1985; Knox, shed have informed the present study, but were unable to consider 1987; Lecce and Pavlowsky, 2001, 2014; Bain and Brush, 2005). As the spatial complexity of sediment storage in Big River. These studies with legacy sediment in general, mining sediment and contaminant focused on understanding channel sediment-metal variability within a storage in watersheds is inherently controlled in large part by single reach (MDNR, 2001, 2003), tailings pile volume and composition geomorphic and factors (Bradley and Cox, 1990; (Newfields, 2006), localized channel storage volume at sites immedi- Graf et al., 1991; Graf, 1994, 1996; Ciszewski and Matys Grygar, 2016). ately below mine input points (Newfields, 2007), and patterns of The Big River (2500 km2) drains the Old Lead Belt mining district channel bar storage (MDNR, 2007a; Wang et al., 2016). This (OLB), which covers 280 km2 of St. Francois County in southeastern study applies a geomorphological sediment/metal budget approach Missouri with its center about 100 km south of St. Louis (Figs. 1 and (e.g., Macklin et al., 2006; Dennis et al., 2009) to quantify and interpret 2). The OLB was a leading producer of Pb worldwide from 1869 to present-day channel and floodplain storage trends of metal contami- 1972, ranking first in USA production for all years except one since nants and their relationship to historical mining and legacy sedimenta- 1908 (Buckley, 1909; Minerals Yearbook, 1972). During this century- tion along 171 km of Big River from Leadwood to its confluence with the long period of intensive mining, large volumes of tailings containing near Eureka, Missouri. high concentrations of Pb and other metals such as Zn, copper (Cu), and cadmium (Cd) were released into nearby streams, including the 2. Study area Big River (Fig. 3). Even after the last mine closed in 1972, tailings mate- rials stored in six large abandoned piles, each covering N1km2, were Big River drains the Ozark Highlands (level III) ecoregion in Missouri still entering waterways through erosion, slope failures, and including portions of St. Francois Knobs and Basins, Meramec River Hills, 56 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

Fig. 1. Big River watershed, Missouri. and Eastern Ozark Border (level IV) subregions (USEPA, 2017b). The sulfide minerals (Smith and Schumacher, 1993). Mineralization headwaters of the river originate at 485 m amsl on metaigneous rocks typically occurs in the Bonne Terre Dolomite of Cambrian age at a of the St. Francois Mountains and the watershed drains a well- depth of 60–300 m but outcrops at the surface in places in the southern dissected landscape with narrow divides and a basin relief of 300 m. and eastern portions of the basin. Large ore bodies were typically over Most of the area of the Big River, including the OLB, is 240 m wide, 360 m long, and 60 m in thickness with some worked underlain by horizontally bedded dolomite with some limestone, continuously for several kilometers (Jackson et al., 1935). shale, and units (Meneau, 1997). The major ore mineral in Pleistocene glaciers did not reach the Big River watershed, but ice the OLB is galena (Pb-sulfide) with a secondary abundance of sphalerite margins were close, being located about 20 km to the north of the (Zn-sulfide), some smithsonite (Zn carbonate), and other less valuable mouth (R-km 0) along the Missouri River and 20 km to the east of the R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 57

main along the (Rovey and Balco, 2011). Upland soils are typically formed in a thin layer of silty Pleistocene loess overlying cherty or noncherty residuum formed in dolomite, limestone, and shale (Brown, 1981; Skaer, 2000; Skaer and Cook, 2005). The climate is moist continental with an average annual temperature of about 13 °C ranging from an average of 0 °C in January to 25 °C in July. The mean annual rainfall is about 102 cm with the wettest period in the spring months (Brown, 1981). The U.S. Geological Survey discharge gaging station (Big River at Byrnesville, MO, #07018500) has a drainage area of 2375 km2 with a mean flow of 25 m3/s since 1921. The flood peak of record occurred on 25 September 1993 at a stage of 9 m and discharge of 180 m3/s. Land use in 2006 in the Big River watershed was 72% forest, 18% grassland, 1% rowcrops, and 7% urban/developed; and population in the 2010 census was 98,252 persons (MDNR, 2013).

2.1. Mining history

Southeastern Missouri has a long mining history beginning in 1720 by French explorers at Mine-La-Mott near Fredricktown located about 40 km southeast of the OLB (Seeger, 2008). Lead was probably first mined in the Big River watershed between 1742 and 1762 near Potosi where relatively large galena crystals were extracted by hand from shallow pits or diggings (Buckley, 1909). The U.S. Bureau of Mine records indicate that these crude mining practices continued sporadi- cally until the 1940s, contributing b2% of the total Pb produced by the OLB (Buckley, 1909). The first organized mining operations in the OLB began about 1864 in Bonne Terre; and large-scale, deep shaft mining began as mining spread to the nearby towns of Leadwood, Desloge, and Flat River in the 1890s. Annual metallic Pb production rose rapidly after 1907 with years of peak production in 1917, 1925, and 1942 and decreased production in the early 1930s during the Great Depression. When the last mine closed in 1972, it was reported that about 9 million Mg of Pb and 1.8 million Mg of Zn metal had been produced

Fig. 2. Big River channel in the mining area. A at R-km 156.1 and B at R-km 147. in the Old Lead Belt (Mineral Yearbook, 1972).

Fig. 3. National Chat Pile in 1953 in the town of Flat River, now called Park Hills, Missouri. Photo credit: U.S. Department of the Interior's Natural Resource Damage Assessment and Restoration Program. https://www.cerc.usgs.gov/orda_docs/CaseDetails?ID=1060. 58 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

Fig. 4. Desloge Tailings Pile in 2010 after remediation by capping and terracing. Note main channel of Big River on the left flowing into the picture.

2.2. Mining sediment and metal inputs Coarse chat tailings with 75% in the 4–8 mm size fraction were generated by dry and wet jigging using sieve boxes and sluices until As compiled from Bureau of Mining annual reports of Mineral around 1930 when better table and flotation methods were introduced Resources of the U.S. and the Mineral Yearbook, mining discharged (Wright, 1918; Jackson, 1929; Newfields, 2006)(Fig. 5). While stored in about 264 million Mg of mine tailings wastes to nearby streams, flat large chat dumps or piles around the district (USFWS and MDNR, 2007), land areas, or constructed ponds from 1866 to 1972 in the Big River chat tailings are easily identifiable in the Big River today as dark gray watershed (Jackson et al., 1935). Up to six major mining sites operated dolomite fragments in the fine gravel fraction of bed and bar deposits in the OLB for periods ranging from 33 to 84 years with a combined mill below mining areas (Fig. 6). Chat tailings typically contained 3000– capacity of 24,000 Mg of ore per day at the peak in 1933. Presently, 5000 mg kg−1 Pb (Jackson et al., 1935). abandoned tailings piles cover over 11 km2 and about 57 million Mg Gravity concentration using wet shaking table methods created of tailings (22%) still remain within tailings confinement areas today tailings with N75% in the fine to medium sand range (0.125 to 0.5 mm). (Newfields, 2006; USFWS and MDNR, 2007). The missing tailings Vibrating shaking tables used hydraulic force to separate the ore parti- were removed by rail for ballast or fertilizer, used locally for fill, cles into concentrate for the smelter, middlings for reprocessing, and or dispersed to nearby lands or waterways (Wright, 1918; Wixson tailings for the dump pile or further grinding for flotation treatment et al., 1983; Mosby et al., 2009). Tailings contain high concentrations based on density differences (Taggart, 1945). Gray and tan sand grains of residual Pb and Zn because metal recovery was not 100%, ranging from mining sources are still relatively abundant in channel deposits from b80 to 95% in the OLB (Taggart, 1945; Wixson et al., 1983). Overall, today. Because of more efficient treatment of the finer feed, tailings Pb content in the tailings piles ranged from 884 mg kg−1 at the Federal from shaking tables typically contained b1200 mg kg−1 Pb (Coghill Mine to 4440 mg kg−1 at Elvins/River mines. In contrast to Pb, Zn and O'Meara, 1932). concentrations in tailings reflected the localized enrichment of Zn in Flotation circuits produced very fine tailings, sometimes referred to some ore bodies and not others. Tailings piles averaged ~5000 mg kg−1 as slimes, with 66% in the and size range (b0.074 mm). Froth Zn at the Leadwood and Elvins/River mines, 1200 mg kg−1 Zn at Desloge, flotation was introduced in 1914 to improve Pb extraction from the and 300–500 mg kg−1 Zn at the Federal, National, and Bonne Terre mines finely-disseminated ores common to the OLB. Using chemical reagents (Newfields, 2006; USFWS and MDNR, 2007)(Fig. 1). to bind air bubbles to sulfide mineral surfaces, rich ore particles were floated to the top of the tank and skimmed off as valuable concentrate (Jackson et al., 1935). Flotation tailings were usually mixed and slurried 2.3. Texture of the mining sediment with gravity mill wastes and then discharged to large tailings or slime ponds near the mill. In general, ultrafine particles such as slimes The grain size characteristics of tailings materials influence the were difficult to manage in concentration mill circuits (i.e., Taggart, ability of fluvial processes to transport contaminated sediment down- 1945; Somasundaran, 1986)withpossibly1–6% of the total tailings stream, with finer particles being transported downstream or on flood- mass being discharged as slimes to tailings ponds or local streams in plains at higher rates compared to coarser particles (Ritcey, 1989). In overflow and other mill effluents (Buckley, 1909; Wright, 1918; the OLB, crude ore was crushed and ground to specificsizestoimprove Jackson et al., 1935). Metal values in overflow slime particles could the recovery of galena by gravity concentration owing to higher particle not be recovered and so they contained high Pb concentrations density and froth flotation using chemical treatments to float and reflecting the grade of untreated ore. Ore grade in the Big River water- concentrate sulfide particles. Mill wastes in the OLB can be generally shed averaged 27,000 mg kg−1 Pb between 1894 and 1972 and up to − classified into three different types: coarse chat, fine tailings, and slimes 60,000 mg kg 1 Pb before rich ore bodies were depleted prior to 1930 (Jackson, 1929; Coghill and O'Meara, 1932; Jackson et al., 1935). (Jackson et al., 1935). R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 59

Fig. 5. Tailings at the National Pile in 2008. Note angular fine gravel-sized chat (2–16 mm) with finer matrix.

