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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

View larger version (18K): [in a new window]   Fig. 1 Boundary conditions to fill digital evaluation model of a plot. Eight copies of the plot surface were arranged symmetrically around the inside plot to obtain a continuous surface ninefold larger than the plot

View larger version (21K): [in a new window]   Fig. 2 Maximum depressional storage (MDS) values as a function of tillage (s = standard deviation; SE = standard error)

View larger version (19K): [in a new window]   Fig. 3 Influence of grid spacing on maximum depressional storage (MDS), mean and standard deviation

View larger version (24K): [in a new window]   Fig. 4 Random roughness (RR), limiting elevation difference (LD), and mean upslope depression (MUD) vs. maximum depressional storage (MDS). d = sample spacing. *** Significant at P = 0.001

View larger version (23K): [in a new window]   Fig. 5 Planchon et al. (1998) tortuosity index (TP), Auerswald tortuosity index (TA), and limiting slope (LS) vs. maximum depressional storage (MDS)

View larger version (25K): [in a new window]   Fig. 6 Influence of sample spacing and tillage on tortuosity (T)

View larger version (33K): [in a new window]   Fig. 7 Evaluation of existing maximum depressional storage (MDS) predicting models. d = sample spacing, RMSE = root mean square error

View larger version (31K): [in a new window]   Fig. 8 Models to predict a single value of maximum depressional storage (MDS) from random roughness (RR), with 95% confidence intervals. (a) all data (n = 221); (b) zoom of (a); (c) lab data (n = 48); (d) field data (n = 173). EV = explained variance