Stochastic Inference to Sediment and Fluvial Hydraulics

Abstract

This forum, supposedly serving as an introduction to the collected stochastic hydraulics papers appearing in this issue, is actually a follow-up of the forum by Dr. Thanos Papanicolaou in the December 1999 issue of this journal, in which a succinct definition of the word stochastic is given. A more extended discussion on the definition of stochastic can be found in Yen ~1988a!. Loosely, a stochastic process may be regarded as a random process that involves space and/or time, or it may be considered as a spatial or temporal process that involves probability. Stochastic hydraulics refers to hydraulic phenomena that are subject to stochastic processes. It is distinctly different from stochastic hydrology, which treats the phenomena without explicitly considering hydraulic principles. There is no shortage of examples of stochastic hydraulic processes: turbulence; flow induced vibration or fluctuation; hydraulic jump; mass; momentum or energy transport and dispersion; safety of hydraulic structures; sediment movement in flow; bed form migration; and stream morphology, just to name a few. Some stochastic perspectives of well known hydraulic problems have been discussed in Yen ~1992!. Traditionally, these problems have been treated in a deterministic manner. As indicated in Table 1, an observed stochastic process can be the product of a deterministic system or deterministic input. With the numerous scientific and popular books and articles on chaos published in the past 2 decades, it is now easy to understand that a system governed by deterministic physical laws, for example, Newton’s second law or the Navier-Stokes equation, can produce stochastic results. Not to mention that even such ‘‘basic’’ laws can themselves be subject to probabilistic analysis ~Chiu 1991!, for example, based on Boltzmann’s concept ~Ghidaoui et al. 2001!. Recasting hydraulic phenomena through the lens of stochastic perspectives can provide a number of benefits, such as: 1. Clarify the physical concept 2. Derive new theoretical concepts 3. Provide a link between stochastic reality and deterministic treatment of hydraulic problems 4. Provide additional or new information for improved design 5. Suggest alternatives to existing hydraulic methods 6. Provide a scientific basis for rational decision making in operational, planning, or management alternatives 7. Serve as a tool in data management for effective planning of data collection and appropriate measurement accuracy