2.4. Geomorphic significance 2007). However, floodplain deposits have the potential to store larger volumes of contaminated sediment compared to channel deposits in While the majority of the tailings piles in the subdistrict have the Big River. For example, the floodplain area available for sediment had some level of stabilization that has reduced or contained erosion, deposition along the Big River is about six times greater than for questions still remain about the fate of the materials presently in transit the river channel. Moreover, compared to higher energy channel bed in the channel system or temporarily stored in floodplain deposits. A conditions, overbank floodplain deposits have the potential to store preliminary assessment of the storage of mining chat and tailings more fine-grained sediment including sand- and slime-sized tailings estimated that 1,600,000 Mg was stored in channel deposits of the Big that typically have higher metal concentrations (Bradley, 1989; River below the mines and 19,000 Mg in Flat River Creek (Newfields, Bradley and Cox, 1990).

Fig. 6. Channel Bar with blue gray dolomite “chat” fragments at R-km 140.6. Chat sediment particles are more sub-angular and rounded compared to those in the tailings pile and represent from 15 to 25% of the bulk channel sediment at this location. 60 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

Besides the greater capacity for fine sediment storage in floodplains, 10 channel cross sections spaced at intervals of one channel width the supply of sediment available for storage in legacy floodplain were used to measure channel capacity and to quantify channel bar deposits may have been enhanced by land use changes in the and bed deposits. The center of each sample reach was located within watershed. Agricultural settlement and timber harvesting resulted in a glide channel unit just above a riffle crest except at three sites where widespread hydrological changes in the Ozark Highlands between low water bridges or affected the character of the river. We 1880 and 1930 (Jacobson and Primm, 1994). Indeed, land use factors surveyed the longitudinal profile along the channel thalweg of each resulted in increased runoff, soil erosion, and channel incision in reach to determine the location of pools, riffles, and glides (Panfil and headwater catchments, increases in flood frequency, and deposition of Jacobson, 2001). Surveys were conducted with an electronic total sand and gravel bars in main channels (Jacobson, 1995; Martin and station or auto level and georeferenced with at least two submeter Pavlowsky, 2011). Coincidentally, these activities overlapped with a resolution global positioning system (GPS) points. period of productive mining in the OLB when relatively crude and We estimated the total thickness of sand and fine gravel sediment inefficient milling and tailings disposal practices were in use (Jackson, stored in the channel using the maximum refusal depth with a tile 1929; Coghill and O'Meara, 1932; Jackson et al., 1935). Even during probe at 5–10 locations across each active channel cross section (similar low flow conditions, streams and downstream river channels to Newfields, 2007). This is a quick but reliable method because the tile were filled with gray suspended sediment (slimes) released from probe can easily penetrate the sand and fine gravel deposits formed by mining operations (Buckley, 1909). Therefore, the excess supply of the mixture of mine tailings and mobile natural bed materials but contaminated fine sediment in Big River suggests that floodplain cannot penetrate the coarse bed substrates, now buried, that formed storage rates of historical mining sediment would be relatively high. the channel boundary prior to historical disturbances (Jacobson and Indeed, increased rates of overbank sedimentation on river floodplains Primm, 1994). As discussed later, given the high number of probe points during the early twentieth century have been reported in other Ozarks collected and typically shallow depths to bedrock in Ozark rivers, we watersheds (Owen et al., 2011). believe that probe depth measurements are relatively accurate indica- tors of stored historical and recent sediment in channel bar and bed 3. Methods deposits in the Big River (Newfields, 2007).

Study site locations are described along the main stem of the Big 3.1.2. Channel sediment sampling River using the river-kilometer (R-km) where R-km 0 is located at the Channel sediments were sampled at sites located along the main mouth of the Big River at the confluence with the Meramec River and stem from above the most upstream mine at Leadwood (R-km 171) to R-km 171 is at the most upstream limit of mining inputs at the conflu- the mouth of the Big River (R-km 0) near bridge crossings, public access ence of Eaton Branch (which drained the Leadwood Mine) (Fig. 1). To areas, or by boat at intervals of b1 to 20 km. Most sites were sampled in evaluate downstream trends in channel geomorphology and storage, 2009 (24), but additional sites were collected in 2010 (3) and 2011 (1). channel characteristics were characterized for 10 different valley Two control sites located above mining influence were included at R-km segments delimited based on the locations of mine sources and 192 and 181. A total of 216 channel bed and bar samples were collected tributary confluence points (Table 1). Segment lengths average for geochemical analysis at 28 sampling sites. Channel bar and bed 17.1 km and range from 12 to 26.5 km (270–490 channel widths). deposits were sampled separately to evaluate sediment texture and geochemistry. Where exposed above the water line during low flow 3.1. Field data collection conditions, bars were sampled from shallow pits by shovel at a depth of approximately three times the maximum clast size observed on the 3.1.1. Geomorphic assessment of channel storage bar surface to exclude the influence of surface armoring on sediment A storage volume assessment including geomorphic analyses and measurements (Bunte and Abt, 2001)(Fig. 7). Typically, three samples sediment characterization was completed at 10 sampling reaches were collected from a given bar deposit at a depth of 10–20 cm along along the main stem of the Big River. The sampling reaches typically the centerline of each bar at the head, middle, and tail locations. range in length from 10 to 12 channel widths and are different than Samples were collected by hand or plastic trowel from heaped material the much longer valley segments described in the previous section. To- contained on the shovel blade which was never in contact with metal. pographic channel surveys were used to determine channel dimen- Where possible, at least two different bar features were sampled within sions, the height of banks or floodplain surfaces, and minimum/ each reach. Beds were usually sampled in about 0.5 m of water at glide maximum depths of potential mining sediment. Along each reach, 9 or units where flow shallows and spreads out at the tail end of a pool prior

Table 1 Channel width and bar areas by river segment.

Segment Tributarya R-kmb Drainage Length Avg. active Avg. bed Bar width Segment % number area (km2)c (km) width (m) width (m) (m) % total Channel length Channel length lacking bars % with N50% barsd

1 Eaton Branch at Leadwood 171 12 16 43.1 29.9 13.2 31 16 2 Flat River Creek 155 137 10.5 35.7 27.5 8.2 23 3 Terre Bleau Creek 144.5 173 12 44.0 29.6 14.3 33 8 4 Cabanne Course Creek 132.5 20 17 43.2 34.7 8.5 20 3 5 Mill Creek 115.5 134 16.5 42.5 34.8 7.7 18 12 6 Mineral Fork 99 490 26.5 54.7 39.4 15.3 28 2 6 7 Ditch Creek 72.5 35 20.5 59.1 40.4 18.7 32 2 15 8 Dry Creek 52 140 17 53.6 44.8 8.8 16 21 6 9 Belews Creek 35 190 18 49.9 45.3 4.6 9 31 10 Heads Creek 17 135 17 46.5 40.6 5.9 13 26 6

a Tributary input at upstream boundary of river segment. b Upstream boundary of river segment. c Big River drainage area is 626 km2 at R-km 171.25 and 2500 km2 at mouth. d Percentage of the segment length where bars cover N50% of the channel area. R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 61

Fig. 7. Channel deposits sampled for this study. A-Glide entering riffle at R-km 156.9. B-Large alternate bar at R-km 156.4. to crossing a riffle crest or from a relatively featureless plane bed sampling, typically 3–6 depth-integrated samples were collected indicative of local aggradation (Panfil and Jacobson, 2001). Glide down each cutbank at intervals based on observed stratigraphic units deposits were collected by pushing a small plastic bucket into the bed and apparent mining influence. Giddings cores were collected along (after removing any armor layer) to obtain a subaqueous core of bed several cross-valley transects to check for vertical and lateral variations sediment to a depth of 15–20 cm (Fig. 7). The sample was dewatered in contaminated depth of the floodplain deposit to background thresh- by decantation before storing in a plastic bag. Up to three samples old concentrations. Typically 8–13 depth increments were sampled were collected at even spacing across each glide unit perpendicular to from each core. For bank and core sampling, samples were collected flow and up to three glides were tested at each sampling site. with a trowel, bagged, and treated similarly as the channel samples. At most sites at least two different floodplain units were sampled, 3.1.3. sediment sampling including one from the recent bankfull floodplain surface and the We sampled geochemical profiles at 68 different points on flood- other from a younger bench feature typically 0.5–1 m lower and plains along the Big River, including 35 cut-bank exposures by hand b10 m wide as determined in the field or located on soil maps and 33 coring sites using a truck-mounted Giddings rig. A total of 502 (Brown, 1981; Royall et al., 2010). In some reaches, multiple bench, individual samples were collected for Pb and Zn analysis. For bank floodplain, and terrace surfaces were sampled. 62 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

