The suspended sediment rating curve model is widely used to estimate river suspended sediment load in the coastal area. In this study, an attempt was made to develop a suspended sediment curve model using simple methods, and to evaluate the developed models, the Nash–Sutcliffe criterion was used along with the graphical criterion. The recorded data from 10 hydrometric stations in the Ghareh-Sou coastal watershed, located in northern Iran, were used to investigate the developed models. Based on the average (A) and median (M), the river discharge data were divided into four categories: A1, A2, A3, A4 and M1, M2, M3, M4, and different models were divided into two parts (A1A2–A3A4 and M1M2–M3M4), three parts (A1–A2A3–A4 and M1–M2M3–M4) and four parts (A1–A2–A3–A4 and M1–M2–M3–M4) were created. The average Nash–Sutcliffe criterion in the conventional model of suspended sediment rating curve was equal to 0.19 which in the models A1A2–A3A4, A1–A2A3–A4, and A1–A2–A3–A4, respectively (0.58, 0.66 and 0.66) and in models M1M2–M3M4, M1–M2M3–M4, and M1–M2–M3–M4, respectively (0.47, 0.60 and 0.60). Considering the Nash–Sutcliffe criterion values in different models, it can be concluded that classification has had a significant effect on improving the accuracy of the suspended sediment rating curve model. The results show that in the classification with average and median, the accuracy of modeling in the number of classes 3 and 4 is the same, and therefore the optimal number of classes is equal to 3. In addition, classification based on average relative to median has led to a more accurate estimation of suspended sediment load. Also, the study of the coefficient of variation of the Nash–Sutcliffe criterion in different models shows that the classification of data based on the average and median has reduced the variability of the estimate of suspended sediment load, which increases the reliability of the developed models. The graphical criterion also confirms that the developed models have improved the estimate of suspended sediment.

悬沙额定曲线模型广泛用于估算沿海地区河流悬沙负荷。在本研究中，尝试使用简单的方法开发悬浮泥沙曲线模型，并使用纳什-萨特克利夫准则和图形准则来评估开发的模型。位于伊朗北部的 Ghareh-Sou 沿海流域的 10 个水文测量站记录的数据被用来研究所开发的模型。根据平均值（A）和中位数（M），将河流流量数据分为四类：A1、A2、A3、A4和M1、M2、M3、M4，不同模型分为两部分（A1A2-创建了 A3A4 和 M1M2–M3M4）、三个部分（A1–A2A3–A4 和 M1–M2M3–M4）和四个部分（A1–A2–A3–A4 和 M1–M2–M3–M4）。常规悬浮泥沙评级曲线模型中的平均 Nash-Sutcliffe 准则等于 0.19，在模型 A1A2-A3A4、A1-A2A3-A4 和 A1-A2-A3-A4 中分别为 0.58、0.66 和 0.66在型号 M1M2–M3M4、M1–M2M3–M4 和 M1–M2–M3–M4 中，分别为（0.47、0.60 和 0.60）。考虑不同模型中的Nash-Sutcliffe准则值，可以得出分类对提高悬浮泥沙评级曲线模型精度有显着效果。结果表明，在均值和中值分类中，类数3和4的建模精度相同，因此最优类数等于3。此外，基于均值相对于中值的分类可以更准确地估计悬浮沉积物负荷。此外，对不同模型中纳什-萨特克利夫准则变异系数的研究表明，基于平均值和中位数的数据分类减少了悬浮泥沙负荷估计的变异性，从而提高了所开发模型的可靠性。图形标准还证实所开发的模型改进了悬浮沉积物的估计。