Handbook of Erosion Modelling 2010
DOI: 10.1002/9781444328455.ch2
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Model Development: A User's Perspective

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Cited by 11 publications
(6 citation statements)
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“…Now, applying model efficiency coefficient (MEC) into the relation between observed and predicted data (Equation ( 12)), it is found that MEC value of RUSLE is 0.48 (Table 10). The MEC > 0.50-0.70 signifies good and satisfactory performance of model in reference to observed erosion results (Morgan, 2011).…”
Section: Predicted Erosion Rate and Comparisonmentioning
confidence: 75%
See 1 more Smart Citation
“…Now, applying model efficiency coefficient (MEC) into the relation between observed and predicted data (Equation ( 12)), it is found that MEC value of RUSLE is 0.48 (Table 10). The MEC > 0.50-0.70 signifies good and satisfactory performance of model in reference to observed erosion results (Morgan, 2011).…”
Section: Predicted Erosion Rate and Comparisonmentioning
confidence: 75%
“…The model efficiency coefficient (MEC), firstly proposed by Nash and Sutcliffe (1970), is now increasingly used an alternative to the correlation coefficient to express the performance of model (Morgan, 2011). Generally, a MEC value of greater than 0.5 is considered that the model performs satisfactorily in the region, and one should not expect values to exceed 0.7 (Morgan, 2005(Morgan, , 2011.…”
Section: Model Validation and Effectiveness Coefficientmentioning
confidence: 99%
“…USLE, RUSLE) are based on experimental observations and on statistical relations between soil loss and erosion factors. The physical models are more complex, based on mathematical equations which describe the erosion and sedimentation processes integrated by continuity equations to respect the conservation of mass and energy (Morgan, ). The simplicity of the empirical models, compared to the physical ones, is both an advantage, as they are easier to apply and require less input data, and a disadvantage, because the simplified nature of processes may lead to results subject to a higher degree of uncertainty.…”
Section: Methodsmentioning
confidence: 99%
“…Identification and quantification of the dominant sediment sources are also crucial to identify the most appropriate models to simulate erosion at the catchment scale Morgan, 2011;Vanmaercke et al, 2012) and avoid their misapplication (Govers, 2011). Poor modelling results are frequently obtained when a single model is applied to a wide series of catchments, as most models are generally designed for describing a limited number of processes (either sheet and rill erosion or gully and bank erosion), but they are rarely designed to simulate the complete range of phenomena (De Vente & Poesen, 2005;De Vente et al, 2013;Haregeweyn et al, 2013).…”
Section: Implications For Catchment Managementmentioning
confidence: 99%