3.2. Laboratory methods and standard hot acid extraction methods (USEPA, 1998). Selected samples were split sampled in the laboratory and sent to a commercial All laboratory work was carried out by Ozarks Environmental laboratory for metal extraction using hot nitric and hydrochloric acids and Water Resources Institute (OEWRI) staff at Missouri State (i.e., aqua regia) and analysis by inductively coupled plasma atomic University. Standard operating procedures can be found at http:// emission spectroscopy (ICP-AES). The ratio of aqua regia over XRF oewri.missouristate.edu/. concentrations was used to convert sediment XRF results to equivalent aqua regia concentrations. Thirteen channel bar samples from the Big 3.2.1. Sample preparation and textural analysis River in St. Francois County yielded median aqua regia:XRF values and All channel and floodplain sediment samples were hand sieved to average quartile ranges as follows: Pb, 1.09 ± 37% and Zn, 1.27 ± 25%. determine the particle size distribution and to isolate size fractions for Fifteen floodplain soil samples from the Big River in St. Francois County further analysis. Samples were dried in an oven at 60 °C, disaggregated yielded median aqua regia:XRF values and quartile ranges as follows: with mortar and pestle, and passed through a sieve set to separate the Pb, 0.82 ± 5% and Zn, 0.88 ± 4%. The XRF concentrations were multi- b2mmandfine gravel fractions for further analysis of the b64 mm plied by the representative median ratio values to determine corrected bulk sediment fraction. Larger clasts (N64 mm) were excluded from aqua regia values that were used to calculate storage budgets. Using the analysis because they were too large for the sampling procedures ratio approach, metal concentrations are adjusted uniformly but being used, rarely originate from mining sources (Jackson et al., 1935; maintain the original site and sample variability as measured by XRF. Taggart, 1945), add increased variability to finer sediment distributions This correction is also relevant for environmental risk assessment as (Bunte and Abt, 2001), and represent a relatively small fraction of the Pb concentrations determined by aqua regia extraction from road bed, bar, and bank deposits of the Big River (b10% in channel bed pebble dusts and soils in mining areas in southeastern Missouri near the pres- counts). Particle size distributions were determined by mass using sieve ent study area were significantly correlated with geochemical mobility sizes according to the following rationale (Taggart, 1945; Rosgen, and digestive uptake by humans (Witt et al., 2014). 1996): (i) N64 mm, initial screening out of any cobble-sized material, if present; (ii) 16 mm, coarse gravel, maximum diameter of mining 3.2.4. Bulk and particle density chat; (iii) 8 mm, medium gravel, coarse tail of chat; (iv) 4 mm, fine The bulk density values for channel and floodplain deposits were gravel, modal size of chat; and (v) 2 mm, very fine gravel, fine tail of needed to convert sediment volume measurements to mass units for chat to 1 mm; and (vi) b2 mm, fine fraction that contained wet table sediment and metal storage calculations (Dennis et al., 2009). Bulk and flotation tailings including slimes as well as natural silt and clay density values for sand and fine gravel deposits and porous particles and organic matter. typically range from 1.9 to 2.2 Mg/m3 (Manger, 1963). Therefore, after also reviewing several tables used by geotechnical engineers and 3.2.2. Grain counts of dolomite fragments excavation contractors, a value of 1.92 Mg/m3 was selected to estimate In the summers of 2013 and 2014, 122 bar samples were collected bulk density of the b2 mm sediment fraction in channel deposits. A for dolomite fragment analysis at 300–500 m intervals from R-km 170 value of 2.2 Mg/m3 was selected to apply to the 2–64 mm mixed gravel to 115. Field observations and laboratory tests indicated that dark gray fraction (Bunte and Abt, 2001). The particle density of pure dolomite angular dolomite fragments from the Bonne Terre Formation typically averages 2.84 Mg/m3 and several samples of the Bonne Terre dolomite comprise almost 100% of the very fine to medium gravel-sized chat averaged 2.66 Mg/m3 (Manger, 1963). Soils formed in fine-grained fraction in tailings piles. This mineral type and shape were produced overbank floodplain deposits along the Big River typically have bulk only by mining operations and are not found in sediment loads from density values of 1.5 Mg/m3 (Brown, 1981). unmined areas. Bar deposits were sampled exclusively to quantify the distribution of stored dolomite fragments. While bed deposits are 3.3. Channel and floodplain feature classification usually coarser than bar deposits, the grain count percentages of dolomite fragments within the 2–16 mm fraction are similar between Geospatial data for the Big River were acquired from ArcGIS®, deposits at a given location. Visual grain counts were used to quantify collected in the field with survey equipment, and georeferenced or the direct mining origin of mining chat in the N2tob16 mm fine gravel downloaded from the Missouri Spatial Data Information Service fraction. Results were tabulated as the percentage of dolomite grains of (MSDIS). Channel bar and bed features were manually digitized based the total number of grains counted (50–150), not including coal or slag on the interpretation of 2013 aerial photographs with submeter resolu- particles that usually composed b20% of the total sample near mining tion (Fig. 8). Active channel width was measured between opposite sites. To reduce size sorting errors during grain counts, heterogeneous lower bank lines identified by the water surface contact or bar margin samples were sieved into 2–4, 4–8, and 8–16 mm fractions; grain counted including the wetted channel bed and, when present, all subaerial bar separately; and then composited to report results by % mass in the 2– deposits. To the extent possible, active (unvegetated) or vegetated bar 16 mm fraction. features were delineated along the low-flow waterline and bank margin. Channel dimensions were averaged within 500-m-long poly- 3.2.3. Geochemical analysis gons or cells along the river-kilometer centerline. X-ray fluorescence (XRF) analysis was used to analyze the geochem- The SSURGO database provided by the Natural Resources Conserva- istry of channel and floodplain sediments (USEPA, 1998). An Oxford tion Service was used to delineate floodplain areas along the valley floor Instruments Portable X-MET 3000 TXS+ was used to determine the of the Big River. Digital copies of the soil surveys were published in 2006 concentrations of Pb and Zn in tailings, sediment/soil, and background representing soil field work completed during the calendar years as sources in the b2 mm sediment fraction. Standard checks and duplicate follows: Jefferson County, 2000; St. Francois County, 1974–1976; and analyses were routinely used every 10–20 samples. All analyses passed Washington County, 2002. Only those floodplain features assumed to quality control requirements at the OEWRI laboratory. Error summaries have formed or received sediment since the beginning of the mining from 22 batches of duplicate channel sediment samples from the Big period to present were included in this analysis. Therefore, only soil River are as follows: Pb accuracy errors typically ranged from −6to1 series classified as flooding once or more every two years relative percent difference (RD%) and precision errors from −3to2 (i.e., frequent flooding) were used to determine overbank floodplain RD%; and Zn accuracy errors typically ranged from −6to−1 RD% and areas. To verify floodplain areas, SSURGO layers were compared precision errors from −3 to 4 RD%. to digital elevation models (DEMs) and aerial photographs. We The laboratory and field results of the portable XRF analyses were also used the elevation and apparent age of floodplain features during converted to equivalent geochemistry results based on more traditional our field studies to verify geomorphic relationships of the mapped R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 63

Fig. 8. Aerial (2013) view of Big River with channel features and floodplain delineated.

soil units. The four soil series used to delineate floodplain area and 4. Results width for the Big River were: (i) Sturkie series on low terraces; (ii) Haymond series on well-drained floodplains; (iii) Wilbur series in 4.1. Channel storage low-lying floodplain areas such as a back-swamp or swale; and (iv) Kaintuck series on recent or incipient floodplain deposits, or bench 4.1.1. Channel bed and bar volumes features (Brown, 1981). Digitized channel bed and bar areas from 2013 aerial photographs were used to determine average channel, bed, and bar widths for 342 channel cells (each 0.5 km long) (Fig. 9). The active channel width of 3.4. Storage budget calculations the Big River averages 48.5 m with a coefficient of variation (Cv%) of 25% from R-km 171 to the mouth. Channel width increases greatly to Sediment and metal storage budgets were calculated from field and its widest below the confluence of Mineral Fork in segments 6, 7, and laboratory measurements including: (i) channel and floodplain area 8 from R-km 99 to 35, where width is N61 m (+1 s limit) over 25% of and depth of the deposit; (ii) bulk density of the deposit to convert its channel length. On average, bar deposits cover 20.3% of the active volume to mass; and (iii) mean metal concentrations within the deposit channel area in the Big River (Table 1). Bar area tends to decrease down- to determine mining-metal mass storage (Dennis et al., 2009; Lecce and stream. Upstream in the mining area, bars cover 23–33% of the channel Pavlowsky, 2014). In addition to the above, the textural composition of area in segments 1–3 with all cells containing bars and up to 16% of the the deposit is often applied in calculations because specific size fractions segment length with N50% bar area. However, in segments 8–10 along may disproportionately contain either more or less of the contaminant the lower 52 km of the river, bar features only cover 9–16% of the or be distributed differently among different deposits (Graf, 1994). To channel area, about a quarter of the channel length contains no bars, remove the influence of naturally occurring metals on the contamina- and only 0–6% of the segment length contains N50% bar area (Table 1). tion budget, the mining metal concentration was used in contaminated The depth of stored sediment in bed and bar deposits was deter- metal storage calculations and was determined as the total metal mined using high resolution field surveys of channel morphology and concentration minus the expected background or premining concentra- probe depth measurements completed at the 10 storage assessment tion. For channel sediment, only the b2 mm sediment fraction reaches (Table 2). Storage depth includes the entire thickness of and 2–16 mm dolomitic chat fragment fraction contributed to contam- material above the probe refusal elevation and is assumed to be con- ination, while the rest of the 2–64 mm fraction was considered to taminated throughout. Probe depths in bed and bar deposits ranged add no mining metal mass to the sediment. For floodplain sediment, from 0 to N2 m within a reach, with the single highest probe depth only the b2 mm sediment fraction contributes to contamination (3.5 m) measured in bed deposits behind the dam at storage site 9. because the content of dolomite fragments in overbank deposits is This range of probe depths within a reach is expected as multiple negligible. (N30) bar and channel depths were collected and a variety of fluvial 64 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

