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DIVISION S-6-SOIL & WATER MANAGEMENT & CONSERVATION

Predicting Depressional Storage from Soil Surface Roughness

^a Unité d'Agronomie Laon/Péronne, INRA, Laon, France
^b Dep. of Physical Geography, Univ. of Utrecht, Utrecht, Netherlands
^c MTT, Jokioinen, Finland
^d Danish Institute of Agricultural Sciences, Foulum, Denmark
^e Scottish Agricultural College, Penicuik, UK
^f Faculty of Sciences, Univ. of Coruña, Coruña, Spain

eva{at}laon.inra.fr

Runoff may be reduced by temporal water storage in depressions at the soil surface. Depressional storage is difficult to measure and is usually estimated from some roughness index. The objective of this study was to compare the ability of selected roughness indices to describe maximum depressional storage (MDS). Height measurements were taken on 221 tilled soil surfaces across a range of roughnesses. Maximum depressional storage was determined from digital elevation models (DEMs). The MDS values ranged from 0 to 13 mm. Five roughness indices were calculated from transects across these DEMs: random roughness (RR), tortuosity (T), limiting elevation difference (LD) and slope (LS), and mean upslope depression (MUD). Regression analysis of MDS on each of five roughness indices showed that RR best described depressional storage . Prediction of MDS in the field based on RR has an uncertainty of ± 3 mm (95% confidence interval). Variation was due to RR and its nonspatial nature. To improve predictions of MDS, the spatial configuration of the surface has to be taken into account.

Abbreviations: DEM, digital elevation model • LD, limiting elevation difference • LS, limiting slope • m, number of sub segments per transect • MDS, maximum depressional storage • MIF, microrelief index x peak frequency • MUD, mean upslope depression • RR, random roughness • T, tortuosity • T_A, tortuosity index, Auerswald (1992) • T_B, tortuosity index, Boiffin (1984) • T_P, tortuosity index, Planchon et al. (1998) • T_S, tortuosity index, Saleh (1993)

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