Soil resistance to flowing water erosion of seven typical plant communities on steep gully slopes on the Loess Plateau of China

Catena 173 (2019) 375–383

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Soil resistance to flowing water erosion of seven typical plant communities on steep gully slopes on the Loess Plateau of China

T

⁎

Bao-jun Zhanga, Guang-hui Zhanga,b, , Han-yue Yangb, Hao Wangb a

State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China b Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Soil erosion Rill erodibility Critical shear stress Steep gully slope The Loess Plateau

Steep gully slopes are widespread and have been recognized as the main sediment source on the Loess Plateau. Different vegetation growth may lead to the differences in soil properties and plant roots, and thus likely affects soil resistance to flowing water erosion, reflected by rill erodibility and critical shear stress. However, few studies have been conducted to evaluate this effect on steep gully slopes on the Loess Plateau of China. This study was performed to investigate the effects of vegetation growth on soil resistance to flowing water erosion on steep gully slopes, and quantify the main potential influencing factors on the Loess Plateau. Three typical shrub communities and four typical grass communities that distributed on different gully slopes were selected. 240 undisturbed soil samples were collected from these seven gully slope lands and one slope farmland (control), and were subjected to detachment by overland flow under six different shear stresses (6.64 to 17.85 Pa). The results showed that the mean detachment capacity of slope farmland was 6.9 to 47.8 times greater than those of steep gully slopes covered with different plant communities. The rill erodibilities of steep gully slopes covered with different plant communities reduced greatly by 77.0% to 95.1% compared to the control slope. The critical shear stress of slope farmland (2.72 Pa) was only 57.2% and 39.6% of that of shrubland (4.76 Pa) and grassland (6.88 Pa). Both shrub and grass communities were effective in reducing soil detachment capacity and rill erodibility, and increasing critical shear stress on steep gully slopes. But the effects were more obvious for the grass communities. The differences in rill erodibility between slope farmland and gully slope lands were mainly explained by the changes in root mass density (82.4%). Plant roots had strong direct effects on increasing soil cohesion (0.78), organic matter content (0.56), and water stable aggregation (0.92). Rill erodibility was negatively related to root mass density as an exponential function (p < 0.05), and soil cohesion and water stable aggregation as power functions (p < 0.05). Critical shear stress was positively related to root mass density and soil water stable aggregation following a logarithmic function.

1. Introduction Soil erosion includes three sub-processes of soil detachment, sediment transport, and deposition (Nearing et al., 1989). Soil detachment is the dislodgment of soil particles from the soil mass at a particular location under a given erosive force (Zhang et al., 2003). Soil detachment by concentrated flowing water, i.e. rill erosion, is generally considered to be the most important process of sediment production on steep slopes (Poesen et al., 2003; Wang et al., 2014a). Soil detachment capacity (Dc) is defined as the maximum soil detachment rate in the case of clear flowing water scouring (Nearing et al., 1991; Zhang et al., 2009). It is controlled by the resistance of the top soils (Knapen et al., 2007b). Rill erodibility (Kr) and critical shear stress (τc) are commonly ⁎

used parameters reflecting soil resistance to flowing water erosion, and also are the important inputting parameters for many process-based soil erosion models (Foster et al., 1981; Nearing et al., 1989; Woodward, 1999). In the Water Erosion Prediction Project (WEPP) model, rill erodibility and critical shear stress are estimated using the measured soil detachment capacity as follow (Nearing et al., 1989): (1)

Dc = Kr (τ − τc ) −2 −1

where Dc is the flow detachment capacity (kg m s ), Kr is the rill erodibility (s m−1), τ is the flow shear stress (Pa), and τc is the critical shear stress (Pa). When the measured soil detachment capacity by concentrated flow is plotted against flow shear stress, rill erodibility and critical shear stress can be determined from the slope and the

Corresponding author at: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China. E-mail address: [email protected] (G.-h. Zhang).

https://doi.org/10.1016/j.catena.2018.10.036 Received 21 December 2017; Received in revised form 21 October 2018; Accepted 26 October 2018 0341-8162/ © 2018 Elsevier B.V. All rights reserved.