Fig. 9. Downstream variations in channel width and bar width. Segments are indicated by the numbers at the top of the plot. Solid black lines are 5-point moving averages. Note that the downstream direction is from right to left on all “distance upstream” graphs. forms and bar types were usually sampled within a sample reach River (Smith, 2013)confirmed our results using probe depth measure- (Table 2). However, mean depth errors at sites were relatively low, ments. The USGS sampled five sites with two to three cores each to and no significant downstream trend was observed among sites determine overall bar thickness and depth of Pb contamination in the (Table 2; Fig. 10). Therefore, single values for average bed depth and b2 mm size fraction. Contaminated sediment depths of 2–3mmea- bar depth were used for storage calculations at all 500-m channel cell sured in the freeze cores fall within the range of the deeper probe areas below Leadwood. Average bed sediment depth was 0.66 m with depths measured for this study (1.2–3.2 m). Further, USGS bar depths a Cv% of 24.5%. Average bar depth was 1.05 m with a Cv% of 13.8%. are similar at all five sites and do not appear to change systematically Sites 9 and 10 were omitted from the analysis for the following reasons. downstream as found in the present study (Smith, 2013). In addition Storage site 9 was located behind an old, but intact, run-of-river mill to verifying contamination depth assumptions used in the present dam. Therefore, compared to the majority of river length, this reach study, the results of the USGS study also confirmed that metal concen- was not representative as bed sediment storage was enhanced (1.2 m trations measured in shallow bar grab samples (20–30 cm) were deep) with no subaerial bar deposits (i.e., zero bar depth) because of representative of the entire thickness of the deposit. high backwater. Storage site 10 was located within a relatively steep bedrock reach where average depth to bedrock refusal was very shallow 4.1.2. Sediment size trends (0.14 m) and bar storage depths were similarly low (0.72 m). Field Downstream variations in sediment size within bed and bar deposits observations suggest that bedrock reach control like that found at site need to be accounted for to apportion mining-metal concentrations in 10 is very rare, and where it is found, its distribution is patchy. the b2mmand2–16 mm size fractions for storage calculations. In this The USGS data using freeze core technology to measure bar study, bulk sediment b64 mm represents the total or 100% of the sediment thickness and contamination profiles in bar deposits in Big sediment mass evaluated for three size fractions: b2, 2–16, and 16–

Table 2 Depth of bed and bar deposits.

Site R-km Drainage Bankfull Reach Storage probe Bar Bed number area (km2) width (m) length (m) points Mean depth Max. depth Mean depth Max. depth (m) (m) (m) (m)

1 170.7 638 49.7 515 63 1.04 2.1 0.43 1.6 2 156.4 378 49.4 484 54 1.28 2.2 0.89 2 3 136.7 1021 41.4 395 62 0.98 2 0.64 1.8 4 115.5 1282 53.9 516 54 1.12 3.2 0.61 1.2 5 97 1861 60.6 520 64 1.13 2.3 0.85 2.1 6 79.3 1959 51.2 428 57 0.8 1.8 0.47 2.1 7 49.6 2164 58.4 534 53 1.13 2.8 0.73 3 8 32.5 2296 58.6 512 33 0.95 1.2 0.7 2.7 9a 17.4 2386 61.9 660 31 0 0 1.2 3.5 10 2 2499 56.2 771 40 0.72 1.9 0.14 0.8

1–8 only Mean: 53 488 55 1.05 2.2 0.67 2.1 Median: 53 514 56 1.08 2.2 0.67 2.1 Min: 41 395 33 0.80 1.2 0.43 1.2 Max: 61 534 64 1.28 3.2 0.89 3.0 SD: 6.3 50.0 9.9 0.15 0.6 0.16 0.6 Cv%: 12 10 18 14 28 25 28

a Not included in depth analysis. R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 65

1.4 fraction is highest in segments 4 and 5 (54–55%) and segment 10 1.2 (66%) (Table 3). In general, the coarse and very coarse gravel fraction (16–64 mm) composes from 14 to 29% of bed sediment and 1 to 20% 1.0 of bar sediment (Fig. 11). Increased sand supply from tailings inputs and from erosion of sandstone bedrock is responsible for increases in 0.8 the b2 mm size fraction in bar deposits between R-km 155 and 99 0.6 (Fig. 11). However, erosion of friable sandstone outcrops is the main source for the increase in the b2 mm size fraction to N80% below Bar

Storage depth (m) 0.4 Bed R-km 25 in bar deposits (Fig. 11). The textural composition of bar fi 0.2 Avg Bar deposits tends to ne downstream in comparison to nearby bed Avg Bed deposits (Table 3). The bar/bed ratio for the percent b2 mm is relatively 0.0 low at 1.2 in segment 1, rises to 1.7 in segments 4 and 5, drops down to 0 20 40 60 80 100 120 140 160 180 1.4 in segment 7, and then rises to 2.6 at segment 10. Distance upstream (river kilometer) 4.1.3. Metal concentration trends Fig. 10. Downstream trends in sediment depth for bed and bar deposits. Values from sites at R-km 17.4 and 2 were omitted in calculating the averages. An estimate of the premining Pb and Zn concentrations in channel sediments is needed to determine the mining contribution to storage. Background metal concentrations in channel sediment not affected by 64 mm. Polynomial equations (third-fifth order) were used to create mining inputs can vary with soil texture, mineralogy, and bedrock downstream trends to predict size distributions for the b2andb16 mm type in the watershed, as well as local factors such as spring seepage fractions (Fig. 11). For the entire river below R-km 171, the mean and and proximity to mineralized outcrops. A sample of 11 channel samples Cv% values for predicted percent b2 mm fraction are 28.7% ± 11% for collected in 2011 from above Leadwood was used to approximate bed deposits and 47.2% ± 20% for bar deposits. For bed deposits, the background levels for Pb and Zn in the Big River. The mean background percentage of the b2 mm sediment fraction is highest upstream in and upper 95% confidence limit (+2 s) threshold concentrations were segments 3 and 4 (33%) and lowest downstream in segments 8, 9, and 20 and 34 mg kg−1 for Pb and 39 and 71 mg kg−1 for Zn respectively. 10 (24–25%) (Table 3). For bar deposits, the percentage of the b2mm The +2 s upper threshold value was subtracted from the total metal

1097654321 8 100 90 a Bed Sediment 80 70 60 <16 mm 50 <2 mm 40 Series3 30 20 Size distribution (% mass) 10 0 0 20 40 60 80 100 120 140 160 180 200 Distance upstream (river kilometer)

1097654321 8 100 90 80 70 <16 mm 60 <2 mm 50 40 Series3 30 20 Size distribution (% mass) 10 b Bar Sediment 0 0 20 40 60 80 100 120 140 160 180 200 Distance upstream (river kilometer)

Fig. 11. Downstream trends in sediment size for (a) bed sediment and (b) bar sediment. 66 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

Table 3 Contaminated sediment storage in channel sediment (b64 mm bulk fraction).

Segment number R-km Bulk volume b2 mm Bulk mass

(m3) Bar (%) Bed (%) Bar (%) Mg Segment (%) b2 mm (%) Dolomite (%) Other (%)

1 171 540,831 41.8 30.1 35.5 1,136,508 8.7 32.2 13.3 54.6 2 155 283,019 32.6 32.0 44.7 591,741 4.5 35.8 19.9 44.3 3 144.5 425,152 43.8 32.8 50.7 884,488 6.7 39.4 15.8 44.7 4 132.5 544,387 27.9 32.8 54.8 1,133,892 8.7 38.6 2.0 59.4 5 115.5 516,187 26.1 31.9 54.4 1,077,463 8.2 37.0 0 63.0 6 99 1,121,969 38.1 29.6 47.4 2,345,916 17.9 35.8 0 64.2 7 72.5 953,997 42.3 26.9 38.6 2,007,958 15.3 31.0 0 69.0 8 52 664,555 23.8 25.1 36.8 1,405,862 10.7 27.4 0 72.6 9 35 629,150 13.9 24.3 44.9 1,332,430 10.2 26.6 0 73.4 10 17 564,790 18.7 24.8 65.8 1,189,127 9.1 30.8 0 69.2 Avg. or total: 6,244,036 31.6a 29.0a 47.0a 13,105,385 100 33.0a 3.3a 63.7a

a Segments are not the same length, so the average of the ten rows does not equal the total average. concentration for all channel samples to determine the mining metal concentrations were about half of those measured in tailings generated concentration. There have been concerns about the toxic risk posed by at nearby mines, which averaged 2382 mg kg−1 at Leadwood and sediment metal contamination in the Big River (Mosby et al., 2009). 2105 mg kg−1 at Desloge (Newfields, 2006; USFWS and MDNR, Further, Pb concentrations in channel sediments were found to be 2007). Lead concentrations remained N1400 mg kg−1 from below Flat above toxic limits for most of the length of the river below mining River Creek to R-km 140, peaking at 1672 mg kg−1 at R-km 151. areas (Roberts et al., 2009). The probable effects concentration (PEC) Below R-km 140, Pb concentrations decreased exponentially to about for metals in sediments above which harmful effects are likely to 300mgkg−1 below the confluence of Mineral Fork at R-km 99. Dilution occur in sediment-dwelling organisms is 128 mg kg−1 for Pb and by background sediment from Belews Creek at R-km 34.5 reduced Pb 459 mg kg−1 for Zn (MacDonald et al., 2000). concentrations to about 130 mg kg−1 in lower channel segments with Historical mining inputs have exerted a significant influence on a slight increase near the mouth. High Pb concentrations below the metal concentrations and downstream trends in the b2 mm sediment confluence of Flat River Creek (R-km 155) are not surprising given fraction of channel bed and bar sediment. Average metal concentrations that the three mines in that tributary watershed produced 65% of the at 26 sites were used to predict downstream variations in metal tailings and 57% of the Pb during the mining period. Interestingly, Pb concentrations in the b2mmfraction(Table 4). Bed and bar sediments concentrations decrease below Turkey Creek at R-km 136.1 even were averaged together at a site, and not stratified by deposit type, though it drained the longest operating mine in the Old Lead Belt at as the geochemical variability for paired bed and bar samples was Bonne Terre. Highly contaminated sediment is available in Turkey generally within 20–40% Cv% for Pb and for Zn. Distance- Creek as demonstrated by four channel sediment samples collected in concentration curves were constructed by manual manipulation of 2011 that contained 3000–5000 mg kg−1 Pb and 500–1000 mg kg−1 trend functions and downstream interpolation to predict downstream Zn. However, the relatively small drainage area of Turkey Creek trends in metal contamination as the uniform application of single (9.4 km2) probably limits the total supply of contaminated sediment linear, exponential, or polynomial regression equations did not produce inputs to the Big River (1031 km2). At the segment scale, average Pb curves that adequately fit the spatial distribution of sample data concentrations were N1100 mg kg−1 in segments 1–3 and peaked at (Fig. 12). In general, metal concentrations in channel sediments tend 1554 mg kg−1 in segment 2, decreasing to b200 mg kg−1 in segments to remain elevated in mining-affected segments, decrease downstream 9and10(Table 4). from mining sources, and drop rapidly below larger that Predicted Zn concentrations in channel sediments exceed the PEC of dilute contaminant concentrations with sediment from nonmining or 459 mg kg−1 for 49 km of the Big River from Leadwood almost to Mill background sources (Graf, 1996; Ciszewski and Matys Grygar, 2016). Creek (Fig. 12b). Recall that Zn concentrations in tailings inputs to the Predicted Pb concentrations in channel sediments exceed the PEC Big River were highest at Leadwood (mean = 4691 mg kg−1)and threshold of 128 mg kg−1 for the entire length of the Big River moderately high at Desloge (1243 mg kg−1)(Jackson et al., 1935; (Fig. 12a). Lead concentrations rose rapidly from b30 mg kg−1 above Newfields, 2006; USFWS and MDNR, 2007). Reflecting these higher Eaton Branch at Leadwood to 1200–1400 mg kg−1 between R-km inputs to the Big River above Flat River Creek, Zn concentrations in 165 at Desloge and R-km 155 at Flat River Creek. These Pb channel sediments rise rapidly from b60 mg kg−1 above Leadwood

