Analysis of soil surface component patterns affecting runoff generation. An example of methods applied to Mediterranean hillslopes in Alicante (Spain)

Geomorphology 101 (2008) 595–606

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Analysis of soil surface component patterns affecting runoff generation. An example of methods applied to Mediterranean hillslopes in Alicante (Spain) E. Arnau-Rosalén a,⁎, A. Calvo-Cases a, C. Boix-Fayos b, H. Lavee c, P. Sarah c a b c

Department of Geography, University of Valencia, Avenida Blasco Ibañez 28, 46010, Valencia. Spain Soil and Water Conservation Department, CEBAS, Spanish Research Council (CSIC), Campus Universitario de Espinardo, PO Box 164, 30100 Murcia, Spain Laboratory of Geomorphology and Soil. Bar-Ilan University, Ramat Gan, Israel

A R T I C L E

I N F O

Article history: Received 4 July 2007 Received in revised form 27 February 2008 Accepted 1 March 2008 Available online 13 March 2008 Keywords: Soil surface components Runoff generation Patterns Hillslope processes

A B S T R A C T Spatial patterns of soil surface components (vegetation, rock fragments, crusts, bedrock outcrops, etc.) are a key factor determining hydrological functioning of hillslopes. A methodological approach to analyse the patterns of soil surface components at a detailed scale is proposed in this paper. The methods proposed are applied to two contrasting semi-arid Mediterranean hillslopes, and the influence of soil surface component patterns on the runoff response of the slopes was analysed. A soil surface components map was derived from a high resolution photo-mosaic obtained in the field by means of a digital camera. Rainfall simulation experimental data were used to characterise the hydrological behaviour of areas with a specific pattern of soil surface components by means of the parameters of the Horton equation. Plot runoff data were extrapolated at the hillslope scale based on the soil surface component maps and their hydrological characterisation. The results show that in both slopes runoff generation is concentrated up- and downslope, with a water accepting area in the centre of both slopes disrupting the hydrological connectivity at the slope scale. This reinfiltration patch at the centre of the slope is related to the type of soil surface component and its spatial pattern. Herbaceous vegetation and ‘on top rock fragments’ increase the infiltration capacity of soils at the centre of the slope. In contrast, embedded rock fragments, rock outcrops, as well as crusted surfaces located in the upper and lower slopes favour runoff generation in these areas. In addition, a general pattern of water contribution areas downslope is apparent on both slopes. The south-facing slope shows a higher hydrological connectivity and more runoff. 55% of the surface of the south-facing slope produces runoff at the end of a 1 hour rainfall event and 17.3% of the surface is covered by a runoff depth between 0.5 and 1 mm. While on the north-facing slope only 38% of the surface produces runoff under the same conditions. Longitudinal connectivity of runoff is higher at the south-facing slope where more runoff-generating surfaces appear and where the vegetation pattern favours the connectivity of bare areas. © 2008 Elsevier B.V. All rights reserved.

1. Introduction The study of the spatial patterns of soil surface components (vegetation, rock fragments cover, rock outcrops, bare soil, soil surface crust) is key to understanding the hydrological behaviour of hillslopes. In Mediterranean environments in which the climatic conditions vary from arid to sub-humid within the semi-arid range, like in SE Spain, an important water deficit exists together with a high seasonality and high intensity of rainfall during storm events (López-Bemúdez and Albadalejo, 1990). In addition to this, the high impact of past and present human activities causes a landscape characterised by a dispersed and patchy vegetation cover which widely influences the hydrological and erosional behaviour of Mediterranean hillslopes.

⁎ Corresponding author. E-mail address: [email protected] (E. Arnau-Rosalén). 0169-555X/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.geomorph.2008.03.001

In this context the basic mechanism of runoff generation at plotand hillslope scale is the infiltration excess or Hortonian overland flow (Yair and Lavee, 1985; Lavee et al., 1998; Beven, 2002) although with a remarkable spatial discontinuity (Calvo-Cases et al., 2003; Boix-Fayos et al., 2006). The Hortonian overland flow appears under certain circumstances to be combined with saturation excess overland flow (Martínez-Mena et al., 1998; Lange et al., 2003; Calvo-Cases et al., 2003). Closely related to the runoff generation mechanisms is the infiltration capacity of the soils. Infiltration capacity is the most important factor controlling runoff. Soil infiltration capacity is characterised by a high spatial variability related to the high spatial variability of soil properties (structure, organic matter content, antecedent soil moisture, etc.). Some soil properties are also related to soil surface characteristics (vegetation cover, rock fragments cover, rock fragments position, different types of crusts, etc.) usually distributed in patches upon the hillslopes (Brakensiek and Rawls, 1994; Lavee et al., 1998; Maestre and Cortina, 2002; Roth, 2004).

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Most of the experimental set-ups developed and used to obtain data on infiltration and runoff processes have been concentrated at the plot scale (variable in size from less than 1 m2 to a significant part of a hillslope) and, both in measurements under natural rainfall events and simulated rainfall experiments, have illustrated the high spatial and temporal variability of the response. On plots covered by vegetation, the general response has been the important reduction of runoff rates at a certain threshold of cover (i.e. 30% in Francis and Thornes, 1990, or 20% in Alexander and Calvo, 1990). Most of the differences in runoff rates were related not only to the total vegetation cover but also to the different interception, stemflow and throughfall as a result of differences in the plants physiognomy and structure (Wainwright et al., 2000; Casermeiro et al., 2004). Between this disperse vegetation the soil in the Mediterranean environments shows a widespread presence of rock fragment cover (Poesen, 1990). When the effects of the rock fragment cover were analysed by examining the percentage of cover, the size and the relative position of rock fragments (on top of the soil or partially embedded) (Poesen et al., 1990; Lavee and Poesen, 1991; Poesen and Ingelmo-Sanchez, 1992; Moustakas et al., 1995), significant changes in the runoff response were found and their dynamic role in the erosion process was taken into consideration (Kirkby et al., 1998). Another important factor responsible for the spatial variability of soil infiltration capacity and runoff generation is the formation and dynamics of soil surface crusts (Morin and Benyamini, 1977; Farres, 1978; Roth and Helming, 1992; Greene and Hairsine, 2004). The results obtained by most of the experimental work done at plot scale allow the understanding of the hydrological response under different conditions of soil protection against the raindrop impacts linked to soil properties. Lavee et al. (1998) pointed out how the variability in the response reflects a spatial heterogeneity of surface characteristics, and stressed the idea of internally homogeneous patches controlled mainly by the spatial distribution of vegetation, stones, crusts, etc. These homogeneous patches, termed surface cover components in Lavee et al. (2004), are considered as an elemental, visible, detectable and discrete expression of such soil surface

