Optimal Estimation of Suspended-Sediment Concentration in Streams (Case Study: Khozestan Province)

Suspended load and stream flow sampling carry out in order to  knowledge of upland watersheds erosion-sediment rate. Suspended load  direct measurement  should have carry out  for most flows but this work operated with unequal intervals and  in other hand is needed to estimates accuracy of concentrations mean. since data have asymmetry and skewness , optimal estimator evaluation for biass reduction is effective. Therefore in this research use from Kalman filter for on-line estimation and an associated smoother for off-line estimation then these estimators compare with generalized least squares and flow-weighting regression estimators. The optimal online and off-line estimator (Kalman smoother) had the lowest error characteristics of those evaluated. Comparison of online and off-line estimator indicate that off-line estimator  have less estimate error and  is used for estimation of suspended-sediment concentrations.