Table 4 Channel sediment and metal storage.

Segment number R-km b2 mm (mg kg−1) Pb storage Zn storage

Pb Zn Mg Segment % Dolomite %a Mg Segment % Dolomite %a

1 171 1129 1986 1065.5 26.4 62.4 906.1 49.9 22.7 2 155 1554 966 841.4 20.8 61.7 225.7 12.4 16.0 3 144.5 1183 756 1019.0 25.2 60.7 281.8 15.5 15.3 4 132.5 694 492 389.3 9.6 25.9 190.9 10.5 3.7 5 115.5 423 199 155.1 3.8 50.9 2.8 6 99 309 156 230.5 5.7 71.5 3.9 7 72.5 276 156 150.6 3.7 53.1 2.9 8 52 276 141 93.1 2.3 27.1 1.5 9 35 188 89 54.6 1.3 6.3 0.3 10 17 152 83 43.1 1.1 4.3 0.2 Avg. or total: 618 502 4042 52.7 1818 14.4

a As described in the text, assumes dolomite fragments contain 4415 mg kg−1 Pb and 1366 mg kg−1 forsegment1and307mgkg−1 downstream of Flat River Creek. R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 67 1097654321 8 1,800 30 1,600 a Pb

) 25 Pb Model -1 1,400 Dolomite 1,200 20

1,000 15 800

600 10

400 Dolomite fragments (%) 5

Pb concentration (mg kg 200

0 0 0 20 40 60 80 100 120 140 160 180 Distance upstream (river kilometer)

1097654321 8 3,500 30

Zn 3,000 b

) 25

-1 Zn Model 2,500 Dolomite 20 2,000 15 1,500 10 1,000 Dolomite fragments (%) 500 5 Zn concentration (mg kg

0 0 0 20 40 60 80 100 120 140 160 180 Distance upstream (river kilometer)

Fig. 12. Downstream trends in metal concentrations in channel sediments (b2 mm) and the abundance of dolomite fragments (2–16 mm) in bar samples. Segments are indicated by the numbers at the top of the plot. Note that PEC values are 128 μgkg−1 Pb and 459 128 μgkg−1 Zn (MacDonald et al., 2000). and peak at 2985 mg kg−1 at R-km 163.4 near the Desloge mine To determine the metal content of the chat tailings fragments, (Fig. 12b). From that point, Zn concentrations drop rapidly to samples of 4–8 mm particles were selected from seven sites, powdered 800 mg kg−1 at Flat River Creek and then remain elevated at that in a ball mill, and subjected to XRF analysis for Pb and Zn. The average level until R-km 140. Below R-km 140, Zn concentrations decrease concentration of Pb was 4415 mg kg−1 with no significant difference gradually below Terre Bleue Creek (R-km 144.5) and Mill Creek (R-km between samples collected above and below Flat River Creek. In com- 115.5) to 300 mg kg−1 and remain b200 mg kg−1 from R-km 101 to parison, at the Federal Mill, which produced more than half of the Pb the mouth. By segment, Zn concentrations are highest in segment 1 in the watershed, chat wastes typically contained 3000–5000 mg kg−1 and then generally decrease in a negative exponential trend all the Pb (Jackson et al., 1935). However, Zn concentrations in three samples way to the mouth (Fig. 12b; Table 4). from segment 1 below Leadwood averaged 1366 mg kg−1, while the four samples collected below Flat River Creek contained much lower concentrations and averaged only 307 mg kg−1 Zn. These differences 4.1.4. Dolomite fragment trends (2–16 mm fraction) reflect the higher concentration of Zn in the Leadwood and Desloge We used dolomite fragments sampled from bar deposits as tracers to tailings released to segment 1 in contrast to lower Zn tailings entering indicate the movement of chat-sized tailings (Figs. 6 and 12). Bulk per- the Big River from Flat River Creek. The average concentrations were centages are 3% at Leadwood (R-km 170) and rise to N20% from R-km applied to the mass of dolomite fragments stored in channel sediments 156 to 137, with a peak of 26% at R-km 145. From R-km 137, fragment to estimate metal storage. For Zn, the higher value was used for segment contributions drop sharply to 5% at R-km 130, then gradually decrease 1andthelowervalueappliedtosegments2,3,and4. to b1% at R-km 121, and are typically absent in bar deposits below Mill Creek at R-km 116.5 (Fig. 12). At the segment scale, dolomite 4.1.5. Contaminated sediment storage fragments are only found in significant abundance in segments 1 A total of about 6.2 million m3 of bulk contaminated channel (13%), 2 (20%), and 3 (16%) (Table 3). This distribution indicates that sediment is stored in the Big River from Leadwood to its confluence chat tailings in the 2–16 mm size range have been transported a maxi- with the Meramec River, with 31.6% of the volume in bar deposits mum distance of about 30 km over a period of 120 years, averaging (Table 3). By mass, 13,105,385 Mg of contaminated sediment in the chan- about 250 m annually. nel is composed of 33% fine sediment (b2mm),3.3%dolomitefragments 68 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

(2–16 mm), and 63.7% uncontaminated gravel (i.e., nondolomitic gravel; 2–64 mm). About 20% of contaminated channel sediment is stored in the three mining segments (1–3) and 40% in St. Francois County above R-km 99. Overall, fine sediment (b2 mm) provides 29% of the contaminated sediment storage in bed deposits and 47% in bar deposits. While dolomite Mg % total fragments contribute relatively little mass (3.3%) to the river as a whole,

– 1

they account for 13 20% of channel sediment storage in the mining − segments. Zn storage 4.1.6. Metal storage trends Channel bed and bar deposits below Leadwood store 4042 Mg of Pb and 1818 Mg of Zn from historical mining sources (Table 4). The three mining segments account for 72.4% of the Pb and 77.3% of the Zn stored, even though these segments comprise only 22% of the total channel

length evaluated. Metal storage is much lower farther downstream Mg % total mg kg below Mineral Fork in Jefferson County where segments 6–10 account 1 for 58% of the contaminated river length but store only 14.1% of the Pb − and 8.9% of the Zn. Although dolomite fragments were generally limited to the mining area, they account for slightly N60% of the Pb stored in the Pb storage three mining segments and 47% of the Pb stored in channel deposits overall. In contrast, dolomite fragments account for only 15–23% of Zn % mg kg in the mining segments and 16.1% overall. The potential importance of the long-term release of Pb and other metals from chat tailings particles to the river by physical and chemical weathering has not been previously recognized.

4.2. Floodplain storage ) Mg 4.2.1. Floodplain sediment volume 3 Based on SSURGO soil data, floodplains cover 37.3 km2 of area along (m the Big River from Leadwood to its confluence with the Meramec River (Table 5). Because of increases in valley width, segment floodplain area generally increases by 2–3 times from the mining area (R-km 171–133) Floodplain depth (m) to below Mineral Fork (R-km 99). As floodplains become wider down- 2.42 3,407,188 5,110,782 3.6 1265 5857 3.2 1347 5778 16.8 stream, geomorphic complexity increases as the number of different soil-landform features increases from one to four. Floodplain width increases measurably downstream in a fluctuating pattern, reflecting 242 2.38 9,781,409 14,672,114 10.2 1118 14,741 8.0 179 141 0.4 163 3.20 6,263,218 9,394,827 6.5 2358 20,627 11.2 993 7434 21.7 171 2.98 5,349,334 8,024,001 5.6 2102 15,647 8.5 1666 11,528 33.6 Contaminated sediment storage Floodplain width (m) bedrock control and tributary confluence location (Fig. 13). 88

