**3. Results**

#### **3.1 The relationship between rainfall amount, rainfall-runoff, and sediment yield**

**Figures 4** and **5** show that if rainfall conditions are held constant, the runoff and sediment yield vary among the five runoff plots with different vegetation types. In the 16 rainfall events, relative to variations in sediment yield, variations in runoff were smaller, and the coefficient of variation was 88.26%. The coefficient of variation for sediment yield was 172.70%. Also, at the preliminary stage after runoff plots had been constructed, vegetation destroyed, and vegetation canopy lowered, the benefits of soil and water conservation were better in *Hippophae rhamnoides* + *Pinus tabuliformis* and *Hippophae rhamnoides* vegetation types. With the recovery of vegetation, the benefits of soil and water conservation increased in all of the vegetation

**Figure 4.** *Runoff trend with rainfall amounts in the study area of Wuqi County, Shaanxi Province, China.*

*Soil Erosion Influencing Factors in the Semiarid Area of Northern Shaanxi Province, China DOI: http://dx.doi.org/10.5772/intechopen.92979*

#### **Figure 5.**

The value of *ξ* ranges from 0 to 1, but generally *ξ* = 0.5. γ *x*,

3. Lastly, the gray relational grade (GRG, *Γ*) is calculated using:

γ *x*,

**3.1 The relationship between rainfall amount, rainfall-runoff, and sediment**

*Runoff trend with rainfall amounts in the study area of Wuqi County, Shaanxi Province, China.*

**Figures 4** and **5** show that if rainfall conditions are held constant, the runoff and sediment yield vary among the five runoff plots with different vegetation types. In the 16 rainfall events, relative to variations in sediment yield, variations in runoff were smaller, and the coefficient of variation was 88.26%. The coefficient of variation for sediment yield was 172.70%. Also, at the preliminary stage after runoff plots had been constructed, vegetation destroyed, and vegetation canopy lowered, the benefits of soil and water conservation were better in *Hippophae rhamnoides* + *Pinus tabuliformis* and *Hippophae rhamnoides* vegetation types. With the recovery of vegetation, the benefits of soil and water conservation increased in all of the vegetation

We selected runoff and sediment yield as the reference sequences; several indicators were used as comparative sequences, including vegetation type, vegetation coverage, rainfall amount, rainfall duration, average rainfall intensity (I5, I10, I15, I30), soil bulk density, soil steady infiltration rate, and slope aspect and gradient. Then, the gray relational grade was calculated for the reference and comparison sequences (**Tables 2** and **3**). Deng pointed out in his book that if the gray relational grade is large, then a close relationship exists between the sequence and reference

<sup>0</sup>ð Þ <sup>k</sup> , *<sup>x</sup>*, *i*

<sup>Γ</sup> <sup>¼</sup> <sup>1</sup> *n* X*n k*¼1

correlation coefficient.

*Soil Moisture Importance*

parameters [65].

**3. Results**

**yield**

**Figure 4.**

**126**

<sup>0</sup>ð Þ <sup>k</sup> k, *<sup>x</sup>*, *i* ð Þ <sup>k</sup> � � is the

ð Þ <sup>k</sup> � � (7)

*Sediment yield trend with rainfall amounts in the study area of Wuqi County, Shaanxi Province, China.*

types at rainfall event. However, the *Pinus tabuliformis* was more obvious, especially in low rainfall intensity and long-duration rainfall events; *Hippophae rhamnoides* + *Pinus tabuliformis* was still low at low slope gradient when contrasted with other vegetation types in runoff plots; *Hippophae rhamnoides* decreased. Comparing grassland and *Hippophae rhamnoides* + *Pinus tabuliformis* in the same slope gradient, we conclude that grass on a slope with a gradient >25° cannot take the initiative to configure arbors or shrubs and make it natural succession to grow. At same time, we suggest that some shrubs and arbors should be active configuration to enhance the effect of soil and water conservation at low slope gradient less than 25 degrees; and considering that soil and water losses in pure *Pinus tabuliformis* forest were greater in the early stage of afforestation, we especially recommend *Hippophae rhamnoides* + *Pinus tabuliformis* mixed forests.

