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Abstract: Sedimentation basins (SBs) are commonly used during highway construction for erosion and sedimentation pollution control as well as for attenuation of overland storm waters. In order to evaluate the sediment removal capacity of these SBs, four basins were selected for monitoring from a new highway construction that extends I-99 to I-80, in Pennsylvania. Between September 2004 and August 2005, ten sampling trips were conducted during which basin inlet and outlet water samples were obtained. The SB samples were analyzed for pH, color, turbidity, total suspended solids (TSS), volatile suspended solids (VSS), total and dissolved iron, magnesium, manganese, aluminum, calcium, sulfate and phosphate. The data showed peaks in concentrations of TSS, total aluminum, total manganese, total iron and total phosphate that closely correlated to localized rainfall peaks. For certain samples, the concentration of TSS in the outlet was higher than the TSS concentration at the basin inlet, suggesting sediment re-suspension. In general SBs managed high flows during wet weather events, but were not effective in capturing particulates. This paper discusses the need for Best Management Practices (BMPs) for the design of SBs that reflect contemporary concerns for management of particle removal and to control the release of particulate-bound metals. This paper also evaluates the water quality impacts of naturally occurring acidic drainages into SBs, as several acidic seeps with pH in the range of 5–6 and having high dissolved concentrations of metals (Fe, Mn, Mg and Ca), sulfate and phosphate were observed draining into the SBs. [Copyright &y& Elsevier]

A graphical screening method was previously developed by Kney and Brandes (2007) for assessing stream water quality data using electronic conductivity (EC) and alkalinity data. The method was aimed at providing citizen scientists involved in stream monitoring programs with a relatively simple way to interpret EC data. The method utilizes a plot of EC against concurrent alkalinity data, and is used to distinguish EC values for impacted or degraded streams from those that can be considered background values in a particular geologic setting. The method performs well in areas underlain by carbonate bedrock, as streams in those areas characteristically have EC values that are strongly correlated with alkalinity. However, in areas of low stream alkalinity (less than approximately 50 mg/L as CaCO3), the Kney and Brandes (2007) method was found to be much less effective in identifying impacted streams. This paper extends the graphical screening approach to streams with low alkalinity, specifically regions underlain by clastic sedimentary or crystalline bedrock, by using the strong correlation between EC and total hardness (TH). A baseline relationship of EC vs. TH is developed using surface water chemistry data from Hydrologic Benchmark Network streams (deemed as having minimal anthropogenic impacts) and regional groundwater quality data. The usefulness of the method is demonstrated by application to publicly available stream chemistry data and to field data collected from streams of eastern Pennsylvania under baseflow conditions. Results demonstrate that for streams with alkalinity <75 mg/L as CaCO3, the TH-based graphical screening method should be used rather than the alkalinity-based method of Kney and Brandes (2007). [Copyright &y& Elsevier]

In areas of varying geology, it is difficult to infer water quality from specific conductance or electrical conductivity (EC) data without an understanding of the expected range of EC values based on local bedrock composition. This paper describes a user-friendly graphical screening method that addresses this issue by plotting the EC against concurrent alkalinity data, which correlates well with the presence of carbonate bedrock under natural conditions, and thus serves as an index of bedrock type. The upper limit of EC vs. alkalinity expected in a stream is determined using regional groundwater quality data, based on the assumption that stream chemistry reflects groundwater under baseflow conditions. Stream samples with EC/alkalinity values that consistently plot above this limit are considered impacted by anthropogenic sources. The effect of dilution and runoff on the EC vs. alkalinity plot of stream samples is considered using a simple baseflow/storm runoff-mixing model. The graphical method''s utility as a screening tool is demonstrated by application to stream chemistry data from watersheds of southeastern Pennsylvania and northwestern New Jersey conductivity in several distinct geologic settings; however the method is general and widely applicable to watersheds in humid temperate regions. Its use is intended for watershed stewards of both professional and nonprofessional qualification. [Copyright &y& Elsevier]