characteristics, and thus as homogeneous hydrological response units. In a similar way to the response units described for broader scales (Casenave and Valentin, 1992; Cantón et al., 2002; Cammeraat, 2004) and as a way of upscaling the analysis (Imeson et al., 1994, 1995). As a consequence of the high variability in the hydrological response, the conceptual runoff model described for semi-arid environments implies the discontinuity of the overland flow (Lavee et al., 1998; CalvoCases et al., 2003; Boix-Fayos et al., 2006), and from a functional hydrological point of view has been described as a mosaic-like pattern of runoff source and sink areas (Yair and Lavee, 1985; Lavee et al., 1998; Ludwig et al., 2005). This discontinuity has also been supported by experiments based on multiscale rainfall simulations (Bergkamp, 1998; Cammeraat and Imeson, 1999; Wainwright et al., 2000; Wilcox et al., 2003), showing how the rate and length of the flow decrease with the plot length because of the progressive reinfiltration in the sink areas (usually covered by plants) downslope. All these considerations have implications for the system functioning at different scales. At patch scale, Puigdefábregas (2005) explains, with the concept of ‘vegetation driven spatial heterogeneity’ (VDSH), the process of spatial differentiation in individual patches by the feedback mechanisms promoted by plants that produce runoff sink areas under the plants. At stand scale, where the spatial structure of the patches and their interaction becomes relevant, the water redistribution process is induced by soil patches of different hydrological properties (Puigdefábregas et al., 1999; Cammeraat and Imeson, 1999) or by the reversing of the ‘Robin Hood effect’ of Ludwig and Tongway (2000). At hillslope scale the discontinuity becomes a hydrological disconnection between the slope parts, affecting the contribution of overland flow to the stream flow. The connection occurs only above certain amounts of rainfall (Yair and Lavee, 1985; Puigdefábregas et al., 1998; Calvo-Cases et al., 2003; Cammeraat, 2004). For some authors the size of the contributing patches or the grain size of the pattern is important qualities affecting the possibilities of water export by surface runoff (Lavee et al., 1998; Puigdefábregas, 2005; Boer and Puigdefábregas, 2005).

Fig. 1. Study area location map. A: Position of the transects in the north- (NFS) and south-facing slopes (SFS). B: Hillslope profiles.

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The two-phase mosaic (vegetated and bare) has an important function in the overall increase of the plant production and diversity, as a result of new nutrients and water resource status (Noy-Meir, 1981; Aguiar and Sala, 1999) at the transition from a regular vegetation cover to a patchy situation occur. Mathematical modelling pointed out that this process can be chiefly responsible for the origin and maintenance of vegetation pattern distributions in arid and semi-arid ecosystems (HilleRisLambers et al., 2001; Rietkerk et al., 2002; Zeng et al., 2005). The relevance of the soil surface components distribution patterns for the hydro-ecological processes, and especially the spatial distribution of the vegetation, has encouraged a series of efforts in mapping and parameterising the morphological characteristics (Wu et al., 2000; Shoshany, 2002; Imeson and Prinsen, 2004; Boer and Puigdefábregas, 2005). The objective of this paper is to develop and apply a methodology devoted to characterising the runoff patterns occurring at hillslope scale in Mediterranean environments, taking into consideration the influence of the spatial distribution of soil surface components (SSC). The methodological approach adopted considers dry, semi-arid environments with a high human impact where soil surface components can play an important role in the hydrological response of soils. The focus of the paper is (i) analysis of the pattern of soil surface components by detailed mapping on contrasting hillslopes and (ii) examination of the influence of soil surface components on the hydrological response of hillslopes during rainfall events.

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isation of the hydrological response of each SSC type by means of field rainfall simulation experiments; and (iii) the simulation of the hydrological response at the hillslope scale.

2. Study area The work has been carried out on the two valley sides (north- and south-facing) of a gully or ravine dissecting NW-SE the Serra Cortina mountains (Fig. 1), near Benidorm (Alicante, Spain). The lithology is composed of Senonian limestones and the climate is Mediterranean semiarid mesothermic (387 mm of annual rainfall and 17.9 °C mean annual temperature) with a high water deficit limiting vegetation development. The soils, classified as Lithic Leptosols and Petric Calcisols according to FAO (1998) (Boix-Fayos et al., 1998; Boix Fayos, 1999) are shallow (10– 30 cm in depth). Carbonates content is high (25–52%) and with very low organic matter content (an average of 5.18% on the north-facing slope and an average of 5.01% on the south-facing slope). The soil structure includes large and massive aggregates due to the high activity of earthworms (Boix-Fayos et al., 2001), although with high bulk density values and low water retention capacity. Present day vegetation series are defined as Stipion tenacissima (Rivas-Martínez, 1987). Agricultural and livestock grazing activities have been absent from the area since 1975. At the valley bottom are the remains of agricultural terraces, and in the lower part of the north-facing slope a concentration of large and homometric rock fragments denote the existence of a series of cultural terraces abandoned in 1940. These old terraces are not reflected in present day topography; walls have collapsed, the soil redistributed and the area is densely covered by vegetation, mainly Pinus halepensis, which also colonise the valley bottom terraces. In these ones only some short gullies have developed in connection with wall collapse, but still there is no continuity in the dissection process. Both hillslopes (Fig. 1B) have a similar form, with a convexity on the summit followed by a long rectilinear segment and a slight increase of slope in the lower 5 m. The average slope is 18° and 22° in the north- and south-facing slopes, respectively. In this context, two transects along the south- and north-facing slopes (SFS and NFS, respectively, in Fig. 1A) were selected to carry out the characterisation of soil surface components. 3. Methods The methodological approach includes: (i) detailed mapping and analysis of the spatial pattern of soil surface components (SSC) affecting runoff generation and sediment movement; (ii) character-

