Effects of land use on annual runoff and soil loss in Europe and the Mediterranean

Abstract

The largest currently compiled database of plot runoff and soil loss data in Europe and the Mediterranean was analysed to investigate effects of land use on annual soil loss (SL), annual runoff (R) and annual runoff coefficient (RC). This database comprises 227 plot-measuring sites in Europe and the Mediterranean, with SL for 1056 plots (PL) representing 7024 plot-years (PY) and R for 804 PL representing 5327 PY. Despite large data variability, continental-wide trends are observed. Construction sites have the highest mean annual RC (57%) and SL (325 Mg.ha^-1.yr^-1). Bare soil, vineyards and tree crops have high mean annual RC (5–10%) and SL (10–20 Mg.ha^-1.yr^-1). Cropland and fallow show similar mean annual RC (8.0 and 7.3%), but lower SL (6.5 and 5.8 Mg.ha^-1.yr^-1). Plots with (semi-)natural vegetation cover show lowest mean annual RC (<5%) and SL (<1 Mg.ha^-1.yr^-1). Plot length and slope gradient correlations with R and SL depend on land-use type and are not concurrent for R and SL. Most land-use types show positive correlations between annual R and SL. Plots in cold climates have higher annual RC than plots in temperate and pan-Mediterranean climates. Annual SL in the pan-Mediterranean is less than in temperate zones, due to stony or clayey soils having a low erodibility. Annual RC in the pan-Mediterranean was higher than in temperate zones. Annual R increases strongly with increasing annual precipitation (P) above 500 mm.yr^-1, while annual SL was found to stabilize at P > 500 mm.yr^-1. For shrubland, annual SL was found to decrease for P > 250–500 mm.yr^-1, which is attributed to an accompanying increase in vegetation cover. However, no such trend was found for R. The results allow a rapid assessment of the impact of land-use changes on annual R, RC and SL, based on field-measured plot data.

Keywords

annual precipitation climatic zone interrill and rill erosion land use runoff plot runoff-soil loss relation

I Introduction

Runoff and soil loss due to interrill and rill erosion are important processes of soil degradation that cause significant on-site and off-site problems (e.g. Boardman and Poesen, 2006; Montgomery, 2007; Poesen and Hooke, 1997). An integrated approach to these problems at subcontinental scale requires runoff and soil loss to be assessed for a wide range of representative environmental conditions. An extensive assessment and mapping approach for large areas (e.g. Evans, 2002; Le Gouée et al., 2010; Oldeman et al., 1991) may provide an overview of the scale of the problem and locate erosion hotspots, but to gain insight into these processes and to develop strategies to mitigate their impacts, more detailed field-measured experimental data that accurately quantify soil loss are needed. Recently, such quantitative assessment of annual soil loss (SL, Mg.ha^-1.yr^-1) rates at a pan-continental scale for Europe has seen several applications like risk assessment mapping through modelling (Kirkby et al., 2004), exploration of spatial variability and controlling factors of annual SL rates (Cerdan et al., 2006, 2010), assessment of scale effects on sediment production (Vanmaercke et al., 2012) and the development of indicator systems to identify and monitor problem areas (e.g. Gobin et al., 2004). All these continental-wide applications either directly make use of available field-measured soil loss data or conclude they would benefit from a validation with such data.

While aforementioned studies place strong emphasis on the assessment of annual SL rates, runoff plays an important role as a causal factor of annual SL and the relations between annual runoff (R, mm.yr^-1), annual runoff coefficients (RC, %) and annual SL are not yet fully understood quantitatively. Nevertheless, several process-based erosion models use runoff in order to estimate annual SL rates (Merritt et al., 2003) and good knowledge on these relations is an important part of soil loss modelling (e.g. Jetten and Favis-Mortlock, 2006; Kinnell and Risse, 1998). Furthermore, annual R and RC also directly relate to on-site problems like agricultural productivity (Rockström et al., 2010) and off-site problems like export of nutrients and pesticides (Rossi Pisa et al., 1999), flash floods (e.g. García-Ruiz et al., 2010; Poesen and Hooke, 1997) and the potential activation of other sediment sources (such as river banks and gullies) further downstream (Vanmaercke et al., 2011a). Hence, it is important to assess both annual R and SL rates in conjunction, as well as the effect of key controlling factors on annual R and SL rates.

Over the last 60 years, numerous quantitative experimental studies on annual R and SL have been conducted throughout Europe and the Mediterranean region, using different experimental methods (e.g. runoff plots, rainfall simulations, rill volume measurements, tracer methods). From these, bounded runoff plot studies under natural rainfall conditions can be considered as the most used and standardized experimental method (e.g. Boix-Fayos et al., 2006; Cammeraat, 1993; Cerdan et al., 2006; Evans, 1995; Hudson, 1993). Studies on runoff and soil loss plots have been extensively used in large-scale coordinated research projects in the United States, leading to the development of the (R)USLE(2) equation (Renard et al., 1997; Wischmeier and Smith, 1960, 1978). However, projects of such an extent have not taken place in Europe where many individual runoff and soil loss plot studies have been reported. As a result, the findings of runoff plot studies in Europe and the Mediterranean region are dispersed over numerous scientific papers, reports and theses. They are mostly designed to analyse effects of erosion controlling factors on annual R and SL in a particular area. These individual studies have provided better insights into runoff and soil loss processes at local scales, but the diversity and natural variability of runoff and soil loss plot studies limit the potential to extrapolate these findings to other environmental conditions. Boardman (1998) showed that published soil erosion rates for large areas, based on a small number of observed data, should be interpreted with care or may not be relevant at all. Furthermore, an overall assessment of runoff and soil loss rates is also hampered by a high temporal variability (e.g. Bagarello et al., 2011; Martínez-Casasnovas et al., 2002; Ollesch and Vacca, 2002).

From this lack of an overview and difficulties in extrapolating local R and SL data to larger areas arises the need for a pan-European compilation of all available R and SL data. As a response to this need, national-scale data sets on soil erosion have recently been assembled for most countries in Europe, although the methodology used and the erosion processes considered differ (Baade and Rekolainen, 2006; Boardman and Poesen, 2006). With respect to annual R and SL, several recent studies have compiled field-measured plot runoff and/or soil loss data at the regional, national or subcontinental scale (Boardman and Poesen, 2006; Table 1).

Table 1.

Overview of studies reporting measured runoff and soil loss plot data without soil and water conservation techniques, collected at country, regional or subcontinental scale for Europe and the Mediterranean. Key: – = not reported in study, + = reported in study, NA = not available, R = annual runoff, SL = annual soil loss, #PY = number of plot-years. Ba = bare, Cr = cropland, Fa = fallow, Fo = forest, Gr = grassland, Pf = post-fire, Sh = shrubland, Tc = tree crops, Vi = vineyard.

Region/country	R	SL	Land-use types	#PY	Source
Mediterranean
MEDALUS project field sites; Spain, France, Italy, Greece	+	+	Cr, Vi, Tc, Sh, Eucalyptus	NA	Kosmas et al., 1997
Portugal, Spain, France, Italy, Greece, Israel	–	+	Cr, Vi, Tc, Sh	c. 150	Wainwright and Thornes, 2004
Spain, Portugal, Greece, Syria	+	+	olive orchards	54	Fleskens and Stroosnijder, 2007
Spain, France, Italy, Morocco	–	+	Cr, Sh	59	Gónzalez-Hidalgo et al., 2007
Italy, Spain	–	+	Sh, Pf, Fo, Cr, Ba, Fa, Gr	74	de Vente et al., 2007
Portugal, Spain, France, Italy, Greece, Israel, Croatia	–	+	Pf, Cr, Vi, Sh, Eucalyptus	NA	Shakesby, 2011
Germany	–	+	Cr, Fa, Gr, Vi, Fo	1,078	Auerswald et al., 2009
Europe	–	+	Ba, Ba, Fo, Gr, Sh, Vi, Tc	2,741	Cerdan et al., 2006, 2010
Europe	–	+	Ba, Cr, Fa, Fo, Gr, Pf, Sh, Tc, Vi	NA	Boardman and Poesen, 2006

From these compilations, a better insight into some key factors determining rates and variability of annual R and SL at (sub)continental and regional scales has been gained. The dominant control of land-use type on annual SL was illustrated by Cerdan et al. (2006, 2010), where also soil type, plot length and slope gradient were used to account for further variability. Kosmas et al. (1997) found that the relation between annual precipitation (P, mm.yr^-1) and annual R and SL at plot scale at eight different sites in the northern Mediterranean is mainly influenced by land use and hence temporal and spatial patterns of vegetation cover. For shrubland, these authors also observed a vegetation feedback mechanism whereby with increasing annual P (up to P = 200–300 mm.yr^-1) SL first increases, then decreases with increasing annual P. This effect is similar to the one described by Langbein and Schumm (1958), who demonstrated for catchments in the United States that the relation between annual P and catchment sediment yield does not only reflect the increasing erosion potential of higher annual P but also includes feedback effects from a larger vegetation biomass with increasing annual precipitation, effectively reducing sediment yield above an annual P threshold of about 254 to 381 mm.yr^-1 (10–15 inch.yr^-1). For the other land uses studied by Kosmas et al. (1997), annual R and SL were all positively related to annual P.

However, several key elements to obtain a comprehensive understanding of annual R, RC and SL rates and controls in Europe and the Mediterranean region are not fully considered in these studies. First and foremost, the existing overviews mainly consider annual SL, while annual R and RC are studied to a lesser extent (Table 1). While Europe-wide assessments of plot-scale annual SL exist (Cerdan et al., 2010; Vanmaercke et al., 2012), this is not the case for annual R. In addition, most of these studies assess the effects of one or more controlling factors on annual R and SL, but recognize that they lack information on other important controlling factors. As such, Cerdan et al. (2006, 2010) acknowledge the importance of annual precipitation but did not include this in their analysis. Similarly, Kosmas et al. (1997) do not assess the effect of plot length or slope gradient but nevertheless cite its importance. Which controlling factors are included in the analysis, and how they are assessed, may have a significant impact on the discussion of annual R and SL rates. For instance, Fleskens and Stroosnijder (2007) argued that average annual SL rates in olive groves are unlikely to exceed 10 Mg.ha^-1.yr^-1, which was contested by Gómez et al. (2008) on the basis that several scale and environmental factors like plot length were not sufficiently taken into account.

Hence, there are still unresolved questions with respect to the relationships between precipitation, runoff (coefficients) and soil loss, and the effect of different land uses on these relations. While several local-scale studies address part of these questions, it is not known whether the findings of these studies also apply to other regions. At a continental-wide scale, there are no studies that comprehensively and quantitatively explore all of these relations. Nevertheless, such analysis is of great use to support model assumptions and contribute to an integrated approach towards soil degradation. Therefore, this study aims (1) to provide an overview of both R and SL rates by interrill and rill erosion, measured at the plot scale for Europe and the Mediterranean region; (2) to assess the variability in both R and SL rates for different land uses and different climatic regions in the study area; and (3) to analyse the relationship between observed R and SL rates, and their relationship to annual precipitation (P, mm.yr^-1).

For a list of abbrevations and symbols used in this paper, see the Appendix.

II Materials and methods

1 Runoff plot selection criteria and database compilation

A database was constructed with annual R and SL data, measured on bounded runoff plots under natural rainfall conditions in Europe and the Mediterranean region (Figure 1). Data were collected from scientific papers, books (Boardman and Poesen, 2006), project reports and PhD theses, and through personal communication with various researchers. Only runoff and/or soil loss measurements conducted on bounded runoff plots under natural rainfall conditions with a known land use, a minimum plot length of 5 m, and for a measuring period (MP) that is representative (see section II(2) below for more details) for at least one year were considered. Results from runoff plots that were treated with soil and water conservation techniques were not included in this analysis since they do not represent prevailing field conditions. A list of the excluded soil and water conservation techniques is given in Table 2a. While plots without any soil cover throughout the year, i.e. bare plots (Table 2b), are not a common land use practice, they are often used in soil erosion studies as reference plots, representing maximum potential SL for the study conditions. However, traditional agricultural practices on cropland often leave the soil bare after tillage during part of the year. Hence, plots with bare soil were included in the database for reference purposes.

Figure 1.

Geographical distribution of plot runoff and soil loss measuring sites over Europe and the Mediterranean with indication of the climatic zones derived from the LANMAP2 classification (Metzger et al., 2005; Mücher et al., 2010). Inset (a): Canary Islands. #PL = number of plots, n = number of plot-measuring sites.

Table 2a.

List of soil and water conservation techniques (SWCT) tested on runoff plots and thus excluded from the plot database used for the analysis of the effects of land use on annual runoff and annual soil loss in Europe and the Mediterranean. Ba = bare, Cr = cropland, Fa = fallow, Fo = forest, Sh = shrubland, Ra = rangeland, Pf = post-fire, Gr = grassland, Vi = vineyards, Tc = tree crops, Cs = construction sites.

SWCT	Land-use types	Description of SWCT
Tillage techniques:
no-tillage	Ba, Cr, Fa, Tc, Vi	no tillage operations when the local practice is conventional tillage (e.g. Turtola et al., 2007)
conservation tillage	Ba, Cr, Fa, Tc, Vi	different forms of reduced tillage resulting in a smaller disturbance of the plough layer than conventional tillage (e.g. Kwaad et al., 1998)
contour tillage	Ba, Cr, Fa, Tc, Vi	tillage operations parallel the contour (e.g. Quinton and Catt, 2004)
deep tillage	Cr	deep non-inversion tillage to improve percolation (e.g. Chomaničová, 1988; Suchanic, 1987)
Soil cover:
cover crops	Ba, Cr, Tc, Vi	cover crop grown during the intercropping season, drilled after harvest (e.g. Laloy and Bielders, 2010)
mulching	Cr, Gr, Pf, Ra, Sh, Vi	application of organic mulch (crop residue or straw)
geotextile	Ba, Cs, Tc, Vi	application of geotextile mats (Bhattacharyya et al., 2008, 2009; Jankauskas et al., 2008; Mitchell et al., 2003)
Sediment traps:
buffer strips	Ba, Cr, Fa, Tc, Vi	Strips of perennial vegetation (usually grasses) used to increase infiltration, slow down runoff and increase sediment deposition (e.g. Uusi-Kämppä, 2005)
contour bunds	Vi	stone or earthen bunds constructed parallel to the contour (e.g. Pinczés, 1982)
strip cropping	Cr	drilling or planting in strips of alternating crop types (e.g. Köse and Taysun, 2002; Köse et al., 1996)
contour cropping	Cr	crop planting or drilling parallel to the contour (e.g. Jung and Brechtel, 1980)
terraces	Ba, Cr, Fo, Gr, Pf, Sh, Tc, Vi	construction of earthen or stone terraces parallel the contour (e.g. Koulouri and Giourga, 2007)
Other:
drainage	Cr, Gr	application of subsurface drainage pipes (e.g. Øygarden, 1996; Øygarden et al., 1997)
soil amendment	Ba, Cr, Fa, Gr, Ra, Sh, Cs	application of soil conditioners to improve soil soil structural stability – e.g. phosphogypsum (Agassi and Benhur, 1991; Agassi et al., 1990) or polyacrylamide (Lopez-Bermudez et al., 1991; Romero-Díaz et al., 1999)

Table 2b.

Land-use types considered in the plot database for Europe and the Mediterranean

Land-use type	Abbreviation	Crop	Description
bare	Ba		continuously bare soil without crops or natural vegetation, sometimes tilled annually
fallow	Fa		plot with natural regrowth of grass and herbaceous species, or sowing of those species in a rotation scheme
cropland	Cr	cereals	cereal (wheat, barley, oats, rye) cultivation
		maize	silage or grain maize cultivation
		sunflower	sunflower cultivation
		sugar beet	sugar beet cultivation
		potato	potato cultivation
		leguminous	leguminous (beans, peas, vetch, lentil, alfalfa, clover, yellow lupine) cultivation
		other	cultivation of other annual crops
tree crops	Tc		olive, almond or fruit (apple, citrus) cultivation
vineyards	Vi		vineyards, rows may have different orientation with respect to the contour
grassland	Gr		permanent grassland
rangeland	Ra		grass- or shrubland browsed by cattle
forest	Fo		natural vegetation or plantation with predominance of tree species
shrubland/matorral	Sh		natural vegetation or plantation with predominance of shrub species
post-fire	Pf		forested land or shrubland, burnt in the recent past (0–30 years)
construction sites	Cs		areas where urban-industrial activity (roadcut sites, mine areas) is the primary source of disturbance

While most plots use collection tanks or flow samplers to determine the total runoff and soil loss by interrill and rill erosion, in a small number of studies, soil loss is determined by measuring the rill volume (Govers and Poesen, 1988; Jankauskas and Fullen, 2002; Jankauskas and Jankauskiene, 2003a; Jankauskas et al., 2004). Based on a literature survey by Govers and Poesen (1988), total soil loss for these studies was calculated by adding 25% to the measured rill soil loss to account for interrill soil loss.

Each runoff and soil loss plot (PL) in the database represents measurements of annual runoff and/or soil loss at a particular measuring site for a specific combination of land use, soil type, plot length and slope gradient. For each of these PL, the corresponding number of plot-years (PY) was also recorded, which indicates the number of years represented by the data for that PL. PY = 1 corresponds to a measuring period of one year on a single runoff plot. When measurements were conducted on several replicate plots with identical experimental setup and results were reported individually for the different replicates, they were included as different PL in the database. If the average annual R and SL value for the replicate plots was reported (e.g. Bagarello and Ferro, 2010; Bagarello et al., 2010a, 2010b; Lopes et al., 2002; Mohammad and Adam, 2010) the average values for all replicates were counted as one PL in the database, while the number of PY was considered to be the sum of all PY of the replicates.

Based on the description given by the authors, all PL were assigned to a land-use type (Table 2b). When different land-use types were present on a single runoff plot (e.g. cropland-fallow rotation or cropland-grassland rotation), the years having the same land use were grouped together as one PL. Hence, data from a runoff plot with a rotation of cropland and fallow is entered in the database as 2 PL, one for cropland and one for fallow. This approach does not take into account possible effects of crop cultivation and soil treatment prior to the measuring period, which may persist during the two following years (Wischmeier and Smith, 1978) and hence may explain part of the observed variability in R and SL rates. Furthermore, the location of each of the plot-measuring sites was determined, either from coordinates given by the authors or from maps and descriptions in the publications. Some studies report data for plots that were installed at different sites close to each other (e.g. different slope aspects or gradients in the same valley). Whenever it was possible to accurately distinguish between these different sites, they were incorporated as separate plot-measuring sites in the database but if this was impossible, the location of the study area where plots were located was included as one plot-measuring site. Subsequently, the climatic zone (CZ) of each of the plot-measuring sites was determined according to the LANMAP2 classification (Metzger et al., 2005; Mücher et al., 2010). Plot-measuring sites in the Near East and northern Africa that fall outside the LANMAP2 cover area were classified as Mediterranean (Figure 1). While soil properties like texture, rock fragment cover, soil organic matter content and soil erodibility are recognized as important determinants of runoff and soil loss (e.g. Cerdan, 2006, 2010; Poesen and Lavee, 1994; Poesen et al., 1994; Sanchis et al., 2008; Torri et al., 1997), quantitative data on these properties were not systematically reported in the literature from which plot data were extracted for the database. Hence, a quantitative analysis of the effect of these soil properties on annual R and SL could not be made.