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profoundly influence the hydraulics of surface runoff and soil physiochemical properties (Zhao et al., 2010), thus might impact the soil resistance to rill erosion. Liu et al. (2016) showed that biological soil crusts could effectively decrease rill erodibility and the reducing effect varied with coverage and type of biological soil crusts. The Loess Plateau of China is one of the most eroded regions in the world, with the mean annual soil erosion rates ranging from 5000 to 10,000 t km−2 yr−1 (Fu and Gulinck, 1994; Zhang et al., 2009). The serious erosion is principally caused by high-intensity storms, easily eroded loess soils, poor vegetation cover, and inappropriate land uses (Fu et al., 2006; Duan et al., 2016). The landform of loess hilly-gully region on the Loess Plateau is a typical dual structure, composed of the ridge land and gully land (Jiang et al., 1966; Xiong et al., 2014). A clear dividing line, named as the shoulder-line, can be identified between the two different terrain areas (Geng et al., 2017a). The two terrains have obvious different landscape characteristics, hydraulic properties and erosion process. For the ridge lands, located above the shoulder-line, the hillslope is relatively smooth. Interrill, rill and ephemeral gully are the main erosion types. But for the gully lands, located below the shoulder-line, the landscape is much more shatter and steeper with the slope gradient of > 25° (Xiong et al., 2014). Soil loss is dominated by rill and gravitational erosion (Fu et al., 2006; Zhu, 2012). In the hilly and gullied areas of the Loess Plateau, gullies cover approximately 50%–60% of the total area, with a density of 3–8 km km−2 (Huang and Ren, 2006). The gully lands have been recognized as the main sediment source on the Loess Plateau region (Jiang et al., 1966). Soil loss of gully lands varies from 52.4% to 82.2% of the watershed total sediment yield (Tang, 2004). Since the flow hydraulics and soil processes on steep slopes are quite different from those on low slopes (Nearing et al., 1997, 1999), it is very important for soil conservation to understand soil erosion processes of the widespread steep gully slopes on the Loess Plateau. The natural vegetation recovery has been considered as the effective practice to control soil and water loss on the Loess plateau (Fu et al., 2006). Influenced by the local semi-arid climate, soil moisture is the critical and limited factor for vegetation recovery (Fu et al., 2003). The spatial and temporal distributions of vegetation are partially controlled by soil moisture (Melliger and Niemann, 2010). Compared to the upper hillslopes, the special topography (steeper and shatter) of the gully slopes likely produce a harsh environment for rainfall infiltration and water storage (Gao et al., 2011). Some studies have found that the development of gullies on gully lands can increase the spatial variability in soil moisture on the Loess Plateau (Melliger and Niemann, 2010; Gao et al., 2013). Generally, the soil moisture of gully lands is less than that of hillslopes (van den Elsen et al., 2003), which has great influences on plant communities and their growth. These differences in vegetation likely lead to the differences in near soil surface characteristics (i.e. soil physiochemical properties, litter, biological crust, and root system), which certainly have great effects on soil resistance to flowing water erosion. However, most previous studies were focused on hillslopes on the Loess Plateau (Zhang et al., 2003, 2009; Li et al., 2015a, 2015b). Up to date, the soil resistance to flowing water erosion is still unknown for the steep gully slopes covered by typical plant communities on the Loess Plateau. Therefore, the objectives of this study were to: (i) investigate the variations in soil resistance to flowing water erosion, reflected by rill erodibility (Kr) and critical shear stress (τc), of different plant communities on steep gully slopes below the shoulder-line on the Loess Plateau and to (ii) further identify the potential influencing factors for these variations. The results are helpful to understand soil erosion mechanism on steep gully lands and evaluate soil and water conservation benefits of vegetation recovery.

intercept on the x-axis of the regression linear line (Flanagan et al., 2007). Many previous studies have shown that both Kr and τc are mainly influenced by soil properties and vegetation characteristics (Knapen et al., 2007b; Wang et al., 2014a). Soil resistance to flowing water erosion is strongly affected by soil properties (Nearing et al., 1988; Morgan et al., 1998; Zheng et al., 2000; Zhang et al., 2009). Geng et al. (2017b) found a strong spatial variation in Kr and a moderate spatial variation in τc for 36 soil types in eastern China. The mean Kr of the northwest Loess Plateau was significantly greater than those of the other five secondary water erosion zones: northeast low mountains and hills, north mountains and hills, south mountains and hills, the Sichuan Basin and surrounding mountains and hills, and Yunnan-Guizhou Plateau. Soil resistance is closely related to soil texture (Line and Meyer, 1989; Geng et al., 2015), and silt loam soils have high Kr and low τc, while clay soils have low Kr and high τc (Sheridan et al., 2000; Knapen et al., 2007b). Soil strength increases with soil bulk density, which enhances the soil resistance to flowing water erosion. Ghebreiyessus et al. (1994), Bennett et al. (2000), and Knapen et al. (2008) demonstrated that τc increased and Kr decreased with bulk density. Soil cohesion and water stable aggregation, are also important parameters reflecting soil erosion resistance (Knapen et al., 2007b). Geng et al. (2015) showed that Kr decreased, but τc increased with soil cohesion and water stable aggregation. Soil organic matter acts as a cementing matter between soil mineral particles and thus also can increase soil resistance to flowing water erosion (Knapen et al., 2007b). Several previous studies have revealed that Kr decreased with soil organic matter (Li et al., 2015a, 2015c). Soil resistance to flowing water erosion is influenced greatly by vegetation characteristics. Plant roots can increase soil shear strength and cohesion and hence reduce the susceptibility of the soil to rilling, due to their biomechanical properties, root traits (i.e. root mass density, root length density), and spatial distribution characteristics (De Baets et al., 2006, 2007, 2008; De Baets and Poesen, 2010; Wang et al., 2014b; Li et al., 2017). The enhanced soil resistance of rooted soils to flowing water erosion can be attributed to the physical binding effect and the chemical exudates-bonding effect (Wang et al., 2014b). Mamo and Bubenzer (2001) showed that the concentrated flow erodibility decreased with root length density. Gyssels et al. (2005), De Baets et al. (2006), and Zhang et al. (2013, 2014) all found that rill erodibility decreases as an exponential function of root mass density. De Baets et al. (2007) indicated that tap roots reduce the erosion rates to a lesser extent compared with fine fibrous roots. Furthermore, plant litter can be incorporated into topsoil through soil splash, sediment deposition and soil animal activities, which also influences soil resistance to rill erosion (Sun et al., 2016b). Sun et al. (2016a) found that the incorporated plant litter was effective to enhance soil resistance to flowing water erosion, and rill erodibility decreased exponentially with the incorporated plant litter rate. Wang et al. (2014b) also revealed that the plant litter-stems contributed to 30.3% of the reduction in soil detachment capacity in a 7-yr restored natural grassland on the Loess Plateau. Besides soil properties and vegetation characteristics, soil resistance to flowing water erosion is also greatly impacted by land uses and tillage practices. Land use influences both soil and vegetation properties, and hence affects rill erodibility (Wang et al., 2014a). Zhang et al. (2008) found that Kr varied from 0.0021 to 0.164 s m−1 for five typical land uses on the Loess Plateau, and the results indicated that the slope cropland had the highest rill erodibility, and then followed by grassland, shrubland, wasteland, and woodland, respectively. Tillage practices disturb the top soil layer strongly, and thus reduce soil resistance to flowing water erosion (King et al., 1995; Knapen et al., 2007b; García-Orenes et al., 2012). Zhang et al. (2009) found that all tillage practices, i.e. planting, ploughing, weeding, and harvesting, disturbed soil surface to form a loose erodible layer, leading to an increase in rill erodibility. Furthermore, biological soil crusts are typical ubiquitous living organisms on soil surface of abandoned farmlands, which can 376

