Abstract:
Transport Effectiveness (TE) of a discharge is defined as the product of the frequency of discharge and corresponding sediment transport rate. Maximization of TE function helps in finding the “effective discharge (Qe)” which is responsible for the transfer of the majority of sediments over a prolonged period. This approach to determine Qe is famously known as Magnitude-Frequency Analysis (MFA). Conventionally, MFA involves the construction of the TE function by assuming (i) a location-specific probability density function (PDF) for discharge and (ii) power-law relationship between discharge and sediment transport rate. There have been attempts in the past to derive expressions for Qe by assuming positively skewed PDFs for discharge. The present study proposes a modified approach to estimate TE-based Qe for general discharge distribution datasets which alleviates the limitation of assuming a location-specific PDF. The approach involves the transformation of discharge data through Box-Cox transformation and subsequently performing MFA to determine Qe. An expression for the analytical solution of TE-based Qe is derived for the proposed framework of MFA. The robustness of the approach is established through a simulation study by generating discharge data using lognormal, Gamma, and log Pearson type III distributions. In this study, the influence of the hysteresis effect was investigated for total as well as seasonal datasets according to the considerations of the rising and falling stages for 14 stream gauges in South Indian Rivers. The analysis is performed by using the suspended sediment load and discharge data whereas the bedload has been excluded. Subsequently, the estimates of Qe based on the proposed approach (QePA) were computed considering various sediment rating curves fitted for total, seasonal, stage and season-stage based datasets. Finally, the variation of QePA with various catchment descriptors was examined.