**Figures 4** and **5** show that vegetation types and rainfall amount had large effects on runoff and sediment yield; however, the change rule was not obvious. This study demonstrated that runoff and sediment yield are not solely determined by rainfall amount or by any single factor but more likely by a combination of vegetation type, vegetation coverage, rainfall amount, rainfall duration, rainfall intensity (average and for specified time periods), soil bulk density, soil steady infiltration rate, slope aspect, and slope gradient. Therefore, this research used the gray correlation method to comprehensively analyze the factors that influence runoff and sediment yield from multiple angles.

#### **3.2 The factors affecting runoff and sediment yield based on gray relational analysis**

While selecting runoff and sediment yield as a reference sequence, multiple indicators were used as comparative sequences, including vegetation type, vegetation coverage, rainfall amount, rainfall duration, average rainfall intensity, rainfall intensity for specified times (I5, I10, I15, I30), soil bulk density, soil steady infiltration rate, slope aspect, and slope gradient. Then the gray relational grade was calculated for the reference and comparison sequences (**Table 2**). Scientists generally agree that if the gray relational grade is large, then a close relationship exists between the sequence and reference parameters.

Several conclusions can be drawn using 5 years of data with the gray correlation method that analyzes the factors that affect runoff. First, rainfall is the most critical factor affecting runoff; it accounted for 27.86% of the total factor weight. This was followed by soil (25.53%), topography (24.34%), and vegetation (22.28%). Second, analysis of the specific factors related to rainfall found that the gray relational grade is 0.7685 for rainfall amount and that rainfall amount has the strongest influence on runoff of the top seven of 13 indicators analyzed here. Average rainfall intensity and I30 ranked second and third, respectively. Soil bulk density, another important factor affecting runoff, had a gray relational grade of 0.6948, which was greater than that of the soil steady infiltration rate. Slope aspect is the most important of the topographic factors affecting runoff, and its gray relational grade was 0.6655, larger than that of slope gradient. Of the vegetation factors, vegetation coverage had the largest effect on runoff and its gray relational grade, 0.5908, was larger than that of vegetation type (**Table 2**).

**3.4 Factors affecting sediment yield**

*DOI: http://dx.doi.org/10.5772/intechopen.92979*

sediment yield.

**Table 4.**

**129**

**Table 4** shows that during PPS, the influence of soil bulk density was significantly higher than that of the other factors, with a GRG of 0.8113. The average rainfall intensity ranked second, with a GRG of 0.7444, followed by the soil steady infiltration rate. Among the rainfall intensity factors, I30 had the closest relationship with sediment yield. The GRG for vegetation type was 0.6487, indicating that this factor is more closely related to sediment yield than vegetation cover. The smallest GRG value was 0.5945, indicating that all the factors had close relationships with

*Soil Erosion Influencing Factors in the Semiarid Area of Northern Shaanxi Province, China*

During PLR, I10 replaced the soil bulk density as the most significant factor affecting the runoff, with a GRG of 0.8012. The GRG values of I5, I15, I30, and average rainfall density were high among the 14 factors, indicating that rainfall intensity had the most important relationship with sediment yield during PLR. The rainfall duration ranked from the 10th to the 5th. In contrast, the soil bulk density ranked the 10th from the 1st during PPS, illustrating that the influence of the soil bulk density changed substantially during PLR. At the same time, the rank of soil steady infiltration rate was down to the eighth from the third. The rank of runoff moved up in comparison with PPS. The effects of vegetation type and vegetation cover on sediment yield were reduced according to the GRG analysis. The rank of

Significant differences were observed among the treatments in terms of runoff and sediment yield during PPS and PLR (**Figure 6**). The runoff and sediment yield during PPS were remarkably larger than during PLR, especially for P. During PPS, the runoff was 13.55-fold higher than that during PLR, and the sediment yield was 3.13-fold higher than that during PLR. In the analysis of grassland during PPS, the

Runoff Runoff 0.6129 13 18.62% 0.6323 11 19.32% Vegetation Vegetation type 0.6487 7 19.31% 0.6119 13 18.73% Vegetation coverage 0.6229 11 0.6141 12 Rainfall Rainfall amount 0.6198 12 20.22% 0.6627 9 22.54% Rainfall duration 0.6316 10 0.6926 5 Average rainfall intensity 0.7444 2 0.6758 6