377

8 52.5 80 47.7 1250

7 64.0 103 58.4 1320

8 69.2 101 54.5 1230

8 60.0 350 58.5 1125

5 50.0 110 62.3 1240

6 72.5 110 42.6 1180

5 65.0 105 56.5 1330

45.0 105 < 10.0 1280

Shrubland

Shrubland

Shrubland

Grassland

Grassland

Grassland

Grassland

KP

SB

SS

NS

DG

RW

GW

N 36° 44′ 52.1″ E 109° 14′ 47.7″ N 36° 43′ 40.0″ E 109° 14′ 31.0″ N 36° 45′ 19.4″ E 109° 15′ 05.0″ N 36° 44′ 09.8″ E 109° 14′ 30.9″ N 36° 45′ 17.1″ E 109° 15′ 06.5″ N 36° 44′ 07.6″ E 109° 14′ 39.6″ N 36° 43′ 46.2″ E 109° 14′ 27.2″ N 36° 44′ 07.3″ E 109° 14′ 26.0″ Farmland

Location

SF

For soil detachment capacity measurement, undisturbed soil samples were collected from the top layer of soil at each sampling site with steel rings (9.8 cm in diameter, 5 cm in height). Before sampling, the flat soil surface nearby the dominant species was selected to fill the sample ring fully, and the plant litter was cleared slowly and completely. The sampling procedure was almost similar for all sampling sites, and the detailed description can be found in previous studies (Zhang et al., 2003, 2009). Thirty soil samples were collected for each site, and 240 soil samples were collected totally for eight sites from August to September 2017. Immediately after sampling at each site, the collected soil samples were sealed with plastic wrap and transported to

Land use

2.3. Soil sampling

Sampling site

Table 1 The basic information of each sampling site.

Elevation (m)

Slope (%)

Aspect (°)

After a completely watershed survey in July 2017, focusing on the steep gully slopes, four typical grassland communities and three typical shrubland communities were selected as the test sites. These selected sites had a similar soil type (Haplustalf soil with a silt loam texture), elevation (1125–1330 m), slope gradient (42.6%–62.3%), and slope aspect (East, except for the Needle-scale Sedge) to minimize the potential effects of these factors on the experimental results. The areas of the selected sites were larger than 1000 m2. At each site, three quadrats, 1 × 1 m2 for grasslands and 2 × 2 m2 for shrublands, were randomly selected to measure the vegetation characteristics of plant species and coverage. Then, the plant richness (total number of species) and abundance (Simpson index of diversity) were calculated (Demenois et al., 2017). For seven different plant communities, the vegetation coverage, species richness, and Simpson index of diversity varied from 50.0% to 72.5%, 5 to 8, and 0.48 to 0.72. The mean coverage (62.5%) and Simpson index of diversity (0.68) of shrub communities were a little higher, but their mean species richness (5) was lower, than those of grass communities (61.4%, 0.60, and 8, respectively). The dominant species of the grassland communities were Russian Wormwood (Artemisia sacrorum), Girald Wormwood (Artemisia giraldii Pamp.), Digitate Goldenbeard (Bothriochloa ischcemum (Linn.) Keng) and Needle-scale Sedge (Carex lanceolata Boott). While Korshinsk Peashrub (Caragana korshinskii Kom), Sea-buckthorn (Hippophae rhamnoides Linn.), and Shrub Sophora (Sophora viciifolia) were the dominant species of the shrub communities, accompanied by some annual or perennial herb species. For comparison, one active slope farmland planted in soybean was selected as the base or control. The basic information of each sampling site is listed in Table 1.

Coverage (%)

Characteristics of plant community

2.2. Sampling sites selection

SF, the slope farmland; KP, the korshinsk peashrub; SB, the sea-buckthorn; SS, the shrub sophora; NS, the needle-scale sedge; DG, the digitate goldenbeard; RW, the Russian wormwood; GW, the girald wormwood.

Artemisia giraldii Pamp. - Artemisia sacrorum 0.59

0.48

Bothriochloa ischcemum (Linn.) Keng - Artemisia sacrorum 0.71

Carex lanceolata Boott - Artemisia sacrorum 0.61

Caragana korshinskii Kom - Artemisia sacrorum

Sophora viciifolia - Artemisia sacrorum 0.67

0.72

– –

0.64

Simpson index Species richness

Most abundant species

The study was conducted in the Zhifanggou small watershed (36°46′28″–36°46′42″N, 109°13′03″–109°16′46″E) of Ansai Soil and Water Conservation Station. It is situated in the typical loess hilly and gully region of the Loess Plateau. The watershed has a total area of 8.27 km2 with the elevation ranged from 1010 to 1431 m and a gully density of 8.06 km km−2 (Fu et al., 2006; Li et al., 2015b). The region exhibits a semi-arid continental climate, with a mean annual temperature of 8.8 °C and a mean annual precipitation of 505 mm. More than 70% of the precipitation is concentrated in the rainy season (from July to September) and the short heavy storms occur frequently (Wang et al., 2014a). The degree of slope varies from 0° to 65° in the whole watershed (Fu et al., 2006). The soil, developed from loess parent material, has a homogeneous silt loam texture, and is easy to be detached (Fu et al., 2006; Li et al., 2015c). The vegetation zones are warm shrub and meadow steppe. Soil erosion is very serious with a mean erosion modulus of 14,000 t km−2 yr−1 before the vegetation restoration efforts began in this region (Liu, 1999).