Fig. 2. Photo-mosaic of the two studied transects (diagonal lines visible in the mosaic are the shadows of the pole used for the camera).

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3.1. Mapping the soil surface components pattern The soil surface along a transect of 5 m-wide transect running from the hillslope summit to the bottom and following the maximum slope, was photographed using a digital camera (Nikon Coolpix 990; 3.4

Megapixels; with a focal length = 8 mm, equivalent to 38 mm in 35 mm format). The camera was placed, by means of a pole, perpendicular to the surface at a height of 6 m in the centre of each rectangle of a 2.5 × 3 m grid previously marked along the transect using highly visible pins. The grid knots were georeferenced in the field using a laser Total Station (Sokkisha SET-5). The resulting images, with about 50 cm overlap, were rectified to the topographical grid using the ArcGis 9 Georeferencing Tool by considering as reference points the four marks (grid knots) present in each photogram. As a result, a photo-mosaic with a 3 mm per pixel resolution (Fig. 2) was obtained. This resolution allows the identification of the soil surface components that are considered as affecting the magnitude of the runoff generation rates. The image was then photo-interpreted by mapping the polygons belonging to each of the twelve Soil Surface Component Classes of the legend (Fig. 3). For the vegetated surfaces four classes were distinguished according to the particular canopy and physiognomy characteristics of the most representative plants considered important in determining the hydrological response. In this sense four vegetated classes were considered: (i) trees (Pinus halepensis); perennial grasses characterised by (ii) Stipa tenacissima and (iii) Brachypodium retusum; and (iv) shrubs (grouping other plants). Plant mapping has been done (including in the polygons all the crown area of each plant or plant clusters) in the horizontal projection (Fig. 3). Field observations and previous work (Boix-Fayos et al., 2001) confirm that the entire crown of most of the plants and specially the Stipa tenacissima, exerts a protective role on the soil surface keeping a good soil structure and giving for each plant a homogeneous hydrological response. The non-vegetated surfaces were sorted in three class intervals of hydrological significance, according to the abundance of rock fragment cover (b25%; 25–70%; N70%) and the position of the rock fragments in relation to the soil surface (‘on top’ or ‘partially embedded’), because of the strong influence over the hydrological response as pointed out by several authors (Poesen et al., 1990). This results in six classes of SSC according to the rock fragment cover range and position. Finally, two more classes including the non-vegetated parts covered by litter and the bare rock outcrops were defined. In the photo-interpretation/digitalisation process a number of criteria have been applied in relation to the minimum polygon size. For the vegetation, individual plants have been mapped down to a minimum size of 20 cm2. Similarly, individual rock outcrops and litter patches have been mapped. For the bare soil and rock fragments covered components, distributed in intervals of cover, the applied criterion of minimum patch size has been established at 100 cm2. 3.2. Characterisation of the hydrological response

Fig. 3. Soil surface components (SSC) map. The inset shows an enlargement from the upper south-facing hillslope of the base image and the resulting map.

The hydrological characterisation of each soil surface component class was made by analysing the data of previous rainfall simulation experiments carried out by Boix-Fayos et al. (1998, 2001) and CalvoCases et al. (2003) on the same hillslopes studied here: 13 experiments on different kinds of vegetated patches (8 on the north- and 5 in the south-facing slope) and 7 plots in un-vegetated patches (2 and 5 in the north- and south-facing slope, respectively). These 20 experiments cover most of the SSC classes, with the exception of the following classes: Pinus (where the rainfall simulation method used is not suitable); rock outcrops; b25% and 25–70% of rock fragments embedded. Also, eleven field experiments carried out by Corell (1998) in a neighbouring and very similar south-facing slope have been taken into consideration. In both areas the field experiments were conducted using the same equipment described in Cerda et al. (1997), with an average rainfall intensity of 55 mm h− 1 and 60 min duration, over plots between 0.17 and 0.27 m2 in surface area and adapted to the microrelief. 12 plots contain homogeneous soil surface properties and the rest composite soil surface classes (i.e. mixed plants types or mixed plants with bare

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surfaces). The experiments were carried out during the summer with the driest possible soil moisture conditions. The rainfall simulation data were adjusted to the Horton model using Eq.(1) (below) adapted to the particular characteristics of infiltration/ runoff data derived from the rainfall simulation experiments: Rnf ¼ ðI  FcÞT½1  exp:ðaTðT  60TPo=IÞÞ

ð1Þ

Where: Rnf (mm h− 1): Runoff I (mm h− 1): Rainfall intensity Fc (mm h− 1): Final infiltration rate at steady state α: Decay rate of infiltration rate according to Horton model or speed at which Fc is reached T (min): Time from the beginning of the rainfall Po (mm): Rainfall needed for runoff initiation The analysis of the rainfall simulation data was based on the three parameters of Eq. (1) (α, Po and Fc). These parameters characterise the dynamics of each type of soil surface component. Using a clustering classification technique with these three variables plus the runoff coefficient and the average runoff rate of the experiments (only for plots with homogeneous surfaces), the main trends in the behaviour of the soil surface component characteristics (i.e. plant morphology, rock fragment cover and position) and the differences induced by aspect, have been identified. Based in this, a number of criteria have been established for extrapolation/assignation of the Eq. (1) parameters to those soil surface component classes without available empirical data. 3.3. Simulation of the hydrological response at the hillslope scale The application of the runoff hydrographs, characterising each soil surface component class, at different timescales to each soil surface component patch mapped along the slope was done in a simple way to obtain a visual and analysable representation of the runoff generation process at the hillslope scale. As a first steep the digital map of the soil surface components was rasterised to a 5 cm per pixel resolution map (maximum size to keep all the patches digitized in vector format) in which each pixel is assigned to a soil surface component and to a hydrograph resulting from the rainfall simulations.

