Bivariate analysis of river flow and suspended sediment load in Aharchai Basin, Iran

چکیده مقاله

Abstract Predicting the suspended sediment load (SSL) in river flow is a principal issue in watershed management and design of water structures along the river. Due to the stochastic nature of runoff and sediment production, probabilistic methods can be used to model these phenomena. In the present study, the dependency structure of river flow and SSL in the Aharchai Basin in Iran was modeled using the copula functions. In this regard, the paired data of river flow and corresponding SSL recorded at Tazekand station in the period 1972–2020 were used. Then, the fitness of different univariate distributions on the observed flow discharge and SSL data was examined. The results revealed that the three-parameter log-normal distribution and the four-parameter Burr distribution had the best fitness on observed flow discharge and SSL data, respectively. Next, the fitness of seven copula functions, including Clayton, Galambos, Gumbel–Hougaard, Ali–Mikhail–Haq, Frank, Farlie–Gumbel–Morgenstern, and Plackett, was examined to create a bivariate distribution of flow discharge–suspended sediment load. The results indicated that the Galambos copula with the dependence parameter θ = 6.8341 had the best fitness on the observed flow discharge–suspended sediment load data of Tazekand station. Therefore, this copula was used to calculate the joint probability and joint return periods, and then, a contour diagram of the joint probability and the joint return period was drawn. These diagrams can be used to estimate the amount of sediment, for a certain probability or return period given a specific flow discharge.