Soybean

2.1. Study area

Hippophae rhamnoides Linn. - Artemisia sacrorum

2. Materials and methods

Artemisia sacrorum - Poa sphondylodes Trin.

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378

0.17d 0.62c 0.62bc 0.88c 0.88b 0.83a 0.64bc 1.26b ± ± ± ± ± ± ± ± 0.33 1.71 2.70 2.20 3.44 5.36 2.56 3.55 0.06e 0.08d 0.04bc 0.00bc 0.11b 0.04a 0.04 cd 0.04bc ± ± ± ± ± ± ± ± 23.57 34.95 24.86 29.97 24.01 25.28 24.98 25.85 1.91a 0.21b 1.99ab 0.35ab 1.15ab 1.37ab 1.54ab 0.94ab ± ± ± ± ± ± ± ±

Silt (%)

63.40 55.88 61.05 59.02 61.27 60.74 61.88 61.37 13.02 ± 0.15a 9.17 ± 0.62b 14.09 ± 1.96a 11.00 ± 1.13ab 14.72 ± 0.10a 13.98 ± 0.04a 13.15 ± 0.16a 12.78 ± 1.66a SF KP SB SS NS DG RW GW

To eliminate the effects of soil moisture on the measurement of soil detachment capacity, the collected soil samples were saturated for 8 h in a container (the water level was increased gradually until it was 0.5 cm below the soil surface), and then drained for 12 h (Zhang et al., 2002; Wang and Zhang, 2017; Wang et al., 2018). Just prior to each test, the flow discharge and flume slope gradient were adjusted to the

Clay (%)

2.5. Soil detachment capacity measurement

Soil texture

where ρ is the density of water (kg m ), g is the constant of gravity (m s−2), and S is the sine of the slope gradient (m m−1). In this study, six combinations of unit width discharge (ranged from 0.0029 to 0.0071 m2 s−1) and flume bed gradient (from 25.9 to 50.0%) were applied, resulting in six different shear stresses of 6.64, 8.66, 10.77, 12.28, 15.05, and 17.85 Pa.

Sampling site

Table 2 Soil and vegetation properties of each sampling site.

(3) −3

Sand (%)

0.06b 1.37a 1.61b 2.28ab 1.27b 1.51b 1.10b 5.26b

where Q is the flow discharge (m s ), v is the mean flow velocity (m s−1), and B is the flume width (B = 0.35 m). Then, the flow shear stress (τ, Pa) was calculated as (Zhang et al., 2003):

D50, median soil grain size; Dg, geometric mean particle diameter; M, the particle size parameter. Values given represent mean values ± standard deviation. The same letter in the same column means that differences are not significant at p = 0.05.

3 −1

τ = ρghS

± ± ± ± ± ± ± ± 213e 417e 397e 577d 244c 1166a 723b 871b ± ± ± ± ± ± ± ± 3028 3618 3334 4317 5017 8241 6012 6143 1066 ± 59bcd 1020 ± 98cde 1154 ± 51a 946 ± 73e 986 ± 80de 1146 ± 104ab 1098 ± 79abc 1000 ± 80de 0.34bc 1.62a 2.80 cd 0.42b 0.93d 1.75 cd 0.27bcd 0.63bcd 28.07 37.73 27.73 32.59 27.19 27.29 28.01 28.99

(2)

± ± ± ± ± ± ± ±

D50 (μm)

0.03bc 0.97a 2.22bc 1.72b 0.41c 0.32c 0.46bc 4.76bc

0.02 0.03 0.02 0.02 0.02 0.02 0.02 0.02

± ± ± ± ± ± ± ±

Dg (mm)

0.00c 0.00a 0.00c 0.00ab 0.00c 0.00c 0.00c 0.00bc

72.47 76.29 69.14 72.63 68.93 69.04 71.34 71.98

M (%)

± ± ± ± ± ± ± ±

The soil detachment capacity was measured in a 4.0 m long and 0.35 m wide flume, as used in previous studies of Zhang et al. (2003, 2009). To simulate the hydraulic roughness of soil sample surfaces, the air-dried soil collected from the field (passing 2 mm sieve) was glued on to the flume bed surface. The slope of the flume could be adjusted mutually from 0% to 60% by a pulley gear. The flow discharge was controlled by a series of valves and was measured with plastic buckets and a volumetric cylinder at the flume outlet. After the flow became stable, the maximum surface flow velocity was measured by the fluorescent dye technique with 60 replications. Then the average was multiplied by a reduction factor to obtain the mean flow velocity (Luk and Merz, 1992). Flow depth (h, m) was calculated as:

Q Bν

0.29 0.42 0.59 0.57 0.63 0.74 0.50 0.55

Organic matter (g kg−1) Water stable aggregation (0–1) Soil cohesion (Pa) Bulk density (kg m−3)

2.4. Experimental flume and hydraulic parameter determination

h=

7.86 ± 0.32f 13.83 ± 0.10c 10.98 ± 0.98e 17.29 ± 1.31b 20.79 ± 1.48a 14.68 ± 0.51c 10.11 ± 0.55e 12.43 ± 0.46d

Root mass density (kg m−3)

Litter mass density (kg m−3)

