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Evaluation of EGEM model performance in predicting ephemeral gully erosion, case study: Ghoorichay Watershed, Ardabil Province

Document Type : Research Paper

Authors

1 PhD Student,, Faculty of Natural Resources and Earth sciences, University of Kashan, Iran

2 Assistant Professor, Faculty of Natural resource and earth sciences, University of Kashan, Iran

Abstract

Ephemeral Gully (EG) erosion is one of the most destructive types of water erosion, which contributes significantly to land degradation. EG erosion prediction is necessary to assess the magnitude of soil loss and to implement the appropriate conservation measures. The aim of current study  was to evaluate the efficiency of EGEM model for EG erosion prediction in Ghoorichay Watershed, Ardabil Province, Iran. For this purpose, a number of 17 EG erosion was identified and monitored between the years 2014 to 2016. The morphological characteristics and erosion rate of EGs were measured and recorded after seven effective rainfall events. In order to calculate the EG erosion, EGEM model requires four major categories of input data, including identification information, watershed data, soil data, and rainfall data. The model has two major components: hydrology and erosion. The runoff induced by a rainfall event in each gully catchment was determined by the Natural Recourses Conservation service (NRCS) Curve Number (CN). The result of EGEM model performance evaluation showed that the eroded soil volume and cross-section were predicted with a determination coefficient of 0.96 and 0.89, respectively. Sensitivity analysis revealed that the curve number was the most sensitive parameter, so that, with a 10% increasing and decreasing in CN, the volume of soil loss varied 22.98 and -18.92%, respectively. It can be concluded that EGEM model was suitable for event-based EG erosion prediction in Ghoorichay Watershed and it can be recommended for studying and planning on EGs in similar watersheds.

Keywords

References
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Watershed Engineering and Management
Volume 12, Issue 2
July 2020
Pages 365-379
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