Study on the impact of vegetation degeneration to hydrology characteristic of the Alpine soil

YiBo Wang , QingBai Wu , FuJun Niu , GenXu Wang , HuiYan Cheng

1. Laboratory of Frozen Soils, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China 2. College of Earth and Environment Science, Lanzhou University, Lanzhou, Gansu 730000, China 3. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China 4. Lanzhou University of Technology, Lanzhou, Gansu 730000, China

Study on the impact of vegetation degeneration to hydrology characteristic of the Alpine soil

YiBo Wang1,2*, QingBai Wu1, FuJun Niu1, GenXu Wang3, HuiYan Cheng4

1. Laboratory of Frozen Soils, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China 2. College of Earth and Environment Science, Lanzhou University, Lanzhou, Gansu 730000, China 3. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China 4. Lanzhou University of Technology, Lanzhou, Gansu 730000, China

Alpine soil infiltration process is an important part of the hydrological characteristics of alpine soil in permafrost. This research is carried out in the source region of the Yellow River where the permafrost is severely degraded, using various methods for choosing typical sample areas, and to experiment, study and simulate the soil water curve, soil saturated hydraulic conductivity, soil infiltration and soil moisture under different characteristics of degraded vegetation. The results indicate that the empirical equationθ=AS-B, proposed by Gradner and Visser, is very reliable in simulating the soil moisture curve; soil saturated hydraulic conductivity and soil infiltration are significantly different under different vegetation coverage: in the soil surface within 0–10 cm, the saturated hydraulic conductivity and infiltration intensity of Black Beach are the strongest; respectively, in soil layers below 30 cm,vegetation has almost no impacts on the saturated hydraulic conductivity, infiltration intensity and soil moisture content. Significant reduction of soil moisture occurs in soil surfaces with degraded vegetation. The more serious the degradation, the more water loss, and it can be up to 38.6% in the worst situation. Soil moisture of developed vegetation root systems in depths within 10–20 cm has the greatest impact on the soil environment, and the loss of moisture induces difficulty in the restoration of degraded meadows. Through a comparative study, the Kostiakov infiltration equationf(t) = at-bis more applicable for studies on the process of soil moisture infiltration of the alpine meadow in the source region of the Yellow River.

vegetation degradation; alpine soil; soil infiltration

1. Introduction

The alpine ecosystem of the headwaters of the Yellow River is a special system with a simple structure which can be easily damaged, and if ecological degradation occurs,recovery will be difficult. In recent years, the ecological environment of the study area, in the headwaters of the Yellow River, is being destroyed at an accelerated rate as a result of population growth, global climate change, and natural resources exploitation (Wanget al., 2001; Liet al., 2004).There are numerous detrimental effects on the deteriorating ecological environment, for example, the area of available grassland has decreased, the water-oil loss has been aggravated, and soil productive capacity has been reduced considerably. The widely distributed meadows and grasslands are the dominate plant communities in the headwaters of the Yellow River, which serves as the main grassland ecological types of the study area. Hydrological processes of alpine areas are affected by many factors such as soil structure,change of surface vegetation coverage, distribution of frozen soils, soil thickness, precipitation, and the precipitation process (Sunet al., 2001; Yanget al., 2002). In recent years,vegetation of alpine-like meadows in the headwaters of the Yellow River has undergone significant degradation (Wanget al., 2003). As a result, hydrological processes of the study area have become very complicated. The two major factors of hydraulic characteristics for these meadows and grasslands are soil and infiltration processes. Soil infiltration is an important part of the water cycle, and spatial variation of soil hydraulic characteristics is the main factor which affects the migration of moisture and solutes (Zhan and Huang, 2000).Also, hydraulic characteristics influence the infiltration process. Soil infiltration is the process by which precipitation or irrigation water enters into the soil from the surface(Jiang, 1997; Zhao and Wu, 2004). This process is one part of the soil moisture movement and one key link of transformation among ground, soil, surface, and atmospheric waters(Liu and Kang, 1999; Zhao and Wu, 2004; Liuet al., 2009).There is a close connection between soil infiltration and natural phenomena’s such as surface runoff, soil moisture redistribution, soil erosion, and nutrient migration with moving water. This investigation on hydraulic characteristics of soil, soil saturated hydraulic conductivity, and infiltration process of alpine-like meadows and grasslands in the headwaters of the Yellow River provides a solid foundation in our understanding of hydrological features and processes over various periods. Ultimately, this knowledge can provide a theoretical basis for ecological protection and restoration of headwater areas of rivers.

