INVERSE OPTIMIZATION METHOD TO DETERMINE LONGITUDINAL DISPERSION COEFFICIENT AND SELECTION OF SAMPLING TIME IN TRACER TESTS

An inverse optimization method is developed for the prediction of longitudinal dispersion coefficients in natural streams. Based on the idea of an inverse problem, the parameter estimation problem was converted to an extreme problem by defining a target function according to the observed concentration profile at a downstream section. A golden section optimization algorithm was applied to the extreme problem solution. As shown by two verified cases, the predicted results indicate that the inverse optimization method can give higher precision for tracer tests. The influencing factors, such as sampling time at the section observed, noise and number of decimal places of the measuring instrument, are analyzed and discussed in detail. It is concluded that the match of sampling time at different observational cross-sections greatly impacts the predicted longitudinal dispersion coefficient. Finally, a new method for determination of reasonable matching sampling times and intervals according to section location is proposed. By this method, the successful calculation of the longitudinal dispersion coefficient can be achieved. This work contributes to the determination of longitudinal dispersion coefficients in tracer tests.