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Using a simple application written in Visual Excel the rainfall– runoff–infiltration process was distributed at one minute intervals. In the distribution process the rainfall reaching the soil in one minute was divided into two parts according to the runoff coefficient obtained from the hydrograph per each time unit. The rainfall fraction resulting in runoff at each time and pixel unit is added to the rainfall of the following time unit in the pixel immediately below and the corresponding runoff coefficient applied successively. Modelling considers only downslope water movement because of the limitation of simulating over a narrow strip of land and in order to avoid water losses through the limits. 4. Results 4.1. Spatial distribution of surface components along the hillslopes Both hillslopes, north- and south-facing, show a relatively uniform distribution of the main plants (Figs. 2, 3). However, this distribution must be placed within a context of a vegetation pattern dominated by a two-phase mosaic (vegetated and non-vegetated patches of different surface component classes). The surface component maps (Fig. 3) and the proportions of each component (Table 1), show a higher proportion of vegetation cover on the north-facing slope. The ratios of vegetation/no vegetation show values of 1.61 and 0.83 for the north- and south-facing slopes, respectively. On the north-facing slope the vegetation is more regularly distributed. In contrast, on the south-facing slope the distribution of plants is structured along three belts that are different in the size of the clusters of plants and in their diversity. The middle part of the slope is characterised by the abundance of herbaceous and smaller plant clusters compared with the upper and lower parts. In the upper and lower slope areas Stipa tenacissima tussocks are dominant. With respect to the cover of ‘on top rock fragments’ it is remarkable that the south-facing slope shows a high percentage of this component (43.86%, Table 1) concentrated along some belts, especially in the lower third of the hillslope (Fig. 4). However, on the northfacing slope the distribution of ‘on top rock fragments’ is mainly concentrated in the lower half of the slope. Looking at the component proportions (Table 1), high vegetation diversity on the north-facing slope contrasts with the dominance of Stipa tenacissima on the south-facing slope. On the contrary, the south-facing slope shows a higher diversity of abiotic components,

Table 1 Soil Surface Components cover (%): (A) directly extracted from the cartography (rock fragments cover in interval classes) and (B) conversion to absolute rock fragment cover with respect to the values of the interval classes centre in cartography (a = 12.5; b = 47.5 and c = 85) Soil surface component type

Surface cover from cartography classes (%) (A)

Surface cover from RF conversion (%) (B)

North-facing slope

South-facing slope

North-facing slope

South-facing slope

61.75 24.96 17.79 11.46 7.54 38.25 2.67 34.27 0.50 15.95 17.83 0.93 0.90 0.04 0.00 0.37

45.29 31.68 5.48 8.13 0.00 54.71 0.50 43.86 7.14 16.21 20.51 8.89 0.65 2.17 6.07 1.46

38.25 2.67 22.79 0.06 7.58 15.15 0.13 0.11 0.02 0.00 0.37 12.29

54.71 0.50 26.02 0.89 7.70 17.43 6.27 0.08 1.03 5.16 1.46 20.45

Vegetated Stipa tenacissima Brachypodium retusum Shrubs Pinus halepensis Non-vegetated Litter On top rock fragments b25%a 25–70%b N70%c Embedded rock fragments b25%a 25–70%b N70%c Rock outcrops Bare crust⁎ ⁎Bare crust cover derived from this conversion.

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In Fig. 5 four ratios between some soil surface components have been calculated showing the variation along the hillslopes at 5 m intervals from the divide. These ratios include the ‘on top rock fragments cover’ vs. ‘other no vegetation’ components, which illustrate the rock fragment distribution in the areas between plants. Also, the ‘vegetated’ vs. ‘non-vegetated’ areas and another two ratios concerning the rock fragment type and abundance (see Fig. 5) are included and calculated always from the proportions of the rock fragment cover recalculated from the map legend intervals contained in Table 1. On the south-facing slope there is a progressive increase in the total rock fragment cover ratio along the slope profile. Distinguishing between ‘on top’ and ‘embedded’, the embedded ratio is higher on the summit, remains low and stable along most of the hillslope and increases considerably at the bottom. In general, the south-facing slope is more structured, with the upper and lower parts as areas with a clear condition of soil erosion. In contrast, the central slope has more bare soil and also a very high amount of ‘on top rock fragments’ cover. On this slope the rock fragments situated on top are highly susceptible to movement and the accumulation of rock fragments following microrelief depressions is frequent. With locally high erosion rates (see Calvo-Cases et al., 2005) and bare soil surfaces with crust, the rock fragments (that are subangular to rounded) are easy to move when trampling or raindrop impacts push them downslope. As a result, the surface covered by ‘on top rock fragments’ increases downslope, along the central part of the south-facing slope (Fig. 4). Near the summit the values are lower, as it corresponds to a source area, and in the last 10 m there is a decrease. On the north-facing slope most of the rock fragment cover corresponds to ‘on top’ and the ‘embedded’ are not important. There is also an increase of the rock fragment cover in the central slope,

Fig. 4. Distribution of the percentage of each SSC at 5 m intervals along the hillslopes.

