Using the topography of the saprolite upper boundary to improve the spatial prediction of the soil hydromorphic index

• Published in: Geoderma Vol. 123; no. 3; pp. 343 - 354
• Main Authors: Chaplot, V., Walter, C., Curmi, P., Lagacherie, P., King, D.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.12.2004; Elsevier
• Subjects: Agronomy. Soil science and plant productions; Areal geology. Maps; Biological and medical sciences; DEM; Earth sciences; Earth, ocean, space; Ecology, environment; Exact sciences and technology; Freshwater; Fundamental and applied biological sciences. Psychology; Geologic maps, cartography; Hydromorphic index; Life Sciences; Modelling; Soils; Sub-surface topography; Surficial geology; Manche France; France; Armorican Massif; Western Europe; HI; C; DG; F; A sm; H; C h; GPS; L; SPI; K c; P; CTI m; S; A s; OC; T; V; ME; Modelling; K p; Z; K t; Sub-surface topography; b; DEM; ES; MAE; q; Sd; r; Long; Hydromorphic index; CTI; Lat; altitude; accuracy; Topographic surface; Hydromorphic soils; spatial distribution; drainage basins; Ground surface; Land slope; spatial variations; soils; correlation coefficient; clastic rocks; landscapes; models; maps; Europe; streams; topography; digital elevation models; saprolite; sedimentary rocks; surface flow; correlation; prediction; statistical analysis; INDEX HYDROMORPHIQUE DU SOL; INDICE DU SOL HYDROMORPHE
• ISSN: 0016-7061; 1872-6259
• DOI: 10.1016/j.geoderma.2004.03.001

So far, soil-landscape models have been based on soil surface topographic information only. However, hillslope hydrology that affects soil distribution is also controlled by sub-surface flow pathways that may not entirely be explained by surface terrain features. This paper compares the accuracy of a model for predicting the spatial variations of the hydromorphic index (HI) using the surface topography with that of a model that uses the sub-surface topography. The study was conducted in an agricultural hillslope of the Armorican Massif (Western France) where two DEMs were generated from observations of the surface topography and the topography of the saprolite upper boundary. For both DEMs, the best correlations with HI occurred for altitude, elevation above the stream bank, and compound topographic index. Predictions of HI using the sub-surface topography greatly decreased prediction errors, especially for intermediary HI values at middleslope position. Finally, the use of subsurface topography as a novel approach to enhance existing techniques in new applications is discussed.