
AbstractMaps of the potential waterlogging of soils were generated using hypotheses about the effect of topography on the soil water regime inspired by Beven and Kirkby's concept of saturation overland flow. The procedure was validated by comparing the simulated maps with maps derived from a 1: 25 000 soil survey for two contrasting catchments. The value and limitations of the method are discussed in the light of this comparison. The approach proposed here is relevant to modelling the distribution of intensely waterlogged soils, provided the relationship between bedrock and the limit values is established. This approach can be used for several purposes: (1) to distinguish positional waterlogging from other types of waterlogging; (2) to control the quality and consistency of waterlogging maps; and (3) to create soil water regime maps for non‐surveyed catchments. Conversely, soil water regime maps can be compared with contributing areas simulated by hydrological distributed models for validation purposes.
570, [SDV]Life Sciences [q-bio], [SDE.MCG]Environmental Sciences/Global Changes, GEOMORPHOLOGIE, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, BASE DE DONNEES, 530, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [SDV] Life Sciences [q-bio], [SDE.MCG] Environmental Sciences/Global Changes, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study
570, [SDV]Life Sciences [q-bio], [SDE.MCG]Environmental Sciences/Global Changes, GEOMORPHOLOGIE, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, BASE DE DONNEES, 530, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [SDV] Life Sciences [q-bio], [SDE.MCG] Environmental Sciences/Global Changes, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study
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