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Effects of tillage on runoff directions: consequences on runoff contributing area within agricultural catchments
Journal of
Hydrology ELSEVIER
Journal of Hydrology 206 (1998) 256-267
Effects of tillage on runoff directions: consequences on runoff contributing area within agricultural catchments V. Souchere a'*, D. King b, J. Daroussin b, F. Papy c, A. Capillon d aINRA-SAD, 16 rue Claude Bernard, 75231Paris, Cedex 05, France bINRA-SESCPF, Ardon, 45160 Olivet, France ClNRA-SAD, 78850 Thiverval, Grignon, France dlNA PG, 16 rue Claude Bernard, 75231 Paris, Cedex 05, France
Received 12 March 1997; accepted 4 February 1998
Abstract In areas of intensive agriculture, e.g. 'Pays de Caux' in France, which was the study area, field observations have shown that runoff directions were modified by agricultural activities. In order to account for factors responsible for modifications of the runoff direction (roughness, tillage direction and agricultural patterns, e.g. dead furrow or dirt tracks), we constructed a discriminant function based on field observations. This function enables us to decide whether flow direction for slopes of up to 15% was imposed by slope direction or tillage direction. It can be applied to any location, provided there are known roughness, known slope intensity, known aspect and known tillage azimuth. In order to examine the effects of these agricultural activities at the catchment scale, we compared two models by analysing the same hydrological variables: the area contributing to runoff and the flow network. The first model (Topo) was built according to the runoff direction derived from a Digital Elevation Model (DEM). The second model (Tillage) was constructed by combining information from the DEM, and information from rules based on field observations or resulting from statistical analysis. For 23 basic catchments, the result of the comparison between the two models (Topo and Tillage) showed that a major part of the catchments and the drainage network was affected by modifications related to the introduction of man-made agricultural factors. For example, for 20 of 23 catchments, the runoff flows over more than 50% of the surface of such areas were produced along the direction imposed by tillage. The introduction of tillage effect brings about modifications of both the shape and size of catchments. © 1998 Elsevier Science B.V. All rights reserved. Keywords: Runoff; Tillage direction; Catchment; Erosion
1. Introduction In the areas of Northern Europe that are underlain by loamy soil, the concentration of runoff is a widespread phenomenon, notwithstanding low rainfall intensity and a mild topography (Fullen and Reed, * Corresponding author. 0022-1694/98/$19.00 © 1998 Elsevier Science B.V. All rights reserved. PII S0022-1694(98)00103-6
1987; Boardman, 1990; Poesen and Govers, 1990; Papy and Douyer, 1991). This form of erosion results from the hydrological link between a runoffcontributing area and a collecting channel, where flow discharge and velocity exceed the critical values for rill initiation and development (Govers, 1985; Rauws and Govers, 1988; Foster, 1990; Govers et al., 1990; Moore and Foster, 1990). Interactions between
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
meteorological conditions, farming operations and topsoil texture bring about rapid and significant changes in the hydraulic properties of topsoil. This is due to soil infiltrability and surface water storage (Monnier et al., 1986; Papy and Boiffin, 1989; King and Le Bissonnais, 1992; Auzet et al., 1995) that determine its aptitude to produce runoff. Thus, gully initiation depends on the dynamics of topsoil crusting degradation (Boiffin et al., 1988). As a result, these studies showed the considerable role of agricultural activity in the development of ephemeral gullies. Nevertheless, many runoff studies have considered only local topography and calculated flow direction according to the slope aspect (Beven and Kirkby, 1979; Moore and Burch, 1986; Morgan et al., 1994; Merot et al., 1995). In the case of gentle slope, however, field observations showed that the preferential pathways for water circulation could be influenced by some man-made agricultural factors, e.g. dead furrows, dirt tracks, ditches and roughness due to tillage operations (Ludwig et al., 1995). The last factor is commonly used for characterising the temporary storage capacity of excess water on the soil surface (Mitchell and Jones, 1978; Onstad, 1984; Zobeck and Onstad, 1987), but its influence on runoff direction is rarely taken into account. Even when the effects of tillage are taken into account (Ludwig et al., 1995), most integration processes remain manual and thus applicable only occasionally, since no suitable procedure exists for automatically deciding runoff direction. This study had a dual aim: first it was desired to automatically consider the effects of certain agricultural factors on the direction of runoff flows; secondly, we wished to quantify the impact of these factors in small agricultural catchments that are chronically eroded. Such modifications have only a small local importance, but cumulative effects along the runoff network can strongly influence the hydrological characters of the catchment, e.g. cumulative areas or location of flow concentration. After describing a typology of the man-made agricultural factors that might influence runoff directions, we present the method used for taking into account these factors in a classical topographic water movement model (Topo) to build another model (Tillage) which attempts to better reflect real water flow. In the second part, we present the equation
257
used for modelling the runoff direction in crop fields. This equation allows the automatic determination of flow direction by using aspect and tillage directions, and can be used for all catchments. Finally, we present the results of the comparison of the two runoff circulation models (Topo and Tillage). This comparison, based on the analysis of the same hydrological variables, should enable the determination of the importance of modifications related to considering agricultural factors.
2. Materials and methods
2.1. Spatial and temporal context The survey was conducted on zero-order catchments. Auzet et al. (1993) defined these units as areas hydrologically related to a relatively wellmarked talweg (longitudinal profile) in the relief and corresponding to the ultimate ramification of a dry valley network. Their area usually ranges from at least 10 to at most 100 hectares. They constitute the representative elementary area (Wood et al., 1988) within which the release mechanism of concentrated flow erosion can be studied (Auzet et al., 1990; King et al., 1992). Sixteen agricultural catchments were selected as they were representative of catchments founding the Pays de Caux (Fig. 1), one of the regions of Northwest Europe in which this type of erosion is causing concern (Papy and Douyer, 1991). These catchments were also selected because they were known to be the site of previous erosion (Ouvry, oral communication). Catchments were observed during two agricultural years 1991-1992 and 1992-1993, providing potentially 32 'year-catchments' (Souchere, 1995). However, only 23 'year-catchments' were used for the study according to the presence of erosion features during the concerned period. In this paper, these 23 'year-catchments' are seen as 23 free independent catchments. They differed by the combination of topography and geometric configuration of farm fields (Table 1). Their topsoil texture was constant, being loamy (on average, 11% clay, 60% silt, 29% sand), which makes them particularly sensitive to porosity closure and the formation of impermeable crusts when subject to the impact of raindrops (Eimberck, 1990;
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
258
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Fig. 1. Location of catchments.
