+ - Volume 4 ‎(2018)
+ - Volume 3 ‎(2015)
+ - Volume 2 ‎(2014)
+ - Volume 1 ‎(2013)

Using Stochastic Modeling Techniques to Predict the Changes of Total Suspended Solids and Sediments in Lighvan Chai Catchment Area in Iran
Journal: Journal of River Engineering
Issue: Journal of River Engineering (Volume: 2, Issue: 1)
Author: Siamak Boudaghpour , Majid Bagheri , Zahra Bagheri
Keywords : Stochastic models , Time series , Total suspended solids , Environmental effects , Sediment , Estimation
Abstract:

Environmental effects of total suspended solids (TSS) and sediments are noticeable and should be considered in various aspects. On the other hand, determination of exact governing equations to assess the volume of sediments and TSS is difficult due to the effect of various conditions and factors which cannot be determined simply at a period of time. In present research, stochastic modeling techniques were applied to determine the changes of TSS and sediments in Lighvan Chai catchment area located in west north of Iran using earlier recorded data. The stochastic models comprised of two autoregressive models, including AR (1) and AR (2) as well as four autoregressive-moving average models including, ARMA (1,1), ARMA (2,2), ARMA (1,2) and ARMA (2,1). The results of AR (1) and AR (2) models showed almost a perfect match between measured and the calculated values of TSS among these models. The results indicated that for the AR (1) and AR (2) models the sum of squared residuals (errors) according to maximum likelihood test were -.00332 and -.00204 and the mean of residuals were 6.85 and 4.45 respectively. Furthermore, for the AR (1) and AR (2) models the maximum residuals were 1 and 0.8 respectively and the minimum residuals were -0.7 and -0.5 respectively. As a results, the AR (1) models are introduced to assess and predict the volume of TSS and sediments with satisfactory achievements.

Article File : [Download (484.6 kB)] ‎1,182 downloads so far
Concessionaire:
SciJour
Director-in-Chief:
Mahdi Moharrampour
Editor-in-Chief:
Prof. Abdolkarim Behnia