Floodplains are contaminated above the background threshold value ” along the entire length of the Big River below Leadwood to depths 21.9 255 2.65 95,772,562 143,658,844 100 1465 184,507 100 505 34,299 100 6 22 387 2.21 15,345,551 23,018,327 16.0 874 17,746 9.6 178 209 0.6 41 221 2.20 8,249,694 12,374,541 8.6 830 9021 4.9 170 17 0.1 27 325 2.36 15,750,732 23,626,098 16.4 994 20,935 11.3 176 158 0.5 253228 137 194 195 3.25 3.10 2.74 7,555,378 9,933,031 11,333,066 14,137,028 14,899,547 21,205,541 7.9 10.4 14.8 2312 1988 1453 24,381 27,415 28,137 13.2 14.9 15.3 583 384 240 4505 3077 1450 13.1 9.0 4.2 3 0 Kaintuck “ Bench usually N2m(Fig. 13). In general, Pb profiles in cores exhibited relatively 0 consistent trends where concentrations rise from background levels, ” peak in the lower to middle portion of the contaminated zone at 2000–10,000 mg kg−1, and then decrease to 1000–2000 mg kg−1 at the surface (Fig. 14). Zinc profilesarenotasconsistentorcontaminated, 7.5 10 14 12 11 0 3 1 5 0 Wilbur “ Backswamp but generally show similar trends. This observation is expected because 0 the primary Zn input was far upstream at the Leadwood mine and ” the supply of Zn to the channel was much less than for Pb. Average contaminated depths for 19 floodplain sites ranged from 2.3–3.1 m and averaged 2.7 m (Fig. 13). In comparison, total bank heights above 62.9 77 59 38 57 75 46 52 92 100 Haymond “ Floodplain 100 the thalweg at the same sites ranged from 4.5 to 5.5 m and averaged

5.0 m, about two times the contaminated depth. ” Contaminated depths average about 3 m in segments 2–7 before decreasing to 2–2.5 m in segments 8–10. Three factors may have contributed to this pattern. First, bed aggradation caused by historical Soil series-Landform Distribution (%) Sturkie “ Low terrace gravel inputs may have filled in and choked the channel by decreasing ) channel cross-sectional area, thereby increasing the frequency of 2 overbank floods and sediment delivery to the floodplain (Jacobson, 1995). Second, floodplain width (controlled by variations in valley 37.3 7.7 area (km geology) may have influenced overbank deposition rates. For a given drainage area, the depth of overbank deposition can be lower for wide 35 6.96 4 52 3.75 9 72.5 6.66 5 132.5115.5 2.3299 3.21 5.17 0 20 19 144.5 1.95 0 R-km Floodplain 155 1.80 0 (sediment deposition is spread out across a larger area) and for narrow 171 1.41 0 valleys (higher flow velocity and transport capacity) but is higher in in- termediate wide valleys (Magilligan, 1985). Finally, additional sediment supply from mining sources or local tributaries may have increased Totals: 10 17 4.11 7 9 8 7 4 5 6 3 Segment number 2 1

floodplain sedimentation rates at the segments above Mineral Fork. Table 5 Floodplain sediment and metal storage. R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 69

1097654321 8 800 4 downstream trend in Pb concentrations. The two high Pb values above 3000 mg kg−1 at R-km 132.8 and 118 include sites with only one core 700 3.5 available for analysis and only three samples for each, therefore more 600 3 weight was put on the trend line to follow other sites with values based on the average of three or more vertical profiles. Lead concentra- 500 2.5 tions N2000 mg kg−1 in floodplains extend 40–50 km downstream 400 2 from the mining area, suggesting high mobility and a supply of fine

300 1.5 tailings particles during mining and, to some degree, post-mining periods. Average floodplain Pb concentrations then level off below 200 1 −1 Floodplain width (m) R-km 80 to about 1000 mg kg where they remain until reaching the Contamination depth (m) Contamination −1 100 Floodplain width 0.5 mouth where they increase somewhat to 1500 mg kg .Thisincrease Contamination depth in Pb contamination is reproducible and we believe it may indicate 0 0 fi 20 40 60 80 100 120 140 160 180 the deposition of suspended sediment carrying ne tailings or slimes fl Distance upstream (river kilometer) during backwater conditions when the Meramec River was in ood. At the segment scale, Pb concentrations are highest (N2000 mg kg1) – Fig. 13. Downstream trends in floodplain width and depth. Segments are indicated by the in segments 2 4 in St. Francois County and then drop below −1 numbers at the top of the plot. 1000 mg kg in segments 7–9(Table 5). Downstream trends in average Zn concentrations in contaminated floodplain deposits could not be adequately defined by a specificequa- 4.2.2. Floodplain concentration trends tion. Therefore, manual fitting was again used to predict concentration Sediment samples from the lower portions of cores or bank expo- values to calculate metal storage (Fig. 15b). Peak Zn concentrations sures extending into premining deposits were analyzed for metals to N2000 mg kg−1 occur at R-km 158.1 and 156.1 in several floodplain determine natural background concentrations. Twenty-three cores cores below Leadwood (but above Flat River Creek near Desloge), were evaluated, including two from above Leadwood, nine within the again underscoring the Leadwood mine source for significant Zn pollu- three mining segments, and four more from above Mineral Fork (R- tion. Sampling density is relatively high below the Desloge Mine, with km 99). The average background metal concentration and 95% upper peak Zn concentrations detected in five cores with a total of 28 samples. confidence limit (+2 s) threshold was 23 and 71 mg kg−1 for Pb and Below Flat River Creek, average floodplain concentrations drop sharply 75 and 169 mg kg−1 for Zn respectively. Toxicity thresholds have downstream to 500 mg kg−1 Zn near Mill Creek and then gradually been estimated for Big River floodplain soils based on ecological harm level off to about 180 mg kg−1 Zn below Mineral Fork and all the way to native plants at 451 mg kg−1 Zn (Stroh et al., 2015) and songbirds to the mouth. At the segment scale, Zn concentrations are highest in at 345 mg kg−1 Pb (Stratus Consulting, 2014). Average Zn concentra- segments 1 (1347 mg kg−1) and 2 (1666 mg kg−1) and then decrease tions in contaminated floodplain deposits exceed 451 mg kg−1 from to b200mgkg−1 below Mineral Fork at R-km 99 (Table 5). Leadwood to Mill Creek (R-km 115.5). Lead concentrations exceed − 345 mg kg 1 in all floodplains sampled below Leadwood. 4.2.3. Contaminated sediment and metal storage in floodplains Average concentrations of metals in the contaminated portion The floodplain deposits sampled for this study averaged 96% fine sed- of overbank deposits at 19 sites were used to quantify downstream iment (b2 mm) based on the results of grain-size analyses performed on trends (Fig. 15). A polynomial curve was used to describe the 181 floodplain samples representing 33 different cores from 17 sites.

Fig. 14. Downstream variability in metal profiles in floodplain deposits. 70 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 1097654321 8 3,500

) 3,000 a Core avg. -1 Floodplain Pb model 2,500

2,000

1,500

1,000

Pb concentration (mg kg 500

0 0 20 40 60 80 100 120 140 160 180 Distance upstream (river kilometer)

1097654321 8 2,500

b Core avg. ) Floodplain Zn model

-1 2,000

1,500

1,000

500 Zn cncentration (mg kg

0 0 20 40 60 80 100 120 140 160 180 Distance upstream (river kilometer)

Fig. 15. Downstream trends in floodplain metal concentrations. Data points represent the mean concentration of multiple cores at a site. Segments are indicated by the numbers at the top of the plot.