2 Annual data and data extrapolation procedures

All data used in this analysis are annual data. More than 84% of #PL (corresponding to >90% of #PY) reported annual R and SL that were obtained during a measuring period of one or more years and are reported as annual values by the author. In some studies, however, measurements were not carried out for full years, but the authors indicated that the data were representative for full years because no or negligible runoff and soil loss occurred during the period that the runoff plots were not in operation. This was the case for some studies during the dry season in the Mediterranean region (e.g. Mohammad and Adam, 2010; Roxo et al., 1996) or during permanent snow cover and frozen soil in colder climates (e.g. Fulajtár and Janský, 2001). In these cases, the measuring period was considered to be full years when calculating the corresponding PY for that PL. Other studies where the MP is shorter than 1 year were only included in the plot database when the authors explicitly report data as annual (extrapolation by the authors), or a reasonable extrapolation could be made. This was only done if measurements were conducted for a period during which at least two-thirds of the annual rainfall depth was recorded and rainfall is distributed uniformly throughout the year. In these cases annual R and SL were estimated by linear extrapolation according to the corresponding annual P. If no annual P data were available, data were extrapolated linearly to annual values according to the corresponding number of days if measurements continued for a period of at least 80% of the year and rainfall is distributed uniformly throughout the year. Uniformity of rainfall was checked visually using the long-term average rainfall distribution for the plot-measuring site, as given by the New_LocClim program (FAO, 2006).

3 Database analyses

Plot length, slope gradient and soil characteristics need to be taken into account to explain variability in annual R, RC and SL. Previous studies indicated that the relationship between plot length or slope gradient and annual SL or R is non-linear (Cerdan et al., 2010; Nearing, 1997; Poesen and Bryan, 1989; Wischmeier, 1966; Wischmeier and Smith, 1978).

The effect of plot length and slope gradient on annual R and SL was assessed by calculating the non-parametric Spearman’s rank correlation coefficients (r_s). For annual SL, also the correlations with the RUSLE length factor (L_PL, equation 1; Renard et al., 1997), a slope factor (S_PL, equation 2; Nearing, 1997) and the product of the L_PL and S_PL (LS-factor, equation 3) were calculated. For all PL with a land-use type for which annual SL was significantly correlated to the LS-factor, the annual unit plot soil loss (SL_u) was calculated using equation 4 (Bagarello et al., 2010b).

L_{P L} = {(\frac{λ}{22.13})}^{0.5}

(1;Renard et al., 1997)

S_{P L} = - 1.5 + \frac{17}{1 + e x p (2 .3 - 6.1 \times s i n θ)}

(2;Nearing, 1997)

L S_{P L} = L_{P L} \times S_{P L}

S L_{u} = \frac{m e a s u r e d p l o t + S L}{L S}

(4; Bagarello et al., 2010b)

where L_PL= plot length factor, λ = plot length (m), S_PL = plot slope gradient factor, Ө = plot slope angle (°), LS_PL= plot LS-factor, SL_u = annual unit plot soil loss (Mg.ha^-1.yr^-1).

As no standard procedure for the correction of annual R and RC values to a unit plot exists, no correction factor could be calculated for annual R and RC. Regardless of other factors, it can be expected that the reliability of average annual R and SL measurements increases with increasing PY, as they capture more of the occurring natural variability. According to the central limit theorem, the standard error of a sample is inversely related to the square root of the number of observations (Tijms, 2004). Therefore, average annual R, RC and SL values were calculated by weighting the reported mean value of each PL with the square root of the number of plot-years. While this is a very basic approach and does not take into account the complex temporal variation in annual SL and often non-normal distributions of annual SL time series (Maetens et al., 2011), it can be expected that this weighting results in more reliable estimates of average annual R, RC and SL rates (Cerdan et al., 2010; Vanmaercke et al., 2011b). A k-sample Kolmogorov-Smirnov test (KS-test) was used to test for significant differences in the distribution of annual R, RC, SL and SL_u data between each combination of two land-use types, whereby the significance level of the test was adapted using Bonferroni’s Inequality to account for familywise error in multiple corrections (Brittain, 1987). The same procedure was applied to test for significant differences between CZ for each land-use type. To further explore the runoff-soil loss relationship, regression equations of the form:

Y = a X^{b}

were calculated, where the dependent variable Y was either annual SL or SL_u, the independent variable X was either annual R or RC and a and b are empirical constants. Both unweighted and regressions weighted according to the square root of the number of plot-years of each plot were calculated.

Precipitation has been studied intensively as the causal factor of runoff and soil loss. The rainfall erosivity index (EI30) has been proposed as a good measure for relating precipitation to (potential) annual SL (Wischmeier and Smith, 1958). While annual P was reported in most of the studies and is generally widely available with detailed spatial and temporal coverage, EI30 values were not consistently reported for the PL included in the database and are not available from other data sources (Gabriëls, 2006). As an alternative, the Modified Fournier Index (Arnoldus, 1980; equation 6) has been used as a measure of climatic erosivity (Gabriëls, 2006):

M F I = \sum_{1}^{12} \frac{p^{2}}{P}

where MFI = Modified Fournier Index (mm².mm^-1), p = average monthly precipitation (mm.month^-1), P = average annual precipitation (mm.yr^-1). MFI was calculated for each of the plot measurement sites, using monthly precipitation data obtained from the CRU CL 2.0 data set (New et al., 2002).

III Results

1 Description of the plot database

The plot database contains data from 227 plot-measuring sites throughout Europe and the Mediterranean region (Figure 1), compiled from 213 individual publications. Annual SL data are available for a total of 1056 PL, corresponding to a total of 7204 PY. Annual R data were available for 804 PL (5327 PY). For 766 of these PL, representing 5013 PY, both annual R and SL data are available. For 673 PL (corresponding to 4583 PY), both R and P are reported, allowing the calculation of annual RC. The distribution of PL and PY over the different countries in the study area and the references to the data sources are given in Table 3.

Table 3.

Overview by country in Europe and the Mediterranean of the number of plots (#PL), number of plot-years (#PY) and sources included in the plot database

Country	#PL	#PY	Source
Albania	14	66	Grazhdani, 2006, personal communication 2010; Grazhdani et al., 1996, 1999
Algeria	60	233	Arabi and Roose, 1993; Mazour, 1992; Mazour et al., 2008; Morsli et al., 2004
Austria	3	33	Klik, 2003, 2010, personal communication 2010; Strauss and Klagerhofer, 2006
Belgium	2	17	Bollinne, 1982; Govers and Poesen, 1988; Verstraeten et al., 2006
Bulgaria	43	377	Kroumov and Malinov, 1989; Rousseva et al., 2006
Croatia	2	10	Basic et al., 2001, 2004
Cyprus	7	14	Lenthe et al., 1986; Lüken, personal communication 1986
Denmark	10	41	Schjønning et al., 1995; Veihe and Hasholt, 2006
Finland	20	102	Puustinen et al., 2005, 2007; Tattari and Rekolainen, 2006; Turtola and Paajanen, 1995; Turtola et al., 2007; Uusi-Kämppä, 2005
France	37	277	AREDVI, 2003; Auzet et al., 2006; Ballif, 1989; Brenot et al., 2006, 2008; Clauzon and Vaudour, 1969, 1971; Le Bissonnais et al., 2004; Martin, 1990; Martin et al., 1997; Messer, 1980; Viguier, 1993; Wicherek, 1986, 1988, 1991
Germany	102	330	Ammer et al., 1995; Auerswald, 2006; Auerswald et al., 2009; Barkusky, 1990; Biemelt et al., 2005; Botschek, 1991; Deumlich and Frielinghaus, 1994; Deumlich and Gödicke, 1989; Dikau, 1983, 1986; Dubber, 1968; Emde, 1992; Emde et al., 2005; Engels, 2009; Felix and Johannes, 1993; Fleige and Horn, 2000; Frielinghaus, 1998; Jung and Brechtel, 1980; Kleeberg et al., 2008; Richter, 1985, 1991; Richter and Kertesz, 1987; Saupe, 1990, 1992; Voss, 1978
Greece	36	84	Arhonditsis et al., 2000; Diamantopoulos et al., 1996; Dimitrakopoulos and Seilopoulos, 2002; Kosmas et al., 1996, 2006
Hungary	14	56	Hudek and Rey, 2009; Kertész, personal communications 2009, 2010; Kertész and Centeri, 2006; Kertész and Huszár-Gergely, 2004; Kertész et al., 2007; Pinczés, 1982; Richter, 1987; Richter and Kertesz, 1987
Israel	29	140	Agassi and Benhur, 1991; Inbar et al., 1997, 1998; Kutiel and Inbar, 1993; Lavee, personal communication 2010; Lavee et al., 1998
Italy	80	609	Bagarello and Ferro, 2010; Bagarello et al., 2010a, 2010b; Basso et al., 1983a, 1983b, 2002; Bini et al., 2006; Caredda et al., 1997; Caroni and Tropeano, 1981; Chisci, 1989; Chisci and Zanchi, 1981; De Franchi and Linsalata, 1983; de Vente et al., 2007; Ollesch and Vacca, 2002; Porqueddu and Rogerro, 1994; Postiglione et al., 1990; Rivoira et al., 1989; Torri et al., 2006; Tropeano, 1984; Vacca, personal communication 2010; Vacca et al., 2000; Zanchi, 1983, 1988a, 1988b
Jordan	2	4	Abu-Zreig, 2006; Abu-Zreig et al., 2011
Lithuania	103	792	Feiza et al., 2007; Jankauskas, personal communication 2009; Jankauskas and Fullen, 2002, 2006; Jankauskas and Jankauskiene, 2003a, 2003b; Jankauskas et al., 2004, 2007, 2008
Macedonia	8	36	Blinkov and Trendafilov, 2006; Jovanovski et al., 1999
Morocco	29	164	Chaker et al., 2001; Heusch, 1970; Laouina et al., 2003; Moufaddal, 2002; Yassin et al., 2009; Yassin, personal communication 2009
Norway	10	82	Børresen, personal communication; Grønsten and Lundekvam, 2006; Lundekvam, 2007; Øygarden, 1996; Øygarden et al., 2006
Palestinian territories	9	42	Abu Hammad et al., 2004, 2006; Al-Seekh and Mohammad, 2009; Mohammad and Adam, 2010
Poland	10	79	Gil, 1986, 1999; Rejman and Rodzik, 2006; Rejman et al., 1998; Skrodzki, 1972; Stasik and Szafranski, 2001; Szpikowski, 1998
Portugal	52	406	Coelho, 2006; de Figueiredo, personal communication 2010; de Figueiredo and Gonçalves Ferreira, 1993; de Figueiredo and Poesen, 1998; de Figueiredo et al., 2004; Lopes et al., 2002; Nunes and Coelho, 2007; Roxo et al., 1996; Shakesby et al., 1994
Romania	22	568	Bucur et al., 2007; Ene, 1987; Ionita, 2000; Ionita et al., 2006; Motoc et al., 1998; Nistor and Ionita, 2002; Teodorescu and Badescu, 1988
Serbia	6	74	Djorovic, 1990; Kostadinov et al., 2006; Sekularac and Stojiljkovic, 2007
Slovakia	62	104	Chomanicová, 1988; Fulajtár and Janský, 2001; Gajdová et al., 1999; Stankoviansky et al., 2006; Suchanic, 1987
Slovenia	4	19	Horvat and Zemljic, 1998; Hrvatin et al., 2006
Spain	156	876	Albaladejo and Stocking, 1989; Albaladejo et al., 2000; Andreu et al. 1998a, 1998b, 2001; Aspizua, 2003; Bautista et al., 1996, 2007; Bienes et al., 2006; Campo et al., 2006; Castillo et al., 1997, 2000; Cerdà and Lasanta, 2005; Chirino et al., 2006; de Vente and Poesen, 2005; Durán Zuazo et al., 2004, 2008; Francia Martínez, 2006; García-Ruiz et al., 1995; Gimeno-Garcia et al., 2007; Gómez et al., 2004, 2009; Gómez Plaza, 2000; González-Pelayo et al., 2010; Guerra et al., 2004; Ingelmo et al., 1998; Lasanta et al., 2006; Lopez-Bermudez et al., 1991; Martinez-Mena et al., 1999, 2001; Martinez-Murillo and Ruiz-Sinoga, 2007; Martínez Raya et al., 2006; Nadal Romero, personal communication 2010; Puigdefábregas et al., 1996; Rodríguez Rodríguez et al., 2002, 2006; Romero-Díaz and Belmonte Serrato, 2008; Romero-Díaz et al., 1999; Rubio et al., 1997; Sanchez et al., 1994; Schnabel et al., 2001; Solé Benet, 2006, personal communication 2010; Soler et al., 1994; Soto and Díaz-Fierros, 1998; Williams et al., 1995
Sweden	6	52	Ulén, 1997, 2006; Ulén and Kalisky, 2005
Switzerland	12	218	Marxer, 2003; Schaub, 1998; Weisshaidinger and Leser, 2006
Syrian Arab Republic	7	20	Bruggeman et al., 2005; Masri et al., 2005; Shinjo et al., 2000
The Netherlands	3	19	Kwaad, 1991, 1994, personal communication 2009; Kwaad et al., 1998, 2006
Tunisia	9	76	Ben Chaabane and Hamrouni, 2008; Bourges et al., 1973, 1975; Kaabia, 1995
Turkey	84	1233	Erpul, personal communication 2010; Kara et al., 2010; Köse and Taysun, 2002; Köse et al., 1996; Oguz, personal communication 2010; Oguz et al., 2006; Özhan et al., 2005
United Kingdom	46	293	Bhattacharyya et al., 2008, 2009; Boardman and Evans, 2006; Brown, 1996; Fullen, 1992, 1998; Fullen and Booth, 2006; Fullen and Brandsma, 1995; Fullen and Reed, 1986; Fullen et al., 2006; Mitchell et al., 2003; Morgan and Duzant, 2008; Quinton and Catt, 2004

The first recorded soil loss measurements in the database started in 1950 at Cean-Turda, Romania (Motoc et al., 1998) and later on the number of plots increased until 1994, after which the number of plots started to decline. The earliest publication discussing plot measurements that could be found dated from 1968 (Dubber, 1968), although most of the publications date from 1986 onwards (Figure 2). The average MP of all runoff and soil loss plots is 6.0 yrs (median: 4 yrs, mode: 1 yr) with a minimum of 1 and a maximum of 42 yrs at Podu-Iloaiei , Romania (Bucur et al., 2007) (Figure 3). For most PL (>84% of #PL and >90% of #PY), measurements continued throughout the year for at least one full year. Annual R and SL data calculated for a MP less than 1 yr which were extrapolated to a full year account for less than 3% of all PL and les than 1% of PY (Table 4). The distribution of the number of plots and plot-years over the different land-use types and CZ is given in Table 5, while the distributions of the number of plots and plot-years according to annual P, plot length and plot slope gradients are given in Figure 4. The different land-use types in the database also show different frequency distributions (Figure 5), with cropland and fallow mainly occurring on gentler slopes (<20%), while forest, vineyards, construction sites and tree crop plots are generally situated on steeper slopes (>20%).

Figure 2.

Evolution of the total number of plots (# plots) in operation per year for which annual soil loss and/or runoff were recorded in Europe and the Mediterranean as well as the total number of publications from which plot data were extracted in this study (# publications) per publication year

Figure 3.

Frequency distribution of the number of plots (# plots) as a function of the measuring period (MP) for which annual runoff or annual soil loss were measured continuously in Europe and the Mediterranean

Figure 4.

Frequency distribution of the number of plots (# PL) and the number of plot-years (# PY) in Europe and the Mediterranean for which annual runoff and/or annual runoff coefficient, and/or annual soil loss data are available with respect to: (a) plot length; (b) plot slope gradient; and (c) annual precipitation (P). Total #PL = 1 096, total #PY = 7 533. NA = not available (i.e. plot length, slope gradient or P not reported).

Figure 5.

Frequency distribution of the % of plots for the different land-use types in Europe and the Mediterranean according to plot slope gradient class. n = total number of plots for a given land-use type.

Table 4.

Data collection period of plot data in the plot database. R = annual runoff, RC = annual runoff coefficient, SL = annual soil loss. Number of plots (#PL) and number of plot-years (#PY) for which plot data were collected (1) during full years (Full Year), (2) during a representative part of the year during which almost all of the annual rain was recorded and the authors considered the data to be representative for a full year (Repr. for Full Year), (3) during a measuring period less than one year during which at least 67% of the annual rain was recorded and for which the data were linearly extrapolated to 100% of the annual rainfall (Extrapol. to Full Year).

Data collection period	#PL (% of total)						#PY (% of total)
Data collection period	R		RC		SL		R		RC		SL
Full Year	683	(84.9%)	567	(84.2%)	908	(86.0%)	5016	(94.2%)	4298	(93.8%)	6853	(95.1%)
Repr. for Full Year	110	(13.7%)	95	(14.1%)	122	(11.6%)	281	(5.3%)	255	(5.6%)	306	(4.2%)
Extrapol. to Full Year	11	(1.3%)	11	(1.6%)	26	(2.4%)	30	(0.5%)	30	(0.6%)	45	(0.6%)
Total	804	(100%)	673	(100%)	1056	(100%)	5327	(100%)	4583	(100%)	7204	(100%)

Table 5.

Overview of the number of plots (#PL) and the number of plot-years (#PY) for which annual runoff (R), annual runoff coefficient (RC) and/or annual soil loss (SL) data for Europe and the Mediterranean are available. NA = not available.

Land-use type	Climatic zone	R	RC	SL
Land-use type	Climatic zone	#PL (#PY)	#PL (#PY)	#PL (#PY)
bare	all data	133 (1,362)	95 (1,058)	182 (1,740)
	pan-Mediterranean	72 (857)	58 (656)	100 (1,129)
	temperate	59 (490)	35 (387)	80 (596)
	cold	2 (15)	2 (15)	2 (15)
construction sites	all data	3 (11)	3 (11)	3 (11)
	pan-Mediterranean	2 (10)	2 (10)	2 (10)
	temperate	1 (1)	1 (1)	1 (1)
cropland	all data	302 (2,018)	244 (1,737)	397 (2,749)
	pan-Mediterranean	161 (1,136)	144 (1,035)	174 (1,232)
	temperate	114 (683)	79 (563)	147 (874)
	cold	27 (199)	21 (139)	76 (644)
fallow	all data	47 (221)	46 (216)	60 (281)
	pan-Mediterranean	23 (165)	23 (165)	25 (173)
	temperate	21 (46)	21 (46)	26 (86)
	cold	3 (10)	2 (5)	9 (22)
forest	all data	59 (301)	55 (277)	59 (334)
	pan-Mediterranean	41 (238)	41 (238)	40 (217)
	temperate	17 (58)	14 (39)	18 (113)
	cold	1 (5)	NA	1 (5)
grassland	all data	69 (506)	52 (431)	109 (779)
	pan-Mediterranean	30 (196)	17 (145)	29 (192)
	temperate	34 (296)	31 (277)	24 (233)
	cold	5 (14)	4 (9)	56 (355)
post-fire	all data	54 (223)	46 (188)	56 (224)
	pan-Mediterranean	49 (202)	43 (179)	51 (203)
	temperate	3 (9)	3 (9)	3 (9)
	cold	2 (12)	NA	2 (12)
rangeland	all data	14 (59)	14 (59)	17 (69)
	pan-Mediterranean	13 (56)	13 (56)	15 (64)
	temperate	1 (2)	1 (2)	2 (6)
shrubland	all data	84 (372)	79 (351)	111 (589)
	pan-Mediterranean	77 (357)	72 (336)	101 (559)
	temperate	7 (15)	7 (15)	10 (30)
tree crops	all data	13 (133)	13 (133)	23 (154)
	pan-Mediterranean	10 (59)	10 (59)	20 (80)
	temperate	3 (74)	3 (74)	3 (74)
vineyard	all data	26 (123)	26 (123)	39 (272)
	pan-Mediterranean	12 (90)	12 (90)	18 (107)
	temperate	14 (33)	14 (33)	21 (165)
Database total		804 (5,327)	673 (4,583)	1,056 (7,204)

2 Effects of plot length and slope gradient on annual runoff, runoff coefficient and soil loss

The range of annual R and SL values recorded in the plot database varies over almost four orders of magnitude (Figure 6). To allow a comparison of the results obtained on plots with different plot lengths and slope gradients, the importance of these topographic variables was examined using the correlation coefficient between plot length and slope gradient and R and RC (Table 6). Annual R was found to be positively correlated with plot length for plots having bare soil, cropland, grassland and tree crops. A significant negative relationship between annual R and plot length was found for plots under forest and plots recently affected by fire. With respect to the relation between slope gradient and annual R only a significant positive correlation was found for post-fire conditions. For grassland and shrubland the relation between R and plot slope gradient was found to be significantly negative. With the exception of vineyards, where a significant negative correlation between slope gradient and annual RC was observed, the same trends, albeit with slightly different r_s values, were found for annual RC.

