en Numerical Investigation مقاله پژوهشي Research Paper <span style="color:#000000;"><span style="font-size:11.0pt"><span new="" roman="" times="">Numerical modeling is the most common approach for predicting harbor channel siltation. It requires a comprehensive calibration process because there are several calibration parameters. The most crucial criterion for model calibration is suspended sediment concentration (SSC). The agreement between the measured and simulated SSC time series is usually verified based on generic statistical parameters such as RMSE and R^{<span style="position:relative"><span style="top:-3.0pt">2</span></span>}. This method does not address the important phenomena related to channel siltation; for instance, the siltation rate during neap and spring tidal cycles cannot be distinguished in such manner. A process-based calibration procedure has been proposed in this paper which considers some criteria facilitating the calibration processes. Based on analyzing the measured turbidity and current speed data, some criteria were established which convey underlying phenomena affecting sediment transport. They are: (1) the difference between maximum SSC (or turbidity) at neap and spring and (2) at ebb and flood tide, (3) the minimum turbidity at slack water during spring tide, and (4) the current speed-SSC (or turbidity) regression curve. The proposed procedure has been used to calibrate channel siltation in a real case study: Shahid Rajaee port access channel located in the Khoran strait, Iran.</span></span><span style="font-size:11.0pt"><span new="" roman="" times=""> As </span></span><span style="font-size:11.0pt"><span new="" roman="" times="">the underlying phenomena affecting sediment transport was considered, the number of simulation runs for calibration processes were considerably decreased.</span></span></span> Mud Transport,Model calibration,Shahid Rajaee Port,Suspended sediment transport,Channel siltation 43 56 http://ijmt.ir/browse.php?a_code=A-10-7630-1&slc_lang=en&sid=1 Seyed Mojtaba Hoseini Chavooshi sm.hoseini@stu.qom.ac.ir 10031947532846004234 10031947532846004234 No University of Qom Reza Kamalian ur.kamalian@qom.ac.ir 10031947532846004235 10031947532846004235 Yes University of qom