Table 1 Characterization of catchments Catchment Measurement number campaign
Area(ha)
% of area in slope intensity class < 1%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
1991-1992 1992-1993 1991-1992 1991-1992 1992-1993 1992-1993 1992-1993 1991-1992 1991-1992 1992-1993 1991-1992 1991-1992 1991-1992 1992-1993 1991-1992 1991-1992 1991-1992 1991-1992 1991-1992 1992-1993 1991-1992 1992-1993 1991-1992
21.90 12.14 12.14 4.96 4.96 19.78 28.96 14.73 8.37 8.20 8.20 13.33 23.03 15.92 43.16 14.73 8.34 63.94 3.48 3.48 19.78 27.36 27.36
13.39 37.53 37.53 10.46 10.46 40.58 11.67 12.68 0.48 32.03 32.03 0.22 14.27 7.13 5.1 12.68 2.99 24.4 10.32 10.32 40.58 20.49 20.49
1-2%
2-5%
5-10%
8.38 37.78 37.78 9.86 9.86 27.29 13.74 17.88 11.22 6.82 6.82 0.6 10.05 17.51 6.67 17.88 26.59 16.24 21.78 21.78 27.29 58.91 58.91
27.02 13.66 13.66 55.73 55.73 26.43 54.78 62.90 42.72 45.55 45.55 48.05 48.01 65.20 41.49 62.90 58.32 42.29 49.86 49.86 26.43 16.15 16.15
24.74 10.04 10.04 23.94 23.94 5.71 17.33 6.53 40.45 15.59 15.59 51.07 27.63 10.15 41.63 6.53 12.10 17.00 17.19 17.19 5.71 3.98 3.98
Number of farm fields
Orientation of farm fields a
5 8 4 3 3 11 10
// T T T T T fl // T T T // T fl // T T // T T T T T
> 10% 26.47 0.99 0.99 0 0 0 2.49 0 5.13 0 0 0.07 0.04 0 5.12 0 0 0.08 0.86 0.86 0 0.47 0.47
a//Orientation more-or-less parallel to the talweg; TOrientation more-or-less perpendicular to the talweg.
1
6 5 5 8 10 6 15 5 3 20 3 3 7 15 15
v. Souchere et aL/Journal of Hydrology 206 (1998) 256-267 Imeson and Kwaad, 1990; Le Bissonnais and Singer, 1992). Wheat, barley, sugar beets, pea and flax account for more than 60% of the arable lands in the Pays de Caux. With these crops, tillage operations are numerous between the beginning of October and the end of April. This period is also characterised by a high probability of precipitation. Since our objective was to show the effect of tillage on runoff direction, most of the observations were carried out during this period. From October to April, the farm fields of catchments were observed once or twice a month. Crop fields were observed from the harvest of the previous crop up to the last tillage operations of the following crop. The observations had the objectives of: (1) monitoring surface degradation in catchment areas; and (2) identifying the factors likely to change runoff flow directions.
2.2. Typology o f man-made agricultural factors that modify runoff directions Some of the factors that can influence runoff directions are permanent, e.g. roads and ditches dug for evacuating their water. Other factors appear and disappear as part of agricultural practice, e.g. dead furrows, ruts, ridges left by certain cropping operations, e.g. the harvesting of sugar beets or digging up of potatoes, and especially roughness created by tillage. On the smooth and impermeable surfaces of roads and dirt tracks, we assume that in the absence of ditches water flow will follow slope orientation. Ditches and dead furrows form water-conducting lines that are sufficiently deep to impose their direction on the surface flow.
Within crop fields, the situation is generally more complex since flow direction varies as a function of terrain roughness. Boiffin et al. (1988) conducted field observations that distinguished between several classes of roughness (Table 2). This classification, further refined by Ludwig et al. (1995), was used for calculating the difference between roughness in the tillage direction and that perpendicular to it on 60 plots localised on hillsides. The knowledge of this difference is of fundamental importance for estimating the obstacle that runoff must overcome to flow in the direction of steepest slope. These measurements were made for plots selected to represent the diversity in roughness, slope and tillage angles that are normal for the area under study. Ten observations were carried out on plots with a difference between the two roughnesses of greater than two classes (e.g. R0 in the tillage direction and R3 perpendicular to it). These observations showed that runoff always follows tillage direction. Fifty observations made on plots with a difference between the two roughnesses of less than or equal to two classes, showed that runoff direction was variable. In order to model the influence of tilling on these plots, we assumed that the runoff direction depends on two major variables: slope intensity, and the angle between azimuth directions of the steepest slope (aspect) and tillage. To verify this assumption, we measured the slope of the 50 plots with an Abney level and the angle between the two directions with a compass. At the same time, the actual runoff direction was noted, either by direct observation during rainstorms, or by analysing the traces left by runoff just after the event. The observations were ranked in two sub-populations corresponding to: (i) plots where the observed runoff follows predominantly the slope direction; and (ii) plots where tillage imposes the
Table 2 Grading of soil surface roughness (Ludwig et al., 1995) Grade
Roughness index
R0 RI R2 R3 R4
0-1 cm 1-2 cm 2-5 cm 5-10cm > 10cm
a
259
Typical agricultural situation Strongly crusted sown fields, harvested fields with intense compacting Sown fields with fine loosened or moderately crusted seedbeds Recently sown fields with a cloddy surface, crusted tilled fields without residues Stubble-ploughed fields and recently sown fields with a very cloddy surface Ploughed fields
a Difference in the heights of the deepest part of microdepressions and the lowest point of their divide.
260
K Souchere et al./Journal of Hydrology 206 (1998) 256-267 GRID DATA in GIS
DEM (Isolines)
Field Observations Legend: TillageDirection ROR.2 Classof roughness . Deadfurrow /
TOPOGRAPHICALFACTORS] Sic ~e As set
/ ~
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AGRICULTURALFACTORS ] Tillage direction Roughness
Dead furrow Dirt track
Diseriminantfunction
TOPO MODEL
TILLAGE MODEL
owLo.
ow;oon
1
Runoff eontributing area
\
Flow network
t
Runoff contributing area
\
Flow network
COMPARISON
Fig. 2. Schematic presentationof the two models of runoff circulation.
runoff direction. Using these data, an analysis of variance and a discriminant analysis were carried out using the two variables chosen: slope intensity, and the angle between aspect and tillage directions, in order to produce a suitable procedure for automatically determining runoff direction.