Figure 6.

Frequency distribution of annual runoff (R), annual runoff coefficients (RC), annual soil loss (SL) and annual unit plot soil loss (SL_u, equation 4) rates in the plot database for Europe and the Mediterranean. #PL = total number of plots.

Table 6.

Spearman’s rank correlation coefficient (r_s) and p-values for the correlation between annual runoff (R), annual runoff coefficients (RC) and plot length and slope gradient on the one hand and annual soil loss (SL) and USLE plot length-factor (L_pl), slope gradient-factor (S_pl) and LS-factor (LS_pl) on the other hand for different land-use types in Europe and the Mediterranean. Values in bold indicate significance at α=0.05. NA = not available.

Land-use type	R				RC				SL
	Plot length		Slope gradient		Plot length		Slope gradient		L_pl		S_pl		LS_pl
	r_s	p	r_s	p	r_s	p	r_s	p	r_s	p	r_s	p	r_s	p
bare	0.21	0.02	0.07	0.45	0.23	0.03	0.09	0.41	0.16	0.04	0.15	0.06	0.22	<0.01
cropland	0.56	<0.01	–0.03	0.65	0.56	<0.01	–0.07	0.30	0.31	<0.01	0.14	<0.01	0.28	<0.01
fallow	0.16	0.29	–0.13	0.40	0.21	0.16	–0.21	0.17	0.21	0.11	0.25	0.06	0.39	<0.01
forest	–0.55	<0.01	–0.02	0.90	–0.33	0.03	0.08	0.62	–0.13	0.39	–0.08	0.58	–0.04	0.79
grassland	0.30	0.02	–0.56	<0.01	0.32	0.03	–0.59	<0.01	0.05	0.61	–0.04	0.66	0.08	0.44
post-fire	–0.58	<0.01	0.47	0.001	–0.71	<0.01	0.38	0.01	–0.06	0.69	0.11	0.44	0.09	0.52
rangeland	–0.35	0.24	0.01	0.98	–0.43	0.14	–0.22	0.47	–0.31	0.24	0.10	0.71	0.07	0.79
shrubland	–0.03	0.79	–0.26	0.03	0.07	0.57	–0.26	0.04	0.13	0.20	0.30	<0.01	0.32	<0.01
tree crops	0.82	<0.01	0.15	0.63	0.80	<0.01	0.25	0.41	0.71	<0.01	0.24	0.29	0.55	0.01
construction sites	NA	NA	0.87	0.67	NA	NA	0.87	0.67	NA	NA	0.87	0.67	0.87	0.67
vineyard	0.20	0.34	–0.23	0.26	–0.16	0.44	–0.60	<0.01	0.61	<0.01	–0.24	0.15	0.04	0.82

For annual SL, a significant positive correlation with the LS-factor (equation 3) was found for bare plots, cropland, fallow, shrubland and tree crops (Table 6). For cropland, the correlation was significant with both the L_PL and S_PL, while for bare and tree crops only a significant correlation with L_PL was found. Nevertheless, the correlation between annual SL and S_PL is also relatively strong. For shrubland, only S_PL was significantly correlated with annual SL, while for vineyards there was only a significant correlation with L_PL. Therefore, unit plot SL (SL_u, equation 4) was calculated for plots where the land use was bare, cropland, fallow, shrubland or tree crops. Although the correlation between annual SL and LS_PL was not significant for construction sites, this is likely due to the limited number of plots for this land-use type. Nevertheless, annual SL_u values were also calculated for PL on construction sites since these PL all have a bare soil surface.

3 Characteristics of the frequency distributions of annual runoff and soil loss for various land uses

Weighted mean values and box-plots indicating the range of annual R, RC, SL and SL_u by land-use type are shown in Figure 7. Weighted mean values are always higher than the median value for annual R, RC and SL, which indicates that annual R, RC and SL have a positively skewed distribution, such as the log-normal distribution (e.g. Bagarello et al., 2010a). Construction sites have consistently the highest annual R, RC and SL. After correction for the plot length and slope gradient, annual SL_u values for construction sites are smaller, which is attributed to the steep slopes associated with the construction site plots (Figure 5). Nevertheless, annual SL_u for construction sites remains considerably higher than for other land-use types. However, the number of plots on construction sites is low, so the corresponding mean values for annual R, RC and SL rates should be interpreted with caution, although they do indicate a high vulnerability to erosion of this land-use type. This is attributed to a presence of bare, disturbed soil with a low structural stability on relatively steep slopes causing very high soil loss rates (Borselli et al., 2006). The remainder of the land-use types can be divided into two groups. A first group consisting of bare plots or plots with some type of crop cultivation (i.e. cropland, fallow, tree crops and vineyards) shows mean annual R rates between 30 and 60 mm.yr^-1, annual RC rates between 5 and 15% and annual SL rates between 1 and 20 Mg.ha^-1.yr^-1. The second group of land-use types consists of PL with a (semi-)natural vegetation cover (i.e. forest, post-fire, shrubland, rangeland and grassland), with annual R, RC and SL rates less than 30 mm.yr^-1, 5% and 1 Mg.ha^-1.yr^-1, respectively (Table 7). While bare plots and plots with crop cultivation have consistently higher mean annual R, RC and SL rates than plots with (semi-)natural vegetation, the ranking of the weighted mean values for the different land-use types within these two groups varies for annual R, RC and SL (Figure 7). The difference between these two groups was confirmed by the application of the Kolmogorov-Smirnov test, whereby significant differences between land-use types were mostly observed between land-use types where crop cultivation was applied and land-use types with (semi-)natural vegetation. Furthermore, for 25 out of 55 pairwise combinations of all the 11 land-use types, the distribution of annual SL data was found to be significantly different, while for annual R and RC only 12 and 8 combinations were found to be significantly different, respectively.

Figure 7.

Frequency distribution of mean annual runoff (R), mean annual runoff coefficient (RC), mean annual soil loss (SL), and mean annual unit plot soil loss (SL_u, equation 4) of all plots in Europe and the Mediterranean, grouped by land-use type. Box-plots in grey indicate mean annual soil losses scaled to a unit plot (SL_u: plot length = 22.1 m, plot slope gradient = 9%). For the other land-use types, the original, measured SL was used. Black dots indicate the mean R, RC, SL and SL_u, weighted by number of plot-years (#PY). Box plots are ordered according to descending weighted mean.

Table 7.

Weighted mean, median and coefficient of variation (CV) for annual runoff (R), annual runoff coefficient (RC), annual soil loss (SL) and annual unit plot soil loss (SL_u) by land-use type for all data and grouped by climatic zone in Europe and the Mediterranean. Weighting was done according to the square root of the number of plot-years. For number of plots and plot-years corresponding to each land use, see Table 5. NC = not calculated because the relation between LS-factor and soil loss for this land-use type was insignificant (see Table 6). NA = no data available.

Land-use type	Climatic zone	R			RC			SL			SL_u
		mean	median		mean	median		mean	median		mean	median
		(mm)	(mm)	CV (-)	(%)	(%)	CV (-)	(Mg.ha^-1.yr^-1)	(Mg.ha^-1.yr^-1)	CV (-)	(Mg.ha^-1.yr^-1)	(Mg.ha^-1.yr^-1)	CV (-)
bare	all data	35.0	15.8	1.8	5.0	2.5	1.5	12.8	5.7	1.9	9.2	3.9	1.7
	pan-Mediterranean	36.0	20.5	1.9	4.9	3.8	1.4	9.1	3.6	1.5	7.4	3.1	1.5
	temperate	33.1	13.5	1.7	5.2	2.4	1.6	18.9	8.7	1.8	12.4	5.6	1.7
	cold	44.5	45.5	0.3	3.0	3.1	0.3	14.8	15.5	0.6	4.7	5.0	0.7
cropland	all data	50.3	11.9	1.7	8.0	3.2	1.4	6.5	1.3	2.8	3.3	0.9	2.2
	pan-Mediterranean	51.0	17.6	1.7	8.6	4.2	1.2	2.9	1.2	1.8	2.3	0.5	2.2
	temperate	19.3	5.8	1.8	3.3	1.3	1.5	9.6	0.9	2.7	4.1	1.1	2.1
	cold	148.9	199.7	0.6	19.5	28.9	0.6	9.0	3.0	1.3	4.1	1.7	1.3
fallow	all data	50.4	8.3	1.6	7.3	1.9	1.5	5.8	1.7	2.1	2.7	1.1	1.7
	pan-Mediterranean	51.1	25.8	1.1	7.7	3.9	1.0	1.5	0.7	1.5	0.7	0.4	1.4
	temperate	17.2	4.5	2.1	3.6	0.8	2.5	7.1	2.9	1.5	4.1	2.1	1.2
	cold	213.3	221.5	0.2	31.3	31.8	0.2	20.0	15.1	1.3	7.4	3.9	1.4
forest	all data	13.9	4.3	2.5	2.9	1.6	1.5	0.7	0.1	5.2	NC	NC	NC
	pan-Mediterranean	9.6	4.6	1.9	2.8	1.6	1.1	0.4	0.1	2.2	NC	NC	NC
	temperate	28.7	2.0	1.9	3.3	0.9	1.7	1.3	0.0	3.6	NC	NC	NC
	cold	3.9	3.9	NA	NA	NA	NA	0.0	0.0	NA	NC	NC	NC
grassland	all data	15.4	3.5	2.3	4.0	0.6	2.1	0.7	0.1	2.0	NC	NC	NC
	pan-Mediterranean	11.7	3.8	1.3	6.2	1.8	1.9	0.6	0.2	1.6	NC	NC	NC
	temperate	7.7	2.2	1.9	1.1	0.3	2.0	1.0	0.1	2.0	NC	NC	NC
	cold	133.9	131.0	0.6	27.5	26.0	0.4	0.6	0.1	2.1	NC	NC	NC
post-fire	all data	28.3	4.6	1.6	3.5	0.9	1.6	1.5	0.2	2.1	NC	NC	NC
	pan-Mediterranean	26.3	4.0	1.7	3.2	0.7	1.7	1.6	0.2	2.1	NC	NC	NC
	temperate	53.0	41.5	0.8	8.0	8.6	0.3	1.1	1.2	0.9	NC	NC	NC
	cold	41.7	41.7	0.1	NA	NA	NA	0.8	0.8	0.3	NC	NC	NC
rangeland	all data	18.8	6.0	1.8	2.7	1.7	0.9	0.7	0.2	2.2	NC	NC	NC
	pan-Mediterranean	19.6	5.5	1.8	2.8	1.8	0.9	0.8	0.2	2.2	NC	NC	NC
	temperate	6.6	6.6	NA	0.8	0.8	NA	0.3	0.3	1.4	NC	NC	NC
shrubland	all data	18.3	5.1	1.6	4.4	1.1	1.8	0.6	0.1	2.0	0.3	0.1	1.6
	pan-Mediterranean	18.5	5.1	1.6	4.4	1.1	1.8	0.6	0.2	1.9	0.3	0.1	1.6
	temperate	14.3	0.0	1.4	3.4	0.0	1.6	0.5	0.0	2.6	0.2	0.0	2.0
tree crops	all data	46.2	36.9	1.2	8.2	5.0	1.1	13.4	9.0	1.4	3.3	2.0	1.7
	pan-Mediterranean	52.7	34.2	1.2	10.2	5.5	1.0	11.6	7.4	1.5	3.0	1.8	1.8
	temperate	34.7	36.9	0.7	4.7	5.0	0.7	18.4	13.8	1.0	4.2	3.9	0.8
construction sites	all data	227.7	230.0	0.2	57.0	59.7	0.3	325.1	299.0	0.4	115.8	73.4	1.0
construction sites	pan-Mediterranean	241.0	241.0	0.1	61.9	61.9	0.1	357.5	357.5	0.2	63.1	63.1	0.2
	temperate	168.0	168.0	NA	34.8	34.8	NA	180.0	180.0	NA	351.3	351.3	NA
vineyard	all data	38.8	21.0	1.5	7.4	4.4	1.2	17.9	0.9	4.1	NC	NC	NC
	pan-Mediterranean	47.6	21.0	1.5	9.8	6.9	1.0	1.8	0.3	1.8	NC	NC	NC
	temperate	25.2	23.1	1.0	3.7	4.3	0.8	32.1	12.4	3.1	NC	NC	NC

4 Relationships of annual runoff coefficients and soil loss for various land uses

The median and distributions of all available annual RC and SL data for different land-use types are shown in Figure 8. This figure clearly indicates that there is a general trend towards higher median annual SL rates with higher median annual RC. For land uses under crop cultivation, tree crops have the highest median annual RC and SL. Vineyards have comparable median annual RC and 75th percentile annual SL values. However, median annual SL is markedly lower for vineyards, indicating that high annual SL rates in the database are more rare for vineyards than for tree crops. The interquartile ranges for cropland and fallow plots are similar for annual RC and annual SL. Median annual RC is lower for fallow plots, however, which indicates that low annual RC are more prevalent on fallow plots. Although annual RC rates on bare and cropland plots are similar, bare plots show higher annual SL rates than cropland plots. Plots with (semi-)natural vegetation are characterized by consistently low median annual SL (0.08–0.3 Mg.ha^-1.yr^-1), but still show somewhat more variation in median annual RC rates (0.5–1.1%).

Figure 8.

Relation between median annual runoff coefficient (RC), median annual soil loss (SL) and median annual unit plot soil loss (SL_u) of all plots in Europe and the Mediterranean by land use with indication of the 25th and 75th percentile for RC and SL, based on the plot database (for details, see Tables 5 and 7). n = number of land-use types.

Using all plot data for which respectively pairs of annual R-SL, RC-SL, R-SL_u and RC-SL_u were available, the best regression correlations (equation 5) are generally observed between annual R and SL (Table 8). Only for plots under grassland and post-fire better correlations between RC and SL were found. As a lack of data on annual P, plot length or plot slope gradient data does not allow the calculation of annual RC or SL_u, respectively, a smaller number of plots was available to calculate annual RC-SL, R-SL_u and RC-SL_u regressions. Nevertheless, the results of the regression analyses did not change using a subdata set of 611 PL where all four variables (annual R, RC, SL and SL_u) are available. In general, regression with unweighted annual R, RC, SL and SL_u data yields slightly better correlation than weighted regression, but weighted regressions were nevertheless considered to be more appropriate as the number of plot-years is taken into account (see section II(3)).

Table 8.

Coefficients of determination (r²) and number of plots (#PL) for the unweighted and weighted annual runoff–annual soil loss (R versus SL), annual runoff coefficient–annual soil loss (RC versus SL), annual runoff–annual unit plot soil loss (R versus SL_u) and annual runoff coefficient–annual unit plot soil loss (RC versus SL_u) regressions. Weighting was done using the square root of the number of plot-years. For each land use, the regression with the highest r² value is indicated in bold. n.s. = regression is not significant at α=0.05. NA = no regression was calculated as no SL_u values were calculated for these land-use types.

Land-use type	Crop	R versus SL			RC versus SL			R versus Sl_u			RC versus SL_u
		#PL	r²		#PL	r²		#PL	r²		#PL	r²
		#PL	unweighted	weighted	#PL	unweighted	weighted	#PL	unweighted	weighted	#PL	unweighted	weighted
bare		126	0.47	0.45	89	0.37	0.35	118	0.40	0.37	84	0.34	0.30
cropland	all data	281	0.19	0.19	228	0.13	0.12	259	0.16	0.15	217	0.10	0.09
	cereals	132	0.29	0.28	105	0.29	0.26	116	0.23	0.22	99	0.22	0.18
	maize	15	n.s.	n.s.	15	n.s.	n.s.	15	n.s.	n.s.	15	0.27	n.s.
	sunflower	8	0.54	n.s.	8	0.64	0.56	8	0.54	n.s.	8	0.64	0.59
	leguminous	23	n.s.	n.s.	21	n.s.	n.s.	23	n.s.	n.s.	21	n.s.	n.s.
	potatoes + sugar beet	6	n.s.	n.s.	4	n.s.	n.s.	5	n.s.	n.s.	4	n.s.	n.s.
	rotation	77	0.05	n.s.	55	n.s.	n.s.	72	n.s.	n.s.	50	n.s.	n.s.
	other	20	0.38	0.36	20	0.27	0.24	20	0.25	0.21	20	n.s.	n.s.
fallow		40	n.s.	n.s.	39	n.s.	n.s.	38	n.s.	n.s.	38	n.s.	n.s.
forest		50	0.48	0.47	48	0.58	0.58	NA	NA	NA	NA	NA	NA
grassland		47	0.26	0.25	30	0.28	0.27	NA	NA	NA	NA	NA	NA
post-fire		53	0.44	0.44	45	0.40	0.39	NA	NA	NA	NA	NA	NA
rangeland		14	0.31	n.s.	14	0.30	n.s.	NA	NA	NA	NA	NA	NA
shrubland		81	0.14	0.08	76	0.12	0.11	71	0.08	n.s.	66	0.08	n.s.
tree crops		13	0.83	0.83	13	0.66	0.65	13	0.81	0.80	13	0.62	0.61
vineyard		26	n.s.	n.s.	26	n.s.	n.s.	NA	NA	NA	NA	NA	NA
construction sites		3	n.s.	n.s.	3	n.s.	n.s.	3	n.s.	n.s.	3	n.s.	n.s.

Regressions between annual R and SL were found not to be significant for fallow, vineyards and construction sites and hence these land-use types were not included in Figures 9a and 9b. As a large number of plots is available for cropland and crop type is expected to have an important effect on annual SL rates in this land-use type (e.g. Auerswald et al., 2009; Gabriëls et al., 2003), a further subdivision according to crop type was made (Table 2b). The regression between annual R and annual SL was only significant for cereals (Figure 10), most likely due to a lack of sufficient data for the other crop types. Nevertheless, for maize, sugar beet and potatoes the available data show high annual RC and SL rates on nearly all of the plots where these crops were planted (Figure 10).

Figure 9a.

Significant (α = 0.05) relationships between annual runoff (R) and annual soil loss (SL) for different land-use types in Europe and the Mediterranean. Regressions are weighted according to the square root of number of plot-years for each plot. n = number of plots.

Figure 9b.

Comparison of the significant (α = 0.05) weighted regressions (SL = aR^b) between annual runoff (R) and annual soil loss (SL) for different land-use types in Europe and the Mediterranean. Regressions are weighted according to the square root of the number of plot-years for each plot. For regression parameters, see Figure 9a.

Figure 10.

Relationship between annual runoff (R) and annual soil loss (SL) for cereal, maize, potato and sugar beet in Europe and the Mediterranean. Only the regression for plots with cereals was found to be significant (α = 0.05) and is given here.

5 Effects of land use on runoff coefficient and soil loss for different climatic zones

In order to investigate possible impacts of the CZ on the relation between annual RC and SL for different land-use types, plot data were grouped according to CZ. After initial data analysis, the division of all plot data into seven different CZ, some of which contain only a few PL, was found to be too detailed. Therefore, the Mediterranean and Anatolian CZ were grouped in a new CZ hereafter referred to as ‘pan-Mediterranean’ (M). Likewise, the Atlantic, Continental and Steppic CZ were grouped in a ‘temperate’ CZ (T) and the Boreal and Alpine CZ in a ‘cold’ CZ (C). Weigthed mean values, median values and coefficients of variation for R, RC, SL and SL_u for each land use and CZ are given in Table 7. Shrubland, rangeland and post-fire occur mainly in the pan-Mediterranean zone and the few PL in the temperate zone are located relatively close to the pan-Mediterranean zone. Therefore, these land-use types were not further considered in this analysis. Also construction sites were disregarded due to insufficient plot data. For the other land-use types the differences in median value and the distribution of R and SL data by CZ are indicated in Figure 11.

