Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data

Jong, S.M. de; Paracchini, Maria Luisa; Bertolo, F.; Folving, Sten; Megier, J.; Roo, A. P. J. De

doi:10.1016/s0341-8162(99)00038-7

Cited by 188 publications

(94 citation statements)

References 9 publications

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“…Among these, the Univeral Soil Loss Equation (USLE) [31,32], European Soil Erosion Model (EUROSEM) [33], Soil Erosion Model for the Mediterranean Region (SEMMED) [34], Water Erosion Prediction Model (WEPP) [35,36], the Soil and Water Assessment Tool (SWAT) [37], and the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) [38]. The USLE model has been widely used worldwide over the last 40 years to estimate soil erosion risk.…”

Section: Soil Loss Estimation Methodsmentioning

confidence: 99%

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

Farhan¹,

Zregat²,

Farhan³

2013

JWARP

115

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Wadi Kufranja catchment (126.3 km 2 ), northern Jordan, was selected to estimate annual soil loss using the Revised Universal Soil Loss Equation (RUSLE), remote sensing (RS), and geographic information system (GIS). RUSLE factors (R, K, LS, C and P) were computed and presented by raster layers in a GIS environment, then multiplied together to predict soil erosion rates, and to generate soil erosion risk categories and soil erosion severity maps. The estimated potential average annual soil loss is 10 ton·ha . Apart from the gentle slopes of the alluvial fan (Krayma town and surroundings), the lower and the middle reaches of the watershed suffer from severe to extreme erosion risk. High terrain, slope steepness, removal of vegetation, and poor conservation practices are the most prominent causes of soil erosion. This investigation demonstrates that remote sensing (RS) and GIS technologies are effective tools in modeling erosion, thus enabling extraction of significant information for implementing soil conservation plans in the north Jordan highlands.

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Section: Soil Loss Estimation Methodsmentioning

confidence: 99%

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

Farhan¹,

Zregat²,

Farhan³

2013

JWARP

115

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“…AGNPS (Young et al, 1989), WATEM/SEDEM (Van Rompaey et al, 2001), USPED (Mitasova et al, 1996), SEMMED (de Jong et al, 1999) and MMF (Morgan et al, 1984) all implement the R factor as the relationship between rainfall energy and intensity developed by Wischmeier and Smith (1978). The rainfall erosivity factor has been widely applied all over the world and it is considered as an important factor for soil erosion assessments under climate change scenarios (e.g.…”

Section: Rainfall Erosivity Factormentioning

confidence: 99%

Modelling soil erosion at European scale: towards harmonization and reproducibility

Bosco

Rigo

Dewitte

et al. 2015

Nat. Hazards Earth Syst. Sci.

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Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water-holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale, because a systematic knowledge of local climatological and soil parameters is often unavailable. A new approach for modelling soil erosion at regional scale is here proposed. It is based on the joint use of low-data-demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available data sets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63 % of a random sample of grid cells are accurate, 83 % at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country-level statistics of pre-existing European soil erosion maps is also provided.

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“…The absence or low quality of available data often impedes the successful application of such models at the catchment scale (Merritt et al 2003, de Vente andPoesen 2005), although the use of satellite imagery and remote sensing techniques has been reported to be successful in some cases (de Jong 1994, de Jong et al 1999, de Vente et al 2009. For large catchments, relatively simple regression models or semi-quantitative expert-based models often give better results for prediction of sediment yield than more complex physically-based models (Van Rompaey and Govers 2002, Jetten et al 2003, de Vente et al 2008.…”

confidence: 99%

Targeting of intervention areas to reduce reservoir sedimentation in the Tana catchment (Kenya) using SWAT

Hunink¹,

Niadas

Antonaropoulos

et al. 2013

Hydrological Sciences Journal

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A measurement campaign was carried out in the Upper Tana basin (Kenya) to quantify soil erosion and reservoir sedimentation rates, including a bathymetric reservoir survey and sediment load sampling during one year. Then, distributed soil erosion modelling was performed to study sediment budgets throughout the basin and to evaluate the potential of upstream erosion control through vegetated contour strips and check dams. Finally, the areas where these measures would be most effective were identified and local stakeholder associations to implement them were prioritized. The influence of the scale of implementation was evaluated by using the model to consider three adoption scenarios. This study illustrates the relevance of distributed erosion models to target erosion control measures when sufficient information on the eroding areas is available from field surveys. Bathymetric surveys were fundamental to validate the long-term model response, while point measurements were valuable to verify the spatial variability of model predictions.Key words soil erosion; sediment yield; sedimentation rate; distributed model; SWAT; Kenya; erosion control; soil conservation; watershed management Détermination des zones d'intervention pour la réduction de la sédimentation des réservoirs du bassin du Tana (Kenya) en utilisant SWAT Résumé Une campagne de mesures a été réalisée dans le bassin du Haut Tana (Kenya) afin de quantifier l'érosion des sols et les taux de sédimentation dans le réservoir, comprenant une étude bathymétrique du réservoir et l'échantillonnage des sédiments déposés pendant un an. Une modélisation distribuée de l'érosion des sols a ensuite été réalisée pour étudier le bilan des sédiments dans le bassin et évaluer le potentiel de contrôle de l'érosion en amont, par des bandes de végétation suivant les courbes de niveau et des barrages de retenue. Nous avons enfin identifié les zones où ces mesures seraient les plus efficaces, de même que les associations d'intervenants locaux susceptibles de les mettre en oeuvre. L'influence de la mise en oeuvre a été évaluée en utilisant le modèle selon trois scénarios. Cette étude illustre la pertinence des modèles d'érosion distribués pour concevoir des mesures de lutte contre l'érosion lorsque suffisamment d'informations sur les zones érodées, provenant d'enquêtes sur le terrain, sont disponibles. Les levés bathymétriques ont été fondamentaux pour valider la réponse du modèle à long terme, tandis que les mesures ponctuelles ont été utiles pour vérifier la variabilité spatiale des prévisions du modèle.

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Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data

Cited by 188 publications

References 9 publications

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan

Modelling soil erosion at European scale: towards harmonization and reproducibility

Targeting of intervention areas to reduce reservoir sedimentation in the Tana catchment (Kenya) using SWAT

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