2.3. Modelling runoff-direction changes at the catchment scale Two models were developed with the help of the GRID module of the Arc/Info Geographic Information System (Fig. 2). The first, Topo, is a standard topographic-runoff
261
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
Table 3 Runoff direction as a function of the types of objects Types of objects
Runoff direction
Field crop (including headlands) Differencebetween the two roughnesses > 2 Difference between the two roughnesses --< 2
Tillage direction Tillage or slope direction (decision as a function of statistical analysis) Furrow direction Direction of greatest slope
Dead furrow Dirt tracks, roads model (Beven and Kirkby, 1979; Moore et al., 1988). Using the contours from the l:25,000-scale IGN maps, a digital elevation model was calculated an elevation value was then attributed to each 10 x 10 m square grid cell. The software then used this value to determine the flow direction along the slopes. Flow paths are processed from cell to cell by directing the flow of each cell to the lowest of its eight neighbours. The drainage network was thus recreated and runoff-contributing area was estimated f6r all points of the catchment. In the case of the second model, Tillage, data obtained from the catchment plots were introduced into the GIS in order to modify runoff circulation directions according to rules based on field observations or resulting from statistical analysis (Table 3). Dirt tracks are linear elements that retain the usual behaviour of the standard model towards water flow movement when converted to raster form. In other words, runoff from one cell is directed to the lowest surrounding cell. On the contrary, well identified dead furrows, ditches and embankment slopes behave as
streams: runoff is forced along the down-sloping direction imposed by these linear features. In raster form, for each cell, unless the direction of the feature coincides with that of the lowest surrounding cell, the flow will be forced into another direction. Within agricultural plots, modelling of runoff direction employs data derived from the DEM (aspect and slope intensities) and data from field observations on each of the plots o f the 23 catchments (tillage direction and roughness). Tillage direction was converted to raster from the parcel data layer and then combined with aspect in order to compute the slope angle. Slope intensity and angle were used by the discriminant function to determine which cell is predominant in directing the flow between topography and tillage. Roughness assessments of each plot were used to determine if a discriminant function was to be applied or if the tillage direction was applied directly in order to reproduce runoff flow in all the cells of the same plot. A m o n g the roughnesses observed during one agricultural period, we used the one measured at the gully initiation. After their introduction, these
Water follows the dir~ticn of:
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V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
262
Table 4 Results of statistical analysis (observations on 50 plots) Analysis of variance
Basic statistics a
Variables
Residual variance
Residual standard deviation
Calculated F
F of Ficher-Snedecor (0.01%, 1.48)
Means
Standard deviations
Angle (°) Slope (%)
275.97 6.34
16.61 2.52
24.09 24.29
7.31 7.31
61.74 5.45
19.95 3.03
a The basic statistics enable variables to be centred and reduced when slopes are expressed as a percentage and the angles in degrees.
modifications then provide a new water circulation network and new values for hydrological variables, e.g. the runoff-contributing area.
3. Results and discussion
3.1. Effect of tillage on runoff directions within crop fields Fig. 3 shows the results of observations made on the 50 plots with a difference between the two roughnesses equal or lower than two classes. This shows the existence of two relatively distinct groups, depending on whether the runoff direction follows the tillage direction (Group 1), or the slope direction (Group 2). Analyses of variance for the 50 plots show the positive role played by each of the variables slope and angle, for distinguishing the two runoff-direction groups. In both cases, the Ficher-Snedecor 'F' was lower than that calculated during analysis (Table 4), but the values obtained (24.09 and 24.29) are too close to envisage the use of one variable rather than the other. Two groups of runoff directions could be distinguished by conducting a linear combination between the two variables (Table 5). When assuming H0 (no group effect), the pseudo F value has a probability that becomes null (Table 5). In reality, this probability is not strictly null, but is very low and below the 1% threshold; it allows H0 to be
discarded and leads to the conclusion that runoff-direction differences indeed exist between the two groups. The calculated pseudo F value of 70.24 is well above the two highest F values of the preceding variance analyses (Table 4). This comparison gives a 'qualitative' idea of the gain provided by a discriminatory analysis. It is thus interesting to combine the two variables when trying to distinguish between the two groups, since discriminatory analysis considers not only the average differences between groups, with variances of each variable, but also the correlations between variables (Tomassone, 1988). During this discriminatory analysis, the following equation is calculated for the discriminating factor axis (D): D = - 0.6646 A n g l e - 0.6669 Slope where the angle is the standardised variable of the angle between the slope aspect and tillage direction; and slope is the standardised variable of the slope intensity. This discriminant function assists in the subsequent classification of observations into one of the two groups corresponding to runoff directions. Any observation with a coordinate on axis D below 0.12 (the value that represents the equidistant point for the centred projections of the two groups on the discriminating axis) is assigned to Group 2, i.e. runoff in the slope direction. For coordinates above 0.12, the observation is assigned to Group 1, i.e. runoff in the tillage direction.
Table 5 Results of discriminatory analysis for 50 observed plots Axis
Ow value
Inertia
Pseudo F
Wilks
ddl
Probab. %
Correlation
1
1.4632
100%
70.24
42.37
2
0.00
0.59
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267 Table 6 Result of classing observations Allocation Groups Well-classifiedobservations:92%
Groupl
Group2
Groups of origin
GI-Tillage (size 21)
19
2
G2-slope (size 29)
2
27
Reclassification of the observations made on the 50 plots showed very good coincidence with initial classification (Table 6). The four 'poorly classified' observations correspond to intermediate situations observed in the field. It was actually seen that runoff can successively follow the slope aspect and then the tillage directions. In this case, we assigned the observations to the majority direction, but this decision remains open for discussion.
3.2. Consequence of considering man-made activities at the scale of catchments We have presented the method using a Geographic Information System to modify a model of topographic circulation of runoff water. The results of these modifications were analysed by calculating the surfaces involved, and examining the transformation of network structure and the aspect of catchments when either of the two models was used (Tillage or Topo).
3.2.1. Surfaces affected by modifications in runoff direction We calculated the percentage of grid meshes affected by a modification for each catchment. This showed that for 20 of 23 catchments, the runoff flows that produced over 50% of the surface of such areas followed the direction imposed by tillage (Table 7). For nine catchments, more than 75% of their surface was concerned by this flow direction. This shows that the modifications affected a large number of pixels in each catchment. The low number of meshes affected by modifications induced by dead furrows is due to the linear character of such features.
3.2.2. Types of modifications For dead furrows, a low number of modified pixels does not necessarily mean that there was no effect on
263
Table 7 Runoff directions in each catchment (as percentage of catchment surface) Catchment number 1
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Mean
Flow direction is imposed by: Slope
Tillage
Dead furrows
53 20 13 33 39 12 7 25 46 5 27 30 38 20 39 19 31 37 62 52 14 34 33 30
47 78 85 58 54 88 93 75 54 91 69 67 61 76 57 81 69 59 22 38 86 61 67 67
0
2 2 9 7 0 0 0 0 4 4 3 1 6 4 0 0 4 16 10 0 5 0 3
runoff direction. It depends on the size of the modification and especially its location in the catchment. It is thus necessary to study the effect that runoff has on the catchment as a whole, taking the cumulated effects into consideration. Two effects are analysed below: the modification in location of the drainage network; and modifications in the catchment surface. The results are presented and discussed on the basis of a single catchment area, but identical results were noted for the other catchments. Fig. 4 shows the circulation network followed by runoff water in Catchment 15 according to the Topo (line a) and Tillage (line b) models. Clear differences are seen between the structures of the two networks. These modifications cause differences in the location of water concentration points in talwegs. Fig. 5 shows the increase in drained surface when going along the main talweg of catchment 15: depending on the runoff model, it can be seen that abrupt increases in drained surfaces do not occur in the same place of the talweg.
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
264
CATCHMENT NUMBER 15 ~~
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Fig. 5. Increase in the drained surface along a thalweg depending upon the runoff model used.
V. Souchere et al./Journal of ttydrology 206 (1998) 256-267
265
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["-"~TILLAGE Modcl
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50.
