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Accuracy and precision of methods for estimating river loads
Author(s) -
Ferguson R. I.
Publication year - 1987
Publication title -
earth surface processes and landforms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 127
eISSN - 1096-9837
pISSN - 0197-9337
DOI - 10.1002/esp.3290120111
Subject(s) - rating curve , statistics , sampling (signal processing) , data set , sample size determination , mathematics , environmental science , soil science , sediment , hydrology (agriculture) , computer science , geology , geotechnical engineering , paleontology , filter (signal processing) , computer vision
Abstract River loads often have to be estimated from continuous discharge data but relatively infrequent sampling of sediment, solute, or pollutant concentrations. Two standard ways of doing this are to multiply mean concentration by mean discharge, and to use a rating curve to predict unmeasured concentrations. Both methods are known from previous empirical studies to underestimate true load. Statistical considerations explain these biases and yield correction factors which can be used to obtain unbiased estimates of load. Simulation experiments with normally‐distributed scatter about log‐linear trends, and sampling experiments using a natural data set, show that the corrected rating curve method has lower sampling variability than other unbiased methods based on average instantaneous load and is thus the recommended procedure when the rating plot is of the assumed form. The precision of all methods increases with sample size and decreases with increasing rating‐curve slope and scatter.