Ansai station for weighting as soon as possible to minimize the influence of evaporation (Zhang et al., 2003; Wang and Zhang, 2017). Additionally, for each site, soil moisture, bulk density, cohesion, particle size distribution, soil organic matter content, and water stable aggregation were measured near where the soil detachment samples were taken. For each site, eight soil cores were taken using steel rings (5 cm in diameter and 5 cm in height) from the top soil layer (0–5 cm), and then sealed with plastic wrap and sent to the station to determine soil moisture and bulk density by oven-dry method. The average soil moisture was used to calculate the original dry mass of soil sample for detachment capacity measurement. Soil cohesion was measured for 10 replicates with a pocket vane (Durham Geo-enterprises, Inc., UK) at the saturated soil surface wetted by a light spraying. At each site, six soil samples were collected with a shovel and ziplock bags from the top soil layer (0–5 cm). These samples were completely mixed and air-dried to pass through a 2-mm sieve for particle size distribution analysis (Mastersizer 2000) and a 0.25-mm sieve for organic matter content (SOM) analysis (potassium dichromate colorimetric method) for four replicates. Then, the median soil grain size (D50), the geometric mean particle diameter (Dg) (Shirazi and Boersma, 1984), and the particle size parameter (M) used in the Universal Soil Loss Equation (Wischmeier and Smith, 1978) were calculated. Water stable aggregation was measured for triplicates at each site by the wet-sieving method with a set of 5, 2, 1, 0.5, and 0.25 mm sieves. All the soil samples were collected from the top soil layer (0–5 cm), and the collected soil samples were carried to the laboratory using aluminum boxes to minimize the influence of disturbance during transportation. The soil properties of each sampling site, expressed by the mean values, are shown in Table 2.

0.72 ± 0.23c 10.58 ± 4.63a 2.07 ± 1.30c 5.83 ± 2.45b 1.06 ± 0.63c 0.47 ± 0.16c 0.82 ± 0.47c 2.77 ± 1.51c

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designed values. The pre-saturated soil sample was inserted into a circle hole (0.5 m above the lower end of flume) on the flume bed, keeping the sample surface even with the flume bed. Then the soil detachment capacity measurement started and ended until a similar scouring depth (2 cm) was reached to minimize the influence of uneven detachment within the sample ring (Nearing et al., 1991; Zhang et al., 2003, 2014). After each test, the scoured sample was oven dried at 105 °C for 24 h and weighed to calculate the final dry soil mass. Soil detachment rate (Dc, kg m−2 s−1) was calculated using the following equation (Zhang et al., 2003, 2009):

Dc =

Mb − Ma At

(4)

where Mb is the initial dry weight of soil sample (kg, the weight of wet soil sample minus the water weight within the soil sample), Ma is the final oven-dry mass of the soil sample (kg), A is the section area of the soil sample (7.54 × 10−3 m2), and t is the test duration (s). Under each shear stress, five soil samples were tested for each sampling site, and the mean value was considered as the soil detachment capacity for that flow shear stress. A total of 240 samples were tested. After the tests, the plant roots and incorporated litters within each soil sample were washed out over a sieve (1 mm) and weighed after oven-drying at 65 °C for 24 h, thus the root mass density (kg m−3) and litter mass density (kg m−3) were calculated through dividing the root and litter weight (kg) by the ring volume (3.77 × 10−4 m3) (Wang et al., 2013; Li et al., 2015c). The average root density and litter density of five soil samples tested under the same flow shear stress were considered as the mean root density and litter density for further analysis (Zhang et al., 2014). Finally, the soil resistance to flowing water erosion, reflected by the rill erodibility (Kr) and critical shear stress (τc), was estimated for each site by the simple linear regression of the measured soil detachment capacity and flow shear stress (Eq. (1)).

Fig. 1. Variations in soil detachment capacity of different sampling sites (the same letter means that differences are not significant at p = 0.05).

steep gully slopes covered with shrub and grass communities. The mean Dc was 0.503, 0.329, and 0.240 kg m−2 s−1 for shrub communities of Caragana korshinskii Kom, Hippophae rhamnoides Linn. and Sophora viciifolia; and was 0.200, 0.178, 0.100, and 0.073 kg m−2 s−1 for grass communities of Carex lanceolata Boott, Bothriochloa ischcemum (Linn.) Keng, Artemisia sacrorum, and Artemisia giraldii Pamp., respectively. The reduction rates in soil detachment capacity ranged from 85.6% to 97.9% for different plant communities. The significant reduction of soil detachment capacity on the gully slopes of different plant communities confirmed that vegetation growth played an important role in controlling soil losses (Wang et al., 2014a). In addition, although the measured detachment capacities varied with plant communities, a significant difference in soil detachment capacity was only found between Caragana korshinskii Kom shrubland, and Artemisia sacrorum and Artemisia giraldii Pamp. grasslands (p < 0.05, Fig. 1). For the grass communities, the mean soil detachment capacity was 0.138 kg m−2 s−1, which was 61.5% less than that of shrub communities (0.357 kg m−2 s−1), reflecting grass communities more effective to reduce soil detachment than shrub communities. Slope farmland had the greatest detachment capacity, followed by the shrubland and grassland in this study. It is in accordance with the conclusion of Zhang et al. (2008, 2009) and Li et al. (2015c) that soil detachment rate was significantly influenced by land use and the cropland was the most easily detached land use on the Loess Plateau. The measured soil detachment capacity of farmland in this study was greater than the previous results of Zhang et al. (2009), Wang et al. (2013) and Li et al. (2015c), which was likely caused by the differences in flow shear stresses. The measured soil detachment capacities of shrublands and grasslands in this study were also a little higher than the results of Zhang et al. (2009) and Li et al. (2015c). This difference might be not only related to the higher flow shear stresses in our study, but also related to the differences in research objects, varying from hillslopes to steep gully slopes, which caused variations in soil properties and plant roots that affecting soil detachment process.