40. 30. 20 10
,dig 2
3
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Fig. 6. Changes in catchment surface according to the runoff model used. Fig. 5 also shows that even though the first increases are offset in space, they have similar amplitudes. Beyond point 50, however, the Topo model not only shows an earlier final increase, but also an amplitude variation. Here, the drained-surface value from the Tillage never reaches that of the Topo model. This indicates a modification not only in the location of erosive phenomena, but also in their intensity. Fig. 4(a) and (b) shows the boundaries of Catchment 15 calculated from each runoff model in bold. It can be seen that both the shape and size of the catchment have changed, the latter from a 43 hectare (ha) surface for the Topo model to 37 ha surface for the Tillage model. About 9 ha of the topographical catchment feed a second outlet [left side of graph (a)], when considering man-made agricultural factors. Taking the same factors into account, however, leads to the recovery of slightly over 3 ha from an adjoining catchment [right side of graph (b)]. Water thus crosses topographic crest lines by following the micro-channels that are created by, e.g. sowing lines. This example is not an exception. Similar changes in catchment surface were observed for all samples investigated. A total of 16 was subjected to variations in their surface to an absolute value of over 25%, and nine had variations of over 50%. This was the case, e.g. for Catchment 1, where the 22 ha of the Topo model were reduced to only 10 ha with the Tillage model (Fig. 6). The same figure shows that some catchments, e.g. 2 or 19, have almost the same surface areas Ibr both runoff models. It is, however,
difficult to provide a general rule for such modifications, since they depend primarily on the arrangement of plots within the catchments and on the direction of the main man-made features within such catchments.
4. Conclusions We have shown that it is possible to use a GIS to model soil surface runoff water by taking into account certain agricultural factors. For a sample of cultivated catchments, the areas modified by considering tillage direction and observed flow paths commonly involve over 50% of the catchment areas. Changes in runoff direction are shown in particular by variations in the location of runoff concentration points within the talweg. The catchment area itself is also modified. This means that any definitions that use only morphological variables to define the geographic boundaries are insufficient when the topography of the catchments is not highly accentuated. More generally, it would be important to take into account these results in the calculation of the runoff contributing area from a DEM because this variable is classically used in hydrology or geomorphology (Moore and Burch, 1986). Even though the existence of modifications of varying importance can be identified, the correct validation of such results at the scale of an entire catchment remains difficult. This is because it would
266
~ Souchere et aL/JournalofHydrology 206 (1998) 256-267
be necessary to measure water flux in all points of the catchment space. To this end, a study is in progress that uses talweg erosion as the possible tracer for the greatest water fluxes. The location of rills and gullies has been investigated in the past (Moore et al., 1988; Thorne et al., 1986), but without considering manmade agricultural factors. Using the newly developed 'Tillage' model, we intend to demonstrate the effect of such man-made agricultural factors on runoff and erosion. The current version of the Tillage model remains incomplete. It does not take into account the true quantities of runoff water, since the infiltration capacities of the plots, as well as precipitation intensities were not included. The height of the runoff water layer certainly plays an important role in a dynamic and interactive process. However, the proposed discriminant function is the first step which can be included in the runoff routing module of erosion or pollution models.
Acknowledgements The authors thanks Alain Couturier for his assistance with data processing, Jeffrey Diamond for the quality of his translation, and the Regional Council of Haute-Normandie for its financial contribution.
References Auzet, A.V., Boiffin, J., Ludwig, B., 1995. Concentrated flow erosion in cultivated catchments: influence of soil surface state, Earth Surface Processes and Landforms, 20, 5. Auzet, A.V., Boiffin, J., Papy, F., Ludwig, B., Maucorp, J., 1993. Rill erosion as a function of the characteristics of cultivated catchments in the North of France, Catena, 20, 41-62. Auzet, A.V., Boiffin, J., Papy, F., Maucorp, J. and Ouvry, J.F., 1990. An approach to the assessment of erosion forms and erosion risk on agricultural land in the Northern Paris Basin, France. In: Boardman, J., Foster, D.L. and Dearing, J.A. (Eds), Soil Erosion on Agricultural Land. John Wiley, Chichester, pp. 383-400. Beven, K.J., Kirkby, M.J., 1979. A physically based, variable contributing area model of basin hydrology, Hydrological Science Bulletin, 24, 43-69. Boardman, J., 1990. Soil erosion on the South Downs: a review. In: Boardman, J., Foster, D.A. and Dearing, J.A. (Eds), Soil
Erosion on Agricultural Land. John Wiley, Chichester, pp. 87-105. Boiffin, J., Papy, F., Eimberck, M., 1988. Influence des syst~mes de culture sur les risques d'6rosion par ruissellement concentr6. I--Analyse des conditions de d6clenchement de l'6rosion, Agronomie, 8, 663-673. Eimberck, M., 1990. Facteurs d'6rodibilit6 des sols limoneux: r6flexions ~ partir du cas du Pays de Caux. Cah, ORSTOM, s6r. P6dol., XXV(I-2), 81-94. Foster, G.R., 1990. Process-based modelling of soil erosion by water on agricultural land. In: Boardman, J., Foster, D.L. and Dearing, J.A. (Eds), Soil Erosion on Agricultural Land. John Wiley, Chichester, pp. 429-445. Fullen, M.A. and Reed, A.H., 1987. Rill erosion on arable loamy sands in the West Midlands of England. In: Bryan, R.B. (Ed.), Rill Erosion, Processes and Significance. Catena, Supplement 8, pp. 85-96. Govers, G., 1985. Selectivity and transport capacity of thin flows in relation to rill erosion, Catena, 12, 35-49. Govers, G., Everaert, W., Poesen, J., Rauws, G., De Ploey, J., Lautridou, J.P., 1990. A long flume study of the dynamic factors affecting the resistance of a loamy soil to concentrated flow erosion, Earth Surface Processes and Landforms, 15, 313-328. lmeson, A.C. and Kwaad, J.P.M., 1990. The response of tilled soils to wetting by rainfall and the dynamic character of soil erodibility. In: Boardman, J., Foster, I.D.L. and Dearing, J.A. (Eds), Soil Erosion on Agricultural Land. John Wiley, Chichester, pp. 3-14. King, D., Le Bissonnais, Y., 1992. R61e des sols et des pratiques culturales dans l'infiltration et l'6coulement des eaux. Exemple du ruissellement et de l'6rosion sur les palteaux limoneux du nord de l'Europe, C.R. Acad. Agric. Fr., 78 (6), 91-105. King, D., Le Bissonnais, Y. and Hardy, R., 1992. Regional assessment of runoff and erosion risk. Example of the Nord/ Pas-de-Calais region, France. In: Wicherek, S. (Ed.), Temperate Plains Environment and Hills. Elsevier, pp. 191-205. Le Bissonnais, Y., Singer, M.J., 1992. Crusting, runoff and erosion response to soil water content and successive rainfalls, Soil Sci. Soc. Am. J., 56, 1898-1903. Ludwig, B., Boiffin, J., Chadoeuf, J., Auzet, A.V., 1995. Hydrological structure and erosion damage caused by concentrated flow in cultivated catchments, Catena, 25, 227-252. Merot, P., Ezzahar, B., Walter, C., Aurousseau, P., 1995. Mapping, waterlogging of soils using digital terrain models, Hydrological Processes, 9, 27-34. Mitchell, J.K., Jones, A.B., 1978. Micro-relief surface depression storage changes during rainfall events and their application to rainfall runoff models, Water Resources Bulletin, 14, 777-802. Monnier, G., Boiffin, J. and Papy, F., 1986. Rdflexions sur l'6rosion hydrique en conditions climatiques et topographiques mod6r6es: cas des syt6mes de grande culture de l'Europe de l'Ouest. Cah. ORSTOM, sdr. Pddol., XXII(2), 123-131. Moore, I.D., Burch, G.J., 1986. Modelling erosion and deposition: topographic effects, Trans. ASAE, 29, 1624-1640.
