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.

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The dry matter and nitrogen yield and estimated metabolizable energy of perennial ryegrass grown for silage were recorded from 1988 to 1990 for three levels of wheel traffic (zero, light and severe) at four rates of nitrogen fertilizer. The traffic treatments were applied by tractor wheels in the spring and summer of 1987 and in the spring of 1988 and 1990. First-harvest yields were reduced consistently by severe traffic: for example, at a rate of 100kg N ha"', dry matter (DM) produced in the severe treatment was 58, 72and84%of that in the zero traffic treatment in successive years. Wheel traffic effects on yield were markedly smaller at second and third cuts than at first cut. Nitrogen uptake and apparent recovery of fertilizer nitrogen were usually less after the relatively severe traffic treatment than after zero or light traffic treatments. Denitrification fluxes, measured in the second and third years, indicated that gaseous losses of nitrogen were largest when soil compaction was greatest.

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Abstract. We present a semi‐quantitative visual and tactile method for assessing soil physical fertility in terms of soil structure, root growth and soil surface condition. A block of topsoil is dug out with a spade. Horizontal layers (usually 2–4) are then identified as they appear. A brief one‐page description of the soil is produced. Using a key, structural and rooting scores are assigned to each soil layer from the appearance of the soil and from its response to tactile assessment. These scores are then combined across depths, with weighting appropriate for the depth of each layer. A separate score was made of soil surface condition. Thus, overall soil physical fertility is assessed as three scores for topsoil structure, rooting and surface condition. The usefulness and sensitivity of the procedure were tested in two ley‐arable organic rotation experiments on sandy loams in northeast Scotland.