Soil erosion modelling with EUROSEM at Embori and Mukogodo catchments, Kenya

Abstract

The applicability of the European Soil Erosion Model (EUROSEM) in Kenya was tested on two subcatchments: Embori, which lies within a large-scale commercial wheat-and barleygrowing region on the slopes of Mt Kenya; and Mukogodo, a dry rangeland region used for communal grazing, which lies at lower altitudes. For both catchments, EUROSEM was used to simulate interrill erosion from single storm events on plots of 10 m by 2 m. The model was calibrated and validated for a barley crop at Embori and three treatments of bare, grass and shrub covers at Mukogodo. The results indicated that EUROSEM was applicable to the Embori catchment, as correlation coefficients of 0·91 and 0·84 were obtained between observed and simulated runoff and soil loss, respectively. However, for Mukogodo, the model did not adequately predict soil loss from vegetated plots having grass or shrubs, although it could predict runoff from bare plots and grass quite well (R 2 = = = = = 0·97, R 2 = = = = = 0·60, respectively) as well as soil loss from bare plots (R 2 = = = = = 0·58), but the standard errors of estimate at 4·67 mm were rather high (P = = = = = 0·95). Thus, EUROSEM requires improvements in terms of being able to predict runoff and soil loss in semi-arid regions of Kenya, so that it can accommodate multiple vegetation covers, rangeland conditions and soils with surface sealing properties. In addition, the model requires further testing to sample a wider range of climatic and land use types for it to be applicable to Kenya and rangeland conditions generally.

Sediment redistribution due to a dense reservoir network in a large semi-arid Brazilian basin

“…Several investigations have presented empirical approaches relating sediment yield to catchment area, combined, or not, with other factors, such as basin shape, topography, runoff, lithology and vegetation cover (Walling, 1983;Church & Slaymaker, 1989;Verstraeten et al, 2003;de Vente et al, 2005;Minear & Kondolf, 2009). Others have presented distributed or semi-distributed hydro-sedimentological models such as WEPP (Flanagan et al, 1995;Ramsankaram et al, 2009), EUROSEM (Morgan et al, 1998;Mati et al, 2006), SWAT (Chen & Mackay, 2004;Rostamian et al, 2008), HIDROSED (de Araújo & Knight, 2005;de Araújo, 2007), WATEM/SEDEM (Verstraeten et al, 2007;de Vente et al, 2008) and SEDNET (Prosser et al, 2001;Wilkinson et al, 2009), for the assessment of soil erosion and sediment yield at the basin scale. However, none of the above-mentioned empirical approaches and hydro-sedimentological models deals with the HdRN problem, as in the case of large basins of the Brazilian semi-arid region.…”

Standing proud: a response to ‘Soil‐erosion models: where do we really stand?’ by Smithet al.

“…Indeed the Mati et al (2006) paper cited by Smith et al, which is an application of EUROSEM, relies upon a standard calibration and validation approach to 'test' the model, seemingly in ignorance of the previous work by Quinton (1994Quinton ( , 1997 within which he calls for erosion-model applications to be accompanied by uncertainty analysis, as '[n]ot doing so misleads the user into believing that the model output is more certain than is actually the case' (Quinton, 1997, p. 115). It is interesting that the only positive experiences they cite other than our papers are in relation to the Rose model.…”

Dealing with Uncertainty in Erosion Model Predictions

“…All of the model analyses reviewed here demonstrate that model users should evaluate model uncertainty, yet it is clear from the literature that most applications of erosion models do not do this. Just one example of this problem is illustrated by Mati et al (2006), who applied the EUROSEM model to the Embori and Mukogodo catchments, Kenya. EUROSEM has been shown to make reasonable (although uncertain) predictions (see above), but here it is applied to predict erosion without any consideration of this uncertainty.…”