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267 Moore, I.D., Burch, G.J., Mackenzie, D.H., 1988. Topographic effects on the distribution of surface soil water and the location of ephemeral gullies, Trans. ASAE, 31 (4), 1098-1107. Moore, I.D. and Foster, G.R., 1990. Hydraulics and overland flow. In: Anderson, M.G. and Burt, T.P. (Eds), Process Studies in Hillslope Hydrology. John Wiley, Chichester, pp. 215-254. Morgan, R.P.C., Quinton, J.N., Rickson, R.J., 1994. Modelling methodology for soil erosion assessment and soil conservation design: the EUROSEM approach, Outlook on Agriculture, 23 (1), 5-9. Onstad, C.A., 1984. Depressional storage on tilled soil surfaces, Trans. Am. Soc. Agric. Engng, 27, 729-732. Papy, F. and Boiffin, J., 1989. The use of farming systems for the control of runoff and erosion. In: Schwertmann, U., Rickson, R.J. and Auerswald, K. (Eds), Soil Erosion Protection Measures in Europe. Soil Technology Series, pp. 29-38. Papy, F., Douyer, C., 1991. Influence des 6tats de surface du territoire agricole sur le drclenchement des innondations catastrophiques, Agronomie, 11 (3), 201-215. Poesen, J. and Govers, G., 1990. Gully erosion in the loam
267
belt of Belgium: typology and control measures. In: Boardman, J., Foster, D.L. and Dearing, J.A. (Eds), Soil Erosion on Agricultural Land. John Wiley, Chichester, pp. 513-530. Rauws, G., Govers, G., 1988. Hydraulic and soil mechanical aspects of rill generation on agricultural soils, Journal of Soil Science, 39, 111-124. Souchere, V., 1995. Mod61isation spatiale du ruissellement ~t des fins d'am6nagement contre l'rrosion de talweg. Application hdes petits bassins versants en Pays de Caux (Haute Normandie), 1-200 pp. Thorne, C.R., Zevenbergen, L.W., Grissinger, E.H. and Murphey, J.B., 1986. Ephemeral gullies as sources of sediment. Proc. Fourth Federal Interagency Sed. Conf., Las Vegas, Nevada, pp. 3.152-3.161. Tomassone, R., 1988. Comment interpreter les rrsultats d'une analyse factorielle discriminante? ITCF, 1-56 pp. Wood, E.F., Sivapalan, M., Beven, K., Band, L., 1988. Effects of spatial variability and scale with implications to hydrologic modelling, J. Hydrol., 102, 29-47. Zobeck, T.M., Onstad, C.A., 1987. Tillage and rainfall effects on random roughness: a review, Soil & Tillage Research, 9, 1-20.
Hydrology ELSEVIER
Journal of Hydrology 206 (1998) 256-267
Effects of tillage on runoff directions: consequences on runoff contributing area within agricultural catchments V. Souchere a'*, D. King b, J. Daroussin b, F. Papy c, A. Capillon d aINRA-SAD, 16 rue Claude Bernard, 75231Paris, Cedex 05, France bINRA-SESCPF, Ardon, 45160 Olivet, France ClNRA-SAD, 78850 Thiverval, Grignon, France dlNA PG, 16 rue Claude Bernard, 75231 Paris, Cedex 05, France
Received 12 March 1997; accepted 4 February 1998
Abstract In areas of intensive agriculture, e.g. 'Pays de Caux' in France, which was the study area, field observations have shown that runoff directions were modified by agricultural activities. In order to account for factors responsible for modifications of the runoff direction (roughness, tillage direction and agricultural patterns, e.g. dead furrow or dirt tracks), we constructed a discriminant function based on field observations. This function enables us to decide whether flow direction for slopes of up to 15% was imposed by slope direction or tillage direction. It can be applied to any location, provided there are known roughness, known slope intensity, known aspect and known tillage azimuth. In order to examine the effects of these agricultural activities at the catchment scale, we compared two models by analysing the same hydrological variables: the area contributing to runoff and the flow network. The first model (Topo) was built according to the runoff direction derived from a Digital Elevation Model (DEM). The second model (Tillage) was constructed by combining information from the DEM, and information from rules based on field observations or resulting from statistical analysis. For 23 basic catchments, the result of the comparison between the two models (Topo and Tillage) showed that a major part of the catchments and the drainage network was affected by modifications related to the introduction of man-made agricultural factors. For example, for 20 of 23 catchments, the runoff flows over more than 50% of the surface of such areas were produced along the direction imposed by tillage. The introduction of tillage effect brings about modifications of both the shape and size of catchments. © 1998 Elsevier Science B.V. All rights reserved. Keywords: Runoff; Tillage direction; Catchment; Erosion
1. Introduction In the areas of Northern Europe that are underlain by loamy soil, the concentration of runoff is a widespread phenomenon, notwithstanding low rainfall intensity and a mild topography (Fullen and Reed, * Corresponding author. 0022-1694/98/$19.00 © 1998 Elsevier Science B.V. All rights reserved. PII S0022-1694(98)00103-6
1987; Boardman, 1990; Poesen and Govers, 1990; Papy and Douyer, 1991). This form of erosion results from the hydrological link between a runoffcontributing area and a collecting channel, where flow discharge and velocity exceed the critical values for rill initiation and development (Govers, 1985; Rauws and Govers, 1988; Foster, 1990; Govers et al., 1990; Moore and Foster, 1990). Interactions between
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
meteorological conditions, farming operations and topsoil texture bring about rapid and significant changes in the hydraulic properties of topsoil. This is due to soil infiltrability and surface water storage (Monnier et al., 1986; Papy and Boiffin, 1989; King and Le Bissonnais, 1992; Auzet et al., 1995) that determine its aptitude to produce runoff. Thus, gully initiation depends on the dynamics of topsoil crusting degradation (Boiffin et al., 1988). As a result, these studies showed the considerable role of agricultural activity in the development of ephemeral gullies. Nevertheless, many runoff studies have considered only local topography and calculated flow direction according to the slope aspect (Beven and Kirkby, 1979; Moore and Burch, 1986; Morgan et al., 1994; Merot et al., 1995). In the case of gentle slope, however, field observations showed that the preferential pathways for water circulation could be influenced by some man-made agricultural factors, e.g. dead furrows, dirt tracks, ditches and roughness due to tillage operations (Ludwig et al., 1995). The last factor is commonly used for characterising the temporary storage capacity of excess water on the soil surface (Mitchell and Jones, 1978; Onstad, 1984; Zobeck and Onstad, 1987), but its influence on runoff direction is rarely taken into account. Even when the effects of tillage are taken into account (Ludwig et al., 1995), most integration processes remain manual and thus applicable only occasionally, since no suitable procedure exists for automatically deciding runoff direction. This study had a dual aim: first it was desired to automatically consider the effects of certain agricultural factors on the direction of runoff flows; secondly, we wished to quantify the impact of these factors in small agricultural catchments that are chronically eroded. Such modifications have only a small local importance, but cumulative effects along the runoff network can strongly influence the hydrological characters of the catchment, e.g. cumulative areas or location of flow concentration. After describing a typology of the man-made agricultural factors that might influence runoff directions, we present the method used for taking into account these factors in a classical topographic water movement model (Topo) to build another model (Tillage) which attempts to better reflect real water flow. In the second part, we present the equation
257
used for modelling the runoff direction in crop fields. This equation allows the automatic determination of flow direction by using aspect and tillage directions, and can be used for all catchments. Finally, we present the results of the comparison of the two runoff circulation models (Topo and Tillage). This comparison, based on the analysis of the same hydrological variables, should enable the determination of the importance of modifications related to considering agricultural factors.
