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Soil erosion is a common global problem that has negative impacts on agriculture production, water storage facilities, water conveyance system, and water quality. To assess water erosion problems in catchments, scientists have developed several spatially distributed soil erosion models with various degree of sophistication. Examples are CREAMS, KYERMO, PRORILL, KINEROS2, LISEM, RUSLE, EUROSEM, EGEM, GLEAMS, and WEPP. Precise estimation of mean flow velocity and sediment transport capacity play a vital role in the accuracy of the outcomes of each spatially distributed soil erosion model. Worldwide, Manning and Darcy-Weisbach formulae are commonly used for the quantification of mean flow velocity in shallow overland flows, which were actually derived for stream flow. Likewise, majority of the functions used for sediment transport estimation were originally derived for channel flow. The applicability of stream flow functions has become questionable under overland flow, because the water layer depths and discharges are usually much smaller in overland flow. Moreover, hillslope surfaces are usually rougher than streams. Hence, the main aims of this study were (i) How suitable are the existing approaches and functions that are used for mean flow velocity and sediment transport capacity quantification under overland flow conditions? (ii) Which hydrological and morphological factors affect and control the mean flow velocity and sediment transport capacity? (iii) What are optimal functions for the quantification of mean flow velocity and sediment transport capacity? To address all the research objectives of this study, it was necessary to precisely measure the hydraulic and sediment parameters under overland flow conditions, which was accomplished by conducting flume experiments under controlled conditions. Experiments were carried out in a 3.0 m long and 0.5 m wide rectangular hydraulic flume. Four non-cohesive, narrowly graded, commercially available sands with median grain diameter equal to 0.233, 0.536, 0.719, and 1.022 mm were selected for study of the variation in mean flow velocity and sediment transport capacity with grain size. In order to analyze the impact of slope and flow discharge on mean flow velocity and sediment transport capacity, the flume was inclined at four slope gradients (5.2, 8.7, 13.2 and 17.6%) and applied inflow discharges ranged from 33 to 1033 x 10-6 m3 s-1. To study the impact of the bed geometry on mean flow velocity and also the variation in bed form evolution with grain size, the flume bed was scanned before and after a run with a profile laser scanner. The performance of the five existing sediment transport capacity functions was evaluated for overland flow conditions using graphical and statistical analysis. The results show that the application of these functions is limited to the range of hydraulic and sediment conditions for which each was formulated. Regression analysis was carried out to examine the impact of different hydraulic and sediment parameters i.e. flow discharge, slope gradient, and median grain size on mean flow velocity and sediment transport capacity. The main aim of the regression analysis was to better understand the processes entailed in flow velocity and sediment transport. In view of the strong impact of flow discharge and median grain size on mean flow velocity, an empirical equation was derived for the estimation of mean flow velocity that was calibrated with five literature datasets. In-addition to this, the results of this study exhibit that unit stream power is an optimal composite force predictor for estimating transport capacity. Based on the unit stream power concept, a new physically based transport capacity function was derived by dimensional analysis using the experimental results. The newly derived function was calibrated using the flume experiment results, but validation is still needed for cohesive soils.
|Qualification||Doctor of Philosophy|
|Award date||5 Mar 2012|
|Place of Publication||S.l.|
|Publication status||Published - 2012|
- geological sedimentation