Nineteen percent of the floodplain samples contained very fine and fine 72.1% stored in the three mining segments and 94% in St. Francois gravel (2–8 mm), which fall within the expected ranges for floodplains County. in soil survey reports (i.e., Sturkie b15%; Haymond b10%; Wilbur 0%; and Kaintuck b25%) (Brown, 1981; Skaer, 2000; Skaer and Cook, 5. Discussion 2005). Because dolomite fragments were rarely found in floodplain deposits, we assumed that 96% of the total storage mass of contaminated 5.1. Amount and distribution of mining sediment and metal storage floodplain material was b2 mm in size and contaminated, while the coarser fraction representing 4% of the mass was considered uncontam- Mining in St. Francois County released 264 million Mg of tailings inated by mining sources. containing 508,000 Mg of Pb and 386,000 Mg of Zn to the Big River Overall, ~96 million m3 (144 million Mg) of contaminated floodplain watershed between 1864 and 1972. Overall, only 22% of the total deposits are stored along the Big River (Table 5). Given the relatively mass still remains at mining sites within stabilized chat piles and narrow width of floodplain areas and shallow contaminated depths in tailings ponds ranging from 19% for the Flat River subdistrict (Elvins, the upper segments below Leadwood, only about 16% of the contami- Federal, and National mines) to 28% on-site at Leadwood and Desloge nated sediment storage is within the mining area (34% in St. Francois (Newfields, 2006; USFWS and MDNR, 2007). While large volumes of County above R-km 99). Contaminated sediment has been transferred tailings were removed from mining sites for construction and agricul- downstream to floodplains in Jefferson County where about one-third tural purposes (Wright, 1918; Mosby et al., 2009), we estimate that of the storage is located within the three most downstream segments. about 37% of the Pb (188,549 Mg) and 9% of the Zn (36,117 Mg) In total, 184,507 Mg of Pb and 34,299 Mg of Zn are stored in floodplain originally discharged in tailings wastes is presently stored in channel deposits (Table 5). Lead storage is uniformly distributed downstream and floodplain deposits along the Big River (Tables 4 and 5). Overall, with 22.9% stored in the three mining segments and 51% in St. Francois ~96 million m3 of contaminated sediments stored in floodplain de- County. In contrast, Zn storage mass is concentrated upstream with posits, which represents 93.9% of the total (i.e., channel + floodplain) R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 71 storage. By mass, floodplains store ~144 million Mg of contaminated because of increases in channel width of up to 50% below Mineral sediment, which is 91.6% of the total storage (Table 5). About Fork (Fig. 9). Similarly, floodplain storage capacity increases down- 6.2 million m3 (only 6.1% of the total) or about 13 million Mg (only stream from Mineral Fork because valleys and floodplains are 2–3 8.4% of the total) of contaminated sediment is stored within the channel times wider than those upstream in the mining area (Table 5; Fig. 13). in bed and bar deposits. Overall, the metal concentration in the fine sediment fraction The spatial distribution of historical mine and tailings dump sites in (b2 mm) and the relative abundance of fine sediment in the deposit the watershed largely explains the present-day contamination trends in are the critical variables that exert primary influence on downstream the Big River as sediment concentrations of Pb and Zn tend to be highest trends in metal concentrations and storage in this study (Figs. 12 and below mine sites and then decrease in an exponential trend with 15). Therefore, increased bar area in the channel and the higher distance downstream (Pavlowsky et al., 2010)(Figs. 12 and 8). percentage of fine sediment in bar deposits also increase the metal However, storage trends are generally determined as the product of mass per unit channel length (Figs. 2 and 4). Furthermore, the impor- metal concentration and volume (or mass) of the deposit and, therefore, tance of additional metal storage associated with dolomite fragments are additionally linked to valley width, channel and floodplain morphol- in channel deposits is another significant factor increasing storage in ogy, and fluvial sorting of the different types of mining wastes. Tailings Big River near the mining area (Table 3; Fig. 11). materials primarily entered the main channel at the Flat River Creek For floodplain storage, in addition to valley width, the depth of confluence (R-km 155) or farther upstream along the Big River (up to contaminated floodplain deposits above the background threshold R-km 171) (Table 6A). The Leadwood (R-km 171) and Desloge (R-km value is also an important factor in explaining spatial variations. 160 km) mines in segment 1 discharged 26% of the tailings Pb and Contaminated sediment depths on floodplains are 0.5–1 m thicker 50% of the Zn. However, the highest amounts of contaminated sediment along the Big River from Flat River Creek to Mineral Fork (segments storage are located in downstream segments below R-km 155 2–5) (Fig. 13). This trend may be explained by the control of valley (Table 6B). For example, 66% of the contaminated sediment and 49% width on floodplain deposition (Magilligan, 1985) or by higher rates of the Pb from historical mining is stored along the lower portion of of sedimentation associated with historical sediment waves caused by the Big River below R-km 99 N 40 km downstream from Bonne Terre land use changes during the settlement period (Jacobson, 1995; James, (the most downstream mine), which was only affected locally by 2013). While it is tempting to suggest that the additional tailings inputs scattered surface mining activities. However, while 94% of Zn is stored from historical mining operations may have increased floodplain depo- above R-km 99 near the mining area as its main input was at R-km sition rates by higher sediment loads, estimates of tailings contributions 171, only 18% is stored in segment 1 because of downstream transport. to fine sediment storage based on carbonate percentages are only about While Flat River Creek drained the largest tailings areas of the Old Lead 5% by mass for contaminated floodplain deposits and 10% for channel Belt, storage assessments of channel deposits by Hill (2016) and flood- sediment. Moreover, direct counts of tailings chat particles indicate an plain deposits by the present authors indicate that alluvial storages in average bulk percentage of about 10% in the channel ranging from 0% Flat River Creek are relatively small (b3%) compared to the Big River in segment 5 to 20% in segment 2 (Table 3). More study is needed to (Table 6). Factors accounting for low storage estimates for Flat River explain the observed variations in the thickness of contaminated flood- Creek include limited depositional areas due to narrow channels, plain deposits along the Big River. confined floodplains, and relatively high transport capacity due to The storage rate in units of contaminated sediment volume per higher slope and frequent bedrock outcrops along the channel bed. kilometer of channel length can be used to remove the influence of Downstream storage patterns are not uniform among coarse variable segment length on storage trends to evaluate storage capacity channel, fine channel, and fine floodplain deposits because of variable rates for the Big River (Fig. 16). Among the 10 segments, channel source input locations, geochemistry and size of tailings particles, and storage rates average 35,563 m3 km−1 with a Cv% of 16% ranging from geomorphic storage capacity (Walling et al., 2003; Ciszewski and 26,954 in segment 2 to 46,536 m3 km−1 in segment 7. Storage rates Matys Grygar, 2016). Geomorphic storage capacity refers to the ability vary downstream with relatively low rates in the mining-affected of the floodplain or channel to store sediment for relatively long segments associated with relatively narrow active channel widths. periods, and it increases with the size of the sedimentation area and However, channel storage rates increase below Mineral Fork from the rate of sediment delivery or deposition within it. More than 60% of R-km 99 to 35 where valley width and sinuosity increase dramatically contaminated bulk sediment storage occurs in downstream segments (Skaer, 2000). Below R-km 35, the channel storage rate decreases to 6–10 for channel and floodplain deposits (Table 6C and D). The geomor- similar levels as in the upstream mining areas as bar storage decreases phic storage capacity of the channel system increases downstream (Table 1). In relative terms, floodplain storage rates are twice as variable as channel rates with an average rate of 550,577 m3 km−1 and Cv% of 3 −1 Table 6 32% ranging from 212,949 in segment 1 to 852,531 m km in segment Downstream distribution of storage by segment. 9. Overall, a significant positive relationship exists between floodplain fl 2 Percent of total storage Percent of total storage width and oodplain storage rates (n = 10, R = 0.879). In addition, unit storage rates for contaminated sediment in floodplains are about Sediment Pb Zn Sediment Pb Zn 15 times greater than those for the channel (Fig. 16). Segment A) Tailings dischargeda B) Total storage 1 22.8 26.9 50.2 3.9 3.4 18.1 5.2. Influence of selective transport on mining sediment storage FRCb 64.7 57.0 45.9 (+1%)c (+2%) (+4%) – 2 5 12.5 16.1 3.9 30.1 47.8 75.9 The spatial distribution of sediment and metal storage within the 6–10d 0 0 0 66.0 48.8 6.0 Big River appears to be controlled by the selective transport of finer Segment C) Channel storage D) Floodplain storage materials farther downstream with the locus of storage shifting farther 1 8.7 26.4 49.9 3.6 3.2 16.8 downstream in the order: coarse channel sediment (chat); fine channel FRC (+2%) (+7%) (+10%) (+1%) (+2%) (+4%) sediment (b2mm);andfloodplain sediment (b2mm)(Fig. 17). Grain- – 2 5 28.1 59.5 41.2 30.4 47.7 77.4 size characteristics of these three sedimentary components appear to 6–10 63.2 14.1 8.9 66.1 49.1 5.8 correlate with the downstream extent and distance of peak storage in a Based on production records in Bureau of Mining Reports. the Big River. First, mining chat in the coarse (fine gravel) channel b Flat River Creek watershed, flows into the Big River at R-km 155. component is the least easily entrained for transport, so storage c Flat River Creek storage in addition to the Big River totals after Hill (2016) and estimates by authors based on unpublished studies. locations are concentrated in upper segments near tailings source d Segments 6 to 10 are in Jefferson County below R-km 99. areas. While chat wastes were generated early in the mining period 72 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75

1097654321 8 60,000 900,000

800,000 50,000 / km) 700,000 /km) 3 3 40,000 600,000

500,000 30,000 400,000

20,000 300,000 Channel 200,000 10,000 Floodplain 100,000 Floodplain storage rate (m Channel storage rate (m

0 0 0 20 40 60 80 100 120 140 160 180 Distance upstream (river kilometer)

Fig. 16. Downstream trends in the contaminated storage rate. Segments are indicated by the numbers at the top of the plot.

