Zahiri, J; Mollaee, Z; Ansari, MR (2020). Estimation of Suspended Sediment Concentration by M5 Model Tree Based on Hydrological and Moderate Resolution Imaging Spectroradiometer (MODIS) Data. WATER RESOURCES MANAGEMENT, 34(12), 3725-3737.

The Estimation of suspended sediment concentration (SSC) is an important factor in river engineering, which is used as an indicator of land-use change, water quality studies, and all projects related to constructions in rivers. In this research, the M5 model tree and the Moderate Resolution Imaging Spectroradiometer (MODIS) data were utilized to estimate the SSC at Ahvaz station on the Karun River. In this study, 135 cloud-free images of the MODIS sensor on the Terra satellite were taken for days corresponding to field SSC data, during the years 2000 to 2015. Input parameters of the model tree in this study were flow discharge, derived from hydrological data, and red (R), near-infrared (NIR) bands, and NIR/R ratio extracted from MODIS imagery. The results of statistical analysis illustrate that the M5 model outperforms the sediment rating curve (SRC) method, which is the most common method of estimating suspended sediment load. The Nash-Sutcliffe efficiency index for the M5 model tree of 0.58 was achieved, which was much better than that of the SRC method (0.26). At high fluxes, the efficiency of the SRC method significantly reduced, while the model tree provides acceptable results. The global sensitivity analysis on the M5 model pointed out that 93% of output variance was established by the main effects of input parameters, and less than 7% belong to the interaction effects. 73% and 12% of output variance specified by the main effects of flow discharge and NIR/R ratio, respectively.