2. Materials and methods
2.1. Spatial and temporal context The survey was conducted on zero-order catchments. Auzet et al. (1993) defined these units as areas hydrologically related to a relatively wellmarked talweg (longitudinal profile) in the relief and corresponding to the ultimate ramification of a dry valley network. Their area usually ranges from at least 10 to at most 100 hectares. They constitute the representative elementary area (Wood et al., 1988) within which the release mechanism of concentrated flow erosion can be studied (Auzet et al., 1990; King et al., 1992). Sixteen agricultural catchments were selected as they were representative of catchments founding the Pays de Caux (Fig. 1), one of the regions of Northwest Europe in which this type of erosion is causing concern (Papy and Douyer, 1991). These catchments were also selected because they were known to be the site of previous erosion (Ouvry, oral communication). Catchments were observed during two agricultural years 1991-1992 and 1992-1993, providing potentially 32 'year-catchments' (Souchere, 1995). However, only 23 'year-catchments' were used for the study according to the presence of erosion features during the concerned period. In this paper, these 23 'year-catchments' are seen as 23 free independent catchments. They differed by the combination of topography and geometric configuration of farm fields (Table 1). Their topsoil texture was constant, being loamy (on average, 11% clay, 60% silt, 29% sand), which makes them particularly sensitive to porosity closure and the formation of impermeable crusts when subject to the impact of raindrops (Eimberck, 1990;
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
258
-.800
F e c a m P ~ L , ~.=l...___s ` ' ' °
~
~-
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o
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- - -
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~ 800: Annual mean precipitation (mm)
15 K m
Fig. 1. Location of catchments.
Table 1 Characterization of catchments Catchment Measurement number campaign
Area(ha)
% of area in slope intensity class < 1%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
1991-1992 1992-1993 1991-1992 1991-1992 1992-1993 1992-1993 1992-1993 1991-1992 1991-1992 1992-1993 1991-1992 1991-1992 1991-1992 1992-1993 1991-1992 1991-1992 1991-1992 1991-1992 1991-1992 1992-1993 1991-1992 1992-1993 1991-1992
21.90 12.14 12.14 4.96 4.96 19.78 28.96 14.73 8.37 8.20 8.20 13.33 23.03 15.92 43.16 14.73 8.34 63.94 3.48 3.48 19.78 27.36 27.36
13.39 37.53 37.53 10.46 10.46 40.58 11.67 12.68 0.48 32.03 32.03 0.22 14.27 7.13 5.1 12.68 2.99 24.4 10.32 10.32 40.58 20.49 20.49
1-2%
2-5%
5-10%
8.38 37.78 37.78 9.86 9.86 27.29 13.74 17.88 11.22 6.82 6.82 0.6 10.05 17.51 6.67 17.88 26.59 16.24 21.78 21.78 27.29 58.91 58.91
27.02 13.66 13.66 55.73 55.73 26.43 54.78 62.90 42.72 45.55 45.55 48.05 48.01 65.20 41.49 62.90 58.32 42.29 49.86 49.86 26.43 16.15 16.15
24.74 10.04 10.04 23.94 23.94 5.71 17.33 6.53 40.45 15.59 15.59 51.07 27.63 10.15 41.63 6.53 12.10 17.00 17.19 17.19 5.71 3.98 3.98
Number of farm fields
Orientation of farm fields a
5 8 4 3 3 11 10
// T T T T T fl // T T T // T fl // T T // T T T T T
> 10% 26.47 0.99 0.99 0 0 0 2.49 0 5.13 0 0 0.07 0.04 0 5.12 0 0 0.08 0.86 0.86 0 0.47 0.47
a//Orientation more-or-less parallel to the talweg; TOrientation more-or-less perpendicular to the talweg.
1
6 5 5 8 10 6 15 5 3 20 3 3 7 15 15
v. Souchere et aL/Journal of Hydrology 206 (1998) 256-267 Imeson and Kwaad, 1990; Le Bissonnais and Singer, 1992). Wheat, barley, sugar beets, pea and flax account for more than 60% of the arable lands in the Pays de Caux. With these crops, tillage operations are numerous between the beginning of October and the end of April. This period is also characterised by a high probability of precipitation. Since our objective was to show the effect of tillage on runoff direction, most of the observations were carried out during this period. From October to April, the farm fields of catchments were observed once or twice a month. Crop fields were observed from the harvest of the previous crop up to the last tillage operations of the following crop. The observations had the objectives of: (1) monitoring surface degradation in catchment areas; and (2) identifying the factors likely to change runoff flow directions.
2.2. Typology o f man-made agricultural factors that modify runoff directions Some of the factors that can influence runoff directions are permanent, e.g. roads and ditches dug for evacuating their water. Other factors appear and disappear as part of agricultural practice, e.g. dead furrows, ruts, ridges left by certain cropping operations, e.g. the harvesting of sugar beets or digging up of potatoes, and especially roughness created by tillage. On the smooth and impermeable surfaces of roads and dirt tracks, we assume that in the absence of ditches water flow will follow slope orientation. Ditches and dead furrows form water-conducting lines that are sufficiently deep to impose their direction on the surface flow.