2. Materials and methods

2.1. General study area

The study area is located in Dari county (33°45'N,99°39'E) in the headwaters of the Yellow River, where the average altitude is 4,000 m, in a typical seasonal frozen area with an annual average temperature of -0.22 °C, rainfall of 546.6 mm, and evaporation of 1,219.3 mm. The county-wide average temperature ranges from -0.1 to -3.5°C, with an extreme high temperature of 20.1 °C, and extreme low temperature of -27.6 °C. This area belongs to an alpine semi-humid climate through out the year, with only two seasons, cold and warm. Due to the complex topography, rock properties, slopes and vegetation, the zonal distribution characteristics of frozen soil are not evident. There are three main alpine soil types in the headwaters of the Yellow River, steppe, meadow, and cold desert. There are also three major alpine vegetation types in the study area, shrub meadow, weed meadow, and grassland. Alpine meadow and grassland are the dominant vegetation types, with mat shaped vegetation and sparse vegetation of debris beach distributed in local high altitude zones. The dominant plant species in the study area includesKobresia pygmaea,K.humilis,K. capillifolia,Stipaaliena,Potentilla multicaulis,K.tibetica, andLeontopodium.

In the study area, we first tested indices such as soil moisture, soil water infiltration rate, and saturated conductivity process of samples with different vegetation including Songxian grass meadows, shrub meadow, degraded grassland, and seriously degraded Black Barren. We then performed a comparative study. According to actual conditions,we picked sites with different types of plant communities which are all at shady slope with gradient (20%–25%). We also selected eight locations with different degradation degrees for soil infiltration experiments. Among these locations are two sites without degradation with vegetation coverage of higher than 85%, two with moderate degradation and vegetation coverage (35%–40%, 45%–50% respectively), two with severe natural degradation and vegetation coverage (5%–20% and 15%–30% respectively), and two with serious degradation called Black Barren.

2.2. Soil moisture measuring method

The characteristic curve of soil moisture, which serves as the main content of hydraulic properties, is measured by a high speed refrigerated centrifuge (SCR20). The soil is saturated when the infiltration rate is maintained at a stable level. After that, the soil sample is centrifuged under various speeds for about 90–120 r/min. Finally, we weigh the sample and obtain the soil water content.

When the speed isni(r/min), the soil substrate forceSi(Pa) is:

whereRis the centrifugal radius (cm).

?gis the soil gravimetric moisture content ofSi:

wherergis the dry density (g/cm3).

2.3. Saturated hydraulic conductivity

The characteristic curve for soil moisture is measured by 2800K1, which is a positioning instrument that can be installed at the desired depth. The index is measured three times at one position, and then we average the three values to obtain the mean value. Therefore, we obtain soil moisture with different vegetation coverage and different soil depths. The data is also recorded every two minutes. We observe the declining liquid surface height in units of time,and record the value when the apparent surface speed is at a stable level over 3–5 continuous intervals. Find out the average liquid surface drop speed and call itR1(cm/s),R1is in the initial hydraulic (H) conditions speed, usually the initial hydraulic (H) value is 5 cm. Once there is a stable value,i.e., a continuous interval of time where the liquid surface descending speed is the same, then we stop the flow. And then the hydraulic is adjusted for 10 cm, and repeat the above operation without moving the equipment, until measured the liquid surface average declinedR2(cm/s).Saturated conductivity water rateKfsand water potentialψmcan be calculated according to the following formula in the field determination.

When using internal and external water of the two storage tubes, we use the following formulas:

When using only internal storage tube water, we use the following formulas:

whereX,Yare water supply area respectively for internal and external storage tube water and only internal storage tube water. Respectively,Xis 35.39 cm2,Yis 2.14 cm2.