while on the north-facing slope the surfaces covered with a high density of rock fragments are dominant. Together with the differences in vegetation cover (61.8% on the north-facing slope and 45.3% on the south-facing slope) the absence of rock outcrops and embedded rock fragments (0.4 and 0.9% respectively) on the north-facing slope is very important, indicating a very small amount of soil loss under present conditions. In contrast, rock outcrops and embedded rock fragments are present on the southfacing slope at 1.5% and 8.9%, respectively. However, the patches of ‘on top rock fragments’ are abundant on both slopes (Table 1) and continuous (Figs. 3, 4). In fact, considering the values of the centre of the mapping class intervals, values that are more similar to those obtained when estimating cover directly in the field, the percentage of rock fragment cover referred to the whole area is 22.9% and 32.3% on the north- and south-facing slopes, respectively. When these values are recalculated to a proportion in relation to only the non-vegetated patches (as is usual in the literature, i.e. Poesen et al., 1998, and more suitable to evaluate the stoniness of bare surfaces) the proportion of rock fragment cover increases to 65.1% and 61.2% on the north- and south-facing slopes, respectively. Looking at the changes at 5 m intervals from the divide to the bottom (Fig. 4), some herbaceous (B. retusum) are dominant in the middle part of both slopes. Trees (P. halepensis) appear mainly in the lower half of the north-facing slope (between 20 and 40 m from the divide). On the south-facing slope, components that are indicators of past or existing soil loss, such as rock outcrops and embedded rock fragments, are located in the upper (between 0 and 25 m from the divide, Fig. 4) and lower parts of the slope (between 60 and 65 m from the divide, Fig. 4).

Fig. 5. Significant ratios of soil surface components in bands of 5 m from the divide to the bottom of the transects: (i) vegetated vs. non-vegetated area; (ii) total RF vs. nonvegetated area (including bare crust, litter and rock outcrops); (iii) on top RF vs. other non-vegetated area (including embedded RF, bare crust, litter and rock outcrops) and (iv) embedded RF + rock outcrops vs. other non-vegetated area (including on top RF, bare crust and litter). RF: Rock fragments.

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plots on 25–70% of rock fragments on top have coefficients of 0.16 on the north-facing slope and 0.3 on the south-facing slope). The available series of rainfall experiment data corresponding to a unique soil surface component (plots in Fig. 6) were analysed in terms of the runoff generation processes, looking at the individual parameter behaviour (Po, α and Fc) that define the runoff hydrographs (Fig. 7) and surface component characteristics. The results of this analysis give criteria for the extrapolation of the measured runoff values to the components without existing information in both, vegetated and nonvegetated soil surface component patches.

Fig. 6. Cluster analysis (Ward's method and Euclidian distance) grouping the rainfall simulation experiments that correspond to plots with homogeneous SSC. Variables: Average runoff rate, Runoff coefficient and α, Po and Fc parameter in Eq. (1). Groups: G = Vegetated plots (A = Stipa tenacissima; B = Brachypodium retusum; C = Shrubs); H = Bare areas (D = Surface sealing; E = Rock fragments ‘on top’ on south-facing slope; F = same as E on north-facing slope).

explained by the collapse of old agricultural terraces, but the ratio trend is progressive and does not seem to reflect excessive movement of the rock fragments. The ratio of ‘vegetation vs. no vegetation’ (Fig. 5) is similar on both hillslopes, with an increase in the centre and lower ratio values at the two ends. 4.2. Characterising the hydrological behaviour of the soil surface components Runoff coefficients in the whole set of experiments show a huge difference between vegetated and bare surfaces; 0.02 and 0.25 on average, respectively. Between the different vegetated plots the variability is very low, and also the differences are minimal considering aspect (0.02 on north- and 0.03 on south-facing slopes, respectively). These values reflect the evident sink function of the vegetation. In the experiments on bare patches aspect introduces important differences (Fig. 7) for the same soil surface component (i.e.

4.2.1. Runoff response on the vegetated components Between the vegetated components there are slight differences in the infiltration capacity ((Fc) values) (Table 2 and Fig. 7). In contrast, the velocity of the hydrological response of the soil (Po, time to runoff) or the runoff increment speeds (α), are more effective in discriminating between the types of response. Those parameters that in the data set are affected by the plants' morphology (physiognomy, height, total cover and density of the plant stems) influence the interception and the stemflow. As can be seen in the dendrogram in Fig. 6 and Table 2, three groups of response were distinguished on both slopes, as aspect seems not to affect the response of the vegetated components. In the first group (cluster A) dominated by the Stipa tenacissima, the runoff initiation and the stabilisation occurs relatively fast. The second group (cluster B), associated with plots covered by short grasses (i.e. B. retusum), is slower in response but very fast in reaching the runoff stability. Finally, the third group (cluster C) is associated with shrubs, plants with a higher morphological complexity (i.e. Rosmarinus officinalis). The same values were assigned to the area covered by trees (P. halepensis), where the rainfall simulation method used is not suitable for obtaining information. This vegetation group (cluster C) shows a higher Po and the increase in runoff is very slow (low α values, as it corresponds to plants with a high water storage capacity on the stems and leaves, with a delayed throughfall and stemflow). Table 2 summarises the Eq. (1) parameters assigned to each of these three soil surface components, obtained by averaging the equation parameter in each of the clusters in Fig. 6. In all cases, vegetated surfaces have very low values of Fc and thus a very high infiltration capacity. 4.2.2. Runoff response on non-vegetated components The range of runoff response values on these components was established according to the percentage of rock fragment cover, their

Fig. 7. Characteristic runoff hydrographs assigned to each SSC and derived from the analysis of rainfall simulation experiments.

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Table 2 Runoff response of each soil surface component distributed by hillslope aspect based on Eq. (1) parameters Criteria (b to N)

Soil surface component (SSC) description

Rock outcrop Bare soil

b 25% 25–70% N 70%

Litter Vegetation

Perenn. grass Shrubs (cluster C) Trees

On top Embedded On top Embedded On top Embedded

Crust Crust Crust Crust

South F.S.