Soil Soil bulk density 0.8113 1 23.15% 0.6532 10 20.14% Soil steady infiltration rate 0.7128 3 0.6652 8 Topography Slope aspect 0.6362 9 18.69% 0.6658 7 19.26% Slope gradient 0.5945 14 0.5949 14

*Gray relational grade between sediment yield and its influential factors.*

I5 0.6668 5 0.7953 2 I10 0.6595 6 0.8012 1 I15 0.6482 8 0.7779 3 I30 0.689 4 0.7593 4

**PPS PLR GRG Rank Proportion GRG Rank Proportion**

slope aspect added, while the rank of slope gradient was down.

**3.5 Runoff and sediment yield under different vegetation types**

Several conclusions can be drawn using the gray correlation method to analyze the factors affecting sediment yield at the loess region study plots during 2009– 2013. First, soil and runoff are the two most critical factors affecting sediment yield, accounting for 22.57% and 21.38% of the total proportion, while rainfall and topography accounted for 20.74% and 18.46%, respectively. Second, for the soil factors, soil bulk density had the largest effect on sediment yield and was the main factor among the 14 indicators measured here. Runoff ranked third in affecting sediment yield among the 14 indicators. Average rainfall intensity had the largest effect on sediment yield among measures of rainfall and ranked second among the 14 specific indicators. Rainfall amount also had a large effect on sediment yield, ranking fourth among the 14 indicators. The gray relational grades of other specific factors related to rainfall were also large and had dominant effects on sediment yield. The effects of vegetation type and vegetation coverage on sediment yield were small relative to other indicators; however, the gray relational grades for vegetation type and vegetation coverage were large (0.5851 and 0.5393, respectively); therefore, sediment yield and vegetation are very closely related.

#### **3.3 Factors affecting runoff**

As shown in **Table 3**, during PPS, it is clear that the slope aspect had the strongest impact on the runoff, with a GRG of 0.6681. The GRG for the soil steady infiltration rate was 0.6524, below only the slope aspect. The third factor was the rainfall amount, with a GRG of 0.6417, followed by rainfall duration, with a GRG of 0.6303. For the rainfall intensity, the GRG for I15 was the largest, and the relationship with runoff was similar. The influences of vegetation type and cover on the runoff were intermediate among the 13 factors and both with GRG values higher than 0.6. The smallest GRG value was I30 and the value was 0.5406 for the 13 factors, which is higher than 0.5. Therefore, all the 13 factors were closely related to runoff.

During PLR (**Table 3**), the rainfall duration replaced the slope aspect as the most critical factor affecting the runoff with a GRG of 0.7443. The GRG for vegetation type was 0.6757 and ranked second among the 13 factors. The rainfall amount ranked third with a GRG of 0.6415, and its influence on runoff showed no change in comparison with PLR. The GRG of the soil steady infiltration rate was ranked fourth (GRG, 0.6231), indicating a strong effect on runoff. I10 was the most critical factor among the rainfall intensity parameters. The influences of slope gradient and vegetation cover on runoff showed little changes. The influence of slope aspect on runoff showed a particularly notable decrease, ranking only at the 11th.

*Soil Erosion Influencing Factors in the Semiarid Area of Northern Shaanxi Province, China DOI: http://dx.doi.org/10.5772/intechopen.92979*

### **3.4 Factors affecting sediment yield**

Several conclusions can be drawn using 5 years of data with the gray correlation method that analyzes the factors that affect runoff. First, rainfall is the most critical factor affecting runoff; it accounted for 27.86% of the total factor weight. This was followed by soil (25.53%), topography (24.34%), and vegetation (22.28%). Second, analysis of the specific factors related to rainfall found that the gray relational grade is 0.7685 for rainfall amount and that rainfall amount has the strongest influence on runoff of the top seven of 13 indicators analyzed here. Average rainfall intensity and I30 ranked second and third, respectively. Soil bulk density, another important factor affecting runoff, had a gray relational grade of 0.6948, which was greater than that of the soil steady infiltration rate. Slope aspect is the most important of the topographic factors affecting runoff, and its gray relational grade was 0.6655, larger than that of slope gradient. Of the vegetation factors, vegetation coverage had the largest effect on runoff and its gray relational grade, 0.5908, was larger than that of