(1890–1933), they have been transported only about 10–20 km channel deposits may be the result of the geochemical release of soluble downstream from the Leadwood Mine or the confluence of Flat River Zn from channel deposits near the mines and binding by fine-grained Creek, which is equivalent to an average travel rate of about 100– sediment, iron (Fe) manganese (Mn) oxide coatings, and organic matter 200 m y−1 (Figs. 12 and 17). Coarse channel particles, as chat or dolo- in surrounding stream and pore waters downstream (Herrmann et al., mite fragments, account for b0.12% of the total contaminated sediment, 1981; Chapman et al., 1988). Secondary Fe-Mn oxides have previously 0.3–0.4% of Pb, and 0.6% of Zn mass storage per segment (Fig. 17a). been identified in contaminated sediments in the Big River (Schmitt Storage trends in the fine channel sediment fraction suggests more and Finger, 1982; Smith and Schumacher, 1991, 1993). They can bind downstream mobility compared to chat with fine channel storage and coprecipitate metals in mining areas as well as release them to extending all the way to the mouth, and peak storage of 1–1.5% of the water column during acidic or low oxygen conditions (Horowitz, total storage occurring in segments 6 and 7, over 70 km farther down- 1991). Further, groundwater seepage into the channel from under- stream than peak chat storage (Fig. 17b). Total Pb storage by mass in ground mine workings can be a source of dissolved Fe and Mn that fine channel deposits gradually decreases downstream from 0.3% in forms oxide coatings on sediment shortly after entering the channel segment 1 to 0.1% in segment 7, extending about 40 km farther down- (Smith and Schumacher, 1993; Newfields, 2006). Once attached to stream compared to Pb in the chat fraction (Fig. 17b). Peak Zn storage silt- and clay-sized particles, fluvial processes can sort by size, transport in fine channel sediment also shifts downstream compared to the chat downstream, and selectively deposit translocated Zn into overbank trend, but only by 10–20 km. The highest concentration of tailings Zn floodplain storage (Bradley, 1989; Bradley and Cox, 1990). entered the Big River far upstream at Leadwood (R-km 171), so most of the Zn is stored within segment 1 at a much greater rate than either 6. Conclusions sediment or Pb (Fig. 17b). The fine sediment in the channel is generally composed of sand and silt and thus is more easily transported down- Widespread watershed disturbances by historical European stream compared to coarser chat grains. settlement and large-scale mining activities in the Old Lead Belt As the third sedimentary component, floodplain deposits are coincided in history to produce an episode of contaminated legacy derived from suspended sediment dominated by silt- and clay-sized sediment deposition along 171 km of the Big River in the Ozark particles (Brown, 1981; Skaer, 2000) including very fine tailings Highlands of southeastern Missouri. A geomorphic assessment of the (slimes) that were capable of being transported downstream even Big River was implemented to improve our understanding of this legacy during low-flow conditions (Buckley, 1909). Therefore, the peak storage deposit and the magnitude and distribution of contaminated sediment of contaminated sediment in floodplains is shifted even farther storage in river systems draining the Ozark Highlands. Although this downstream to segments 7–9 where 7–15% of total storage occurs study describes contaminated legacy sediment on floodplains along (Fig. 17c). In contrast, the location of peak Pb storage in floodplains the Big River below Leadwood, uncontaminated legacy deposits only extends to segments 5 and 6, shifting 30 km farther downstream also occur on floodplains upstream of the mining area and along its than the channel Pb and representing about 15% of the total Pb storage major tributaries. Channel sediments and floodplain deposits are (Fig. 17c). Peak Zn storage shows a dramatic shift from segment 1 contaminated with Pb to toxic levels along the entire 171-km length where the Zn is found in fine channel sediment, to segment 2 where of the Big River below Leadwood. Toxic concentrations of Zn in the the Zn resides in floodplain deposits that account for over 30% of the channel and floodplain sediments extend about one-third of the total storage. In addition, the downstream limit of major Zn storage distance (50–60 km) to the mouth. Mean concentrations in floodplain shifts from segment 4 in the channel to segment 6 in the floodplain cores N2000 mg kg−1 for Pb and N1000 mg kg−1 for Zn extend 40– which contains 4% of total storage (Fig. 17c). 50 km downstream from the mining area in association with the supply Increased geochemical mobility of Zn may have influenced the of fine tailings particles that are easily dispersed downstream in the downstream concentration and storage trends for Zn. Given the suspended load. Mean concentrations in channel bed and bar sediments carbonate and sulfide ore mineralogy of tailings in the OLB and neutral ranging from 1400 to 1700 mg kg−1 for Pb extend 30 km below the to alkaline water/sediment chemistry of the Big River, the solubility and mines, while Zn concentrations of 1000–3000 mg kg−1 extend 20 km overall environmental mobility of Zn tends to be greater than that for Pb downstream. Coarse tailings have been transported a maximum (Smith and Schumacher, 1991, 1993; Miller and Orbock Miller, 2007; distance of about 30 km along the 171-km length of the Big River over Stroh et al., 2015). Therefore, the large shift in relative Zn storage a period of 120 years. Coarse dolomitic chat fragments in the 2– downstream from the mine source in floodplain deposits compared to 16 mm channel sediment fraction provide significant storage of Pb R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 73

Channel (chat) the 1.5 billion Mg of hydraulic mining sediment in the Bear and 1.0 a American rivers in California (144,000 Mg km−2)(James, 1999)and 0.9 Sed 240 million Mg of tailings in the Kawerong-Jaba River system from the 0.8 Pb Panguna copper mine on Bougainville Island, Papua New Guinea 0.7 −2 Zn (685,700 Mg km )(Archer et al., 1988; Jeffery et al., 1988). A recent 0.6 review of major tailings dam failures reported a range of releases from 0.5 340,000 Mg to 13 million Mg (Kossoff et al., 2014). However, Big River 0.4 mining sediment storage exceeds some notable mining districts in the 0.3 USA. Only about 42 million Mg of tailings from the Homestake gold 0.2 mine were stored in floodplains along the Whitewood Creek-Belle −2 0.1 Fourche River system in South Dakota (2320 Mg km )(Marron, Percent of total storgae (%) 0.0 1992). Further, 11 million Mg tailings from gold mining along Silver fl 10 123456789 Bow Creek and copper mining at Butte were stored in oodplains and along the Clarks Fork River in Montana (471 Mg km−2) Segment (Moore and Luoma, 1990). Channel (<2 mm) The downstream distribution of contaminated sediment and 2.5 metal storage is influenced by fluvial sorting and selective transport of b finer sediment farther downstream and into overbank floodplain 2 areas. About three-fourths of the contaminated channel sediment is located within 25 km of the mining area, compared to just 16% of the contaminated floodplain sediment. A total of 188,549 Mg of Pb 1.5 and 34,299 Mg of Zn are stored in channel and floodplain deposits. Channel bed and bar deposits store 4042 Mg of Pb and 1818 Mg of Zn. 1 Most of the metal mass (82% for Pb and 88% for Zn) is stored within 25 km of the mines (i.e., segments 1–4). Coarse dolomite tailings frag- 0.5 ments account for about 60% of the Pb stored in channel sediment near the mines. Most of the metal mass in the Big River system is stored Percent of total storgae (%) in the floodplains that contain 98% of the Pb (184,507 Mg) and 95% of 0 the Zn (34,299 Mg). Only 24% of Pb is stored within 25 km of the mining 10 123456789 area in floodplains, while 85% of the Zn is stored close to the mining Segment area. Environmental assessments of streams in mining areas typically Floodplain b fi 35 focus on evaluating metal concentrations in the 2mmor ner c fractions because these particles tend to be more geochemically active 30 and available to biota compared to coarser sediment (Horowitz, 25 1991). Indeed, elevated levels of metals have been found in aquatic plants and fish in contaminated segments of the Big River (Schmitt 20 and Finger, 1982; Gale et al., 2002, 2004). In addition, mussels are 15 less abundant and less diverse in channel locations below mining sites where metal concentrations exceed PEC limits (Roberts et al., 10 2009). This study emphasized the geomorphic approach to describing the 5 distribution of mining contamination in channel and floodplain sedi- Percent of total storgae (%) 0 ments of the Big River (Lecce and Pavlowsky, 2014). An adequate un- 10 123456789 derstanding of the rates at which geochemical processes affect the Segment weathering of mining sediment and thereby influence metal solubility and chemical redistribution among temporary and long-term sediment Fig. 17. Downstream trends in relative storage distribution. storages is lacking. However, as the weathering of coarse sand tailings and chat progresses over time, the mass of metals in transport or storage may shift to finer sediments in more mobile and biologically available forms. This investigation shows that the distribution of contaminated and Zn in the Big River. While the storage of dolomite fragments is sediment in the Big River can be explained largely as a function of sed- relatively low for the entire river system (3.3%), this component repre- iment source and transport phenomenon (Pavlowsky et al., 2010). sents 13–20% of the bulk sediment storage mass in the channel and can Coarse mine wastes (chat tailings) presently account for over half of − − contain N4000 mg kg 1 Pb and N1000 mg kg 1 Zn. Indeed, mining chat the mining Pb stored in Big River channel sediments. These coarse sed- accounts for 52% of the Pb and 14% of the Zn stored in channel sediment iments may be an important source of metals to stream water in the fu- in the Big River below Leadwood. ture because of weathering by abrasion and dissolution of contaminated Overall, we estimate about 37% of the Pb and 9% of the Zn originally particles in channel sediments. Further, the magnitude and basinwide released to the watershed in tailings wastes from concentration mills distribution of Pb and Zn storage in legacy floodplain sediments ensures remains stored in the Big River. Moreover, ~7 million Mg of tailings that remobilization by bank erosion will be a continuing problem for were added to the river producing a total of 157 million Mg of water quality far into the future. contaminated sediment stored in channel and floodplain deposits − (63,000 Mg km 2 of drainage area) with 144 million Mg (92%) located Acknowledgements in floodplain deposits typically contaminated to depths of 1.5–3.5 m. The extent of mining contamination in the Big River is significant at The authors thank David Mosby and the U.S. Fish and Wildlife the global scale. Some watersheds store more mining wastes such as Service for the funding to support this project through the cooperative 74 R.T. Pavlowsky et al. / Geomorphology 299 (2017) 54–75 ecosystems studies unit agreement #301816J229 and task order Graf, W.L., Clark, S.L., Kammerer, M.T., Lehman, T., Randall, K., Schroeder, R., 1991. Geo- morphology of in the sediments of Queen Creek, Arizona, USA. Catena #301819T003. Jennifer Witt and Susan Helwig helped to collect the 18, 567–582. bar samples and complete chat counts for this project. Benjamin Young Happ, S.C., Rittenhouse, G., Dobson, G.C., 1940. Some Principles of Accelerated Stream and and David Fritsche helped to collect and analyze additional channel Valley Sedimentation. 695. U. S. Dept. Agricultural Tech. Bull (133 pp.). Herrmann, R., Thomas, W., Schrimpf, E., 1981. (Zn, PO4,NO2, PAH, BHC, samples from the lower Big River. Patrick Womble, Benjamin Young, coprostanol) transport and its modeling in a small stream. Catena 8, 191–199. W. Patrick Dryer, Gitonga Muchiri, Lindsay Olson, Megan Harrington, Hill, R.J., 2016. Channel Sediment and Mining-lead Storage in Flat River Creek, Old Lead Anna Larkin, Andrew DeWitt, David Speer, and Jess Whitson provided Belt, Missouri. (Unpublished Master's Thesis). Department of Geography, Geology, fi field assistance and laboratory work toward completing this project. and Planning, Missouri State University, Spring eld, MO. Hinck, J.E., McMurray, S.E., Roberts, A.D., Barnhart, M.C., Ingersol, C.G., Wang, N., We would like thank Missouri State Parks and other units of the Augspurger, T., 2012. Spatial and temporal trends of freshwater mussel assemblages Missouri Department of Natural Resources for their cooperation and in the Meramec River basin, Missouri, USA. J. Fish Wildl. Manag. 3 (3), 319–331. Hoffmann, T., Thorndycraft, V.R., Brown, A.G., Coulthard, T.J., Damnati, B., Kale, V.S., support during this project. The authors thank two anonymous fl fi Middlelkoop, H., Notebarert, B., Walling, D.E., 2010. 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