sedigeh mohamadi; Ali Salajegheh; Hassan Ahmadi; Jamal Ghoddousi; Ali Kianirad
Abstract
Suspended sediment load is the biggest non-point pollution source and a major factor of degradation of surface water quality. Because of hydraulic models of sediment transport can not predict the suspended sediment load, sediment rating curves as usual hydrological methods are utilized spread for this ...
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Suspended sediment load is the biggest non-point pollution source and a major factor of degradation of surface water quality. Because of hydraulic models of sediment transport can not predict the suspended sediment load, sediment rating curves as usual hydrological methods are utilized spread for this goal. Cause of regression equations of rating curve have a lot of bias due to logarithmic convert, correction factors in optimization of sediment rating curve were used for eliminating of logarithmic conversion effect and bias of extrapolation in 20 hydrometric stations in up streams and major rivers of Sefidrood watershed. Comparing of 9 rating curve methods as one-linear, one-linear with correction factors as CF1, CF2, FAO, two-linear, mean loads within discharge classes, mean loads within discharge classes with correction factors as CF1, CF2 and FAO was conducted by RMSE and NASH criteria. Results showed that mean loads within discharge classes, mean loads within discharge classes with CF1 and CF2 correction factors have the most fitting to Sefidrood watershed stations. Our findings illustrated that CF1 and CF2 correction factors in majority of stations have compensated underestimation of rating curves and increased efficiency of models. Power of equation between sediment load and area was more than of one. According to results 30 million ton suspended sediment load enter to reservior of Sefidrood dam annually. Key words: sediment rating curve, Sefidrood, model efficiency, logarithmic conversion, NASH criteria.
