| Abstract: | ABSTRACT: The detection of change in a hydrologic varaible, particularly water quality, is a current problem. A method is presented for testing whether there has been a shift in the mean of a hydrologic variable based on the well established bivariate normal distribution theory. In this technique, the dependent, or target, and the independent, or control, variables are formed as weighted linear combinations of the mean values at a number of locations in a selected target and control area. The weighting factors are determined based on a mathematical programming technique which minimizes the conditional coefficient of variation thereby minimizing the number of observations required to detect a change of a preselected magnitude in the mean of the target area. The result is a situation where a savings in the number of observations required to detect a change is a consequence of adding more stations: the space-time tradeoff. Two applications of the technique are presented, the first using electrical conductivity (EC) data from two sets of river basins and the second using EC data from a set of basins as the target variable and annual discharge as the control. The results indicate that a significant savings in time can be achieved by using this method. |
