Analysis and modeling of the spatial variations of sediment in seasonal stream using rainfall simulator

Document Type : Research Article

Authors

1 M.Sc. Student in Watershed Management, Faculty of Natural Resources, University of Torbat Heydarieh, E.Mail: akbari

2 Assistant Professor, Department of Plant Production, Faculty of Agricultural and Natural Resources, University of Torbat Heydarieh,

3 Department of range and watershed management, Faculty of natural resources, university of torbat heydarieh, Khorasan-Razavi, Iran

Abstract

Study of the spatial variations of sediment and its influencing factors, is essential to control it. In this study, the spatial variations of production characteristics and sediment concentration in a seasonal stream located in an erosional pediment, studied. The location of plots at the 50 meters intervals selected and experiments done in 10 locations (with 3 replications). Then a rainfall with rainfall intensity of 1.4 mm/min and duration of 10 minutes, created using rainfall simulator and in the vicinity of each plot, surface soil samples were taken. The statistical analysis performed then using the cokriging method, the spatial distribution of characteristics prepared. The results showed that for sediment concentration variable among 10 locations, was no significant difference, but for the sediment load variable it was significant. The results of fitting experimental models on semivariograms, showed that the best fitted model to the spatial pattern of sediment concentration was gaussian and for sediment load was exponential model, respectively. Also two mentioned variables had strong spatial patterns. The results of the validation of applied model showed that the point-cokriging method has low accuracy to estimate sediment concentration, but for estimation of sediment load, the method has higher accuracy.

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Main Subjects

References

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Iranian journal of Ecohydrology
Volume 5, Issue 2
July 2018
Pages 571-584

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History

  • Receive Date: 23 August 2017
  • Revise Date: 25 November 2017
  • Accept Date: 23 January 2018
  • First Publish Date: 22 June 2018
  • Publish Date: 22 June 2018

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