2.6. Statistical analysis One-way ANOVA analysis was used to detect the differences in soil and vegetation properties, soil detachment capacity, and soil resistance to flowing water erosion between slope farmland and gully slope lands with different plant communities. The significance level was conventionally set at 0.05. General linear model (GLM) was utilized to test the influence of soil and vegetation properties on soil resistance to flowing water erosion. A structural equation model (SEM) was performed to explore the direct causal links among vegetation properties and soil properties. The goodness of fit index (GFI), the non-normed fit index (NFI), and the root mean square error of approximation (RMSEA) were used to assess the goodness of fitted results (Wang et al., 2017). The simple regression method was employed to analyze the relationships between rill erodibility and critical shear stress, and soil properties and root mass density. The regression results were evaluated by the coefficient of determination (R2). GLM analysis was conducted using MATLAB R2014a software and SEM analysis was performed by IBM SPSS AMOS 21.0 software, and the other statistical analyses were carried out by SPSS 20.0 software and Origin Pro 2015 software. 3. Results and discussion 3.1. Variations in soil detachment capacity The measured soil detachment capacity varied significantly between the slope farmland and steep gully slopes with different plant communities (Fig. 1). For comparison, the measured soil detachment capacities under six shear stresses were averaged for each sampling site. Soil detachment capacity of the slope farmland was significantly greater than those of steep gully slopes with different vegetation growths (Fig. 1). The mean Dc of the slope farmland was 3.485 kg m−2 s−1, which was 6.9 to 14.5 times and 17.4 to 47.8 times greater than that of

3.2. Soil resistance to flowing water erosion The estimated rill erodibility and critical shear stress of each site are shown in Table 3. Rill erodibility showed significant differences among eight sampling sites. The slope farmland had the maximum rill erodibility (0.381 s m−1), which was 4.4 to 7.7 times and 12.1 to 20.6 times greater than those of shrublands (0.049 to 0.088 s m−1) and grasslands 379

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(Linn.) Keng, Artemisia sacrorum, and Artemisia giraldii Pamp. This result is contrary to the finding of Li et al. (2015a), who reported that the rill erodibilities of Artemisia communities were greater than that of Carex lanceolata Boott and Bothriochloa ischcemum (Linn.) Keng. This difference was probably caused by the cover of biological soil crusts on soil surface of Artemisia communities in this study. Wang et al. (2013, 2014b) and Liu et al. (2016) found that biological soil crusts could effectively decrease rill erodibility on the Loess Plateau. Furthermore, the differences in rill erodibilities of different plant communities might also be related to the root mass density and root architecture (De Baets et al., 2006, 2007). The variations in rill erodibilities of different plant communities are meaningful for soil conservation planning to effectively reduce soil erosion on bare steep gully slopes. The fitted critical shear stress (τc) of slope farmland was 2.72 Pa, while the τc of steep gully slopes covered with different plant communities varied from 1.84 to 7.47 Pa, with a mean of 5.97 Pa (Table 3). The estimated τc values in this study are very similar to the values reported by Nearing et al. (1999), Zhang et al. (2002), and Geng et al. (2017a). The τc values of steep gully slopes were significantly greater than the control slope in most cases, except for Caragana korshinskii Kom shrubland. The differences in the mean τc were also observed among different land uses (Fig. 2). For the gully slopes, the mean τc of shrub communities and grass communities was 4.76 and 6.88 Pa, separately. But the critical shear stress of farmland was only 57.2% and 39.6% of that of shrubland and grassland. These results also demonstrated that vegetation growth on steep gully slopes can effectively increase soil critical shear stress to flowing water erosion on the Loess Plateau. Additionally, the grassland had a higher τc than shrubland (though not significant, p = 0.195), which also implied that grass communities seemed to be more effective in increasing τc than shrub communities.

Table 3 Rill erodibility (Kr) and critical shear stress (τc) for each sampling site. Sampling site

Land use

Regression equation

SF KP SB SS NS DG RW GW

Cropland Shrubland Shrubland Shrubland Grassland Grassland Grassland Grassland

Dc = 0.381 Dc = 0.088 Dc = 0.062 Dc = 0.049 Dc = 0.032 Dc = 0.025 Dc = 0.023 Dc = 0.019

τ − 1.037 τ − 0.161 τ − 0.437 τ − 0.265 τ − 0.236 τ − 0.134 τ − 0.166 τ − 0.134

Kr (s m−1)

τc (Pa)

R2

0.381 0.088 0.062 0.049 0.032 0.025 0.023 0.019

2.72 1.84 7.08 5.37 7.47 5.42 7.23 7.39

0.86 0.82 0.88 0.88 0.88 0.82 0.85 0.74

Dc, soil detachment capacity; τ, flow shear stress.

(0.019 to 0.032 s m−1) on steep gully slopes, respectively. Compared to the slope farmland, the rill erodibilities of steep gully slopes covered with different plant communities reduced greatly by 77.0% to 95.1%, and the reducing effect was more obvious for grass communities. This result implied that vegetation recovery on steep gully slopes was effective to reduce rill erodibility on the Loess Plateau. The estimated rill erodibilities (Kr) in this study were within the ranges reported by Zhang et al. (2002). But they were two orders of magnitude greater than those reported in the WEPP rill erosion study (Laflen et al., 1991) and were 2.9 to 47.9 times greater than that reported by Nearing et al. (1999). These differences were likely caused by the differences in experimental methods (Nearing et al., 1999). Furthermore, the measured rill erodibilities in this study were greater than the previous similar studies carried out on the Loess Plateau (Wang et al., 2014a; Li et al., 2015a; Geng et al., 2015, 2017a). These differences were likely related to the differences in soil properties and plant roots between the hillslopes and steep gully slopes. Rill erodibility was also influenced significantly by land use (Fig. 2). On average, rill erodibility of shrubland was 0.066 s m−1, while the mean rill erodibility of grassland was 0.025 s m−1. The mean Kr of grass communities was significantly lower than that of shrub communities (p < 0.05). Rill erodibility followed the order of farmland > shrubland > grassland, which is consistent with the conclusion of Li et al. (2015a), who found that cropland had the highest rill erodibility, and then followed by shrubland and grassland. For the gully slopes covered with different shrub communities, rill erodibility decreased in the order of Caragana korshinskii Kom, Hippophae rhamnoides Linn. and Sophora viciifolia, which is consistent with the result of Li et al. (2015a). For the gully slopes covered with different grass communities, rill erodibility decreased in the order of Carex lanceolata Boott, Bothriochloa ischcemum