2.4. Infiltration process

Rainfall simulation and the 2-ring infiltration device are two test methods that can be used to study the laws and features of soil water infiltration process for a degraded alpine ecosystem. The 2-ring infiltration device is used by the Water Resources Department at Xi’an University of Technology to measure the process of soil water infiltration in the field. The instrument is composed of improved Marriott containers and circular concentric double casing ring. Marriott containers (Markov tube) are sealed and controlled by an air valve, with an inlet valve which opens or closes the sealed lid on the top, and an outlet at the bottom at the same level as the glass water meter. The outlet connects with the test soil. The changes of infiltration volume correlated with time can be deduced by changing water level.

First, we set up the Marriott container on the site and debug it, select a suitable location for the experiment, and then take down lower the original water level of Marriott container. Second, we open the water gate by pulling up the rubber plug with organic ring when the water flows into the infiltration ring. At the same time, a stopwatch is started to record the time. When the water level of the infiltration ring reaches the bottom of the organic glass ring, rapidly plugged the small hole use the rubber plug, then record the drop in water height at every interval (5 or 10 minutes) until the infiltration water is basically stable for four consecutive time intervals.

The amount of infiltration will decrease after a period of time. In order to improve sensitivity, we should shut one of the two inlet valves. During the whole test process, we should add water to the outer ring to keep the surface heights of the outer and inner ring at the same level. After the test,we use the cup of water metering to measure the volume of water remaining in the organic ring. Thus, we can easily calculate the amount of water initially added.

We use a self-made device to simulate rainfall in the experiments. There are several parameters (Gaoet al., 2000)for this device, such as maximum height of rainfall (2.0 m)which can be adjusted, pressure gauge readings is 0.3×10-3Pa, repeatability error of rainfall intensity (1.5%–5.5%),uniformity coefficient of rainfall (0.92–0.99), and simulated rainfall intensity (0.4 mm/min–10.0 mm/min). Within this study, locations with different vegetation coverage of alpine meadows are measured respectively.

2.5. Soil moisture

We use ground auger and TDR to test soil moisture with different vegetation species. At the same time at each site,we tested soil moisture at various depths. We should also measure the volume of soil moisture of the same soil sample three times, then average the three to find the mean value of this sample.

3. Results and analysis

3.1. Soil hydraulic parameters

3.1.1 Soil moisture curve

The soil moisture curve can reflect the interactions between soil water and soil solids (the function between adsorption force, capillary force and soil water). The curve also reveals the relationship between soil water energy index(matrix suction) and quantitative index (matrix suction).sample sites were chosen based on different types of vegetation and coverage, and soil samples were obtained at various depths (generally 0–20 cm and 20–50 cm). Then tested the soil moisture feature curve (Table 1).

Analytical results of the exponential curve can be clearly seen in Table 1. First, we can conclude that the difference of soil moisture content of samples at various depths at one site is rather small when the samples are under the same soil water suction, and the soil profile is homogeneous. Thus, the soil water content can be demonstrated by one characteristic curve of soil moisture (Figure 1). At each measurement site, the average of soil moisture content of samples at various depths is considered to be the value of this location. The relationship between soil moisture content (θ, cm3/cm3) and soil water suction (S, 0.1 MPa) fits with the power function empirical formulas and index empirical formula, respectively. We find that the best regression equation isθ＝19.67S-0.1816, and the correlation coefficientRis 0.9975.

It is evident that the empirical equationθ=AS-B, which was put forward by Gradner (1970), fits well with the soil moisture curve of this area (Hua and Wang, 1993; Graham and Butts, 2005). The height of the curve is determined by the value of A which represents the water holding capacity.When the value of A is large, the holding water capacity is strong. The curve trend is decided by the value of B which indicates the changing rate of reducing soil moisture content with decreasing soil water. The values of A and B are mainly determined by soil texture (such as organic matter and soil structure), and the soil texture at the test bed is known to be sandy loam. When the soil water suction is below 0.1 MPa,the corresponding curve is steep, when the suction is over 0.1 MPa, the corresponding curve is flat. Within the narrow range of suction (lower than 0.1MPa), the volume of water retained or released by the soil mainly depends on the capillary force. In contrast, at high suction level (higher than 0.1 MPa), the volume of water retained or released by the soil mainly depends on the adsorption force (Lei, 1988). Because the pores of sandy loam are large, the capillary force is weak.Therefore, water within the large pores is easily released under small soil water suction. In contrast, water in small pores will be released only when the suction is large enough.Therefore, we conclude that soil texture (especially the large pore size of the sandy loam) determines the low ability of retaining water of alpine meadow soil in the headwaters of the Yellow River.

