Stochastic Analysis of Inundation Simulations and Evacuation Planning
Date Issued
2015
Date
2015
Author(s)
Shih, Yi-Hsuan
Abstract
Flood inundation is one of the most usual hazards in Taiwan. To mitigate the impact of flood, inundation mapping plays a significant role. In general, a deterministic approach using optimal parameter sets is applied to analyze the inundation. However, without taking the impact of uncertainties into consideration, it may cause over or underestimate of the model. The stochastic process will improve the weakness of deterministic model. Also, it provides a better basis for decision makers, for example, evacuation planning. Although stochastic approach considers the influence of uncertainties, it is often a time consuming process. In the study, four sampling strategies (Monte Carlo Simulation, Latin Hypercube Sampling, Maximin Distance, Minimum Correlation), three uncertainty factors are applied to a one dimensional hydraulic model. The uncertainty factors include five water flows as upper boundary condition, five water stages as lower boundary condition, and seventeen manning roughness coefficients. The mean water stage of 425 combination of parameter sets are taken as a reference in comparison of each sampling strategy. Result represents that Latin Hypercube sampling performs almost ten times better than Monte Carlo simulation. And though other sampling strategies can enhance sampling discrepancy, the improvement of the result is not significant. The sample size chosen may depend on the tradeoff between acceptance accuracy of model and computational time. The suggested sample sizes are 35% and 50% of total simulation area. The study also proposes a multiobjective stochastic programming analysis for uncertain inundation evacuation. A two stage stochastic programming model under inundation uncertainty is built. Expansion of shelter capacity is decided in the first stage before flood. The second stage determines the evacuation plan providing the optimal route to shelters for all evacuees. A case study of MuZha, Taipei is conducted. Based on the result of hydraulic model, three different regions of warning zone for overflow are taken to be the uncertainty resource. The model with multiobjective shows the tradeoff between shelter expansion and transportation time. The result shows that as the unit cost of shelter expansion exceed to a certain level, the total evacuation time and amount of shelter expansion will remain the same. It represents the minimum shelter expansion and maximum evacuation time. From the hydraulic model to optimal programming, the study focuses on how uncertainty affects the models, provides a decision making system for flood inundation.
Subjects
Uncertainty
Latin Hypercube Sampling
Flood simulation
multiobjective stochastic programming
evacuation planning
SDGs
Type
thesis