North F.S.

D (α)

R (Po)

P (Fc)

α=

Po=

Fc=

α=

Po=

Fc=

1 7 6 5 4 2 3

1 3 2 6 4 7 5

1 3 2 6 5 7 4

0.90 0.17 0.19 0.20 0.43 0.77 0.67 0.07 1.21 4.06 0.17 0.17

1.27 1.27 1.27 3.85 1.97 5.47 2.67 0.75 3.45 9.51 13.63 13.63

10.00 30.14 30.00 35.73 33.07 35.74 30.41 10.20 54.64 53.99 53.98 53.98

0.90 0.15 0.16 0.17 0.37 0.66 0.57 0.06 1.21 4.06 0.17 0.17

1.27 1.44 1.44 4.38 2.24 6.21 3.03 0.85 3.45 9.51 13.63 13.63

10.00 37.25 37.09 44.17 40.89 44.18 37.59 12.61 54.64 53.99 53.98 53.98

Stipa tenacissima (cluster A) Brachypodium retusum (cluster B) Pinus halepensis

D = Dynamic surfaces; R = Roughness at centimetre scale; P = Soil protection against raindrop impacts (see text). Cluster groups in Fig. 6. Values in bold correspond to SSC with rainfall simulation experiments.

relative position in relation to the soil surface and the presence of a mineral crust and litter. The results in Fig. 6 show a significant variety of values and also differences between the north- and south-facing slopes, with higher infiltration values in the north as reported by Boix-Fayos (1999).

In general terms, the infiltration capacity (Fc) is higher when surface armouring is bigger with the increase in the rock fragment cover and especially when rock fragments are located on top of the soil surface related to soil protection against raindrop impacts (clusters E

Fig. 8. A) Map of the sequences of the overland flow distribution on the hillslopes after simulating a rainfall event of 55 mm for 1 h. B) Area proportion of the runoff volume intervals reached at each time span during the simulation.

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and F in Fig. 6). This is in agreement with the experimental results obtained by Poesen et al. (1990) in the laboratory and under field conditions observed by Valentin (1994). The times to runoff initiation (Po) are shorter when the rock fragments are embedded and/or the cover is low, as apparent in the correspondence with surface roughness degree at centimetre scale (cluster E in Fig. 6). In relation to the form of the hydrograph (α), the lower values (gradual curve increment) indicate dynamic changes during the process/rainfall event; dynamism which is favoured as the proportion of mineral crust increases (usually with lower rock fragments cover), at the same time that surface sealing by embedded rock fragments reduces the dynamics in the response. The extrapolation of the Eq. (1) parameters for the soil surface component classes without experimental data (i.e. b25%; 25–70% of rock fragments embedded and rock outcrops) has been done by sorting the existing values according to the aforementioned criteria (Table 2) and averaging with the neighbours in the ranking. For the bare rock surfaces a minimum Fc (10 mm h− 1) has been assigned considering that in the studied area the limestones are very fragmented allowing percolation through the cracks; here the aspect influence has not been considered. For all the other soil surface components on the north-facing slope a corrective coefficient has been applied to each parameter on the basis of the differences in the experiments from both hillslopes (Table 2). Similarly a parameter for the litter has been calculated from the experimental data obtained by Corell (1998) in a nearby location in relation to the class b25% of rock fragments on top. The results have remarkably high runoff values, but are in agreement with the results reported by Cammeraat and Imeson (1999), and are explained by the water repellence of the litter material coming from Stipa tenacissima tussocks. The resulting runoff hydrographs for each soil surface component and each hillslope (Fig. 7) have similar forms (α) and the main differences reside in the final infiltration rates (Fc).

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4.3. Modelling runoff dynamics at hillslope scale Combining the detailed soil surface component maps and the runoff hydrographs, the runoff generation and redistribution process was simulated for an event of 55 mm and 1 h duration with uniform rainfall intensity, using the procedure described in the methods. The resulting maps of infiltration excess runoff values at eleven significant time intervals (Fig. 8a) reproduce the spatial and temporal evolution of the runoff patterns and the chances of continuity of the runoff on a specific hillslope. The main changes in the sequence occur during the first 15 min and there is an important contrast related to aspect. In the beginning (i) runoff is generated only in small and disperse patches, associated with the rock outcrops and areas with litter. On the south-facing slope this situation appears only during the first minute and on the northfacing slope this situation lasts until minute 4 (t1 to t4 in Fig. 8). After this (ii) larger contributing areas with slight interconnectivity progressively appear (t6 in Fig. 8). On both hillslopes, the activity is higher in the upper and lower parts; however runoff generation in the central part is delayed until minute 10 on the north-facing slope (t10, Fig. 8). The runoff patterns become stable on the north-facing slope at minute 10 (t10, Fig. 8) and at minute 15 on the south-facing slope (t15, Fig. 8). The south-facing slope shows a higher variety of soil surface component patches that is reflected in a larger range of runoff values. (iii) After minute 10 for the north-facing slope and minute 6 for the south-facing slope the runoff patterns are stable, no new generating areas appear, but there is a progressive increase in the runoff volume of some generating bare soil patches (Fig. 8b). On the north-facing slope 62% of the surface does not produce runoff, and 45% on the south-facing slope. Also, on the latter, the runoff depth is higher (always more than 0.3 mm), the range 0.5– 1 mm of runoff depth covers the 17.3% of the hillslope surface in minute 60 of the rainfall event (t60, Fig. 8). On the north-facing slope the range 0.1–0.3 mm of runoff depth covers 33.4% of the hillslope

Fig. 9. Surface proportions for the different runoff values (mm) at the different simulated times at 5 m intervals from the divide to the bottom of the hillslopes.

