The primary method for measuring suspended sediment concentration (SSC) is the gravimetric analysis of water–sediment samples collected using grab or bottle samplers from the sea or rivers at regular or irregular intervals. Although this method is reliable, it requires substantial effort and cost for sampling, transportation to the laboratory, and long processing times for sample analysis. This study aims to introduce an alternative method for estimating SSC based on measuring the water turbidity (WT) of water–sediment samples. A case study was conducted in the coastal waters of the Caspian Sea to determine the Pearson correlation coefficients between these two parameters.

In-lab calibration between SSC and WT data using site-specific sampling is essential, as the mean particle size and particle size distribution (PSD) can vary considerably in space and time. Therefore, several water–sediment samples were collected from inside and outside the basins of Amirabad and Anzali ports, and grain-size analyses were performed. Subsequently, sediment–seawater mixtures (50 L) were prepared stepwise at eleven concentrations: 125, 250, 500 mg/L and 1, 2, 3, 4, 5, 6, 7, and 8 g/L. For each concentration, WT was measured using a HATCH 2100N turbidimeter and an auxiliary TSW-20 turbidity sensor.

Sieve and hydrometer analyses were conducted, and particle size distribution curves for two water–sediment samples from inside the basins of Amirabad and Anzali ports were plotted. The D10, D30, D50, D60, and D90 statistics were extracted and compared. WT values for the eleven sediment mixtures were measured using the HATCH 2100N turbidimeter. Pearson correlation coefficients between SSC and WT were calculated for linear, second-order polynomial, third-order polynomial, and power regression fittings, and SSC–WT correlation curves were drawn.

A step-by-step alternative method for estimating SSC based on WT measurements using a laboratory turbidimeter was designed. Applying this method to the case study yielded Pearson correlation coefficients between SSC and WT for water–sediment samples from Amirabad Port. The proposed approach is suitable for use in a real-time and continuous sediment monitoring network, enabling the integration of WT as a surrogate parameter for SSC in the national sediment monitoring database.