Headwater Catchments: Estimating Surface Drainage Extent Across North Carolina and Correlations Between Landuse, Near Stream, and Water Quality Indicators in the Piedmont Physiographic Region

Abstract

The study used the traditional contour crenulation (T-CC) method to map-measure drainage lengths in seven first-order blue-line (FO-BL) drainage areas located in the Piedmont of North Carolina. They were compared to field measured lengths. Results indicated strong correlations between the lengths (R = 0.98) and between lengths and areas for both methods (R = 0.99 and R = 0.97). Drainage densities for each method were compared using ANOVA and Tukey-Kramer procedures. Mean field-measured and T-CC Dds were not significantly different. Both were greater than the mean FO-BL Dd.

The study was expanded and included 122 FO-BL catchments across five regions. Results indicated that catchment size and map contour intervals were important factors in predicting T-CC lengths. T-CC length prediction equations were tested and T-CC and predicted Dds were compared. Results indicated that mean T-CC and predicted Dds were not different for either region. By region, the T-CC lengths were 2 to 4 times greater than FO-BL lengths.

Macroinvertebrate family taxa richness (FTR) and Hilsenhoff family biotic index (FBI) values were used to assess the near-stream habitat and runoff condition of 33 headwater catchments. Near-stream habitat condition (HR) included bank stability, bank vegetation protection, riparian zone width, and riparian zone vegetation structure. Runoff condition was estimated using curve numbers (CN). Three control sites represented small, medium, and large size-class reference conditions. Catchment areas and the assessment variables were normally distributed within catchment size-classes, as were the CN and FBI variables for the 33 catchments combined.

Relationships between CN and assessment variables, as well as between each variable was examined using linear regression. The analysis was performed for each catchment class-size and for all 33 catchments combined. A strong negative correlation between the CN by HR combination suggested that increased runoff condition is related to decreases in HR. A strong negative correlation between HR by FBI suggested that as habitat quality is reduced, water quality is also reduced. The very strong positive correlation between CN by FBI suggested that increased runoff condition is related to decreases in overall water quality. Regression equations were developed to predict FBIs using CNs.