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surface in the minute 60 of the rainfall event (t60, Fig. 8). What is very relevant is the role of the central part of both slopes that acts as a water accepting patch, related to the type of vegetation and the high proportion of ‘on top rock fragments’ (Fig. 9). In contrast, the upper and lower parts of both slopes (especially on the south-facing slope), the higher proportion of bare rock and embedded rock fragments produces important runoff volumes. 5. Discussion The methodological approach tested in this paper succeeded in creating a quantitative image of the runoff generation and water redistribution processes on a semi-arid hillslope. In previous work (Calvo-Cases et al., 2003) including data from plots under natural rainfall, the runoff generation process described on these hillslopes implies fundamentally a mechanism of infiltration excess, with reinfiltration along the slope in the sink areas. The data series from the plots (Calvo-Cases et al., 2005) on the south-facing hillslope show that with rainfall events with ca. 100 mm, the soil under vegetation patches becomes saturated and begins to contribute to runoff, shifting from a discontinuous infiltration excess model to a mixed model that includes areas on slope where saturation excess contributes to runoff. The hydrological modelling applied does not consider saturation excess, as a less than 100 mm rainfall is applied. A more realistic simulation, not presented here, needs to incorporate other variables such soil water storage capacity to simulate the role of runoff by saturation excess over certain thresholds. At the present stage the combination of detailed hydrological information obtained by field plots and mapping of the soil surface components can be used as a method for scaling upward results from field plots in the sense of spatial aggregation of individual responses; where spatial arrangement and hydrologic dynamics of homogeneous response units (soil surface components) are crucial in the final hillslope response. This approach is especially interesting now due to the availability of high spatial resolutions aerial photographs or satellite images, and the huge amount of runoff data obtained by field plots over recent decades (Boix-Fayos et al., 2005, 2006, 2007). The use of these very high resolution images allows an automatic or supervised classification of more individual soil surface components (i.e. individual rock fragments, bare soil and vegetation patches). Photo-interpretation has been adopted in order to discriminate between ranges of cover (easier to correlate with the hydrological response obtained in the plots) and also to be able to distinguish the position of the rock fragments (‘embedded’ or ‘on top’) and bed rock outcrops. The close and accurate description of soil surface component patterns provides valuable information for the interpretation and analysis of the geomorphological processes taking place at the slope scale. The contrast in vegetation cover between the north- and southfacing slopes follows similar trends to those reported by Kutiel et al. (1998), Kutiel and Lavee (1999), Shoshany (2002), Cantón et al. (2004) and Badano et al. (2005) in similar environments. Moreover, Katra et al. (2007) found important aspect-induced differences in soil moisture and a higher duration of the moisture content on north-facing slopes. Bellot et al. (2004), measuring the chlorophyll fluorescence, found differences in the vegetation physiology on slopes of different aspect. In our case both vegetation physiology and differences in soil moisture between slopes, controlled by the microclimatic contrast, have effects on the feedback mechanisms responsible of general soil conditions/ properties, and then this has consequences on the hydrological response of north- and south-facing slopes. The vegetation pattern on the slopes studied here differs from the one reported by other authors in similar environments. The vegetation distribution in the Benidorm hillslopes is more homogeneous and without the downslope increment found by Kutiel et al. (1998), who

applied a similar methodology. On the two slopes studied here the ratio of vegetation/no-vegetation areas shows an increase in the central part of the slope, where the infiltration capacity is also improved by the ‘on top rock fragments’ cover. This vegetation pattern shows, in part, a geomorphological control due to the historical evolution of the hillslopes. These slopes have a straight profile, with a slight increase in slope at the bottom linked to the incision of the main channel and affected by soil removal to replenish agricultural terraces at the bottom of the valley. In consequence, the lower part of the slope shows different conditions than those found commonly in other semiarid areas, where the slope toe is a place with more sediment accumulation and better hydrological conditions. The study area fits within the semi-arid situation described by Lavee et al. (1998) where the abiotic factors become important. This means that although the vegetation plays an important role in the dynamics of the degradation/recovery processes, the armour loop described in Kirkby et al. (1998), Kirkby (2002) is the dominant cycle. On both hillslopes, the upper third is characterised by a higher ratio of vegetation vs. rock fragment cover, but downslope the ratio decreases and the ‘on top rock fragments’ fraction increases, improving the soil protection and the hydrological conditions. On the north-facing slope this situation favours the progressive colonisation upslope of trees covering the agricultural terraces of the bottom of the valley. The concentration of rock fragments on the soil surface is usually explained as a result of the selective removal of fine material by runoff (Parsons et al., 1992; Cooke et al., 1993; Simanton et al., 1994). The south-facing slope, with higher erosion rates, shows a higher proportion of rock fragments. However, the north-facing slope shows also a high proportion of rock fragments within the nonvegetated patches, as found by Kutiel et al. (1998). On the south-facing slope, a redistribution of the rock fragments can be assumed because of the mobility of the fragments (see Calvo-Cases et al., 2005) by gravity, raindrop impact or trampling. This mobility explains the abundance of patches with less than 25% of rock fragments compared to the north-facing slope, where this class is scarce. The main contrast in the hydrological response occurs between the vegetated and the non-vegetated components. Within the vegetated components the stemflow and throughfall greatly affect the interception depending on the plant physiognomy (Martinez-Meza and Whitford, 1996; Wainwright et al., 2000). This factor and the role of the vegetation structure and plant growth pointed out by Casermeiro et al. (2004) appeared as important factors determining runoff rates in the rainfall simulations and were considered in the modelling exercise. In Bochet et al. (2006), studying the influence of plant morphology on soil loss and runoff within natural rainfall plots, the differences in the soil response under Stipa and Rosmarinus are also visible. The runoff patterns resulting from the modelling show a progressive increase in the source areas and thus the runoff rate during the rainfall event as in other experiments in Mediterranean conditions (Yair and Lavee, 1985; Davenport et al., 1998; Puigdefábregas et al., 1999; Yair and Kossovsky, 2002; Cammeraat, 2002, 2004). This translates into a progressive interconnection between different hillslope parts after certain rainfall thresholds. Those thresholds values can be established for the studied slopes at 9.2 mm and 13.8 mm of rainfall (Fig. 8a), for the south- and north-facing slopes, respectively, using the runoff coefficients obtained from the rainfall simulations. Under natural rainfall conditions the rainfall threshold values given in Cammeraat (2004), in a similar geo-ecosystem, on hillslopes covered mainly by Stipa, are slightly higher (19 ± 10 mm) but not too far in excess taking into consideration that the runoff coefficients applied here are derived from field experiments using a high rainfall intensity. 6. Conclusions - Mapping the soil surface components (SSC) that influence runoff generation processes along hillslopes is revealed as a feasible

