A new approach for suspended sediment load calculation based on generated flow discharge considering climate change

Abstract

Use of general circulation models (GCMs) is common for forecasting of hydrometric and meteorological parameters, but the uncertainty of these models is high. This study developed a new approach for calculation of suspended sediment load (SSL) using historical flow discharge data and SSL data of the Idanak hydrometric station on the Marun River (in the southwest of Iran) from 1968 to 2014. This approach derived sediment rating relation by observed data and determined trend of flow discharge time series data by Mann-Kendall nonparametric trend (MK) test and Theil-Sen approach (TSA). Then, the SSL was calculated for a future period based on forecasted flow discharge data by TSA. Also, one hundred annual and monthly flow discharge time series data (for the duration of 40 years) were generated by the Markov chain and the Monte Carlo (MC) methods and it calculated 90% of total prediction uncertainty bounds for flow discharge time series data by Latin Hypercube Sampling (LHS) on Monte Carlo (MC). It is observed that flow discharge and SSL will increase in summer and will reduce in spring. Also, the annual amount of SSL will reduce from 2,811.15 ton/day to 1,341.25 and 962.05 ton/day in the near and far future, respectively. HIGHLIGHTS Use of data generation methods and trend tests for detection of climatic change.; Determination of 90% of total prediction uncertainty bounds by LHS on MC.; Increase of monthly flow discharge and SSL in summer from 2014 to 2094.; Reduction of monthly flow discharge and SSL in spring from 2054 to 2094 .;

Keywords

• flow discharge
• latin hypercube sampling
• markov chain method
• monte carlo method
• suspended sediment loads