Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 505727
Title Modeling Sediment Yield in Semi-Arid Pasture Micro-Catchments, NW Iran
Author(s) Vaezi, Ali Reza; Abbasi, Mohammad; Bussi, Gianbattista; Keesstra, Saskia
Source Land Degradation and Development 28 (2017)4. - ISSN 1085-3278 - p. 1274 - 1286.
DOI http://dx.doi.org/10.1002/ldr.2526
Department(s) Soil Physics and Land Management
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2017
Keyword(s) Check dams - Sediment production - Slope steepness - Soil organic matter - Vegetation cover
Abstract Modeling sediment yield is a complex task because of the nonlinearity of natural processes intervening at slope and basin scale. In this study slope steepness, vegetation cover, and soil properties along with sediment yield were studied in 20 pasture micro-catchments in a semi-arid region, NW Iran in order to understand and predict sediment yield. The micro-catchments included only one first-order gully and drain toward a rock check dam in the outlet. The sediment yield of each micro-catchment was calculated using the measurement of sediment mass in the check dams for a 16-year period (1994-2010). Relationships between sediment yield and drainage characteristics were analyzed using correlation matrix and multiple linear regression method. Based on the results, sediment yield in the micro-catchments varied from 0.29Mgha-1y-1 to 14.81Mgha-1y-1, with an average of 5.04Mgha-1y-1. It was significantly related to slope steepness, vegetation cover, and soil organic matter using a linear regression equation (R2=0.87, p
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