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method for analysing the spatial distribution of runoff generation factors visible on the soil surface. - Combining the SSC mapping with existing runoff measurements from small size plots, is possible to illustrate how larger landscape units, such as hillslopes, behave, and to have a tool for better understanding runoff generation in this kind of environment where important spatial discontinuities in the processes exist and are characteristic of its dynamics. - The studied slopes show a central area that act as water accepting patch visible on the soil surface component map and related to the different vegetation cover with more grass and the increase of on top rock fragment cover (both accepting patches) mainly in the more dynamic south-facing slope. Both hillslopes are hydrologically connected, from the upper to the lower segment, after a rainfall threshold established as 9 and 14 mm for south- and northfacing slopes, respectively. Acknowledgements We are grateful to R. Shah for reviewing the English in the manuscript and to A. Basurto-Vidal for his help in fieldwork. The work reported here forms part of the project REN2003-04570/GLO del Plan Nacional de I+D+I and a research grant provided by the Fundación Mapfre and the Servicio de Seguridad, Salud y Calidad Ambiental of the Universitat de València. C. Boix-Fayos was financially supported by a Ramón y Cajal contract from the Spanish Science and Education Ministry. References Aguiar, M.R., Sala, O.E., 1999. Patch structure, dynamics and implications for the functioning of arid ecosystems. Trends in Ecology & Evolution 14, 273–277. Alexander, R., Calvo, A., 1990. The influence of lichens on slope processes in some Spanish badlands. In: Thornes, J.B. (Ed.), Vegetation and Erosion, Processes and Environments. John Wiley & Sons, Ltd., Chichester, pp. 385–398. Badano, E.I., Cavieres, L.A., Molina-Montenegro, M.A., Quiroz, C.L., 2005. Slope aspect influences plant association patterns in the Mediterranean matorral of central Chile. Journal of Arid Environments 62, 93–108. Bellot, J., Maestre, F.T., Hernández, N., 2004. Spatio-temporal dynamics of chlorophyll fluorescence in a semi-arid Mediterranean shrubland. Journal of Arid Environments 58, 295–308. Bergkamp, G., 1998. A hierarchical view of the interactions of runoff and infiltration with vegetation and microtopography in semiarid shrublands. Catena 33, 201–220. Beven, K., 2002. Runoff generation in semi-arid areas. In: Bull, L.J., Kirkby, M.J. (Eds.), Dryland Rivers: Hydrology and Geomorphology of Semi-arid Channels. John Wiley & Sons Ltd., Chichester, pp. 57–105. Bochet, E., Poesen, J., Rubio, J.L., 2006. Runoff and soil loss under individual plants of a semi-arid Mediterranean shrubland: influence of plant morphology and rainfall intensity. Earth Surface Processes and Landforms 31, 536–549. Boer, M., Puigdefábregas, J., 2005. Effects of spatially structured vegetation patterns on hillslope erosion in a semiarid Mediterranean environment: a simulation study. Earth Surface Processes and Landforms 30, 149–167. Boix Fayos, C., 1999. Procesos geomórficos en diferentes condiciones ambientales mediterráneas: el estudio de la agregación y la hidrología de los suelos. Col.lecció Tesis Doctorals en Microfitxa, Universitat de València. 394pp, ISBN 84-370-4321-2. Boix-Fayos, C., Calvo-Cases, A., Imeson, A.C., Soriano-Soto, M.D., Tiemessen, I.R., 1998. Spatial and short-term temporal variations in runoff, soil aggregation and other soil properties along a Mediterranean climatological gradient. Catena 33, 123–138. Boix-Fayos, C., Calvo-Cases, A., Imeson, A.C., Soriano-Soto, M.D., 2001. Influence of soil properties on the aggregation of some Mediterranean soils and the use of aggregate size and stability as land degradation indicators. Catena 44, 47–67. Boix-Fayos, C., Martínez-Mena, M., Calvo-Cases, A., Castillo, V., Albaladejo, J., 2005. Concise review of interrill erosion studies in SE Spain (Alicante and Murcia): erosion rates and progress of knowledge from the 1980s. Land Degradation & Development 16, 517–528. Boix-Fayos, C., Martínez-Mena, M., Arnau-Rosalén, E., Calvo-Cases, A., Castillo, V., Albaladejo, J., 2006. Measuring soil erosion by field plots: understanding the sources of variation. Earth-Science Reviews 78, 267–285. Boix-Fayos, C., Martínez-Mena, M., Calvo-Cases, A., Arnau-Rosalén, E., Albaladejo, J., Castillo, V., 2007. Causes and underlying processes of measurement variability in field erosion plots in Mediterranean conditions. Earth Surface Processes and Landforms 32, 85–101. Brakensiek, D.L., Rawls, W.J., 1994. Soil containing rock fragments — effects on infiltration. Catena 23, 99–110. Calvo-Cases, A., Boix-Fayos, C., Imeson, A.C., 2003. Runoff generation, sediment movement and soil water behaviour on calcareous (limestone) slopes of some Mediterranean environments in southeast Spain. Geomorphology 50, 269–291.

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