3.3. Factors influencing soil erosion resistance Vegetation recovery on steep gully slopes influenced vegetation properties greatly. In this study, the root mass densities and litter mass densities of different plant communities on steep gully slopes increased significantly compared to the control slope (p < 0.05), except for the litter mass density of Bothriochloa ischcemum (Linn.) Keng (Table 2). The root mass densities and litter mass densites of different plant communities were 5.2 to 16.2 and 0.7 to 14.7 times greater than those of control. The changes in soil properties induced by natural vegetation recovery may vary greatly due to the differences in vegetation properties (Wang et al., 2014a, 2018). However, the reuslts of one-way analysis of variance showed that no significant differences were detected in soil texture (clay, silt, and sand contents, D50, Dg, and M) between the control slope and most of vegetation restored gully slopes (p > 0.05), except for Caragana korshinskii Kom community (Table 2). No significant difference was found in soil bulk density between the control slope and most of vegetation restored steep gully slopes (Table 2). These results indicated that vegetation restoration could not influence soil texture and bulk density significantly on steep gully slopes on the Loess Plateau, which are inconsistent with the conclusions of previous studies on hillslopes (Wang et al., 2014a, 2018). Many studies have shown that vegetation growth could promote soil cohesion, organic matter and soil aggregate stability (De Baets et al., 2006, 2008; Wang et al., 2014a, 2018; Demenois et al., 2017). In this study, soil cohesion, water stable aggregation and organic matter content of different plant communities on steep gully slopes increased significantly compared to the control slope (Table 2). Soil cohesion, water stable aggregation, and organic matter content of different vegetation communities were 1.1 to 2.7, 1.4 to 2.6, and 1.3 to 2.6 times greater than those of control. Significant differences were also detected in soil cohesion, water stable aggregation and organic matter content between most of plant communities (p < 0.05, Table 2). Vegetation restoration influences vegetation characteristics and soil properties, and thus likely affects soil resistance to flowing water

Fig. 2. Comparison of rill erodibility (Kr) and critical shear stress (τc) between different land use types (the same letter means that differences are not significant at p = 0.05). 380

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erosion. The results of GLM analysis demonstrated that root mass density was the main influencing factor on rill erodibility, which explained 82.4% of the variations in rill erodibility. For critical shear stress, soil particle size parameter explained the largest proportion (53.6%) of its variation, followed by the interaction between soil particle size parameter and root mass density (23.0%), and root mass density (10.7%). These results verified that the development of plant root was effective to enhance soil resistance to flowing water erosion (Mamo and Bubenzer, 2001; Gyssels et al., 2005; De Baets et al., 2006; Wang et al., 2015; Wang and Zhang, 2017). The plant root system can interweave into soil mass through its physically binding, and adhere soil particles to root surface firmly through its intermolecular bonding effect (Wang et al., 2015; Wang and Zhang, 2017). Some previous studies have shown that the incorporated residue or litter within topsoil layer can also increase soil resistance to flowing water erosion (Brown et al., 1989; Sun et al., 2016a). However, no significant relationships were found in this study between litter mass density of topsoil layer, and rill erodibility and critical shear stress. This difference was probably derived from the differences in plant litter species (including their densities, shape and mechanical traits, and decomposition rates), and soil properties (Brown et al., 1989; Sun et al., 2016a). The effect of root system reducing soil detachment is related to its diameter, length or mass density, area ratio, and architecture (i.e., tap and fibrous roots) (Mamo and Bubenzer, 2001; Gyssels et al., 2005; De Baets et al., 2006, 2007; De Baets and Poesen, 2010; Wang and Zhang, 2017). Many studies have proven that rill erodibility decreased and critical shear stress increased with root mass density (Gyssels et al., 2005; De Baets et al., 2006, 2007; De Baets and Poesen, 2010; Zhang et al., 2013; Geng et al., 2015; Li et al., 2015a). In our study, regression results showed that the fitted rill erodibility decreased exponentially (Fig. 3), and critical shear stress increased as a logarithmic function with root mass density (Fig. 4). These results corroborate the conclusions of most related previous studies. In this study, soil sampling was taken nearby the dominant vegetation species, which was different from the method applied by Wang and Zhang (2017), who clipped the aboveground plants for soil sampling to quantify the effects of plant root systems on soil detachment process by overland flow. Actually, the root mass densities of different plant communities restored on steep gully slopes were likely underestimated in this study since the larger roots were not collected completely. The root traits (i.e. diameter, length density and area ratio) of different plant communities were quite different. Therefore, further studies are needed to quantify the effects of plant root systems on soil resistance to flowing water erosion on steep

Fig. 4. Critical shear stress (τc) as a function of root mass density (RMD).