Figure 11.

Relation between median annual runoff coefficient (RC) and median annual soil loss (SL) for all plots in Europe and the Mediterranean by land-use type and climatic zone, with indication of the 25th and 75th percentiles for R and SL. M = pan-Mediterranean, T = temperate, C = cold. For the number of plots (#PL) and number of plot-years (#PY), see Table 5, for the division in climatic zones, see Figure 1.

Mean annual SL values are smaller in the pan-Mediterranean than in the other two CZ for all land-use types (Table 7). With respect to the median, median annual SL rates for bare, fallow, tree crops and vineyards are significantly lower in the pan-Mediterranean zone than in the other CZ, except the differences between the pan-Mediterranean and cold CZ for bare PL, and the difference between pan-Mediterranean and temperate CZ for tree crops. These non-significant differences in annual SL are likely due to insufficient data for bare plots in the cold CZ and tree crops in the temperate CZ. Median annual SL in the pan-Mediterranean zone is not smaller for cropland, grassland and forests. However, mean annual SL for all these land-use types is smaller in the pan-Mediterranean zone compared to the temperate zone, indicating that the highest annual SL on cropland occur more frequently in the temperate zone than in the pan-Mediterranean (Figure 11). Only differences between the pan-Mediterranean and temperate CZ for cropland and between pan-Mediterranean and cold CZ for grassland were found to be significant.

With respect to annual RC, median annual RC is significantly higher in the cold CZ than in the other CZ for cropland, fallow and grassland. Also, mean annual RC is the highest in the cold CZ for all land-use types. For grassland, there is no significant difference in median annual SL between the different CZ, but differences in median annual RC between different CZ are significantly different, indicating that while grassland has consistently low annual SL rates throughout the study area, annual RC rates differ depending on CZ.

6 Effects of annual precipitation on annual runoff and soil loss for different land uses

Figure 12 displays the relation between P and the weighted mean annual R, RC, SL and SL_u for the different land-use types. As all PL on construction sites fall within the 250–500 mm annual P-class, they were not included in this figure. Separate graphs displaying the annual R, RC and SL by precipitation class for the different land-use types are presented in Figures 13a, 13b and 13c. It should be noted that for some land-use types only a few PL are available and hence some of the observed trends are uncertain. Nevertheless, clear trends can be observed. For all land-use types, annual R generally increases with increasing annual P (Figure 13a). For plots under cropland, there is already a substantial increase in annual R for 500–750 mm annual P, while for plots with a (semi-)natural vegetation cover, the most substantial increases in annual R occur in the 750–1000 mm and >1000 mm annual P classes. Application of the Kolmogorov-Smirnov test between subsequent precipitation classes indicated that the distribution of R data was only significantly different between the 250–500 mm annual P classes for cropland, fallow, post-fire forest and shrubland plots. For forest, also the difference between the 0–250 and 250–500 mm classes was significant. For annual RC, however, no clear general trend with P over all land-use types can be noted (Figure 13b).

Figure 12.

Weighted mean annual runoff (R), annual runoff coefficient (RC), annual soil loss (SL) and annual unit plot soil loss (SL_u) for each land-use type in Europe and the Mediterranean as a function of the annual precipitation (P) interval.

Figure 13a.

Median trend, distribution and weighted mean of annual runoff (R) by annual precipitation (P) interval and land-use type in Europe and the Mediterranean. Significant differences (α=0.05) in R between subsequent P classes are indicated by full lines while insignificant differences are indicated by dashed lines. PL= number of plots, PY= number of plot-years.

Figure 13b.

Median trend, distribution and weighted mean annual of runoff coefficient (RC) by annual precipitation (P) interval and land-use type in Europe and the Mediterranean. Significant differences (α=0.05) in RC between subsequent P classes are indicated by full lines while insignificant differences are indicated by dashed lines. PL= number of plots, PY= number of plot-years.

With respect to annual SL (Figure 13c), there is a general trend towards higher annual SL with higher annual P in plots with crop cultivation (vineyard, tree crops, bare, cropland and fallow). Mean annual SL under bare conditions increases between 250–500 mm and 500–750 mm, but levels afterwards and even decreases between the 750–1000 mm and >1000 mm annual P classes. Similarly, annual SL in cropland generally increases with increasing annual P, but mean annual SL for the >1000 mm annual P class is higher than for the 750–1000 mm class. Annual SL increases gradually with increasing annual P for post-fire, rangeland and forest annual PL. For grassland, the highest annual SL are observed in the 500–750 mm class. For shrubland, annual SL first increases to a maximum in the 250–500 mm class, and then declines over the 500–750 mm and 750–1000 mm classes. Mean annual SL increases again between the 750–1000 and >1000 mm classes, but the latter class corresponds to only 3 PL so results are not conclusive. Significant differences in annual SL between subsequent P-classes were found between the 0-250mm and 250-500mm classes for shrubland and between the 250-500mm and 500-750mm classes for bare, cropland and shrubland plots. For cropland, also the 500–750 mm and 750–1000 mm classes were found to have significantly different distributions. Corrections for plot length and slope gradient resulted generally in annual SL_u rates that are lower than the original annual SL rates. Nevertheless, the trends observed in the graph depicting the relation between annual P and annual SL (Figure 13c) were found to persist. Correlating the Modified Fournier Index with annual R, RC and SL did not yield clearer trends than using annual P measured on the plots (Figure 14).

Figure 13c.

Median trend, distribution and weighted mean of annual soil loss (SL) by annual precipitation (P) interval and land-use type in Europe and the Mediterranean. Significant differences (α=0.05) in R between subsequent P classes are indicated by full lines while insignificant differences are indicated by dashed lines. PL= number of plots, PY= number of plot-years.

Figure 14.

Relations between Modified Fournier Index (MFI) and annual precipitation (P), annual runoff (R) and annual soil loss (SL) for cropland plots in Europe and the Mediterranean

IV Discussion

1 How representative are the available plot runoff and soil loss data for Europe and the Mediterranean?

The assessment of annual R and annual SL rates based on the review of data measured on runoff and soil loss plots is inherently biased since runoff plot experiments are generally set up to answer specific research questions and not to be representative for the entire range of actual hillslope conditions (Auerswald et al., 2009; Cerdan et al., 2006; Vanmaercke et al., 2012). Many plot-measuring sites are located in areas that experience interrill and rill erosion. Furthermore, no plots are located in Iceland or in Scandinavia above 61 degrees latitude (Figure 1), probably due to logistic problems in cold environments and the low population density in these areas. A comparatively small number of runoff plots was found for northeastern Europe (Table 3), since many of these data have not been published in international journals and are not easily accessible. While even more plot data are likely existing, the database compiled in this study is currently the largest compilation of field-measured annual R and SL data at plot scale and for Europe and the Mediterranean region.

The relatively short measuring periods for the plots (mean: 6 yrs, median: 4 yrs) can be attributed to the relatively short duration of research or PhD projects during which most of the plots are established. This also means that it is difficult to assess temporal variability in R_a and SL_a on the longer term for a specific plot, which is nevertheless an important aspect for conservation planning (Bagarello et al., 2011). Figure 2 shows a clear decline of the number of plots in operation after 1996. This can be attributed to the fact that plot measurements are time- and labour-consuming and field-measured plot experiments are abandoned in favour of modelling studies, which have become more prevalent with increasing and cheaper computing power over the last 20–30 years (Merritt et al., 2003). A similar decline in catchment sediment yield studies was observed by Vanmaercke et al. (2011b), but was already starting between 1970 and 1980 when many large state-led monitoring schemes were abandoned. Most plot-scale studies are conducted by individual researchers however, and the number of publications on runoff and soil loss plots has not decreased in recent years (Figure 2). Moreover, recent publications review previously published data to assess erosion rates and variability under field conditions at national or regional scales (Table 1), to use these data in new spatial analyses (e.g. Cerdan et al., 2010) or to validate erosion models (e.g. Amore et al., 2004; Licciardello et al., 2009; Quinton, 1994; Tsara et al., 2005). Hence, there is an ongoing interest in field-measured annual R and SL data and a review and regular update of existing data sets offers opportunities to use these data in new analyses and thus to give added value to previously published studies (Baade and Rekolainen, 2006).

A large proportion of research has been carried out on bare and cropland plots (Table 5). Runoff and soil loss after wildfires have received considerable attention, despite annual R and SL rates still being low in comparison to those witnessed on some other land uses (Shakesby, 2011; Table 7). Permanent crops (tree crops and vineyards) have received more attention in plot studies in comparison to the areal percentage they represent in the CORINE land-cover map (Vanmaercke et al., 2012). Despite the relatively small area occupied by these land-use types, they are important contributors to total soil loss in Europe (Cerdan et al., 2010) and can be the dominant land-use type in certain regions. Furthermore, some of the highest annual RC (up to 40.2%) and SL rates (up to 151 Mg.ha^-1.yr^-1) recorded in the database occurred on permanent crops (i.e. vineyards and tree crops) (Figure 7, Table 7). The quantitative measurements currently available for these land-use types may still not be sufficient to make a comprehensive assessment of erosion risk in these land-use types (e.g. Gómez et al., 2008).

Also the distribution of plot lengths and slope gradients of the plots shows a research bias (Figure 4). Plots with a plot length between 20 and 30 m, i.e. close to the standard USLE plot (22.1 m; Renard et al., 1997), are by far the most frequent. Plot length is mainly determined by logistic limitations of the studies, and the relation to actual field slope lengths, for which very few data are available, is unknown. On the other hand, observed frequency distributions of the plot slope gradients for different land-use types (Figure 5) show both a difference between slope gradient distributions for different land-use types as they occur in the field as well as a research bias towards steeper slopes. This was demonstrated by Cerdan et al. (2006) who found that mean slope gradient of plots on grassland, forest and shrubland corresponded well to mean slope gradient for these land-use types on the reclassified CORINE land cover map, while mean slope gradients for arable, vineyards, orchard and post-fire plots were found to be steeper than the CORINE average. On the whole, the plots show a relatively steep slope gradient, with the majority of plots having a slope gradient above the 9% of the standard USLE plot (Figure 4). As was shown by Boardman (1998), careless extrapolation or generalization of these data can therefore lead to overestimations of annual SL rates. Therefore, the controlling environmental variables should always be accounted for when evaluating or extrapolating rates of annual R, RC and SL (Cerdan et al., 2010; de Vente et al., 2011). Hence, the rates of annual R and SL presented in this study may not be representative for the flat regions in Europe and the Mediterranean (Cerdan et al., 2010). Nevertheless, the extent of the database compiled in this study allows for the best representation of the relations between measured runoff, soil loss and annual precipitation for different land-use types currently available.

While the use of runoff and soil loss plots allows for a relatively easy assessment of annual runoff, runoff has received considerably less attention than soil loss in the literature as can be noted in the literature review (Table 1) and the number of plots and plot-years (Table 5). One of the problems underlying this discrepancy is the complex relationship between R and environmental variables (Wischmeier, 1966) and as a result also the relation between annual R and SL is less studied. Nevertheless, the assessment of annual R is an important part of many erosion models (Merritt et al., 2003) and hence a better understanding of runoff generation and runoff-soil loss relationships would contribute towards better erosion models (e.g. Kinnell and Risse, 1998). Runoff generation is also an important problem in itself, both on-site (e.g. loss of plant available water; Wallace, 2000) and off-site (e.g. flash floods). For instance, water is a key resource in the Mediterranean (Araus, 2004; Vanmaercke et al., 2011b) and annual RC are often higher than annual RC for comparable land uses in temperate regions, while annual SL rates tend to be lower in the pan-Mediterranean CZ than in the temperate CZ (Table 7, Figure 11), hence excessive runoff may be of more concern than soil loss.

2 Effects of plot length and slope gradient on annual runoff, runoff coefficient and soil loss

Annual SL on bare, cropland and tree crop plots are positively correlated to plot L-factor (Table 6). This finding concurs with results found by Cerdan et al. (2010). For these land-use types, also annual R and RC are positively correlated with plot length (Table 6). This can be attributed to the high connectivity along flow paths under these land-use types, allowing runoff to accumulate along the flow path over longer plot lengths and resulting in higher annual SL due to the increased detachment and transport capacity of the overland flow (Govers and Poesen, 1988; Prosser and Rustomji, 2000). A significant effect of plot S-factor on annual SL was only found for cropland and shrubland, although the correlations between the plot S-factor and annual SL are also relatively strong for bare plots and fallow plots (Table 6, p = 0.06).

With respect to climatic zone, Cerdan et al. (2010) found that for arable and bare plots the relation between LS-factor (equation 3) and annual SL was only significant for plot data collected outside the Mediterranean CZ and not for plots in the Mediterranean CZ, which was attributed to the higher surface rock fragment cover in the Mediterranean, especially on steeper slopes (Poesen et al., 1998). In this study, similar results are found for bare plots in the temperate CZ where the relation between the L-factor (r_s = 0.62, p < 0.01), S-factor (r_s = 0.25, p = 0.03) and LS-factor (r_s = 0.44, p < 0.01) was significant, while for plots in the pan-Mediterranean CZ none of these relations were significant. However, for cropland in both the temperate and pan-Mediterranean CZ significant relations between L-factor and annual SL (r_s = 0.36, p < 0.01 and r_s = 0.20, p = 0.01, respectively) and between LS-factor and annual SL (r_s = 0.33, p < 0.01 and r_s = 0.17, p = 0.03, respectively) were found. This could be due to the inclusion of more pan-Mediterranean cropland plots in the database as compared to the database used by Cerdan et al. (2010). By including more plots, the probability of including low-frequency, high-intensity events for which there is a significant topographic effect increases. Nevertheless the correlation coefficient between LS-factor and annual SL remains smaller for cropland plots in the pan-Mediterranean (r_s = 0.17, p = 0.03) than for cropland plots in the temperate zone (r_s = 0.33, p < 0.01).

For grassland, no significant correlations were found between the L-, S- or LS-factor and annual SL. This can be explained by the high root density of the grass, which reduces soil erodibility (De Baets et al., 2006). The correlation between plot length and R was significantly positive (Table 6) however, which may be explained by the fact that runoff is more likely to converge on longer slopes, and the effect of grass cover on annual R retention is often less pronounced and more variable than the effect on annual SL, as is shown by studies on the effectiveness of grass buffer strips (e.g. Blanco-Canqui et al., 2004) and grassed waterways (e.g. Fiener and Auerswald, 2003). Contra-intuitively, a significant negative relation was noted between slope gradient and both R and RC for grassland. This is probably due to the fact that grasslands in the northern regions often lie on gentle slopes but are very wet due to a clayey subsoil. These soils often need drainage (e.g. Øygarden, 1996; Øygarden et al., 1997; Turtola and Paajanen, 1995; Turtola et al., 2007; Warsta et al., 2009). For plots under forest and post-fire a significant negative correlation between plot length and annual R and annual RC was found (Table 6). This is probably related to the heterogeneity of soil cover and macropore distribution in these land-use types, meaning that as plot length increases, runoff is more likely to flow through patches with increased roughness or infiltration capacity. For shrubland, a significant negative correlation between slope gradient and annual R and RC is observed, while the correlation between the S-factor and annual SL is positive (Table 6). An explanation for this can be offered by the reduced tendency in surface sealing of bare patches with steeper slopes (Poesen, 1984, 1986), reducing runoff but increasing splash erosion (Bradford et al., 1987). Nevertheless, plots under shrubland are characterized by a high spatial variability at plot scale and hence the establishment of relations between plot length and slope gradient and annual R, RC and SL is difficult (Cammeraat, 2002).

No significant effect of plot length on annual R or RC was found for vineyards, but the L-factor was significantly correlated with annual SL (Table 6). This is mainly due to the fact that high annual R and RC already occur on short plots, resulting in high runoff rates independent of plot length. For tree crops, which are also considered as a land-use type with permanent cultivation, a positive relation between plot length and annual R and RC was found. This difference with vineyards may be due to differences in soil types or the generally higher vegetation cover associated with tree crops, though no data were available to check these hypotheses. As was already indicated by Cerdan et al. (2010), our results illustrate that the relations between plot length and/or slope gradient and annual SL depend on the considered land use. In addition, our analyses show that also relations of plot length and slope gradient with R and RC depend on land-use type. Plot length and slope gradient may affect annual R and RC differently than they affect annual SL. Furthermore, a further subdivision of the major land-use types analysed by Cerdan et al. (2010) (bare, arable, permanent cultivation and permanent vegetation) reveals that also within these groups, relations between topographic factors and annual SL may vary. For instance, in the permanent vegetation group, no significant relation between LS-factor and annual SL was found for forest, grassland and rangeland plots, but there was a significant relationship between the LS-factor and annual SL for shrubland (Table 6).

3 Frequency distributions and relationships between annual runoff and soil loss for various land uses

Previous studies (e.g. Cerdan et al., 2010; Kosmas et al., 1997) showed the importance of vegetation cover as an important determinant of annual SL on a (sub)continental scale. This study further confirms this, as significant differences between the distributions of SL data were mostly found between land-use types with cultivation and land-use types with semi-natural vegetation. Construction sites have the highest observed annual SL rates (Figure 7, Table 7), although the limited amount of available data (Table 5) does not allow clear conclusions on the frequency distribution of the observed values. Bare plots and plots with crop cultivation (cropland, vineyards and tree crops) form a second cluster with high R, RC and SL rates (Figures 7 and 8). All these land-use types are characterized by severe anthropogenic disturbance (construction sites and bare PL) or intensive tillage of the soil for agriculture (cropland, tree crops and vineyards). On these plots, annual SL regularly exceeds tolerable soil loss rates (T-values) of 5–12 Mg.ha^-1.yr^-1 (Montgomery, 2007). The mean annual SL rate of 11.6 Mg.ha^-1.yr^-1 for tree crops in the pan-Mediterranean zone (Table 7) was found to be much higher than reported in previous studies such as Cerdan et al. (2010) who found an average annual SL rate for orchards in the Mediterranean of 1.67 Mg.ha^-1.yr^-1 and Fleskens and Stroosnijder who concluded that annual SL in olive orchards is unlikely to exceed 10 Mg.ha^-1.yr^-1. Annual SL in olive orchards is often the result of infrequent high-intensity rain events and depends strongly on spatial scale and land management (Gómez et al. 2008). Depending on which data are included in the analysis and the way the available data are analysed they may be deemed low (Fleskens and Stroosnijder, 2007) or frequently in excess of tolerable rates (Gómez et al., 2008). The use of a larger database (20 PL, corresponding to 80 PY) in this study indicates that annual SL in tree crops in the pan-Mediterranean zone can frequently exceed tolerable levels.

