Page - 978 - in Book of Full Papers - Symposium Hydro Engineering

many times. The accuracy of the results increases as the number of simulations is increased. Application of Monte Carlo simulation in geotechnical engineering and its extension to correlated variables has been demonstrated by Nguyen and Chowdhury [15,16]. Such uncertainties have systematic components. Systematic uncertainty includes statistical error in the mean due to insufficient number of tests or observations (small sample size) and bias in measurement methods. Over relatively short distances, the value of a geotechnical parameter may vary far more from the mean value than it does if averaged over relatively long distances. Thus, estimating the standard deviation of a geotechnical parameter requires careful analysis of data. Therefore, in this paper the Monte Carlo method was adopted to evaluate the stabilizing effect of vegetation in order to improve the economic efficiency as well as conserving environment. Depend on the desired level of confidence in the solution, as well as the number of variables being considered, the number of required Monte Carlo trials is calculated from Eq. 4. 𝑁 = [ 𝑑 2 4(1−𝜀 )2 ]𝑧 [4] Where N is number of Monte Carlo trials, ε is the desired level of confidence (0 to 100%) expressed in decimal form, d is the normal standard deviation corresponding to the level of confidence illustrated in Fig. 3 and z is number of variables [17]. The standard deviation is considered 1.645 (with the level of Figure 1. Probability distribution functions for parameters in unrooted system Figure 2. Probability distribution functions for additional parameters in rooted system (T and cR) 978