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.
yaser ghasemi aryan; yaser Ghasemi aAryan; ali kiani rad
nasim arman; Ali Salajegheh; Sadat Feiznia; Hassan Ahmadi; Jamal Ghoddousi; ali kiani rad
Abstract
Identification of homogenous watershed sub basins allows generalization of environmental study results. For this purpose, first available data for 27 selected watersheds in North Alborz regarding 21 variables including physiographic and climatic characteristics was gathered. The most important factors ...
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Identification of homogenous watershed sub basins allows generalization of environmental study results. For this purpose, first available data for 27 selected watersheds in North Alborz regarding 21 variables including physiographic and climatic characteristics was gathered. The most important factors impacting upon soil erosion and sediment yield were equivalent rectangular length, mean annual precipitation, rock susceptibility, aspect and drainage density which were identified using factor analysis (Principle Component Analysis : PCA) and a 80.72 percent variation of data was observed (KMO =0.516). For determination of homogenous region, different methods of cluster analysis (hierarchical, K-means and two step clustering) were used and three homogeneous regions were specified. Discriminant function analysis was employed and confirmed the results of cluster analysis in homogenous region. On the other hand, based on these five factors, a discriminant function was defined and canonical correlation, chi-square, wilks’ lambda values revealed that three homogenous regions were quite separate.