Advancing Understanding of the Surface Water Quality Regime of Contemporary Mixed-Land-Use Watersheds: An Application of the Experimental Watershed Method

Abstract

A representative watershed was instrumented with five gauging sites (n = 5), partitioning the catchment into five nested-scale sub-watersheds. Four physiochemical variables were monitored: water temperature, pH, total dissolved solids (TDS), and dissolved oxygen (DO). Data were collected four days per week from October 2010-May 2014 at each gauging site. Statistical analyses indicated significant differences (p < 0.05) between nearly every monitoring site pairing for each physiochemical variable. The water temperature regime displayed a threshold/step-change condition, with an upshifted and more variable regime attributable to the impacts of urban land uses. TDS, pH, and DO displayed similar spatiotemporal trends, with increasing median concentrations from site #1 (agriculture) to #3 (mixed-use urban) and decreasing median concentrations from site #3 to #5 (suburban). Decreasing concentrations and increasing streamflow volume with stream distance, suggest the contribution of dilution processes to the physiochemical regime of the creek below urban site #3. DO concentrations exceeded water quality standards on an average of 31% of observation days. Results showed seasonal trends for each physiochemical parameter, with higher TDS, pH, and DO during the cold season (November-April) relative to the warm season (May-October). Multivariate modeling results emphasize the importance of the pH/DO relationship in these systems, and demonstrate the potential utility of a simple two factor model (water temperature and pH) in accurately predicting DO. Collectively, results highlight the interacting influences of natural (autotrophic photosynthesis, organic detritus loading) and anthropogenic (road salt application) factors on the physiochemical regime of mixed-land-use watersheds.

A Systematic Study of Sustainable Development Goal (SDG) Interactions

“…Unlike Pearson's correlation analysis, Spearman's analysis is able to capture nonlinear correlation between the variables and is less sensible to outliers (Hauke & Kossowski, 2011). Spearman's analysis is widely used to identify general relation beyond the linear correlation between two variables in various disciplines (e.g., Kellner & Hubbart, 2017;Sesnie et al, 2017;Sidney et al, 2017;Yoon, 2012). We carry out the correlation analysis only with the data pairs consisting of more than three data points.…”

Quantifying Escherichia coli and Suspended Particulate Matter Concentrations in a Mixed-Land Use Appalachian Watershed

“…Stream water grab-samples were collected following the USGS methods described in the National Field Manual for the Collection of Water-Quality Data [39] and as per Petersen et al [35], Hubbart et al [40], Kellner and Hubbart [41], and Zeiger and Hubbart [42,43] from each monitoring site (stream order ≤3). The sampling regime was determined by stream stage (based on the streamflow descriptions by Zeiger and Hubbart [42]) at the sites to ensure sample extraction occurred during low (approximately 25% bankfull), medium (approximately 40-60% bankfull) and high(er) (approximately >60% bankfull) stages.…”

Advancing Understanding of Land Use and Physicochemical Impacts on Fecal Contamination in Mixed-Land-Use Watersheds

“…For the current work, weekly water grab-samples were collected as per Petersen et al [6], Hubbart et al [52], Kellner and Hubbart [38], and Zeiger and Hubbart [37,53] from each monitoring site (stream order ≤ 3). Water sample collection proceeded through numerical order of sites starting at 09:00 at site #1.…”