Table 1 Soil volumetric water content (%)

Figure 1 The average soil moisture exponential curve at 0–50 cm depth

3.1.2 Soil saturated conductivity water rate

There is a close relationship between soil saturated conductivity water rate and soil structure, density and pore characteristics. According to our test results, the relationship between soil hydraulic conductivity and soil depth is logarithmic (Figure 2). Soil hydraulic conductivity decreases with the increase of soil depth. There are three major types of vegetation in the study area, with vegetation coverage for alpine weed meadow of 80%, alpine shrub meadow of 60%, and Black Beach of 5%. Through experimentation, we find a logarithmic relation between soil guide water rate and soil depth which exists for all samples with the three different vegetation types. However, there are considerable differences among these logarithmic curves (Table 2). Among soil samples with a depth of lower than 10 cm, the largest conducting water rate is found at Black Beach. The low soil moisture content at Black Beach is due to lack of protection of the soil surface.Conducting water rate of samples at alpine weed meadow is larger than that of alpine shrub meadow because there are innumerable tiny guide water channels and water-saving spaces as a result of root distribution. Additionally, alpine meadow soil is rich in organic matter and minerals, and these substances are strong hydrophilic. This leads to an increased loss of soil moisture due to plant growth and plant transpiration. The changing rate of guide water to soil sample depth (10–60 cm) is stronger at the weed meadow (98%)than at Black Beach (85%) and shrub meadow (60%).Among soil sample layers with depths of 30–60 cm, the changing speed for guide water rate is minimal at Black Beach (38%). Guide water rate of shrub meadow and weed meadow is continuously decreasing, which shows that vegetation has a certain influence on soil guide water rate.Among soil sample layers with a depth of 30 cm, conducting water rate at both meadows is minimal as a result of shallow(usually at 5–20 cm) root systems of the grassland vegetation. Therefore, it is difficult for moisture within the 30 cm layer to be removed by the vegetation. Thus, soil moisture content is large and guide water rate is low. In a typical gully model, the shrub and weed meadow grasslands are seriously degraded due to the widespread use of miscellaneous poisons. This leads to the disappearance of the dominant species, replaced with opportunistic species of low vegetation coverage on thin soils (only 20–40 cm), and a tremendous amount of sand and gravel. Among all samples of the three major vegetation types, the soil water rate experiment proves that the changing rate of infiltration for the grass meadow is the highest, while the conducting water rate at Black Beach is the highest. This indicates that soil porosity, particle structure, and water permeability changes along with vegetation degradation. Vegetation types and plant community structure become simpler, plant roots become shallow, and surface soil is severely eroded. This leads to soils with coarsening particles and increasing soil permeability which is easy to dry out (Peng, 1995; Bao and Chen, 1999; Niu,1999; Guoet al., 2004). As a whole, these changes severely affect the soil guide water rate.

Figure 2 Soil saturated hydraulic conductivity at various depths

Table 2 Relationship between soil hydraulic conductivity (Kfs) and soil depth (h)

3.2. Soil infiltration process

Infiltration is the main process of soil hydrology which is an important link of mutual transformation between precipitation, surface water, soil water and groundwater. It is of great theoretical and practical significance to investigate the soil infiltration process for surface runoff reduction, soil infiltration growth, soil erosion prevention, and ecological environment improvement. Soil water infiltration process is an extremely complex process under great effects of the physical and chemical properties of soil, precipitation and permafrost (Chenget al., 2004). In theory, soil infiltration process belongs to the 2-d movement consisting of vertical and lateral infiltration while field observation generally refers to only vertical infiltration (Jiang and Huang, 1986).Soil water infiltration capacity determines the size of runoff and the level of soil erosion, and at the same time influences the amount of soil moisture, groundwater, and underground runoff. Outside of China, relevant research on infiltration is focused mainly on: 1) the Horton infiltration model and the Philip formula (Philip, 1957); 2) solving the flow continuity equation; 3) the quantitative analysis (Numerical analysis method) of infiltration effect factors (mainly profile level-oriented, surface crust and rainfall); 4) numerical analysis of soil moisture during the process of redistribution(Yao and Cheng, 1986).

