Assessment, simulation and comparison of runoff on coarse and fine soil textures under traveling rain-gun machine

Document Type : Original Article

Author

Associate Professor of Water Engineering, Shahrekord University, Shahrekord

Abstract

Abstract
Although moving sprinkler systems such as traveling rain-gun are usually designed, so that the instantaneous water application rate which is associated with low pressure is less than the soil final infiltration rate to avoid runoff; there are a growing number of sprinkler systems where potential runoff increases so much causing soil erosion. Moving sprinkler systems such as travelling rain-gun and center pivot can have excessively high water application rates and are prone to runoff problems. This is exacerbated by the trend to low pressure operation, for the reason of saving energy which adds to the problem. The purpose of this paper is to assess, compare and simulate a more fundamentally based approach to predict runoff from sprinkler irrigation systems under moving rain gun conditions on coarse and fine soil textures practiced on both simple plane and ridge and furrow. Experiments were carried out on both simple plane and ridge and furrow plots sloped 0.67 percent with three replications. A travelling rain-gun with length of 200 m was employed to generate rainfall at three different speeds. Results showed no runoff with runoff coefficient of zero on coarse soil. However, a remarkable runoff with coefficient of 0.162 was considered from the fine soil texture on both simple plane and ridge and furrow practices plots, as machine run with the speed of 10 m/hr. Therefore, one of the approaches to overcome runoff problem and increasing irrigation coefficient is using this system over fine soil textures. On the hand, as much as the machine speed is lower, the potential for runoff is larger. In addition to field experiments, there was a good relationship between observed and predicted runoff using EUROSEM. This is because of a high regression coefficient (R > %90) and minimum Residual Mean Square Error (RMSE < 0.2) between them

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