Probabilistic delineation of hyporheic zone depth using heat transfer analysis

Abstract

Delineating the hyporheic zone, where groundwater and surface water mix, is of great importance for managing groundwater contamination introduced through surface water. A prior study proposed a method for estimating the hyporheic zone’s depth using heat transfer analysis; this approach’s high sensitivity compared with conventional tracer tests made it more appropriate for delineate the hyporheic zone depth. However, that method treated all related parameters as deterministic values, while real-world parameters are not fixed but vary widely around their means. In this study, we improved on this approach by converting it into a probabilistic method, in which the principal parameters in the governing equation were considered random values and were sampled using Monte-Carlo simulation. We conducted repeated heat transfer analyses for each case and collected the resulting hyporheic zone depths as probabilistic distributions. This allowed us to calculate the distribution of the hyporheic zone and its mean value more accurately and time-efficiently.