Several conclusions can be drawn using the gray correlation method to analyze the factors affecting sediment yield at the loess region study plots during 2009– 2013. First, soil and runoff are the two most critical factors affecting sediment yield, accounting for 22.57% and 21.38% of the total proportion, while rainfall and topography accounted for 20.74% and 18.46%, respectively. Second, for the soil factors, soil bulk density had the largest effect on sediment yield and was the main factor among the 14 indicators measured here. Runoff ranked third in affecting sediment yield among the 14 indicators. Average rainfall intensity had the largest effect on sediment yield among measures of rainfall and ranked second among the 14 specific indicators. Rainfall amount also had a large effect on sediment yield, ranking fourth among the 14 indicators. The gray relational grades of other specific factors related to rainfall were also large and had dominant effects on sediment yield. The effects of vegetation type and vegetation coverage on sediment yield were small relative to other indicators; however, the gray relational grades for vegetation type and vegetation coverage were large (0.5851 and 0.5393, respectively); therefore, sediment

As shown in **Table 3**, during PPS, it is clear that the slope aspect had the strongest impact on the runoff, with a GRG of 0.6681. The GRG for the soil steady infiltration rate was 0.6524, below only the slope aspect. The third factor was the rainfall amount, with a GRG of 0.6417, followed by rainfall duration, with a GRG of 0.6303. For the rainfall intensity, the GRG for I15 was the largest, and the relationship with runoff was similar. The influences of vegetation type and cover on the runoff were intermediate among the 13 factors and both with GRG values higher than 0.6. The smallest GRG value was I30 and the value was 0.5406 for the 13 factors, which is higher than 0.5. Therefore, all the 13 factors were closely related to

During PLR (**Table 3**), the rainfall duration replaced the slope aspect as the most critical factor affecting the runoff with a GRG of 0.7443. The GRG for vegetation type was 0.6757 and ranked second among the 13 factors. The rainfall amount ranked third with a GRG of 0.6415, and its influence on runoff showed no change in comparison with PLR. The GRG of the soil steady infiltration rate was ranked fourth (GRG, 0.6231), indicating a strong effect on runoff. I10 was the most critical factor among the rainfall intensity parameters. The influences of slope gradient and vegetation cover on runoff showed little changes. The influence of slope aspect on runoff showed a particularly notable decrease,

vegetation type (**Table 2**).

*Soil Moisture Importance*

yield and vegetation are very closely related.

**3.3 Factors affecting runoff**

ranking only at the 11th.

runoff.

**128**

**Table 4** shows that during PPS, the influence of soil bulk density was significantly higher than that of the other factors, with a GRG of 0.8113. The average rainfall intensity ranked second, with a GRG of 0.7444, followed by the soil steady infiltration rate. Among the rainfall intensity factors, I30 had the closest relationship with sediment yield. The GRG for vegetation type was 0.6487, indicating that this factor is more closely related to sediment yield than vegetation cover. The smallest GRG value was 0.5945, indicating that all the factors had close relationships with sediment yield.

During PLR, I10 replaced the soil bulk density as the most significant factor affecting the runoff, with a GRG of 0.8012. The GRG values of I5, I15, I30, and average rainfall density were high among the 14 factors, indicating that rainfall intensity had the most important relationship with sediment yield during PLR. The rainfall duration ranked from the 10th to the 5th. In contrast, the soil bulk density ranked the 10th from the 1st during PPS, illustrating that the influence of the soil bulk density changed substantially during PLR. At the same time, the rank of soil steady infiltration rate was down to the eighth from the third. The rank of runoff moved up in comparison with PPS. The effects of vegetation type and vegetation cover on sediment yield were reduced according to the GRG analysis. The rank of slope aspect added, while the rank of slope gradient was down.

