Variable-ity in power to detect change

Authors: Jacob McDonald*, University of Georgia
Topics: Geomorphology, Water Resources and Hydrology, Quantitative Methods
Keywords: Fluvial Geomorphology, Power Analysis, Change Detection
Session Type: Paper
Day: 4/6/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Hoover, Marriott, Mezzanine Level
Presentation File: No File Uploaded

Power analyses are uncommon in geomorphic research. Tools in Fluvial Geomorphology (Kondolf and Piegay, 2016) explicitly states that power analyses have not been applied to studies of fluvial geomorphology. This study analyzed the results of 66 stream surveys (16 in the Piedmont of Georgia and 50 in the Southern Blue Ridge Mountains of western North Carolina) to determine whether there is sufficient power to detect change. Five levels of correlation (0.5, 0.6, 0.7, 0.8, and 0.9) were used to simulate second surveys. It was assumed that the coefficient of variation of the hypothetical second survey was proportional to the first survey. The results indicate that the power to detect change is site and variable dependent. The main driver of power is the standard deviation of the variable. For the majority of the sites and variables, there was high power to detect change. Wetted width had the lowest power to detect change because of the wide range in variability where different geomorphic channel units occur. The reason why a few sites did not have sufficient power to detect change was because of outlier transects (e.g., presence of floodplain on a few transects in mostly entrenched streams [affecting channel-full widths] or hillslopes encroaching on the stream [affecting channel-full heights]). The results indicate that there is no magic number of transects that will be representative of all variables in a reach. An initial survey should be conducted at each reach to be surveyed to determine the amount of variability in the measured variables.

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