Within crop fields, the situation is generally more complex since flow direction varies as a function of terrain roughness. Boiffin et al. (1988) conducted field observations that distinguished between several classes of roughness (Table 2). This classification, further refined by Ludwig et al. (1995), was used for calculating the difference between roughness in the tillage direction and that perpendicular to it on 60 plots localised on hillsides. The knowledge of this difference is of fundamental importance for estimating the obstacle that runoff must overcome to flow in the direction of steepest slope. These measurements were made for plots selected to represent the diversity in roughness, slope and tillage angles that are normal for the area under study. Ten observations were carried out on plots with a difference between the two roughnesses of greater than two classes (e.g. R0 in the tillage direction and R3 perpendicular to it). These observations showed that runoff always follows tillage direction. Fifty observations made on plots with a difference between the two roughnesses of less than or equal to two classes, showed that runoff direction was variable. In order to model the influence of tilling on these plots, we assumed that the runoff direction depends on two major variables: slope intensity, and the angle between azimuth directions of the steepest slope (aspect) and tillage. To verify this assumption, we measured the slope of the 50 plots with an Abney level and the angle between the two directions with a compass. At the same time, the actual runoff direction was noted, either by direct observation during rainstorms, or by analysing the traces left by runoff just after the event. The observations were ranked in two sub-populations corresponding to: (i) plots where the observed runoff follows predominantly the slope direction; and (ii) plots where tillage imposes the
Table 2 Grading of soil surface roughness (Ludwig et al., 1995) Grade
Roughness index
R0 RI R2 R3 R4
0-1 cm 1-2 cm 2-5 cm 5-10cm > 10cm
a
259
Typical agricultural situation Strongly crusted sown fields, harvested fields with intense compacting Sown fields with fine loosened or moderately crusted seedbeds Recently sown fields with a cloddy surface, crusted tilled fields without residues Stubble-ploughed fields and recently sown fields with a very cloddy surface Ploughed fields
a Difference in the heights of the deepest part of microdepressions and the lowest point of their divide.
260
K Souchere et al./Journal of Hydrology 206 (1998) 256-267 GRID DATA in GIS
DEM (Isolines)
Field Observations Legend: TillageDirection ROR.2 Classof roughness . Deadfurrow /
TOPOGRAPHICALFACTORS] Sic ~e As set
/ ~
t-,~ ,
.
V
AGRICULTURALFACTORS ] Tillage direction Roughness
Dead furrow Dirt track
Diseriminantfunction
TOPO MODEL
TILLAGE MODEL
owLo.
ow;oon
1
Runoff eontributing area
\
Flow network
t
Runoff contributing area
\
Flow network
COMPARISON
Fig. 2. Schematic presentationof the two models of runoff circulation.
runoff direction. Using these data, an analysis of variance and a discriminant analysis were carried out using the two variables chosen: slope intensity, and the angle between aspect and tillage directions, in order to produce a suitable procedure for automatically determining runoff direction.
2.3. Modelling runoff-direction changes at the catchment scale Two models were developed with the help of the GRID module of the Arc/Info Geographic Information System (Fig. 2). The first, Topo, is a standard topographic-runoff
261
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
Table 3 Runoff direction as a function of the types of objects Types of objects
Runoff direction
Field crop (including headlands) Differencebetween the two roughnesses > 2 Difference between the two roughnesses --< 2
Tillage direction Tillage or slope direction (decision as a function of statistical analysis) Furrow direction Direction of greatest slope
Dead furrow Dirt tracks, roads model (Beven and Kirkby, 1979; Moore et al., 1988). Using the contours from the l:25,000-scale IGN maps, a digital elevation model was calculated an elevation value was then attributed to each 10 x 10 m square grid cell. The software then used this value to determine the flow direction along the slopes. Flow paths are processed from cell to cell by directing the flow of each cell to the lowest of its eight neighbours. The drainage network was thus recreated and runoff-contributing area was estimated f6r all points of the catchment. In the case of the second model, Tillage, data obtained from the catchment plots were introduced into the GIS in order to modify runoff circulation directions according to rules based on field observations or resulting from statistical analysis (Table 3). Dirt tracks are linear elements that retain the usual behaviour of the standard model towards water flow movement when converted to raster form. In other words, runoff from one cell is directed to the lowest surrounding cell. On the contrary, well identified dead furrows, ditches and embankment slopes behave as
streams: runoff is forced along the down-sloping direction imposed by these linear features. In raster form, for each cell, unless the direction of the feature coincides with that of the lowest surrounding cell, the flow will be forced into another direction. Within agricultural plots, modelling of runoff direction employs data derived from the DEM (aspect and slope intensities) and data from field observations on each of the plots o f the 23 catchments (tillage direction and roughness). Tillage direction was converted to raster from the parcel data layer and then combined with aspect in order to compute the slope angle. Slope intensity and angle were used by the discriminant function to determine which cell is predominant in directing the flow between topography and tillage. Roughness assessments of each plot were used to determine if a discriminant function was to be applied or if the tillage direction was applied directly in order to reproduce runoff flow in all the cells of the same plot. A m o n g the roughnesses observed during one agricultural period, we used the one measured at the gully initiation. After their introduction, these
Water follows the dir~ticn of:
A T~llasc • Slopc
14
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12
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V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
262
Table 4 Results of statistical analysis (observations on 50 plots) Analysis of variance
Basic statistics a
Variables
Residual variance
Residual standard deviation
Calculated F
F of Ficher-Snedecor (0.01%, 1.48)
Means
Standard deviations
Angle (°) Slope (%)
275.97 6.34
16.61 2.52
24.09 24.29
7.31 7.31
61.74 5.45
19.95 3.03
a The basic statistics enable variables to be centred and reduced when slopes are expressed as a percentage and the angles in degrees.
modifications then provide a new water circulation network and new values for hydrological variables, e.g. the runoff-contributing area.
3. Results and discussion
3.1. Effect of tillage on runoff directions within crop fields Fig. 3 shows the results of observations made on the 50 plots with a difference between the two roughnesses equal or lower than two classes. This shows the existence of two relatively distinct groups, depending on whether the runoff direction follows the tillage direction (Group 1), or the slope direction (Group 2). Analyses of variance for the 50 plots show the positive role played by each of the variables slope and angle, for distinguishing the two runoff-direction groups. In both cases, the Ficher-Snedecor 'F' was lower than that calculated during analysis (Table 4), but the values obtained (24.09 and 24.29) are too close to envisage the use of one variable rather than the other. Two groups of runoff directions could be distinguished by conducting a linear combination between the two variables (Table 5). When assuming H0 (no group effect), the pseudo F value has a probability that becomes null (Table 5). In reality, this probability is not strictly null, but is very low and below the 1% threshold; it allows H0 to be
discarded and leads to the conclusion that runoff-direction differences indeed exist between the two groups. The calculated pseudo F value of 70.24 is well above the two highest F values of the preceding variance analyses (Table 4). This comparison gives a 'qualitative' idea of the gain provided by a discriminatory analysis. It is thus interesting to combine the two variables when trying to distinguish between the two groups, since discriminatory analysis considers not only the average differences between groups, with variances of each variable, but also the correlations between variables (Tomassone, 1988). During this discriminatory analysis, the following equation is calculated for the discriminating factor axis (D): D = - 0.6646 A n g l e - 0.6669 Slope where the angle is the standardised variable of the angle between the slope aspect and tillage direction; and slope is the standardised variable of the slope intensity. This discriminant function assists in the subsequent classification of observations into one of the two groups corresponding to runoff directions. Any observation with a coordinate on axis D below 0.12 (the value that represents the equidistant point for the centred projections of the two groups on the discriminating axis) is assigned to Group 2, i.e. runoff in the slope direction. For coordinates above 0.12, the observation is assigned to Group 1, i.e. runoff in the tillage direction.
