African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6688

Full Length Research Paper

Factors controlling suspended sediment yield from catchments in central Ardabil Province, Iran

Abazar Esmali Ouri* and Ardavan Ghorbani
  Department of Range and Watershed Management, University of Mohaghegh Ardabili, P. O. Box: 179, Ardabil, Iran.  
Email: [email protected]

  •  Accepted: 05 September 2011
  •  Published: 12 October 2011



Twenty two catchments were equipped to hydrometric stations and 9.5 to 7482 km2 were selected in central areas of Ardabil Province, Iran, and have been a site for collection of suspended sediment yield data since 46 years ago. Various catchment properties were analyzed in order to recognize the effective factors controlling suspended sediment yield. Selected effective factors were mapped and classified in geographic information system (GIS). The mean suspended sediment yield of each catchment was estimated using mean load within discharge classes method and available data. Area specific sediment yield varies from 6.5 to 449.5 t km-2 year-1for the selected catchments. Relationships among different geo-environmental and climatic factors and suspended sediment yields using multiple regressions were derived the most effective controlling factors. From these analyses, some regional models were derived for suspended load yields. The results showed that the main factors controlling suspended sediment yield in the study area are: catchment area, mean annual discharge, peak discharge, geological formation susceptibility, mean catchment slope, mean channel slope and mean annual temperature. Moreover, it was concluded that using the values of Napierian Logarithm (LN) of sediment yield and controlling factors can lead to better results in multiple regressions. Furthermore, assessment of the presented models in some eastern catchments of the study areas showed that, a multiple regression model including some catchment properties is a valuable tool to predict total and specific sediment yields in central Ardabil Province. Finally, results showed that a normal multiple regression model can explain 73% of total sediment yield, and a Napierian multiple regression model can explains 78% of specific sediment yield.


Key words: Erosion, sediment, geo-environmental factors, regression models, geographic information system (GIS).