Shahid Chamran University of AhvazIrrigation Sciences and Engineering2588-595240320171122An Evaluation of various developing methods for sediment rating curve and computer simulationmodels for sediment load estimation in Mazandaran basin, IranAn Evaluation of various developing methods for sediment rating curve and computer simulationmodels for sediment load estimation in Mazandaran basin, Iran1511661331310.22055/jise.2017.13313FAJournal Article20160130A sediment curving rate is a method to describe the relationship between river discharge and suspended sediment load for a particular location. The rating curves have been used to predict sediment load by hydrologists for more than sixty years (Horowitz, 2002). Obtaining more accuracy in determination of sediment load needs to long-term continuous data with a sufficient frequency. Mostly, a power function regression is used for sediment rating curves (Asselman, 2000): <br /> <br />Q<sub>s</sub>= aQ<sup>b</sup> (1) <br /> <br />The other form of this equation is linear log-transformation: <br /> <br />Log (Q<sub>s</sub>) = log (a) + b log (Q) (2) <br /> <br />Where Q is river discharge (m<sup>3</sup>/s), Q<sub>s</sub> is suspended load discharge (ton/year), and a and b are regression coefficients . The back transformation of the sediment load to the arithmetic domain creates a bias which can lead to load underestimation (Crowder et al. 2007). The main objective of this study is to determine the sediment rating curve for different 26 hydrometric stations in the Mazandaran basin, Iran, with various data separation methods (daily, monthly, seasonal, annually, classified, and high discharge and low discharge flow months). The efficiency of each rating curve was evaluated using different statistical characteristics. Another objective is to evaluate the sediment load and sediment yield of Mazandaran basin.A sediment curving rate is a method to describe the relationship between river discharge and suspended sediment load for a particular location. The rating curves have been used to predict sediment load by hydrologists for more than sixty years (Horowitz, 2002). Obtaining more accuracy in determination of sediment load needs to long-term continuous data with a sufficient frequency. Mostly, a power function regression is used for sediment rating curves (Asselman, 2000): <br /> <br />Q<sub>s</sub>= aQ<sup>b</sup> (1) <br /> <br />The other form of this equation is linear log-transformation: <br /> <br />Log (Q<sub>s</sub>) = log (a) + b log (Q) (2) <br /> <br />Where Q is river discharge (m<sup>3</sup>/s), Q<sub>s</sub> is suspended load discharge (ton/year), and a and b are regression coefficients . The back transformation of the sediment load to the arithmetic domain creates a bias which can lead to load underestimation (Crowder et al. 2007). The main objective of this study is to determine the sediment rating curve for different 26 hydrometric stations in the Mazandaran basin, Iran, with various data separation methods (daily, monthly, seasonal, annually, classified, and high discharge and low discharge flow months). The efficiency of each rating curve was evaluated using different statistical characteristics. Another objective is to evaluate the sediment load and sediment yield of Mazandaran basin.https://jise.scu.ac.ir/article_13313_554ab112ff97d55852ccb881045de47a.pdf