Determining the trend of suspended sediment changes for selected river basins during recent decades

Many Iranians believe that the amount of erosion and sedimentation is annually increasing. This opinion was based on expert /empirical estimates not on rigorous research/measurement. Previous studies have failed in assessing its accuracy due to the lack of sufficient input data and method failing as well. This study has attempted to assess the trend in river sediment in seven measuring sites in Iran having relative adequate sediment data collected during 30 to 40 years. Several hydrological and statistical methods were used to examine sedimentation trends. The sediment yield data was anlyzed as well as sediment concentration and flow rate data; since changes in the first one is a function of changes in the two subsequent factors. Given the importance of flood flows on transporting of more than 85% suspended sediment, the sediment trend was studied with whole flow data at first which was then followed by using one to three tenth of high efficient discharges only. Furthermore, the analyses were performed in two scales; the entire period and by dividing it into 3-4 decades. Finally, the results of three methods including hydrologic, Kruskal-Wallis and Kendall correlation on the last tenth of discharge data were chosen for determination of sediment trend. Different charts under the hydrologic method were showed better flexiblility than those two statistical methods to investigate sediment trend. However, nonparamethrric Kendal statistics were able to distinguish the trend direction and its significance level as well. While, Ghazaghly showed a significant increasing trend during the study period; significant decreasing trends in suspended sediment weight were seen in three sites namely Karesang, Gilavan and Loshan.Three remained gauging sites showed insignificant trends. Therefore, the conventional increasing trend hypothesis in sedimention rates is not true in all parts of Iran and it should be studied in each river basin based on intensive hydrologic data collection.