gully slopes under different plant communities including additional root traits. Although significant relationships between rill erodibility, and soil texture and bulk density were reported in previous studies on the Loess Plateau (Li et al., 2015a; Geng et al., 2017a), no significant correlation was detected in this study. This difference was probably caused by the relative small range of the tested soil texture and bulk density in this study (Table 2). This result also implied that the variation in rill erodibility was not controlled by soil texture and bulk density in the current study. Vegetation growth on steep gully slopes increased soil cohesion, organic matter content and water stable aggregation significantly, which affected soil resistance to flowing water erosion indirectly. The simulated results of the SEM model showed that root mass density had strong positive direct effects on soil cohesion (0.78), organic matter content (0.56), and water stable aggregation (0.92) with NFI and GFI > 0.9, and RMSEA < 0.001. Consequently, soil cohesion, organic matter and water stable aggregation exerted a slight direct effect on rill erodibility. Soil cohesion is closely related to the cohesive force between soil particles, and has been widely used to reflect the effect of soil properties on soil resistance to flowing water erosion (Wang et al., 2014a; Li et al., 2015a; Sun et al., 2016b; Geng et al., 2015, 2017a). In our study, rill erodibility decreased with soil cohesion as a power function (Fig. 5). This result is consistent with the findings of Wang et al. (2014a) and Li et al. (2015a). Meanwhile, a linear trend was observed between critical shear stress and soil cohesion, but not significant. Soil aggregate stability (i.e. the resistance of large aggregates against breakdown by the action of flowing water) is generally used as an indicator for soil erosion resistance (Knapen et al., 2007b; Li et al., 2015a). As shown in Fig. 6, rill erodibility decreased with water stable aggregation following a power function with a coefficient of determination of 0.97. Li et al. (2015a) also reported rill erodibility decreased with water stable aggregation as a power function, while Geng et al. (2015, 2017a) found that rill erodibility decreased exponentially with water stable aggregation. Furthermore, although not significant, critical shear stress was positively correlated with water stable aggregation following a logarithmic function (Fig. 7). This trend agrees with the results of Geng et al. (2015). Soil organic matter is effective to improve soil aggregation and control soil crusting, thereby promoting soil resistance to flowing water erosion (Knapen et al., 2007b; Li et al., 2015a). Several previous studies have demonstrated that rill erodibility decreased with organic matter content as a power function (Li et al., 2015a; Geng et al., 2017b). However, a negative relationship was detected between rill

Fig. 3. Rill erodibility (Kr) as a function of root mass density (RMD). 381

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erodibility and soil organic matter content in this study, but not significant. Both soil properties and vegetation characteristics change with vegetation restoration, and thus affect soil detachment process by overland flow (Wang et al., 2014a). As discussed above, the results of this study indicated that the factors determining the variations in soil resistance to flowing water erosion on steep gully slopes on the Loess Plateau were root mass density, soil cohesion and water stable aggregation. The plant root system can enhance soil resistance by the exudates-bonding effect and physically binding effect (De Baets et al., 2007, 2008; Wang et al., 2014b, 2017). The increases in soil cohesion and water stable aggregation with the development of plant root can also increase the resistance of soil to erosion by flowing water (Knapen et al., 2007a; Zhang et al., 2008, 2009; Wang et al., 2015). Therefore, rill erodibilities of steep gully slopes were reduced significantly compared to slope farmland in this study, which can be attributed to the significant increases in soil cohesion, water stable aggregation, and root mass density due to the natural plant growth. 4. Conclusion

Fig. 5. Rill erodibility (Kr) as a function of soil cohesion (Coh).

This study was conducted to quantify the effectiveness of vegetation recovery on soil resistance to flowing water erosion on steep gully slopes, using undisturbed soil samples collected from one slope farmland and seven gully slopes covered with different plant communities. The mean detachment capacity of the slope farmland was 6.9 to 47.8 times greater than those of vegetation restored gully slopes. Rill erodibilities of steep gully slopes covered with different plant communities reduced greatly by 77.0% to 95.1% compared to slope farmland. The mean rill erodibility of grass communities (0.025 s m−1) was significantly lower than that of shrub communities (0.066 s m−1). The critical shear stress of slope farmland was only 57.2% and 39.6% of the mean values of shrubland (4.76 Pa) and grassland (6.88 Pa). Vegetation recovery was effective in enhancing soil resistance to flowing water erosion on steep gully slopes on the Loess Plateau. The function of grassland was greater than shrubland to prevent soil from erosion judging from soil detachment by overland flow alone. The increase in soil erosion resistance of vegetation restored steep gully slopes could be explained by the differences in root mass density, soil cohesion, and water stable aggregation. Rill erodibility decreased exponentially with root mass density, and declined with soil cohesion and water stable aggregation following a power function. Critical shear stress increased with root mass density and water stable aggregation following a logarithmic function. The findings of this study have important implications to understand erosion processes and provide valuable references to evaluate soil conservation benefit of vegetation recovery on steep gully slopes on the Loess Plateau.

Fig. 6. Rill erodibility (Kr) as a function of water stable aggregation (WSA).

Acknowledgements Financial assistance for this work was provided by the National Key R & D Program of China (2017YFC0504702), and State Key Program of National Natural Science of China (41530858). We thank the members of the Ansai Research station of Soil and Water Conservation, the Chinese Academy of Sciences and Ministry of Water Recourses for their technical help. References Bennett, S.J., Casalí, J., Robinson, K.M., Kadavy, K.C., 2000. Characteristics of actively eroding ephemeral gullies in an experimental channel. Trans. ASAE 43, 641–649. Brown, L., Foster, G., Beasley, D., 1989. Rill erosion as affected by incorporated crop residue and seasonal consolidation. Trans. ASAE 32, 1967–1978. De Baets, S., Poesen, J., 2010. Empirical models for predicting the erosion-reducing effects of plant roots during concentrated flow erosion. Geomorphology 118, 425–432. De Baets, S., Poesen, J., Gyssels, G., Knapen, A., 2006. Effects of grass roots on the erodibility of topsoils during concentrated flow. Geomorphology 76, 54–67.

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