3.2.1 Results

The most common model:

The Kostiakov formula is as follows:

wheref(t) is the infiltration rate (cm/min);tis the infiltration time (min); and a, b are the data fitting parameters of the test.a is the begin permeation ratio, and b is reduce degree of infiltration velocity time.

The Horton experiential formula (Horton, 1940) is as follows:

wheref(t) istmoment instantaneous infiltration rate;fcis the steady infiltration rate;f0is the initial infiltration rate; andkreflect soil characteristics of parameters;tis the infiltration time (min).The Philip formula is as follows:

wheref(t) istmoment instantaneous infiltration rate;tis the infiltration time; and A, B are test obtained parameters. This is a hypothetical formula based on the theory of saturated infiltration, and according to the simplest of physical soil models, introduces a one-dimensional water infiltration equation.

The General empirical formula is as follows:

wheref(t) istmoment instantaneous infiltration rate;tis the infiltration time; and a1, b1,nare parameters obtained by the test (a1amounts to steady infiltration rate).

3.2.2 Model simulation and analysis

According to the preceding four infiltration models (Han and Wu, 2004; Wanget al., 2004), shallow soil water infiltration process of eight kinds of alpine meadows with different vegetation types, different coverage and different degradation degree was analyzed by SPSS, respectively(Figure 3).

As can be seen from Figure 3, the Kostiakov formula for different vegetation types and coverage changes between 4.4706 and 18.119, and the minimum value occurs when coverage for Songxian grass meadows exceeds 90%. In contrast, the maximum values occur at samples with coverage of 50%–60% such as the Songxian grass meadows. The higher the initial water content, the larger the bulk density.With a smaller 'a' value, corresponding infiltration rate is smaller. The value range for 'b' is 0.2669–0.7931. The larger the 'b' value, the faster the infiltration rate decreases with time. Infiltration ratio of the meadows and Black Beach decreases rapidly and the infiltration rate of thickets reduce slower. There are numerous parameters influencing infiltration rate, such as soil thickness, degree of soil compaction,and degree of root density. Therefore, the permeability of alpine meadows with high organic matter content, loose structure, and large porosity is higher than that of thickets. In addition, water infiltration rate is high for Black Beach due to high degradation and large particle gaps.

When we use the Horton formula to fit the experimental results,fc(steady infiltration rate) ranges from 0.2759 to 2.5817. The steady infiltration rate of the shrub meadow with high coverage (over 90%) is the largest, while that of the weed meadow with low coverage (30%) is the lowest.Kchanges within the range of 0.0271–0.0453. This change determines the decreasing speed from initial infiltration rate to steady infiltration rate. Infiltration rate of the weed meadow reduces faster than that of the shrub meadow, and the infiltration ratio of Black Beach, which is seriously degraded, also decreases rapidly.f0-fcranges from 2.1319 to 4.2206. With the same vegetation coverage, the initial infiltration rate of the shrub meadow is higher than that of the weed meadow. After degradation, the initial infiltration rate of secondary grass and Black Beach is also high.

When we use the Philip formula to fit the experimental results, the value of parameterAranges between 5.0613 and 19.3721. The minimum value appears in Black Beach with a high degree of degradation, while the maximum value appears in the meadows with 50%–60% coverage. In the general empirical formulas, parameter a1amounts to the steady infiltration rate. The product of b1andt-nreflects the changing rate of infiltration. The larger the product of b1andt-nis, the more quickly the infiltration rate drops. Infiltration ratio of the weed meadow and Black Beach with serious degradation changes rapidly, however, that of shrub meadow reduces slowly. Secondary grassland after degradation often shows a similar infiltration trend with the weed meadows and shrub meadow (both with low vegetation coverage), and is involved with elements such as soil structure, secondary grass root structure, soil bulk density,and moisture content. This shows that there is a close relationship between the changing rate of soil infiltration and vegetation coverage.

Fitted values of the four various infiltration formulas(given above) were compared with the measured value to determine the fitting degree, respectively, as follows (Figure 3).

As can be seen from Figure 3, the permeation rate drastically changes at the beginning, then alters slightly, finally achieves stability. According to this law, the soil infiltration process can be divided roughly into three stages, transient(0–15 min), infiltration gradient (15–60 min), and infiltration stable (after 60 min). Measured infiltration rates of soils with different vegetation types and coverage are listed in Table 4.At the same time, according to the graphs of the best fit curve below, the fitting degree is divided into three levels,good (+ +), better (+), and poor (-).

