Detecting base flow impacts in Coastal Plain streams. A major objective of the study was to assess the sensitivity of the different methods in detecting base flow changes. Base flows represent streamflows that are derived entirely from ground water. I subjected base flows at two continuously gaged Pinelands study sites to simulated flow reductions. I then used simple linear regression to relate base flows at these two sites to base flows at five Pinelands index sites generally unaffected by major streamflow impacts.
Residuals are the predicted study-site base flows subtracted from the actual values.
I used the smallest-detectable percentage reduction within a given simulation that was significant at an alpha level of 0.10 as an estimate of the sensitivity of a trend test. Autocorrelation or serial correlation in regression analysis describes a condition where the residuals are dependent or correlated to each other through time. Autocorrelation arose when the time intervals between samples were short. My analysis also revealed that when data were missing for a particular sampling event, the ability to detect autocorrelation decreased. Trend-test sensitivity appeared to improve when the number of sampling events before and after a base flow impact were equal.