Vineyards show a high coefficient of variation for SL_a in addition to a high average SL_a value (Table 7). This is attributed to the high erosion susceptibility of this land-use type after vineyard establishment. Wicherek (1991) reports a sharp decline in soil losses over the first three years after vineyard establishment in the Aisne region, northern France (57.3, 28.7 and 1.4 Mg.ha^-1.yr^-1, respectively). Tropeano (1984) also reports the highest soil loss (8.3 Mg.ha^-1.yr^-1) to occur in the first year after vineyard establishment in the Piemonte region, northwestern Italy, which was reduced to 1.2 Mg.ha^-1.yr^-1 in the following year. This is also illustrated by Engels (personal communication 2009) who notes that soil loss from an old undisturbed vineyard in the Moselle region, western Germany, is considerably lower (0.5 Mg.ha^-1.yr^-1) than that from an adjacent vineyard where vines were removed and roots destroyed (4.4 Mg.ha^-1.yr^-1). Nevertheless, no clear trends in annual SL between 8 and 17 years after vineyard establishment were found for vineyards in the Douro region, northern Portugal (de Figueiredo, personal communication 2010; de Figueiredo and Gonçalves Ferreira, 1993; de Figueiredo and Poesen, 1998). Brenot et al. (2006) measured soil loss by vine stock unearthing (i.e. over the complete period since vineyard establishment) for vineyards of different ages (10–54 years) in Burgundy, France, but no trend in annual SL with respect to vineyard age is observed. In contrast to the high SL_a observed for several vineyards, some vineyards established on very steep slopes (c. 45%) with very stony soils show comparatively very low mean SL_a values in the Douro region, Portugal (0.2–0.5 Mg.ha^-1.yr^-1: de Figueiredo and Gonçalves Ferreira, 1993; de Figueiredo and Poesen, 1998) or the Moselle region (0.02–0.5 Mg.ha^-1.yr^-1: Richter, 1980). Although the number of available plots on which SL data were collected directly after vineyard (re)planting (n = 1) or removal of the vines (n = 1) is limited, these results indicate that vineyards are in general very vulnerable to soil loss after establishment or periodical replanting of the vines due to the often intense soil disturbances (Borselli et al., 2006). After a number of years, annual SL in vineyards often decreases to relatively low rates as is shown by the median annual SL of 0.9 Mg.ha^-1.yr^-1 for the whole of Europe and the Mediterranean (n = 39, Table 7). This is attributed to the stony soils often associated with vineyards which develop an erosion pavement with a high rock fragment cover which drastically reduces SL (Poesen et al., 1994).

Land-use types with a (semi-)natural vegetation generally have mean annual SL values well below the T-value, illustrating the dominant control of vegetation cover over annual SL (Montgomery, 2007). However, SL rates up to 7 Mg.ha^-1.yr^-1 can be observed on all land-use types and differences between land-use types are mainly situated in the frequency of occurrence for high annual SL values (i.e. above 10 Mg.ha^-1.yr^-1) (Figure 7). Scaling of annual SL values to unit plot soil loss rates results generally in somewhat lower annual SL_u rates (Figure 6), but does not change the differences between different land-use types observed above (Figure 7, Table 7). Hence, while plot length and slope gradient may have an effect on annual SL values, they cannot fully account for the differences between different land-use types.

The distribution of annual R and RC values follows the same pattern as annual SL, with land-use types with a (semi-) natural vegetation cover having generally lower annual R and RC rates (Figure 7). However, fewer significant differences are observed between different land-use types combinations than for annual SL. There is a larger overlap between the annual R and RC data distributions (Figure 7) which indicates that the effect land-use types have on annual SL is more pronounced than they are on annual R and RC. No standard exists for tolerable annual R and RC levels, but excessive runoff also has several negative off-site effects such as gully formation (Poesen et al., 2006) and flooding (García-Ruiz et al., 2010).

With respect to the relations between annual R/RC and SL/SL_u, the small differences between r² values obtained for weighted and unweighted regressions (Table 8) can be explained by the distribution of the number of plot-years since a large part of the number of plots corresponds to a low number of plot-years and hence has similar weights (Figure 3). The generally better correlations between annual R and SL than between annual RC and SL (Table 8) can be explained by the fact that mainly the total runoff volume, rather than the runoff coefficient, determines the erosive power and transport capacity of the overland flow. Nevertheless, the inclusion of differences in annual precipitation makes it easier to compare RC rates between different plots. Hence, both annual R and RC are important variables to consider. The general trend in the relation between annual R and SL is that (semi-)natural land uses show annual SL rates of up to one order of magnitude less than SL values for land-use types with crop cultivation for the same annual R rate (Figure 9b). This is not the case for tree crops, however, where the increase in annual SL with increasing R is much stronger than for other land-use types (Figure 9a). However, this trend should be interpreted with caution as it is based on only 13 PL. For shrubland, clusters of data that correspond to individual plot-measuring sites show a good correlation between annual R and SL (Figure 9a), while the global regression is affected by more scatter in the data, which is most likely determined by local environmental factors that differ from plot site to site. Summer crops like maize, potatoes and sugar beet were found to result in R and SL rates which are among the highest for cropland (Figure 10).

4 Effects of land use on runoff coefficient and soil loss for different climatic zones

The higher annual RC observed in the cold zone may be attributed to the combination of snowmelt and a frozen soil in spring (e.g. Alström and Bergman, 1990; Wade and Kirkbride, 1998) and the generally lower annual evapotranspiration rate at high latitudes (Weiß and Menzel, 2008). Furthermore, annual R and RC rates in the pan-Mediterranean zone are generally higher than in the temperate CZ (Table 7, Figure 11). This is likely due to the combination of soil properties, the often smaller and more discontinuous natural vegetation cover in the pan-Mediterranean region, and the seasonality of the rainfall with a large fraction of the annual rainfall concentrated in a few important events during a short winter season (Altava-Ortiz et al., 2011; Mehta and Yang, 2008).

Nevertheless, these higher annual R and RC rates in the pan-Mediterranean do not result in high annual SL (Figure 11, Table 7). Smaller annual SL rates in the Mediterranean were also observed by Cerdan et al. (2010) and can be explained by the generally higher rock fragment cover in Mediterranean soils which is known to reduce soil loss rates (Poesen and Lavee, 1994; Poesen et al., 1994). Especially for vineyards, which are often located on stony soils, annual SL rates in the pan-Mediterranean CZ are much smaller than those in the temperate CZ (Figure 11). Nevertheless, Sanchis et al. (2008) observed that also for soils with a low rock fragment content (<10% content by mass) soil erodibility was lower in the Mediterranean. This is attributed to a dominance of clay rich soils in arable land in the Mediterranean and the associated low soil erodibility of these soils (Torri et al., 1997). Furthermore, very erodible soil types like loess-derived soils occur almost exclusively in the temperate CZ. Hence, it should be noted that differences between CZ include more than just a climatic effect as CZ is also a proxy for particular soil properties which affect annual R and SL like soil susceptibility to cracking. Apart from differences between precipitation and soil characteristics between the temperate and pan-Mediterranean CZ, differences in conventional land management like tillage frequency and depth in cropland may also account for part of the observed variability. Furthermore, for grassland and forest, there is no significant difference between median SL rates for plots in the pan-Mediterranean zone and plots in the temperate CZ, which again indicates the important effect of vegetation in controlling annual SL.

5 Effects of annual precipitation on annual runoff and soil loss for different land-use types

For all land uses, there is a consistent trend towards higher annual R with increasing annual P which is more pronounced for land-use types with crop cultivation than land-use types with (semi-) natural vegetation (Figure 13a). For all land-use types with crop cultivation, except for vineyards, there is a trend towards increasing annual RC with increasing precipitation, indicating that as rainfall increases there is a larger percentage of excess rainfall (Figure 13b). This may be related to distribution of rainfall patterns throughout the year, with areas with high annual P generally having a more uniform precipitation distribution throughout the year. This causes seasonal saturation of the soil and faster runoff formation (Ponce and Hawkins, 1996).

For annual SL, there is also an increase in annual SL rates with increasing annual P for most land-use types (Figure 13c) but, unlike annual R, the increase is more gradual. For bare and cropland plots, there is even a decrease in annual SL in the highest annual P classes (>750 mm for bare and >1000 mm for cropland). This is likely due to variations in seasonality of the rainfall. The relatively uniform rainfall distribution in regions with high annual P makes these regions less prone to unfrequent extreme rainfall events in periods of the year when the soil is vulnerable to erosion (Edwards and Owens, 1991; Larson et al., 1997).

Shrubland is generally limited to the pan-Mediterranean region and a maximum in SL is observed in the 250–500 mm annual P class (Figure 13c), and both the differences between the lower and higher precipitation class are significant. A similar trend was noted by Kosmas et al. (1997) who attributed this to an initial increase in annual SL with increasing annual P as the erosion potential of the rain also increases, combined with insufficient vegetation cover in drylands. However, as annual P futher increases the vegetation cover also increases, effectively reducing annual SL for higher annual P. This is similar to the mechanism and trend for sediment yield proposed by Langbein and Schumm (1958). However, this trend is not observed for other land-use types, as vegetation cover in shrubland can be expected to be the most sensitive to changes in annual P. Contrary to the study by Kosmas et al. (1997), this maximum is not noticeable for annual R, which may indicate that, at a Mediterranean-wide scale, runoff volume is more determined by other environmental characteristics than vegetation cover, such as surface sealing and rock fragment cover.

In general, significant differences in the frequency distribution of both annual R and annual SL were mostly found between the 250–500 mm and 500–750 mm P classes (Figures 13a and 13c). This may indicate that significant changes in the rainfall-runoff and rainfall-soil loss relations occur at around these annual P values which are likely related to changes in rainfall regime and distribution throughout the year. Hence, comparison of annual R and SL rates with measures that take rainfall distribution throughout the year into account could improve the analysis. Nevertheless, the use of MFI as an indicator of climatic effect on annual R, RC and SL did not yield better correlations than the use of annual P (Figure 14). The MFI values used in this analysis represent long-term average (i.e. climatological) values which may not be representative for the specific years of plot measurements. This explains why low annual R and SL rates occur regularly in zones with high MFI values. Furthermore, the relation between MFI and annual P (Figure 14) and MFI and EI30 values (Torri et al., 2006) is not straightforward.

VI Conclusions

While a decrease in the number of studies using runoff and soil loss plots under natural rainfall has occurred since the mid-1990s in Europe and the Mediterranean, there is still an interest in plot data. Recently, several studies have assessed the erosion problem by reviewing existing soil loss data from plots and by using these data in empirical studies or erosion model validations. Many of these studies investigated soil loss rates in relation to land use, topography and soil properties. However, plot-scale runoff has been largely neglected in these studies and the relation between runoff and soil loss has not been reviewed on a scale covering Europe and the Mediterranean. Nevertheless, runoff estimation and its relation to soil loss are important parts of many erosion models. On a (sub)continental scale also climatological differences are often not taken into account in overview studies. To address these issues, the largest data set of runoff and soil loss plot data for Europe and the Mediterranean region was compiled in this study, which includes for the first time both annual runoff and annual runoff coefficients at the continental scale. In general, soil loss studies using runoff plots are mainly focused on bare plots and cropland and fewer data are available for construction sites, tree crops and vineyards, in spite of the high soil losses that may be associated with these land-use types. Variation in annual runoff and soil loss rates observed on the plots ranges over several orders of magnitude. While land-use types with crop cultivation (cropland, fallow, tree crops and vineyards) have higher mean soil loss rates than land-use types under (semi-)natural vegetation (grassland, rangeland, shrubland, forest and post-fire), there are still large variations within each of these land-use types, which can only be partly accounted for by topographic (i.e. plot length and slope gradient) differences. Annual runoff rates follow the same pattern as annual soil loss rates, but differences between land uses are less clear. The generally good relations between annual runoff and annual soil loss illustrate the key importance of the relation between runoff and soil loss for a good assessment of soil loss rates. Further quantitative analysis of this relation may also contribute significantly to improve predictions in erosion models. Furthermore, the relation between annual runoff and soil loss also depends on climate, with comparatively high runoff coefficients in cold climates and lower soil losses in the pan-Mediterranean region. This indicates that runoff-soil loss relations may show important regional variations. Apart from the importance of runoff as a causal factor of soil loss, runoff in itself is associated with several problems such as flooding and plant-available water. Techniques specifically aimed at reducing runoff and runoff coefficients can contribute to a more efficient use of rainwater on-site to increase food production, especially in drier regions like the Mediterranean. As expected, annual rainfall was found to be related to annual runoff and soil loss, and the vegetation feedback effect for shrubland proposed by Kosmas et al. (1997) was also observed on a Mediterranean-wide scale for soil loss, but not for runoff. Nevertheless, a large part of the variation in runoff and soil loss rates remains unexplained and better relations between annual precipitation and runoff and soil loss can likely be obtained by accounting for rainfall erosivity, but use of a Modified Fournier Index did not yield better results than the use of the annual precipitation measured on the plots. Hence there are still possibilities to expand the research to better account for rainfall erosivity. Further research may also focus on the effects of several important soil characteristics (e.g. texture, organic matter content) and a more detailed analysis of several relations for which general trends were established in this study (e.g. the relation between annual runoff and plot length and plot slope gradient, the relation between annual runoff and soil loss). In conclusion, this meta-analysis of field plot data for Europe and the Mediterranean allows a quick assessment of the impact of land-use change scenarios on annual runoff, runoff coefficient and soil loss on a continental scale.

Footnotes

Appendix: List of abbreviations and symbols

Land-use types:

Climatic zones:

Funding

The research reported in this paper was conducted in the framework of the EC-DG RTD- 6th Framework Research Programme (sub-priority 1.1.6.3) - Research on Desertification- project DESIRE (037046): Desertification Mitigation and Remediation of land - a global approach for local solutions. M. Vanmaercke received grant-aided support from the Research Foundation Flanders (FWO), Belgium.

References

Abu Hammad

Borresen

Haugen

(2006) Effects of rain characteristics and terracing on runoff and erosion under the Mediterranean. Soil and Tillage Research 87(1): 39–47.

Abu Hammad

Haugen

Borresen

(2004) Effects of stonewalled terracing techniques on soil-water conservation and wheat production under Mediterranean conditions. Environmental Management 34(5): 701–710.

Abu-Zreig

(2006) Control of rainfall-induced soil erosion with various types of polyacrylamide. Journal of Soils and Sediments 6(3): 137–144.

Abu-Zreig

Tamimi

Alazba

(2011) Soil Erosion control and moisture conservation of arid lands with stone cover. Arid Land Research and Management 25(3): 294–307.

Agassi

Benhur

(1991) Effect of slope length, aspect and phosphogypsum on runoff and erosion from steep slopes. Australian Journal of Soil Research 29(2): 197–207.

Agassi

Shainberg

Morin

(1990) Slope, aspect and phosphogypsum effects on runoff and erosion. Soil Science Society of America Journal 54(4): 1102–1106.

Albaladejo

Stocking

(1989) Comparative evaluation of two models in predictiong storm loss from erosion plots in semi-arid Spain. Catena 16(3): 227–236.

Albaladejo

Castillo

Diaz

(2000) Soil loss and runoff on semiarid land as amended with urban solid refuse. Land Degradation and Development 11(4): 363–373.

Al-Seekh

Mohammad

(2009) The effect of water harvesting techniques on runoff, sedimentation, and soil properties. Environmental Management 44(1): 37–45.

10.

Alström

Bergman

(1990) Water erosion on arable land in southern Sweden. In: Boardman

Foster

IDL

Dearing

(eds) Soil Erosion on Agricultural Land. Chichester: Wiley, 107–117.

11.

Altava-Ortiz

Llasat

M-C

Ferrari

. (2011) Monthly rainfall changes in central and western Mediterranean basins, at the end of the 20th and beginning of the 21st centuries. International Journal of Climatology 31(13): 1943–1958.

12.

Ammer

Breitsameter

Zander

(1995) Der Beitrag des Bergwaldes zum Schutz gegen Oberflächenabfluß und Bodenabtrag. Forstwissenschaftliches Centralblatt 114: 232–249.

13.

Amore

Modica

Nearing

. (2004) Scale effect in USLE and WEPP application for soil erosion computation from three Sicilian basins. Journal of Hydrology 293 (1–4): 100–114.

14.

Andreu

Imeson

Rubio

(2001) Temporal changes in soil aggregates and water erosion after a wildfire in a Mediterranean pine forest. Catena 44(1): 69–84.

15.

Andreu

Rubio

Cerni

(1998a) Effects of mediterranean shrub cover on water erosion (Valencia, Spain). Journal of Soil and Water Conservation 53(2): 112–120.

16.

Andreu

Rubio

Gimeno-García

. (1998b) Testing three Mediterranean shrub species in runoff reduction and sediment transport. Soil and Tillage Research 45 (3–4): 441–454.

17.

Arabi

Roose

(1993) Gestion conservatoire de l’eau et de la fertilité des sols en montagne semi-aride Algérienne. Bulletin du Réseau Erosion 18: 230–240.

18.

Araus

(2004) The problems of sustainable water use in the Mediterranean and research requirements for agriculture. Annals of Applied Biology 144(3): 259–272.

19.

AREDVI (2003) Guide de Protection du Vignoble 2003. Aix-en-Provence: Association Régionale d’Expérimentation et de Développement Viti-vinicole.

20.

Arhonditsis

Giourga

Loumou

(2000) Ecological patterns and comparative nutrient dynamics of natural and agricultural Mediterranean-type ecosystems. Environmental Management 26(5): 527–537.

21.

Arnoldus

(1980) An approximation of the rainfall factor in the Universal Soil Loss Equation. In: De Boodt

Gabriëls

(eds) Assessment of Erosion. Chichester: Wiley, 127–132.

22.

Aspizua

(2003) Erosion assessment and conservation measures in sloping and mountainous olive production systems in Andalucía. OLIVERO Student Report Series No. 2.

23.

Auerswald

(2006) Germany. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 213–230.

24.

Auerswald

Fiener

Dikau

(2009) Rates of sheet and rill erosion in Germany – a meta-analysis. Geomorphology 111 (3–4): 182–193.

25.

Auzet

Le Bissonnais

Souchère

(2006) France. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 369–383.

26.

Baade

Rekolainen

(2006) Existing soil erosion data sets. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 717–728.

27.

Bagarello

Ferro

(2010) Analysis of soil loss data from plots of differing length for the Sparacia experimental area, Sicily, Italy. Biosystems Engineering 105(3): 411–422.

28.

Bagarello

Di Stefano

Ferro

. (2010a) Statistical distribution of soil loss and sediment yield at Sparacia experimental area, Sicily. Catena 82(1): 45–52.

29.

Bagarello

Di Stefano

Ferro

. (2011) Using plot soil loss distribution for soil conservation design. Catena 86(3): 172–177.

30.

Bagarello

Ferro

Giordano

(2010b) Testing alternative erosivity indices to predict event soil loss from bare plots in southern Italy. Hydrological Processes 24(6): 789–797.

31.

Ballif

(1989) Erosion dans le vignoble champenois: Influence des techniques culturales (France). Cahiers ORSTOM, Séries Pedologie XXV (1–2): 151–156.

32.

Barkusky

(1990) Schutz vor Wassererosion im Silomais durch Zwischen- und Untersaat. Archiv für Acker- Pflanzenbau und Bodenkunde 6: 385–391.

33.

Basic

Kisic

Butorac

. (2001) Runoff and soil loss under different tillage methods on Stagnic Luvisols in central Croatia. Soil and Tillage Research 62 (3–4): 145–151.

34.

Basic

Kisic

Mesic

. (2004) Tillage and crop management effects on soil erosion in central Croatia. Soil and Tillage Research 78(2): 197–206.

35.

Basso

Barbieri

Linsalata

(1983a) Relation between hydrological parameters and erosion of a clay soil at 2 year rotation: horsebean for seed durum wheat under different tillage systems. (In Italian: Relazione tra parametri idrologici ed erosione di un terreno argilloso a rotazione biennale: Favino da seme-frumento duro sottoposto a differenti modalità di lavorazione.). Problemi Agronomici per la Difesa dai Fenomeni Erosivi, Quaderni della Ricerca del CNR n.129. Roma: CNR, 186–207.

36.

Basso

Barbieri

Linsalata

. (1983b) Relation between hydrological parameters and erosion in different crop systems. (In Italian: Relazione tra parametri idrologici ed erosione in differenti sistemi colturali). Problemi Agronomici per la Difesa dai Fenomeni Erosivi, Quaderni della Ricerca del CNR n.129. Roma: CNR, 96–112.

37.

Basso

Pisante

Basso

(2002) The Agri Valley – sustainable agriculture in a dry environment: Crop systems and management. In: Geeson

Brandt

Thornes

(eds) Mediterranean Desertification – A Mosaic of Processes and Responses. Chichester: Wiley, 331–383.