From Table 3, we can see that there are considerable differences among the initial soil infiltration rates, the steady infiltration rates, and the time elapsed to reach steady infiltration rates, of samples with eight vegetation types. Soil water infiltration is a complicated hydrologic process and it has a close connection with surface runoff, surface soil structure, density and soil moisture. In alpine meadows,there are large differences of soil permeability because it is influenced by other factors, such as dominant vegetation types, vegetation coverage, organic matter content, and root distribution.

It can be concluded from Table 4 that during the transient and gradient stages of infiltration, the Kostiakov and Philip formulas fit better than the Horton and general empirical formulas. However, during the stable stage, all four formulas fit well. Both the Kostiakov and Philip formulas fit ideally while the Kostiakov formula is the best with respect to the fitting results ofR2. Thus, it is evident that the Kostiakov infiltration formulaf(t) = at-bis the most suitable equation for the alpine meadows soil water infiltration process in the study area.

Figure 3 Fitting comparison of four different infiltration models of Alpine Meadow with different coverage

Table 3 Infiltration rate of various land types at different times (mm/min)

Table 4 Fitting evaluation of infiltration equation and experimental observations

3.2.3 Change of soil water infiltration of samples with different vegetation coverage

Soil infiltration is an important part of the hydrological process in alpine meadow areas, and it not only directly determines the amount of surface runoff, but also affects soil water content and groundwater dynamics. Infiltration also plays a key role in vegetation growth and recovery in the headwaters of the Yellow River. Soil infiltration experiments were performed in four experimental sites of various vegetation coverage in the headwaters of the Yellow River. Despite the differences among water infiltration rates, the sites share similar changing trends (the initial infiltration rate is large and diminishes rapidly with increasing amount of infiltration)(Figure 4). It is also the experiments that at the beginning,soil infiltration rate of samples with high vegetation coverage is lower than that of samples with low vegetation coverage. Therefore, initial infiltration rate of Black Beach is the largest (generally 3–5 times larger than meadows with better vegetation). In the subsequent process, the soil infiltration rate of all samples with various coverage remains at a stable level. Infiltration process of meadows with high vegetation coverage is slowed down by plant roots; therefore the surface soil moisture content can easily reach saturation. In contrast, after a heavy rainfall, soil at Black Beach with coverage of less than 5% is eroded much more seriously than at sites with higher vegetation coverage. Also, the surface water at Black Beach with coverage of less than 5% is depleted at a more rapid rate than that of sites with high vegetation coverage. With this knowledge of the infiltration process, we can explain some familiar phenomenon at Black Beach with low vegetation coverage, such as surface drying, serious soil erosion, and difficult vegetation restoration.

3.3. Change of soil moisture

Soil moisture is one feature of soil hydrology, and there is a tight connection between soil moisture and vegetation.Vegetation degradation can impact surface soil features,such as soil water supply, migration and evapotranspiration,and ultimately influences soil internal hydrological processes. In particular, in the permafrost area of the Qinghai-Tibet Plateau, under the influences of frozen soil, vegetation, and climate factors, the hydrological processes is very complex and polytrophic. As seen in Table 5, vegetation degradation greatly influences soil moisture content, espe-cially for layers at depths of 15–20 cm (equaling the depth distribution of plant roots). As the vegetation coverage reduces from 85% to 30% and 5%, soil moisture content of the same layers are significantly reduced, dropping by 10.8% and 38.6% in the 0–5 cm layer, and by 11.3% and 32.7% in the 15–20 cm layer, respectively. It is significant that the reduction of Black Beach soil is maximum, as the vegetation coverage dropped from 90% to lower than 5%,and soil moisture decreased by 43% accordingly. The impact of vegetation change on soil water content is relatively minor in soil samples at depth of over 30 cm. In samples of Black Beach, soil moisture content increases below 30 cm,with growth characteristics of cold adapted plant of the Qinghai-Tibet Plateau as one major explanation. In anoxic conditions of the alpine, plant root depth is generally shallow (0–25 cm), thus the direct effects of plant growth process on deep soil moisture is minimum. Accordingly, the influence of vegetation degradation on deep soil water is minor. Due to vegetation degradation, and reduced effects of water retention and interception on the surface, water can migrate intensively and permeate deep into the soil in large volumes. This is the reason why soil moisture content rises slightly and then remains stable for samples at depths of over 40 cm in Black Beach. This indicates that vegetation degradation in alpine regions have a direct effect on soil hydrological features. Shallow (0–30 cm) soil moisture is modified due to vegetation degradation, and the reduction of soil moisture has an adverse effect on the formation of soil nutrients, plus exchange and migration of soil composition,which eventually reduces soil fertility. There are several typical characteristics of surface soil at Black Beach without vegetation protection, such as serious erosion, increased loss of water, reduced holding water capacity, decreased soil nutrients and other ingredients, and poor ability to recover.