Table 5 Results of discriminatory analysis for 50 observed plots Axis
Ow value
Inertia
Pseudo F
Wilks
ddl
Probab. %
Correlation
1
1.4632
100%
70.24
42.37
2
0.00
0.59
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267 Table 6 Result of classing observations Allocation Groups Well-classifiedobservations:92%
Groupl
Group2
Groups of origin
GI-Tillage (size 21)
19
2
G2-slope (size 29)
2
27
Reclassification of the observations made on the 50 plots showed very good coincidence with initial classification (Table 6). The four 'poorly classified' observations correspond to intermediate situations observed in the field. It was actually seen that runoff can successively follow the slope aspect and then the tillage directions. In this case, we assigned the observations to the majority direction, but this decision remains open for discussion.
3.2. Consequence of considering man-made activities at the scale of catchments We have presented the method using a Geographic Information System to modify a model of topographic circulation of runoff water. The results of these modifications were analysed by calculating the surfaces involved, and examining the transformation of network structure and the aspect of catchments when either of the two models was used (Tillage or Topo).
3.2.1. Surfaces affected by modifications in runoff direction We calculated the percentage of grid meshes affected by a modification for each catchment. This showed that for 20 of 23 catchments, the runoff flows that produced over 50% of the surface of such areas followed the direction imposed by tillage (Table 7). For nine catchments, more than 75% of their surface was concerned by this flow direction. This shows that the modifications affected a large number of pixels in each catchment. The low number of meshes affected by modifications induced by dead furrows is due to the linear character of such features.
3.2.2. Types of modifications For dead furrows, a low number of modified pixels does not necessarily mean that there was no effect on
263
Table 7 Runoff directions in each catchment (as percentage of catchment surface) Catchment number 1
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Mean
Flow direction is imposed by: Slope
Tillage
Dead furrows
53 20 13 33 39 12 7 25 46 5 27 30 38 20 39 19 31 37 62 52 14 34 33 30
47 78 85 58 54 88 93 75 54 91 69 67 61 76 57 81 69 59 22 38 86 61 67 67
0
2 2 9 7 0 0 0 0 4 4 3 1 6 4 0 0 4 16 10 0 5 0 3
runoff direction. It depends on the size of the modification and especially its location in the catchment. It is thus necessary to study the effect that runoff has on the catchment as a whole, taking the cumulated effects into consideration. Two effects are analysed below: the modification in location of the drainage network; and modifications in the catchment surface. The results are presented and discussed on the basis of a single catchment area, but identical results were noted for the other catchments. Fig. 4 shows the circulation network followed by runoff water in Catchment 15 according to the Topo (line a) and Tillage (line b) models. Clear differences are seen between the structures of the two networks. These modifications cause differences in the location of water concentration points in talwegs. Fig. 5 shows the increase in drained surface when going along the main talweg of catchment 15: depending on the runoff model, it can be seen that abrupt increases in drained surfaces do not occur in the same place of the talweg.
V. Souchere et al./Journal of Hydrology 206 (1998) 256-267
264
CATCHMENT NUMBER 15 ~~
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TOPO MODEL (a)
" " ,,,. TILLAGE MODEL (b)
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Fig. 4. Trajectories followed by water according to the runoff model.
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Measure points along the talweg [--
TILLAGE Model - -
TOPO Model
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Fig. 5. Increase in the drained surface along a thalweg depending upon the runoff model used.
V. Souchere et al./Journal of ttydrology 206 (1998) 256-267
265
70-
I 1 T O P O Model
["-"~TILLAGE Modcl
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50.
40. 30. 20 10
,dig 2
3
4
5
6
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Catchment number
Fig. 6. Changes in catchment surface according to the runoff model used. Fig. 5 also shows that even though the first increases are offset in space, they have similar amplitudes. Beyond point 50, however, the Topo model not only shows an earlier final increase, but also an amplitude variation. Here, the drained-surface value from the Tillage never reaches that of the Topo model. This indicates a modification not only in the location of erosive phenomena, but also in their intensity. Fig. 4(a) and (b) shows the boundaries of Catchment 15 calculated from each runoff model in bold. It can be seen that both the shape and size of the catchment have changed, the latter from a 43 hectare (ha) surface for the Topo model to 37 ha surface for the Tillage model. About 9 ha of the topographical catchment feed a second outlet [left side of graph (a)], when considering man-made agricultural factors. Taking the same factors into account, however, leads to the recovery of slightly over 3 ha from an adjoining catchment [right side of graph (b)]. Water thus crosses topographic crest lines by following the micro-channels that are created by, e.g. sowing lines. This example is not an exception. Similar changes in catchment surface were observed for all samples investigated. A total of 16 was subjected to variations in their surface to an absolute value of over 25%, and nine had variations of over 50%. This was the case, e.g. for Catchment 1, where the 22 ha of the Topo model were reduced to only 10 ha with the Tillage model (Fig. 6). The same figure shows that some catchments, e.g. 2 or 19, have almost the same surface areas Ibr both runoff models. It is, however,
difficult to provide a general rule for such modifications, since they depend primarily on the arrangement of plots within the catchments and on the direction of the main man-made features within such catchments.
4. Conclusions We have shown that it is possible to use a GIS to model soil surface runoff water by taking into account certain agricultural factors. For a sample of cultivated catchments, the areas modified by considering tillage direction and observed flow paths commonly involve over 50% of the catchment areas. Changes in runoff direction are shown in particular by variations in the location of runoff concentration points within the talweg. The catchment area itself is also modified. This means that any definitions that use only morphological variables to define the geographic boundaries are insufficient when the topography of the catchments is not highly accentuated. More generally, it would be important to take into account these results in the calculation of the runoff contributing area from a DEM because this variable is classically used in hydrology or geomorphology (Moore and Burch, 1986). Even though the existence of modifications of varying importance can be identified, the correct validation of such results at the scale of an entire catchment remains difficult. This is because it would
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~ Souchere et aL/JournalofHydrology 206 (1998) 256-267
be necessary to measure water flux in all points of the catchment space. To this end, a study is in progress that uses talweg erosion as the possible tracer for the greatest water fluxes. The location of rills and gullies has been investigated in the past (Moore et al., 1988; Thorne et al., 1986), but without considering manmade agricultural factors. Using the newly developed 'Tillage' model, we intend to demonstrate the effect of such man-made agricultural factors on runoff and erosion. The current version of the Tillage model remains incomplete. It does not take into account the true quantities of runoff water, since the infiltration capacities of the plots, as well as precipitation intensities were not included. The height of the runoff water layer certainly plays an important role in a dynamic and interactive process. However, the proposed discriminant function is the first step which can be included in the runoff routing module of erosion or pollution models.
Acknowledgements The authors thanks Alain Couturier for his assistance with data processing, Jeffrey Diamond for the quality of his translation, and the Regional Council of Haute-Normandie for its financial contribution.
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