vahid chitsaz; Aliakbar Nazari Samani; Saeed Soltani; sadat feiznia
Abstract
Sediment and erosion are two natural phenomena in watersheds. Due to irregular recording and sampling difficulties, daily data are not available for sediment records. Therefore, decision makers and researchers have to apply interpolating methods to estimated sediment yields. In this study, 30 watershed ...
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Sediment and erosion are two natural phenomena in watersheds. Due to irregular recording and sampling difficulties, daily data are not available for sediment records. Therefore, decision makers and researchers have to apply interpolating methods to estimated sediment yields. In this study, 30 watershed characteristics including physiography, geomorphology, vegetation, climate conditions in 69 watersheds located in the Karoon and Karkheh basins were used to statistical analysis. Based on the principle component analysis, eight characteristics including area, perimeter, river length, relief, mean of elevation at 85% upstream and 15% point of longest flow path and the number of landslide events were selected. Then using Cluster Analysis, six homogenous regions were identified and multiple regression models were applied. Due to constriction of large dames on the studied watersheds, access to the reliable data is a challenges for sediment yield analysis. Based on the sediment-precipitation double-mass curves 29 out of 35 stations were influenced by upstream dam. Results indicated that the effects of large reservoir dams can influence the downstream sediment yield along 98 Km of river length. The results show that in each group a particular combination of variables influence the sediment yields of the watersheds. According to the validation indices (NS and R2) the obtained models have the high performance (R2 = 0.71 and NS=0.72). In general, the physiographic characteristics of the watershed such as length, area, main flow path and relief are more important than other climatic, vegetation and geological factors. The total explain variance by the mentioned variables is 87.3%.
