Strategic Assessment of Dam Overtopping Reliability Using a Stochastic Process Approach

Abstract

Earth-fill dam overtopping could pose significant threats to public safety if the necessary reliability assessments are not taken into consideration in the design process. Dam overtopping is caused by several hydrometeorological random variables, including intensive rainfall, flood or flash flood, and wind coupled with waves. Because random variables are the main effective variables, a stochastic processes can be used to capture the leading failure factors. This study proposes a load-resistance-based approach to assess the reliability of Jamishan Dam, Iran, overtopping by considering several random variables simultaneously. Uncertainty sources such as (1) parameters of the hydrological model (e.g., loss, base flow, and unit hydrograph parameters), (2) hydraulic parameters (coefficient and length of spillway parameters), (3) initial reservoir water level, (4) wave height (e.g., wind setup and wave run-up parameters), and (5) rainfall parameters, are quantified using the Monte Carlo simulation (MCS) technique. Besides, the impact of stochastic sources and dam dimension design on overtopping reliability is considered through two indices, called reliability relative difference index (Rd) and reliability variation index (Rv). The uncertainty of hydrological parameters is quantified using the generalized likelihood uncertainty estimation (GLUE) method, which helps to extract their posterior probability distribution functions (PDFs). Reliability of dam overtopping has negligible sensitivity on the performance measures and behavioral threshold value of the GLUE approach. Results indicate that rainfall depth (Rd=2.04) is the most significant random variable affecting the overtopping reliability, with hydraulic random parameters (Rd=0.1) as the minimum level. Loss parameters (Rd=0.47) have the highest impact on overtopping reliability compared with other hydrological parameters. Overall, the significant of the stochastic sources such as meteorological parameters (e.g., rainfall depth, duration, and pattern), and hydrological parameters (e.g., loss parameters) on dam overtopping should be further studied to obtain reliable perspective for decision makers.