#### **3.5 Runoff and sediment yield under different vegetation types**

Significant differences were observed among the treatments in terms of runoff and sediment yield during PPS and PLR (**Figure 6**). The runoff and sediment yield during PPS were remarkably larger than during PLR, especially for P. During PPS, the runoff was 13.55-fold higher than that during PLR, and the sediment yield was 3.13-fold higher than that during PLR. In the analysis of grassland during PPS, the


#### **Table 4.**

*Gray relational grade between sediment yield and its influential factors.*

variations in soil water content in the early stage of vegetation recovery and because surface runoff differed as topography varied (**Figure 1** and **Table 1**). Low soil water content affects the infiltration capacity of soil water. If soil water content is high, soil infiltration is slow; therefore, runoff generation from excess rain leads to soil erosion [25, 26, 75–79]. The effect of rainfall intensity on runoff and sediment yield in a high runoff year was ranked from high to low, from I5, I10, I15, to I30. However, the ranking of the effect of rainfall intensity on runoff and sediment yield in most years was I30, I15, I10, and I5. Both rankings are related to the soil water content

*Soil Erosion Influencing Factors in the Semiarid Area of Northern Shaanxi Province, China*

The weights of different factors on runoff differed significantly during PPS and PLR (**Figures 2** and **3**). **Table 3** shows that the weight significance order of the factors was topography>soil>vegetation>rainfall during PPS and the order was vegetation>rainfall>topography>soil in PLR. During PPS, the plot environments were severely degraded by trampling and digging (**Figure 2**). Slight soil disturbances do not produce serious runoff or soil erosion problems [80, 81]. In the study areas, the surface soil was destroyed, and the vegetation was heavily reduced with low vegetation coverage and canopy. The vegetation growth conditions became poor and were fragile at this time; however, stable and suitable vegetation was an

during the early stage of rainfall.

*DOI: http://dx.doi.org/10.5772/intechopen.92979*

be produced at each runoff plot [89].

runoff [43].

**131**

**4.2 Effects of land disturbance and restoration on runoff**

effective method for reducing runoff and sediment yield [25, 82, 83].

spondingly decreased [39, 61, 84]. At the same time, vegetation roots were

the decrease in water erosion rates with increasing root mass is exponential.

destroyed; vegetation roots can modify the structure of soil pores and can improve the soil infiltration capacity, thus reducing runoff [16, 85–88]. It has been noted that

The soil surface was degraded in an irregular manner by the construction of runoff plots; therefore, the disturbances in each plot were quite different. Thus, the soil characteristics were significantly changed, especially the soil bulk density and soil steady infiltration rate. At the same time, the topography of each plot was also affected, especially the microtopography. Wilcox et al. noted that disturbances can modify surface topographical features and change the vegetation patch structure, eventually decreasing water storage within the hillslope [39]. Mohr et al. found that the impact of microtopography on surface runoff connectivity and water-repellent properties is the first-order control for hydrological and erosion processes. Therefore, during PPS, the weights of soil and topography were greater than those of vegetation and rainfall. Thus, topography and soil were major influential factors on

However, due to the different vegetation succession stages, the processes of runoff and soil loss are complicated and uncertain in terms of the interaction of

During PPS, the influence of vegetation on runoff is relatively weak, ranking the third (**Table 3**). We speculated that the protective function of vegetation on runoff was small, because during this period, all the runoff plots collected large amounts of runoff after rainfall events (**Figure 6**). Rainfall ranked fourth, for the same reason as vegetation: as long as there are rainfall-runoff events, large amounts of runoff can

In this study, we found that trampling and digging quantitatively decreased plant cover and vegetation, reduced soil aggregate stability, reduced soil fertility, and therefore lead to increased runoff. When the land was disturbed and the plant cover decreased, canopy interception of raindrops was low (**Figure 2** and **Table 1**). All these changes resulted in decreased mulches in the runoff plots, and thus the soil surface could not be effectively protected. This situation led to decreased rainwater infiltration and soil moisture content, and the threshold of runoff generation corre-

**Figure 6.** *Annual runoff and sediment yield during PPS and PLR for five different vegetation types.*

runoff and sediment yield were 8.59-fold and 1.70-fold than those for PLR. In addition, the fold differences between PPS and PLR for the RPa, RPb, and R vegetation types in terms of runoff were 4.81, 4.60, and 3.07; the fold differences in sediment yield were 1.35, 2.17, and 2.03. This result demonstrates that vegetation recovery can effectively reduce the runoff and sediment yield.
