Stochastic Modeling and Long-Term Forecasting of Suspended River Sediment

In the past years the climate change has altered the behavior of river flow and led to more frequent extreme hydrological events such as flash floods with high sediments. This has made it very important to know the different characteristics of river sediments when planning for and designing water structures. In this study, a new Standardized Sediment Index (SSI) was developed and different characteristics of sediment, including probability density function (PDF), magnitude, intensity, etc., were determined for the western of Lake Urmia basin using a Monte Carlo simulation process. For this purpose, first, the sediment data was determined according to different models of rating curve, and then the synthetic data series of sediment (1000 series) were generated using a suitable stochastic model and were used to determine different characteristics of sediment. The results showed that in most stations, the method of estimating the rating relationship according to the innovative method of this study, i.e. using the flow discharge index method to classify the relationship between flow and sediment, has the higher performance compared to other methods proposed in different studies. Also, the PDF of sediment data completely follows the normal distribution, as expected from a normalized natural process, and has a systematic behavior with skewness data. Finally, the results of this study are a comprehensive guide for accurate and real inference of river sediment phenomenon according to the SSI index and can significantly reduce the damages caused by sediments.