38.

Bautista

Bellot

Vallejo

(1996) Mulching treatment for postfire soil conservation in a semiarid ecosystem. Arid Soil Research and Rehabilitation 10(3): 235–242.

39.

Bautista

Mayor

Bourakhouadar

. (2007) Plant spatial pattern predicts hillslope semiarid runoff and erosion in a Mediterranean landscape. Ecosystems 10(6): 987–998.

40.

Ben Chaabane

Hamrouni

(2008) Influence de la mise en defens ou en culture sur la dynamique des flux érosifs en milieu dégradé de Tunesie centrale. In: Roose

Albergel

De Noni

. (eds) Efficacité de la Gestion de l’Eau et de la Fertilité des Sols en Milieux Semi-arides. Paris: AUF, EAC et IRD éditeurs, 217–222.

41.

Bhattacharyya

Davies

Fullen

. (2008) Effects of palm-mat geotextiles on the conservation of loamy sand soils in east Shropshire, UK. Advances in Geoecology 39: 527–538.

42.

Bhattacharyya

Fullen

Davies

. (2009) Utilizing palm-leaf geotextile mats to conserve loamy sand soil in the United Kingdom. Agriculture Ecosystems and Environment 130 (1–2): 50–58.

43.

Biemelt

Schapp

Kleeberg

. (2005) Overland flow, erosion, and related phosphorus and iron fluxes at plot scale: A case study from a non-vegetated lignite mining dump in Lusatia. Geoderma 129 (1–2): 4–18.

44.

Bienes

Marqués

Jiménez

. (2006) Study and quantification of the loss of fertility by water erosion. In: Proceedings of the 4th Conference of International Soil Conservation Organization. Water Management and Soil Conservation in Semi-Arid Environments. Marrakech, Morocco, 14–19 May. ISCO, 143–144.

45.

Bini

Gemignani

Zilocchi

(2006) Effect of different land use on soil erosion in the pre-alpine fringe (north-east Italy): Ion budget and sediment yield. Science of the Total Environment 369 (1–3): 433–440.

46.

Blanco-Canqui

Gantzer

Anderson

. (2004) Grass barrier and vegetative filter strip effectiveness in reducing runoff, sediment, nitrogen, and phosphorus loss. Soil Science Society of America Journal 68(5): 1670–1678.

47.

Blinkov

Trendafilov

(2006) Macedonia. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 289–296.

48.

Boardman

(1998) An average soil erosion rate for Europe: Myth or reality? Journal of Soil and Water Conservation 53(1): 46–50.

49.

Boardman

Evans

(2006) Britain. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 439–453.

50.

Boardman

Poesen

(2006) Soil Erosion in Europe. Chichester: Wiley.

51.

Boix-Fayos

Martínez-Mena

Arnau-Rosalén

. (2006) Measuring soil erosion by field plots: Understanding the sources of variation. Earth-Science Reviews 78 (3–4): 267–285.

52.

Bollinne

(1982) Etude et prevision de l’erosion des sols limoneux cultives en moyenne Belgique. PhD thesis, Faculty of Sciences, Geography, Université de Liège, Belgium.

53.

Borselli

Torri

Øygarden

. (2006) Land levelling. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 643–658.

54.

Botschek

(1991) Bodenkundliche Detailkartierung erosionsgefährdeter Standorte in Nordrhein-Westfalen und Überprüfung der Bodenerodierbarkeit (K-Faktor). Hamburger Bodenkundliche Arbeiten 16: 131.

55.

Bourges

Floret

Pontanier

(1973) Etude d’une toposequence type du sud Tunisien. Djebel Dissa. Les sols, bilan hydrique, érosion, vegetation. (Résultats de la saison 1972–1973). Report, Office de la Recherche Scientifique et Technique d’Outre-Mer (ORSTOM). Ministère de l’Agriculture, Direction des Resources en Eau et en Sol, Division des Sols.

56.

Bourges

Floret

Potanier

(1975) Etude d’une toposequence type du sud Tunisien. Djebel Dissa. Les sols, bilan hydrique, érosion, vegetation. (Résultats de la saison 1973–1974). Report, Office de la Recherche Scientifique et Technique d’Outre-Mer (ORSTOM). Ministère de l’Agriculture, Direction des Resources en Eau et en Sol, Division des Sols.

57.

Bradford

Ferris

Remley

(1987) Interrill soil erosion processes: I. Effect of surface sealing on infiltration, runoff, and soil splash detachment. Soil Science Society of America Journal 51(6): 1566–1571.

58.

Brenot

Quiquerez

Petit

. (2006) Soil erosion rates in Burgundian vineyards. Bollettino della Società Geologica Italiana – Volume Speciale 6: 169–173.

59.

Brenot

Quiquerez

Petit

. (2008) Erosion rates and sediment budgets in vineyards at 1-m resolution based on stock unearthing (Burgundy, France). Geomorphology 100 (3–4): 345–355.

60.

Brittain

(1987) P-values for the multi-sample kolmogorov-smirnov test using the expanded bonferroni appoximation. Communications in Statistics – Theory and Methods 16(3): 821–835.

61.

Brown

(1996) Effect and interaction of rotation, cultivation and agrochemical input levels on soil erosion and nutrient emissions. Aspects of Applied Biology 47: 409–412.

62.

Bruggeman

Masri

Turtelboom

(2005) Strategies to sustain productivity of olive groves on steep slopes in the northwest of the Syrian Arab republic. In: Benites

Pisante

Stagnari

(eds) Integrated Soil and Water Management for Orchard Development; Role and Importance. FAO Land and Water Bulletin 10. Rome: FAO, 75–87.

63.

Bucur

Jitareanu

Ailincai

. (2007) Influence of soil erosion on water, soil, humus and nutrient losses in different crop systems in the Moldavian Plateau, Romania. Journal of Food Agriculture and Environment 5(2): 261–264.

64.

Cammeraat

(1993) MEDALUS Field Manual. Bristol: University of Bristol.

65.

Cammeraat

(2002) A review of two strongly contrasting geomorphological systems within the context of scale. Earth Surface Processes and Landforms 27(11): 1201–1222.

66.

Campo

Andreu

Gimeno-García

. (2006) Occurrence of soil erosion after repeated experimental fires in a Mediterranean environment. Geomorphology 82 (3–4): 376–387.

67.

Caredda

Porqueddu

Sulas

. (1997) Analisi ambientale di sistemi cerealicolo-zootecnici sardi: Aspetti erosivi. Nota I. Agricoltura Ricera 170: 43–50.

68.

Caroni

Tropeano

(1981) Rate of erosion processes on experimental areas in the Marchiazza basin (northwestern Italy). In: Walling

Tacconi

(eds) Erosion and Sediment Transport Measurement (Proceedings of the Florence Symposium, June 1981), Florence, Italy, 22–26 June. IAHS Publication 133. Wallingford: International Association of Hydrological Sciences, 457–466.

69.

Castillo

Gómez Plaza

Martínez-Mena

. (2000) Respuesta hidrológica en medios semiáridos: Las cuencas experimentales de la sierra del Picarcho, Murcia (España). Cuadernos de Investigación Geográfica 26: 81–94.

70.

Castillo

MartinezMena

Albaladejo

(1997) Runoff and soil loss response to vegetation removal in a semiarid environment. Soil Science Society of America Journal 61(4): 1116–1121.

71.

Cerdà

Lasanta

(2005) Long-term erosional responses after fire in the Central Spanish Pyrenees – 1. Water and sediment yield. Catena 60(1): 59–80.

72.

Cerdan

Govers

Le Bissonnais

. (2010) Rates and spatial variations of soil erosion in Europe: A study based on erosion plot data. Geomorphology 122 (1–2): 167–177.

73.

Cerdan

Poesen

Govers

. (2006) Sheet and rill erosion. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 501–513.

74.

Chaker

Laouina

Naciri

. (2001) Runoff and land degradation rates in relation with land use changes in Morocco. A comparison study between three Moroccan regions. Proceedings of EU INCO-MED Water Conference MEDAQUA. Amman, Jordan, 11–13 June, 8.

75.

Chirino

Bonet

Bellot

. (2006) Effects of 30-year-old Aleppo pine plantations on runoff, soil erosion, and plant diversity in a semi-arid landscape in south eastem Spain. Catena 65(1): 19–29.

76.

Chisci

(1989) Measures for runoff and erosion control on clayey soils: A review of trails carried out in the Apennines hilly area. In: Schwertmann

Rickson

Auerswald

(eds) Soil Erosion Protection Measures in Europe. Soil Technology Series No.1. Cremlingen: Catena Verlag, 53–71.

77.

Chisci

Zanchi

(1981) The influence of different tillage systems and different crops on soil losses on hilly silty-clayey soil. In: Morgan

RPC

(ed.) Soil Conservation: Problems and Prospects. Chichester: Wiley, 211–217.

78.

Chomaničová

(1988) Erózne Procesy vo Flysovej Oblasti. Bratislava, Slovakia: VÚPÚ.

79.

Clauzon

Vaudour

(1969) Observations sur les effets de la pluie en Provence. Zeitschrift für Geomorphologie 13: 390–405.

80.

Clauzon

Vaudour

(1971) Ruissellement, transports solides et transports en solution sur un versant aux environs d’Aix-en-Provence. Revue de Géographie Physique et de Géologie Dynamique 13(5): 489–504.

81.

Coelho

COA

(2006) Portugal. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 359–367.

82.

De Baets

Poesen

Gyssels

. (2006) Effects of grass roots on the erodibility of topsoils during concentrated flow. Geomorphology 76 (1–2): 54–67.

83.

de Figueiredo

Gonçalves Ferreira

(1993) Erosão dos solos em vinha de encosta na região do Douro, Portugal. XII Congreso Latinoamericano de la Ciencia del Suelo. Sociedad Española de la Ciencia del Suelo. Salamanca, Spain, 15–25 September, 79–89.

84.

de Figueiredo

Poesen

(1998) Effects of surface rock fragment characteristics on interrill runoff and erosion of a silty loam soil. Soil and Tillage Research 46 (1–2): 81–95.

85.

de Figuiredo

Fonseca

Guerra

. (2004) Erosional response of recently installed forest areas: Effects of site-preparation techniques. Fourth International Conference on Land Degradation (ICLD4). Cartagena, Spain, 12–17 September, 1–4 (CD-ROM).

86.

De Franchi

Linsalata

(1983) Results of a ten-year study on erosion intensity in Wischmeier plots. (In Italian: Un decennio di resultati sull’intensità del processo erosivo in parcelle Wischmeier.). Problemi Agronomici per la Difesa dai Fenomeni Erosivi, Quaderni della Ricerca del CNR n.129. Roma: CNR, 125–145.

87.

de Vente

Poesen

(2005) Predicting soil erosion and sediment yield at the basin scale: Scale issues and semi-quantitative models. Earth-Science Reviews 71 (1–2): 95.

88.

de Vente

Poesen

Arabkhedri

. (2007) The sediment delivery problem revisited. Progress in Physical Geography 31(2): 155–178.

89.

de Vente

Verduyn

Verstraeten

. (2011) Factors controlling sediment yield at the catchment scale in NW Mediterranean geoecosystems. Journal of Soils and Sediments 11(4): 690–707.

90.

Deumlich

Frielinghaus

(1994) Methoden zur Erfassung der Wassererosion auf Ackerschlägen durch natürliche Niederschläge. Wasser und Boden 46(12): 10–13.

91.

Deumlich

Gödicke

(1989) Untersuchungen zu Schwellenwerten erosionsauslösender Niederschläge im Jungmöränengebiet der DDR. Archiv für Acker- Pflanzenbau und Bodenkunde 11: 709–716.

92.

Diamantopoulos

Pantis

Sgardelis

. (1996) The Petralona and Hortiatis Field Sites (Thessaloniki, Greece). In: Brandt

Thornes

(eds) Mediterranean Desertification and Land Use. Chichester: Wiley, 229–245.

93.

Dikau

(1983) Der Einfluss von Niederschlag, Vegetationsbedeckung und hanglänge auf Oberflächenabfluss und Bodenabtrag von Messparzellen. Geomethodica 8: 149–177.

94.

Dikau

(1986) Experimentelle Untersuchungen zu Oberflächenabfluß und Bodenabtrag von Messparzellen und landwirtschaftlichen Nutzflächen. Heidelberger Geographische Arbeiten 81: 195.

95.

Dimitrakopoulos

Seilopoulos

(2002) Effects of rainfall and burning intensity on early post-fire soil erosion in a Mediterranean forest of Greece. In: Rubio

Morgan

RPC

Asins

. (eds) Proceedings of the Third International Congress Man and Soil at the Third Millennium. Valencia, 28 March–1 April. Logroño: Geoforma Ediciones, 1351–1357.

96.

Djorović

(1990) Experimental-study of erosion and crop production on bench terraces on sloping land. In: Boardman

Foster

IDL

Dearing

(eds) Soil Erosion on Agricultural Land. Chichester: Wiley, 531–536.

97.

Dubber

(1968) Untersuchungen über den Bodenabtrag auf Tonmergel-und Kalksteinverwitterungsböden der Schwäbischen Alb und ihres Vorlandes. Zeitschrift für Kulturtechnik und Flurbereinigung 9: 85–101.

98.

Durán Zuazo

Martínez

JRF

Raya

(2004) Impact of vegetative cover on runoff and soil erosion at hillslope scale in Lanjaron, Spain. The Environmentalist 24(1): 39–48.

99.

Durán Zuazo

Rodríguez Pleguezuelo

Francia Martínez

. (2008) Harvest intensity of aromatic shrubs vs. soil erosion: An equilibrium for sustainable agriculture (SE Spain). Catena 73(1): 107–116.

100.

Edwards

Owens

(1991) Large storm effects on total soil erosion. Journal of Soil and Water Conservation 46(1): 75–78.

101.

Emde

(1992) Experimentelle Untersuchungen zu Oberflächenabfluß und Bodenaustrag in Verbindung mit Starkregen bei verschiedenen Bewirtschaftungssystemen in Weinbergsarealen des oberen Rheingaus. Geisenheimer Berichte 12.

102.

Emde

Friedrich

Löhnertz

(2005) Weinbergsböden und Bodenschutz in den Weinbaugebieten Rheingau und Mittelrhein. Mitteilungen Deutsche Bodenkundliche Gesellschaft 105: 115–122.

103.

Ene

(1987) Studii si cercetari privind valorificarea terenurilor in panta, prin rotatia culturilor si ingrasaminte, in zona de curbura a Subcarpatilor. PhD thesis, Romanian Academy of Agricultural and Forestry Sciences.

104.

Engels

(2009) Einfluss von Rodung auf die Erosions- und Oberflächenabflussdynamik eines Steillagen-Weinbergs. PhD thesis, Fachbereich VI Geographie/Geowissenschaften – Physische Geographie, Universität Trier, Germany.

105.

Evans

(1995) Some methods of directly assessing water erosion of cultivated land – a comparison of measurements made on plots and in fields. Progress in Physical Geography 19(1): 115–129.

106.

Evans

(2002) An alternative way to assess water erosion of cultivated land – field-based measurements and analysis of some results. Applied Geography 22(2): 187–208.

107.

Feiza

Feiziene

Jankauskas

. (2007) Soil use and management impact on surface runoff and SOM/SOC content on hilly landscape of lithuania. Off-site Impacts of Soil Erosion and Sediment Transport. Proceedings of the COST 634 – Erosion International Conference. Prague, 1–3 October, 55–72.

108.

Felix

Johannes

(1993) Untersuchung der Beziehung zwischen Niederschlag, Oberflächenabfluß und Bodenerosion auf unterschiedlich genutzten Hochgebirgsstandorten. Forschungsbericht Nationalpark Berchtesgaden. Nationalparkverwaltung, Berchtesgaden, Germany.

109.

Fiener

Auerswald

(2003) Effectiveness of grassed waterways in reducing runoff and sediment delivery from agricultural watersheds. Journal of Environmental Quality 32(3): 927–936.

110.

Fleige

Horn

(2000) Field experiments on the effect of soil compaction on soil properties, runoff, interflow and erosion. Advances in Geoecology 32: 258–268.

111.

Fleskens

Stroosnijder

(2007) Is soil erosion in olive groves as bad as often claimed? Geoderma 141 (3–4): 260–271.

112.

Francia Martínez

Durán Zuazo

Martínez Raya

(2006) Environmental impact from mountainous olive orchards under different soil-management systems (SE Spain). Science of the Total Environment 358 (1–3): 46–60.

113.

Frielinghaus

(1998) Bodenschutzprobleme in Ostdeutschland. In: Richter

(ed.) Bodenerosion – Analyse und Bilanz eines Umweltproblems. Darmstadt: Wissenschaftliche Buchgesellschaft, 204–221.

114.

Food and Agriculture Organization (FAO) (2006) NewLocClim climate database and interpolation software. Available at: ftp://ext-ftp.fao.org/SD/Reserved/Agromet/New_LocClim.

115.

Fulajtár

Janský

(2001) Soil Erosion and Soil Conservation. (In Slovak: Vodná erózia pôdy a protierózna ochrana.). Bratislava: VÚPOP a PRIFUK.

116.

Fullen

(1992) Erosion rates on bare loamy sand soils in east Shropshire, UK. Soil Use and Management 8: 157–162.

117.

Fullen

(1998) Effects of grass ley set-aside on runoff, erosion and organic matter levels in sandy soils in east Shropshire, UK. Soil and Tillage Research 46 (1–2): 41–49.

118.

Fullen

Booth

(2006) Grass ley set-aside and soil organic matter dynamics on sandy soils in Shropshire, UK. Earth Surface Processes and Landforms 31(5): 570–578.

119.

Fullen

Brandsma

(1995) Property changes by erosion of loamy sand soils in east Shropshire, UK. Soil Technology 8(1): 1–15.

120.

Fullen

Reed

(1986) Rainfall, runoff and erosion on bare arable soils in east Shropshire, England. Earth Surface Processes and Landforms 11(4): 413–425.

121.

Fullen

Booth

Brandsma

(2006) Long-term effects of grass ley set-aside on erosion rates and soil organic matter on sandy soils in east Shropshire, UK. Soil and Tillage Research 89(1): 122–128.

122.

Gabriëls

(2006) Assessing the Modified Fournier Index and the Precipitation Concentration Index for some European countries. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 675–684.

123.

Gabriëls

Ghekiere

Schiettecatte

. (2003) Assessment of USLE cover-management C-factors for 40 crop rotation systems on arable farms in the Kemmelbeek watershed, Belgium. Soil and Tillage Research 74 (1): 47–53.

124.

Gajdová

Hucko

Kollár

. (1999) Vplyv eróznych procesov v pol’nohospodársky využivanej krajine na kvalitu vody v tokoch. Bratislava: VÚVH.

125.

García-Ruiz

Lana-Renault

Beguería

. (2010) From plot to regional scales: Interactions of slope and catchment hydrological and geomorphic processes in the Spanish Pyrenees. Geomorphology 120 (3–4): 248–257.

126.

García-Ruiz

Lasanta

Ortigosa

. (1995) Sediment yield under different land uses in the Spanish Pyrenees. Mountain Research and Development 15(3): 229–240.

127.

Gil

(1986) The role of land use in the processes of the surface runoff and wash-down on flysch slopes (in Polish). Przeglad Geograficzny Geograficzny 58: 51–65.

128.

Gil

(1999) Circulation of water and washing on flysch slopes under agricultural use in the years 1980–1990 (in Polish). Zeszyty IGiPZ PAN 60: 77.

129.

Gimeno-Garcia

Andreu

Rubio

(2007) Influence of vegetation recovery on water erosion at short and medium-term after experimental fires in a Mediterranean shrubland. Catena 69(2): 150–160.

130.

Gobin

Jones

Kirkby

. (2004) Indicators for pan-European assessment and monitoring of soil erosion by water. Environmental Science and Policy 7(1): 25–38.

