Record extension for short-gauged water quality parameters using a newly proposed robust version of the Line of Organic Correlation technique

摘要

In many situations the extension of hydrological or water quality timeseries at short-gauged stations is required. Ordinary least squaresregression (OLS) of any hydrological or water quality variable is atraditional and commonly used record extension technique. However, OLS tendsto underestimate the variance in the extended records, which leads tounderestimation of high percentiles and overestimation of low percentiles,given that the data are normally distributed. The development of the line oforganic correlation (LOC) technique is aimed at correcting this bias. On theother hand, the Kendall-Theil robust line (KTRL) method has been proposed asan analogue of OLS with the advantage of being robust in the presence ofoutliers. Given that water quality data are characterised by the presence ofoutliers, positive skewness and non-normal distribution of data, a robustrecord extension technique is more appropriate. In this paper, fourrecord-extension techniques are described, and their properties areexplored. These techniques are OLS, LOC, KTRL and a new technique proposedin this paper, the robust line of organic correlation technique (RLOC). RLOCincludes the advantage of the LOC in reducing the bias in estimating thevariance, but at the same time it is also robust in the presence of outliers.A Monte Carlo study and empirical experiment were conducted toexamine the four techniques for the accuracy and precision of the estimateof statistical moments and over the full range of percentiles. Results ofthe Monte Carlo study showed that the OLS and KTRL techniques have seriousdeficiencies as record-extension techniques, while the LOC and RLOCtechniques are nearly similar. However, RLOC outperforms OLS, KTRL and LOCwhen using real water quality records.