131.

Gómez

Giráldez

Vanwalleghem

(2008) Comment on ‘Is soil erosion in olive groves as bad as often claimed?’ by L. Fleskens and L. Stroosnijder. Geoderma 147: 93–95.

132.

Gómez

Guzmán

Giráldez

. (2009) The influence of cover crops and tillage on water and sediment yield, and on nutrient, and organic matter losses in an olive orchard on a sandy loam soil. Soil and Tillage Research 106(1): 137–144.

133.

Gomez

Romero

Giraldez

. (2004) Experimental assessment of runoff and soil erosion in an olive grove on a Vertic soil in southern Spain as affected by soil management. Soil Use and Management 20(4): 426–431.

134.

Gómez Plaza

(2000) Variabilidad espacio-temporal del contenido de humedad del suelo en una zona Mediterránea semiárida. Efectos de las condiciones antecedentes en la respuesta hidrológica. PhD thesis, Escuela Técnica Superior de Ingenieros de Montes, Departamento de Proyectos y Planificación Rural, Universidad Politécnica de Madrid, Spain.

135.

González-Hidalgo

Peña-Monné

de Luis

(2007) A review of daily soil erosion in western Mediterranean areas. Catena 71(2): 193–199.

136.

González-Pelayo

Andreu

Gimeno-García

. (2010) Rainfall influence on plot-scale runoff and soil loss from repeated burning in a Mediterranean-shrub ecosystem, Valencia, Spain. Geomorphology 118 (3–4): 444–452.

137.

Govers

Poesen

(1988) Assessment of the interrill and rill contributions to total soil loss from an upland field plot. Geomorphology 1(4): 343–354.

138.

Grazhdani

(2006) Albania. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 263–270.

139.

Grazhdani

Jacquin

Sulce

(1996) Effect of subsurface drainage on nutrient pollution of surface waters in south eastern Albania. Science of the Total Environment 191 (1–2): 15–21.

140.

Grazhdani

Sulejman

Dhima

(1999) Conserving farming effect on soil and nutrient erosion in agricultural land of mountainous terrain. Journal of Natural and Technical Sciences 6: 23–32.

141.

Grønsten

Lundekvam

(2006) Prediction of surface runoff and soil loss in southeastern Norway using the WEPP Hillslope model. Soil and Tillage Research 85 (1–2): 186–199.

142.

Guerra

Arbelo

Armas

. (2004) Water erosion rates and mechanisms in andosols and volcanic aridisols in two contrasting bioclimatic regions (Canary Islands, Spain). ISCO 2004 – 13th International Soil Conservation Organization Conference. Conserving Soil and Water for Society: Sharing Solutions. Brisbane, 4–8 July, 1–4 (CD-ROM).

143.

Heusch

(1970) L’érosion hydraulique au Maroc: Son calcul et son controle. Al Awamia 36: 39–63.

144.

Horvat

Zemljic

(1998) Protierozijska vloga gorskega gozda (Mountain forest as a countererosion factor). Gorski Gozd (Mountain Forest) – Conference Proceedings of the 19th Forestry Days. Logarska Dolina, Slovenia, 26–27 March. Ljubljana: Biotechnical Faculty, University of Ljubljana – Department of Forestry and Renewable Forest Resources, 411–424.

145.

Hrvatin

Komac

Perko

. (2006) Slovenia. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 297–310.

146.

Hudek

Rey

(2009) Studying the effects of Mahonia aquifolium populations on small-scale mountain agro-ecosystems in Hungary with the view to minimise land degradation. Land Degradation and Development 20(3): 252–260.

147.

Hudson

(1993) Field Measurement of Soil Erosion and Runoff. FAO Soils Bulletin 68. Rome: FAO.

148.

Inbar

Tamir

Wittenberg

(1998) Runoff and erosion processes after a forest fire in Mount Carmel, a Mediterranean area. Geomorphology 24(1): 17–33.

149.

Inbar

Wittenberg

Tamir

(1997) Soil erosion and forestry management after wildfire in a Mediterranean woodland, Mt. Carmel, Israel. International Journal of Wildland Fire 7(4): 285–294.

150.

Ingelmo

Ibáñez

Pomares

. (1998) Measures for soil protection in citrus orchards and in abandoned fields in the community of Valencia (Spain). In: Rodríguez Rodríguez

Jiménez Mendoza

Tejedor Salguero

(eds) The Soil as a Strategic Resource: Degradation Processes and Conservation Measures. Logroño: Geoforma Ediciones, 431–439.

151.

Ionita

(2000) Geomorfologie Aplicata. Procese de Degradare a Terenurilor Deluroase. Iasi: Editura Universitatii ‘Al. I.Cuza’.

152.

Ionita

Radoane

Mircea

(2006) Romania. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 155–166.

153.

Jankauskas

Fullen

(2002) A pedological investigation of soil erosion severity on undulating land in Lithuania. Canadian Journal of Soil Science 82(3): 311–321.

154.

Jankauskas

Fullen

(2006) Lithuania. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 57–65.

155.

Jankauskas

Jankauskiene

(2003a) Erosion-preventive crop rotations for landscape ecological stability in upland regions of Lithuania. Agriculture Ecosystems and Environment 95(1): 129–142.

156.

Jankauskas

Jankauskiene

(2003b) Long-term soil erosion studies on the Žemaiciai upland: 2. Intensity of water erosion. Žemdirbyste. Mokslo Darbai 82: 20–34.

157.

Jankauskas

Jankauskiene

Fullen

(2004) Erosion-preventive crop rotations and water erosion rates on undulating slopes in Lithuania. Canadian Journal of Soil Science 84(2): 177–186.

158.

Jankauskas

Jankauskiene

Fullen

(2007) Soil erosion and changes in the physical properties of Lithuanian Eutric Albeluvisols under different land use systems. Acta Agricultura Scandinavica, Section B – Soil and Plant Science 58(1): 66–76.

159.

Jankauskas

Jankauskiene

Fullen

. (2008) Utilizing palm-leaf geotextiles to control soil erosion on roadside slopes in Lithuania. Žemes Ukio Mokslai 15(3): 22–28.

160.

Jetten

and Favis-Mortlock

(2006) Modelling soil erosion in Europe. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 695–716.

161.

Jovanovski

Blinkov

Micevski

. (1999) Influence of soil, land cover, rainfall intensity and slopes on the erosion intensity in central and eastern Macedonia – scientific project supported by the Ministry of Science of the republic of Macedonia, final report. Skopje, Republic of Macedonia.

162.

Jung

Brechtel

(1980) Messung von Oberflächenabfluß und Bodenabtrag auf verschiedenen Böden der BRD. Hamburg: Parey.

163.

Kaabia

(1995) Effets de quelques systèmes de culture sur l’érosion hydrique, le ruissellement et la fertilité du sol dans le semi-aride Tunisien. Bulletin du Réseau Erosion 15: 382–392.

164.

Kara

Sensoy

Bolat

(2010) Slope length effects on microbial biomass and activity of eroded sediments. Journal of Soils and Sediments 10(3): 434–439.

165.

Kertész

Centeri

(2006) Hungary. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 139–153.

166.

Kertész

Huszár-Gergely

(2004) The effect of soil physical parameters on soil erosion. Foldrajzi Ertesito LIII (1–2): 77–84.

167.

Kertesz

Toth

Szalai

(2007) The role of geotextiles in soil erosion and runoff control. Off-site Impacts of Soil Erosion and Sediment Transport. Proceedings of the COST 634 – Erosion International Conference. Prague, 1–3 October, 45–53.

168.

Kinnell

PIA

Risse

(1998) USLE-M: Empirical modeling rainfall erosion through runoff and sediment concentration. Soil Science Society of America Journal 62(6): 1667–1672.

169.

Kirkby

Jones

RJA

Irvine

. (2004) Pan-European soil erosion risk assessment: The PESERA Map, Version 1 October 2003. Explanation of Special Publication Ispra 2004 No.73 (S.P.I.04.73). European Soil Bureau Research Report No.16, EUR21176. Luxembourg: Office for Official Publications of the European Communities.

170.

Kleeberg

Schapp

Biemelt

(2008) Phosphorus and iron erosion from non-vegetated sites in a post-mining landscape, Lusatia, Germany: Impact on aborning mining lakes. Catena 72(3): 315–324.

171.

Klik

(2003) The impact of different tillage practices on surface runoff, soil erosion and nutrient and pesticide losses. (In German: Einfluss unterschiedlicher Bodenbearbeitung auf Oberflächenabfluss, Bodenabtrag sowie auf Nährstoff- und Pestizidausträge.) Österreichische Wasser- und Abfallwirtschaft 55 (5–6): 89–96.

172.

Klik

(2010) Agronomische Bodenschutzmaßnahmen und ihre Auswirkungen. Umweltökologisches Symposium. Raumberg-Gumpenstein, Austria, 2–3 March. Lehr- und Forschungszentrum für Landwirtschaft, 17–22.

173.

Köse

Taysun

(2002) Su havzalarinda toprak ve su kaynaklarinin korunmasi, Gelistirilmesi ve yönetimi sempozyumu. In: Önder

(ed.) Türkiye tarim alanlarinda erozyon kontrolü bakimindan seritvari tarim sisteminin etkisi ve önemi. Antakya, Turkey, 18–20 September. Mustafa Kemal University – Faculty of Agriculture, 364–370.

174.

Köse

Yakar

Taysun

(1996) Effect of strip-cropping system on water erosion in Gediz Basin. Toprak ve su Kaynaklari Araştirma Yilliği (Soil and Water Resources Research Yearbook). Köy Hizmetleri Genel Müdürlüğü – Apk Dairesi Başkanligi, 52–68.

175.

Kosmas

Danalatos

Cammeraat

. (1997) The effect of land use on runoff and soil erosion rates under Mediterranean conditions. Catena 29(1): 45–59.

176.

Kosmas

Danalatos

Kosma

. (2006) Greece. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 279–288.

177.

Kosmas

Moustakas

Danalatos

. (1996) The Spata field site: I. The impacts of land use and management on soil properties and erosion. II. The effect of reduced moisture on soil properties and wheat production. In: Brandt

Thornes

(eds) Mediterranean Desertification and Land Use. Chichester: Wiley, 207–228.

178.

Kostadinov

Zlatić

Dragović

. (2006) Serbia and Montenegro. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 271–277.

179.

Koulouri

Giourga

(2007) Land abandonment and slope gradient as key factors of soil erosion in Mediterranean terraced lands. Catena 69(3): 274–281.

180.

Kroumov

Malinov

(1989) Erosion-protection efficiency of naturally regenerating plants on strongly degraded pastures. Soil Science and Agrochemistry 24(5): 75–79.

181.

Kutiel

Inbar

(1993) Fire impacts on soil nutrients and soil erosion in a Mediterranean pine forest plantation. Catena 20 (1–2): 129–139.

182.

Kwaad

FJPM

(1991) Summer and winter regimes of runoff generation and soil erosion on cultivated loess soils (The Netherlands). Earth Surface Processes and Landforms 16(7): 653–662.

183.

Kwaad

FJPM

(1994) Cropping systems of fodder maize to reduce erosion of cultivated loess soils. In: Rickson

(ed.) Conserving Soil Resources, European Perspectives. Wallingford: CAB International, 354–368.

184.

Kwaad

FJPM

de Roo

APJ

Jetten

(2006) The Netherlands. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 413–426

185.

Kwaad

FJPM

van der Zijp

van Dijk

(1998) Soil conservation and maize cropping systems on sloping loess soils in the Netherlands. Soil and Tillage Research 46 (1–2): 13–21.

186.

Laloy

Bielders

(2010) Effect of intercropping period management on runoff and erosion in a maize cropping system. Journal of Environmental Quality 3 9 (3): 1001–1008.

187.

Langbein

Schumm

(1958) Yield of sediment in relation to mean annual precipitation. Transactions of the American Geophysical Union 30(6): 1076–1084.

188.

Laouina

Chaker

Naafa

(2003) Suivi et mesure de l’érosion hydrique des terres au Marco, 15 ans de recherche et d’expérimentation. Revue de Géographie Marocaine 21: 79–98.

189.

Larson

Lindstrom

Schumacher

(1997) The role of severe storms in soil erosion: A problem needing consideration. Journal of Soil and Water Conservation 52(2): 90–95.

190.

Lasanta

Beguería

García-Ruiz

(2006) Geomorphic and hydrological effects of traditional shifting agriculture in a Mediterranean mountain, central Spanish Pyrenees. Mountain Research and Development 26(2): 146–152.

191.

Lavee

Imeson

Sarah

(1998) The impact of climate change on geomorphology and desertification along a Mediterranean-arid transect. Land Degradation and Development 9(5): 407–422.

192.

Le Bissonnais

Lecomte

Cerdan

(2004) Grass strip effects on runoff and soil loss. Agronomie 24(3): 129–136.

193.

Le Gouée

Delahaye

Bermond

. (2010) SCALES: A large-scale assessment model of soil erosion hazard in Basse-Normandie (northern-western France). Earth Surface Processes and Landforms 35(8): 887–901.

194.

Lenthe

Lüken

Krone

(1986) Measurement of soil erosion in Cyprus. Transactions of the XIII Congress of the International Society of Soil Science. Hamburg, 13–20 August. ISSS-AISS-IBG, 1584–1585.

195.

Licciardello

Govers

Cerdan

. (2009) Evaluation of the PESERA model in two contrasting environments. Earth Surface Processes and Landforms 34(5): 629–640.

196.

Lopes

PMS

Cortez

Goulão

JPN

(2002) Rainfall erosion in cambisols from central Portugal. Some statistical differences between wet and dry years. In: Rubio

Morgan

RPC

Asins

. (eds) Proceedings of the Third International Congress Man and Soil at the Third Millennium. Valencia, 28 March–1 April. Logroño: Geoforma Ediciones, 1291–1299.

197.

Lopez-Bermudez

Romero-Díaz

Martinez-Fernandez

(1991) Soil erosion in a semi-arid Mediterranean environment. El Ardal experimental field (Murcia, Spain). In: Sala

Rubio

García-Ruiz

(eds) Soil Erosion Studies in Spain. Logroño: Geoforma Ediciones, 137–152.

198.

Lundekvam

(2007) Plot studies and modelling of hydrology and erosion in southeast Norway. Catena 71(2): 200–209.

199.

Maetens

Poesen

Vanmaercke

(2011) Inter-annual variation of runoff and soil loss in Europe and the Mediterranean in relation to land use and climate. EGU General Assembly 2011 . Geophysical Research Abstracts 13. EGU2011-2285. Vienna, 3–8 April, 1.

200.

Martin

(1990) Relations entre les pertes de terre mensuelles et les conditions climatiques sur une parcelle défrichée du massif de Maures, France. In: Molnár

(ed.) Hydrology in Mountainous Regions II – Artificial Reservoirs; Water and Slopes (Proceedings of the two Lausanne Symposia, August 1990). IAHS Publication 194. Lausanne, Switzerland, 27 August–1 September. Wallingford: International Association of Hydrological Sciences, 253–258.

201.

Martin

Allée

Béguin

. (1997) Mésure de l’érosion mécanique des sols après un incendie de forêt dans le massif des Maures. Géomorphologie: Relief, Processus, Environnement 2: 133–142.

202.

Martínez-Casasnovas

Ramos

Ribes-Dasi

(2002) Soil erosion caused by extreme rainfall events: Mapping and quantification in agricultural plots from very detailed digital elevation models. Geoderma 105 (1–2): 125–140.

203.

Martinez-Mena

Castillo

Albaladejo

(2001) Hydrological and erosional response to natural rainfall in a semi-arid area of south-east Spain. Hydrological Processes 15(4): 557–571.

204.

Martinez-Mena

Rogel

Albaladejo

. (1999) Influence of vegetal cover on sediment particle size distribution in natural rainfall conditions in a semiarid environment. Catena 38(3): 175–190.

205.

Martínez-Murillo

Ruiz-Sinoga

(2007) Seasonal changes in the hydrological and erosional response of a hillslope under dry-Mediterranean climatic conditions (Montes de Málaga, South of Spain). Geomorphology 88 (1–2): 69–83.

206.

Martinez Raya

Durán Zuazo

Francia Martinez

(2006) Soil erosion and runoff response to plant-cover strips on semiarid slopes (SE Spain). Land Degradation and Development 17(1): 1–11.

207.

Marxer

(2003) Oberflächenabfluss und Bodenerosion auf Brandflächen des Kastanienwaldgürtels der Südschweiz mit einer Anleitung zur Bewertung der post-fire Erosionsanfälligkeit (BA EroKaBr). Physiogeographica – Basler Beiträge zur Physiogeographie 33.

208.

Masri

El-Naeb

Zöbisch

. (2005) Land management strategies to sustain productivity of olive groves on steep slopes in northwest Syria. In: Benites

Pisante

Stagnari

(eds) Integrated Soil and Water Management for Orchard Development; Role and Importance. FAO Land and Water Bulletin 10. Rome: FAO, 75–91.

209.

Mazour

(1992) Les facteurs de risque de l’érosion en nappe dans le bassin versant D’Isser, Tlemcen Algerie. Bulletin du Réseau Erosion 12: 300–313.

210.

Mazour

Boughalem

Mededjel

(2008) La gestion de la matière organique et ses effets sur la conservation de la fertilité du sol dans le nord-ouest de l’algérie. In: Roose

Albergel

De Noni

. (eds) Efficacité de la Gestion de l’Eau et de la Fertilité des Sols en Milieux Semi-arides. Paris: AUF, EAC et IRD éditeurs, 175–181.

211.

Mehta

Yang

(2008) Precipitation climatology over Mediterranean Basin from ten years of TRMM measurements. Advances in Geosciences 17: 87–91.

212.

Merritt

Letcher

Jakeman

(2003) A review of erosion and sediment transport models. Environmental Modelling and Software 18 (8–9): 761–799.

213.

Messer

(1980) Soil erosion measurements on experimental plots in Alsace vineyards (France). In: De Boodt

Gabriëls

(eds) Assessment of Erosion. Chichester: Wiley, 455–462.

214.

Metzger

Bunce

RGH

Jongman

RHG

. (2005) A climatic stratification of the environment of Europe. Global Ecology and Biogeography 14(6): 549–563.

215.

Mitchell

Barton

Fullen

. (2003) Field studies of the effects of jute geotextiles on runoff and erosion in Shropshire, UK. Soil Use and Management 19(2): 182–184.

216.

Mohammad

Adam

(2010) The impact of vegetative cover type on runoff and soil erosion under different land uses. Catena 81(2): 97–103.

217.

Montgomery

(2007) Soil erosion and agricultural sustainability. Proceedings of the National Academy of Sciences of the United States of America 104(33): 13268–13272.

218.

Morgan

RPC

Duzant

(2008) Modified MMF (Morgan-Morgan-Finney) model for evaluating effects of crops and vegetation cover on soil erosion. Earth Surface Processes and Landforms 33(1): 90–106.

219.

Morsli

Mazour

Mededjel

. (2004) Influence de l’utilisation des terres sur les risques de ruissellement et d’érosion sur les versants semi-arides du nord-ouest de l’Algérie. Science et Changements Planétaires/Sécheresse 15: 96–104.

220.

Motoc

Ionita

Nistor

(1998) Erosion and climatic risk at the wheat and maize crops in the Moldavian Plateau. Romanian Journal of Hydrology and Water Resources 5: 1–38.

221.

Moufaddal

(2002) Les premiers résultats des parcelles de mesure des pertes en terre dans le bassin-versant de oued Nakhla dans le Rif occidental. Bulletin du Réseau Erosion 21: 244–254.

222.

Mücher

Klijn

Wascher

. (2010) A new European Landscape Classification (LANMAP): A transparent, flexible and user-oriented methodology to distinguish landscapes. Ecological Indicators 10(1): 87–103.

223.

Nearing

(1997) A single, continuous function for slope steepness influence on soil loss. Soil Science Society of America Journal 61(3): 917–919.

224.

New

Lister

Hulme

. (2002) A high-resolution data set of surface climate over global land areas. Climate Research 21(1): 1–25.

225.

Nistor

Ionita

(2002) Development of soil erosion control in Romania. In: Rubio

Morgan

RPC

Asins

. (eds) Proceedings of the Third International Congress Man and Soil at the Third Millennium. Valencia, Spain, 28 March–1 April. Logroño: Geoforma Ediciones, 299–309.

226.

Nunes

Coelho

(2007) Land use change in inland of Portugal: Implications on overland flow and erosion rates. Off-site Impacts of Soil Erosion and Sediment Transport. Proceedings of the COST 634 – Erosion International Conference. Prague, 1–3 October, 124–139.

227.

Oguz

Cebel

Özden

. (2006) Türkiye Üniversal Denklem Toprak Kaybi Esitligi Rehberi. Report No. TAGEM – BB – TOPRAKSU 2006/01. Soil and Water Resources Research Institute of Tokat, Turkey.

228.

Oldeman

Hakkeling

RTA

Sombroek

(1991) World map of the status of human-induced soil degradation. An explanatory note. Global Assessment of Soil Degradation - GLASOD. International Soil Reference and Information Centre (ISRIC) – United Nations Environment Programme (UNEP).

229.

Ollesch

Vacca

(2002) Influence of time on measurement results of erosion plot studies. Soil and Tillage Research 67(1): 23–39.

230.

Øygarden

(1996) Erosion and surface runoff in small agricultural catchments. In: Walling

Webb

(eds) Erosion and Sediment Yield: Global and Regional Perspectives (Proceedings of the Exeter Symposium July 1996). IAHS Publication 236. Exeter, 15–19 July. Wallingford: International Association of Hydrological Sciences, 283–291.

231.

Øygarden

Kvaerner

Jenssen

(1997) Soil erosion via preferential flow to drainage systems in clay soils. Geoderma 76 (1–2): 65–86.

232.

Øygarden

Lundekvam

Arnoldussen

. (2006) Norway. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 1–15.

233.

Özhan

Balci

Ozyuvaci

. (2005) Cover and management factors for the Universal Soil-Loss equation for forest ecosystems in the Marmara region, Turkey. Forest Ecology And Management 214 (1–3): 118–123.

234.

Pinczés

(1982) Variations in runoff and erosion under various methods of protection. Hydrological Sciences Journal – Journal des Sciences Hydrologiques 27(2): 232–232.

235.

Poesen

(1984) The influence of slope angle on infiltration rate and Hortonian overland flow volume. Zeitschrift für Geomorphologie, Supplement Band 49: 117–131.

236.

Poesen

(1986) Surface sealing as influenced by slope angle and position of simulated stones in the top layer of loose sediments. Earth Surface Processes and Landforms 11(1): 1–10.

237.

Poesen

van Wesemael

Bunte

, (1998) Variation of rock fragment cover and size along semiarid hillslopes: a case-study from southeast Spain. Geomorphology 23(24): 323–335.

238.

Poesen

Bryan

(1989) Influence de la longueur de pente sur le ruissellement: Rôle de la formation de rigoles et de croûtes de sédimentation. Cahiers ORSTOM, Séries Pedologie XXV (1–2): 71–80.

239.

Poesen

Hooke

(1997) Erosion, flooding and channel management in Mediterranean environments of southern Europe. Progress in Physical Geography 21(2): 157–199.

240.

Poesen

Lavee

(1994) Rock fragments in top soils – significance and processes. Catena 23 (1–2): 1–28.

241.

Poesen

Torri

Bunte

(1994) Effects of rock fragments on soil erosion by water at different spatial scales: A review. Catena 23 (1–2): 141–166.

242.

Poesen

Vanwalleghem

de Vente

. (2006) Gully erosion in Europe. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 515–536.

243.

Ponce

Hawkins

(1996) Runoff curve number: Has it reached maturity? Journal of Hydraulic Engineering 1(1): 11–19.

244.

Porqueddu

Roggero

(1994) Effetto delle tecniche agronomiche di intensificazione foraggera sui fenomeni erosivi dei terreni in pendio in ambiente mediterraneo. Rivista di Agronomia 28: 364–370.

245.

Postiglione

Basso

Amato

. (1990) Effects of soil tillage methods on soil losses, on soil characteristics and on crop production in a hilly area of southern Italy. Agricoltura Mediterranea 120: 148–158.

246.

Prosser

Rustomji

(2000) Sediment transport capacity relations for overland flow. Progress in Physical Geography 24(2): 179-193.

247.

Puigdefábregas

Alonso

Delgado

. (1996) The Rambla Honda field site: Interactions of soil and vegetation along a catena in semi-arid southeast Spain. In: Brandt

Thornes

(eds) Mediterranean Desertification and Land Use. Chichester: Wiley, 137–168.

248.

Puustinen

Koskiaho

Peltonen

(2005) Influence of cultivation methods on suspended solids and phosphorus concentrations in surface runoff on clayey sloped fields in boreal climate. Agriculture Ecosystems and Environment 105(4): 565–579.

249.

Puustinen

Tattari

Koskiaho

. (2007) Influence of seasonal and annual hydrological variations on erosion and phosphorus transport from arable areas in Finland. Soil and Tillage Research 93(1): 44–55.

250.

Quinton

(1994) The validation of physically based erosion models – with particular reference to EUROSEM. PhD thesis, Silsoe College, Cranfield University, UK.

251.

Quinton

Catt

(2004) The effects of minimal tillage and contour cultivation on surface runoff, soil loss and crop yield in the long-term Woburn Erosion Reference Experiment on sandy soil at Woburn, England. Soil Use and Management 20(3): 343–349.

252.

Rejman

Rodzik

(2006) Poland. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 95–106.

253.

Rejman

Turski

Paluszek

(1998) Spatial and temporal variations in erodibility of loess soil. Soil and Tillage Research 46 (1–2): 61–68.

254.

Renard

Foster

Weesies

. (1997) Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture Handbook No. 703. Washington, DC: US Department of Agriculture, Agricultural Research Service.

255.

Richter

(1980) Three years of plot measurements in vineyards of the Moselle-Region – some preliminary results. Zeitschrift für Geomorphologie, N.F. Supplement Band 35: 81–95.

256.

Richter

(1985) Soil erosion research in the region of Trier, some experiments and experiences. International Workshop on Soil Erosion and Hillslope Hydrology with Emphasis on High Magnitude Events. Leuven, Belgium, 27–30 March. KU Leuven, Department of Geography.

257.

Richter

(1987) Investigation of soil erosion in central Europe. Seesoil 3: 14–27.

258.

Richter

(1991) The soil erosion measurement station and its program. Forschungsstelle Bodenerosion 10: 97–108.

259.

Richter

Kertesz

(1987) Seasonal variations of runoff rates from field plots in the Federal Republic of Germany and in Hungary during dry years. In: Walling

Yair

Berkowicz

(eds) Erosion, Transport and Deposition Processes (Proceedings of the Jerusalem Workshop, March–April 1987). IAHS Publication 189. Jerusalem, March–April. Wallingford: International Association of Hydrological Sciences, 161–168.

260.

Rivoira

Roggero

Bullitta

(1989) Influenza delle tecniche di miglioramento dei pascoli sui fenomeni erosivi dei terreni in pendio. Rivista di Agronomia 23: 372–377.

261.

Rockström

Karlberg

Wani

. (2010) Managing water in rainfed agriculture – the need for a paradigm shift. Agricultural Water Management 97(4): 543–550.

262.

Rodríguez Rodríguez

Arbelo

Sánchez

(2006) Spain: Canary Islands. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 347–357.

263.

Rodríguez Rodríguez

Guerra

Gorrín

. (2002) Aggregates stability and water erosion in andosols of the Canary Islands. Land Degradation and Development 13(6): 515–523.

264.

Romero-Díaz

Belmonte Serrato

(2008) Erosíon en Forestaciones Aterrazadas en Medios Semiáridos: Región de Murcia. Murcia: Universidad de Murcia.

265.

Romero-Díaz

Cammeraat

Vacca

. (1999) Soil erosion at three experimental sites in the Mediterranean. Earth Surface Processes and Landforms 24(13): 1243–1256.

266.

Rossi Pisa

Preti

Rossi

. (1999) Water, soil and chemical losses: Field experiments and model analysis. Water Science and Technology 39(3): 93–102.

267.

Rousseva

Lazarov

Tsvetkova

. (2006) Bulgaria. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 167–181.

268.

Roxo

Cortesao Casimiro

Soeiro de Brito

(1996) Inner lower Alentejo Field site: Cereal cropping, soil degradation and desertification. In: Brandt

Thornes

(eds) Mediterranean Desertification and Land Use. Chichester: Wiley, 112–228.

269.

Rubio

Forteza

Andreu

. (1997) Soil profile characteristics influencing runoff and soil erosion after forest fire: A case study (Valencia, Spain). Soil Technology 11(1): 67–78.

270.

Sanchez

Mangas

Ortiz

. (1994) Forest fire effect on soil chemical properties and runoff. In: Sala

Rubio

(eds) Soil Erosion and Degradation as a Consequence of Forest Fires. Logroño: Geoforma Ediciones, 53–65.

271.

Sanchis

MPS

Torri

Borselli

. (2008) Climate effects on soil erodibility. Earth Surface Processes and Landforms 33(7): 1082–1097.

272.

Saupe

(1990) Winterweizen – unterschätzte Erosionsgefahren? Feldwirtschaft 31: 367–368.

273.

Saupe

(1992) Wirkung von Konturgrasstreifen zur Erosionsbekämpfung unter Praxisbedingungen. Zeitschrift für Kulturtechnik und Flurbereinigung 33: 150–162.

274.

Schaub

(1998) Gebietsbilanzen von Bodenerosion und der damit verbundenen Stoffumlagerungen. Habilitationsschrift, Universität Basel, Switzerland.

275.

Schjønning

Sibbesen

Hansen

. (1995) Erosion plot studies 1989–92: Fit of a simple model to surface runoff from agricultural land. In: Kronvang

Svendsen

Sibbesen

(eds) Sediment and Phosphorus. Erosion and Delivery, Transport and Fate of Sediments and Sediment-associated Nutrients in Watersheds. Proceedings from an International Workshop held in Silkeborg, Denmark. NERI Technical Report 178. Silkeborg, Denmark, 9–12 October. Ministry of Environment and Energy – Natural Environment Research Institute, 51–52.

276.

Schnabel

González

Murillo

. (2001) Different techniques of pasture improvement and soil erosion in a wooded rangeland in SW Spain; Methodology and preliminary results. In: Conacher

(ed.) Land Degradation. Dordrecht: Kluwer, 239–253.

277.

Sekularac

Stojiljkovic

(2007) Annual runoff and erosion losses of humus-silicate soil from two specific uses due to precipitation in one part of western Serbia. Polish Journal of Environmental Studies 16: 433–440.

278.

Shakesby

(2011) Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth-Science Reviews 105 (3–4): 71–100.

279.

Shakesby

Coelho

Ferreira

. (1994) Fire, post-burn land management practice and soil erosion response curves in Eucaluptus and pine forests, north-central Portugal. In: Sala

Rubio

(eds) Soil Erosion and Degradation as a Consequence of Forest Fires. Logroño: Geoforma Ediciones, 111–132.

280.

Shinjo

Fujita

Gintzbuger

. (2000) Impact of grazing and tillage on water erosion in northeastern Syria. Soil Science and Plant Nutrition 46(1): 151–162.

281.

Skrodzki

(1972) Present-day water and wind erosion of soils in NE Poland. Geographia Polonica 23: 77–92.

282.

Solé Benet

(2006) Spain. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 311–346.

283.

Soler

Sala

Gallart

(1994) Post fire evolution of runoff and erosion during an eighteen month period. In: Sala

Rubio

(eds) Soil Erosion and Degradation as a Consequence of Forest Fires. Logroño: Geoforma Ediciones, 149–191.

284.

Soto

Díaz-Fierros

(1998) Runoff and soil erosion from areas of burnt scrub: Comparison of experimental results with those predicted by the WEPP model. Catena 31(4): 257–270.

285.

Stankoviansky

Fulajtár

Jambor

(2006) Slovakia. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 117–138.

286.

Stasik

Szafranski

(2001) An attempt to apply the USLE model for predicting intensity of water erosion of soils in the area of Gniezno Lakeland (in Polish). Folia Univesitatis Agriculturae Stetinensis 217: 213–216.

287.

Strauss

Klaghofer

(2006) Austria. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 205–212.

288.

Suchanic

(1987) Assessment of erosion processes and proposed soil conservation measures in period 1986–7. (In Slovak: Zhodnotenie eroznych procesov a navrhnutych protieroznych opatreni v rokoch 1986–7.) Research Report. SSCRI, Bratislava, Slovakia.

289.

Szpikowski

(1998) Magnitude and mechanics of water erosion of cultivated soils on moraine slopes (Chwalimski brook catchment, West Pomerania) (in Polish). Bibliotheca Fragmenta Agronomica 4B: 113–124.

290.

Tattari

Rekolainen

(2006) Finland. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 27–32.

291.

Teodorescu

Badescu

(1988) Cercetari privind eroziunea in suprafata in plantatiile pomicole intensive. Analele I.C.P.A. 49: 225–234.

292.

Tijms

(2004) Understanding Probability: Chance Rules in Everyday Life. Cambridge: Cambridge University Press.

293.

Torri

Borselli

Guzzetti

. (2006) Italy. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 245–261.

294.

Torri

Poesen

Borselli

(1997) Predictability and uncertainty of the soil erodibility factor using a global dataset. Catena 31 (1–2): 1–22.

295.

Tropeano

(1984) Rate of soil-erosion processes on vineyards in central Piedmont (NW Italy). Earth Surface Processes and Landforms 9(3): 253–266.

296.

Tsara

Kosmas

Kirkby

. (2005) An evaluation of the pesera soil erosion model and its application to a case study in Zakynthos, Greece. Soil Use and Management 21(4): 377–385.

297.

Turtola

Paajanen

(1995) Influence of improved subsurface drainage on phosphorus losses and nitrogen leaching from a heavy clay soil. Agricultural Water Management 28(4): 295–310.

298.

Turtola

Alakukku

Uusitalo

. (2007) Surface runoff, subsurface drainflow and soil erosion as affected by tillage in a clayey Finnish soil. Agricultural and Food Science 16(4): 332–351.

299.

Ulén

(1997) Nutrient losses by surface run-off from soils with winter cover crops and spring-ploughed soils in the south of Sweden. Soil and Tillage Research 44 (3–4): 165–177.

300.

Ulén

(2006) Sweden. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 17–25.

301.

Ulén

Kalisky

(2005) Water erosion and phosphorus problems in an agricultural catchment – need for natural research for implementation of the EU Water Framework Directive. Environmental Science and Policy 8(5): 477–484.

302.

Uusi-Kämppä

(2005) Phosphorus purification in buffer zones in cold climates. Ecological Engineering 24(5): 491–502.

303.

Vacca

Loddo

Ollesch

. (2000) Measurement of runoff and soil erosion in three areas under different land use in Sardinia (Italy). Catena 40(1): 69–92.

304.

Vanmaercke

Maetens

Poesen

. (2012) A regional comparison of hillslope erosion rates with catchment sediment yields in Europe. Journal of Soils and Sediments 12(4): 586–602.

305.

Vanmaercke

Poesen

Maetens

. (2011a) Sediment yield as a desertification risk indicator. Science of The Total Environment 409(9): 1715–1725.

306.

Vanmaercke

Poesen

Verstraeten

. (2011b) Sediment yield in Europe: Spatial patterns and scale dependency. Geomorphology 130 (3–4): 142–161.

307.

Veihe

Hasholt

(2006) Denmark. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 33–42.

308.

Verstraeten

Poesen

Goossens

. (2006) Belgium. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 385–411.

309.

Viguier

(1993) Mesure et modélisation de l’érosion pluviale. Application au vignoble de Vidauban (Var). PhD thesis, Faculté des Sciences de Luminy, Université d’Aix-Marseille, France.

310.

Voss

(1978) Ermittlung der Nährstoffumlagerung durch Erosion und Charakterisierung der Erosionsfracht einiger Vorfluter in hessischen Mittelgebirgs-Kleinlandschaften. Diss. thesis, University Gießen, Germany.

311.

Wade

Kirkbride

(1998) Snowmelt-generated runoff and soil erosion in Fife, Scotland. Earth Surface Processes and Landforms 23(2): 123–132.

312.

Wainwright

Thornes

(2004) Environmental Issues in the Mediterranean: Processes and Perspectives from the Past and Present. London: Routledge.

313.

Wallace

(2000) Increasing agricultural water use efficiency to meet future food production. Agriculture, Ecosystems and Environment 82 (1–3): 105–119.

314.

Warsta

Paasonen-Kivekäs

Karvonen T

. (2009) Modelling surface and subsurface flow of water and erosion at clayey, subsurface drained agricultural field. In: Anderssen

Braddock

Newham

LTH

(eds) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation. Cairns, Australia, 13–17 July, 1901–1907.

315.

Weiß

Menzel

(2008) A global comparison of four potential evapotranspiration equations and their relevance to stream flow modelling in semi-arid environments. Advances in Geosciences 18: 15–23.

316.

Weisshaidinger

Leser

(2006) Switzerland. In: Boardman

Poesen

(eds) Soil Erosion in Europe. Chichester: Wiley, 231–244.

317.

Wicherek

(1986) Ruissellement, érosion sur les versants de la France des plaines et des collines. Exemple Cessières (02 Aisne, France). Hommes et Terres du Nord 4: 254–261.

318.

Wicherek

(1988) Les relations entre le couvert végétal et l’érosion en climat tempéré de plaines. Ex: Cessières (Aisne, France). Zeitschrift für Geomorphologie 32: 339–350.

319.

Wicherek

(1991) Viticulture and soil erosion in the north of Parisian Basin. Example: the mid Aisne region. Zeitschrift für Geomorphologie 83: 115–126.

320.

Williams

Ternan

Elmes

. (1995) A field study of the influence of land management and soil properties on runoff and soil loss in central Spain. Environmental Monitoring and Assessment 37(1): 333–345.

321.

Wischmeier

(1966) Relation of field-plot runoff to management and physical factors. Soil Science Society of America Journal 30(2): 272–277.

322.

Wischmeier

Smith

(1958) Rainfall energy and its relationship to soil loss. Transactions of the American Geophysical Union 39: 285–291.

323.

Wischmeier

Smith

(1960) A universal soil-loss equation to guide conservation farm planning. Transactions of 7th International Congress of Soil Science. Madison, USA. International Society of Soil Science, 418–425.

324.

Wischmeier

Smith

(1978) Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. Agriculture Handbook 537. Washington, DC: US Department of Agriculture, Science and Education Administration.

325.

Yassin

El Bahi

Renard

. (2009) Application du modèle universel de perte en terre révisé (RUSLE) aux terrains forestiers du Plateau Central. Annales de la Recherche Forestière au Maroc 40: 50–64.

326.

Zanchi

(1983) Influenza dell’azione battente della pioggia e del ruscellamento nel processo erosivo e variazioni dell’erodibilità del suolo nei diversi periodi stagionali. Annali Instituto Sperimentale Studio E Difessa Suolo – Firenze XIV: 347–358.

327.

Zanchi

(1988a) The cropping pattern and its role in determining erosion risk: Experimental plot results from the Mugello valley. In: Bordas

Walling

(eds) Sediment Budgets (Proceedings of the Porto Alegre Symposium, December 1988). IAHS Publication 174. Porto Alegre, Brazil, 11–15 December. Wallingford: International Association of Hydrological Sciences, 139–145.

328.

Zanchi

(1988b) Soil loss and seasonal variation of erodibility in two soils with different texture in the Mugello valley in central Italy. Catena Supplement 12: 167–173.