Figure 4 Soil infiltration changes in different vegetation coverage (10–20 cm)

Table 5 Soil moisture content changes in different vegetation coverage

4. Conclusion

(1) There are several structures of alpine meadows, including gravel, powdery and clastic composition, and the texture is sandy loam or light loam. Experimental results show that equation (θ=AS-B) put forward by Gradner(1970) fits well with the soil moisture curve for this area.The connection between soil moisture content (θ, cm3/cm3)and soil water suction (S, 0.1 MPa) is fit by the power function empirical formulas and index experience formula,respectively, and we find that the best regression equation isθ＝19.67S-0.1816, and corresponding correlation coefficient is 0.9975.

(2) There are three main vegetation types in the headwaters of the Yellow River, Songxian grass meadows, shrub meadows, and Black Beach. The changing rate of the saturated conductivity water rate of samples with depths of 10–60 cm, and vegetation types referred above are 59.7%,86.1%, and 98.3%, respectively. Soil guide water rate of Songxian grass meadow changes most evidently with increasing soil depth. In soil layers with depths of 0–10 cm,the saturated conductivity water rate of Black Beach is the largest under the combined effects of vegetation coverage,root distribution, soil particle structure, and soil water permeability.

(3) Infiltration process of alpine meadows with various vegetation and dominant species is observed in the field.Four infiltration models are used to fit the test data, meanwhile, soil infiltration process is divided into three stages including transient (0–15 min), infiltration gradient (15–60 min) and infiltration stable (above 60 min). The fitting results indicate that both Kostiakov and Philip formulas are more suitable, and the Kostiakov infiltration formula,f(t)=at-b, is the best equation for soil water infiltration process of alpine meadows in the study area. Under simulated rainfall conditions, the infiltration process of soils at depths of 10–20 cm with high vegetation coverage is slowed down by roots;accordingly, surface soil moisture can easily reach saturation.Meanwhile, soil hydraulic erosion of Black Beach with high degree of vegetation degradation is much more serious than meadows of high vegetation coverage.

(4) Soil water of alpine meadows changes with vegetation degradation. Soil water of samples with depths of 0–20 cm is significantly altered. When the vegetation coverage reduces from 85 to 5%, surface soil moisture is reduced by 38.6% (0–5 cm) and by 32.7% (main root layer roughly 15–20 cm), respectively. The direct effect of vegetation degradation on soil moisture content is weak when soil depth is over 30 cm. This is mainly because vegetation degradation reduces soil holding capacity of water, thus, soil water migration process and the environment changes while correspondingly soil infiltration and evaporation increases.

This work was supported by the Global Change Research Program of China (2010CB951404); in part by the Important Orientation Projects of the CAS (KZCX2-YW-Q03-04); The Outstanding Youth Foundation Project, National Natural Science Foundation of China (Grant No. 40625004); The State Key Program of National Natural Science of China (Grant No.41030741); The State Key Laboratory of Frozen Soil Engineering Open Fund (SKLFSE200804).

Bao WK, Chen QH, 1999. The degraded processes and features of ecosystem. Chinese Journal of Ecology, 18(2): 36–42.

Cheng GW, Yu XX, Zhao YT, 2004. Hydrological Cycle and Mathematical Modeling in Mountain Forest Ecosystems. Science Press, Beijing.193–227.

Gao XM, Li ZL, Jia X, 2000. Development and application of artificial rainfall device. Radiation Protection, 20(2): 86–90.

Graham DN, Butts MB, 2005. Flexible integrated watershed modeling with MIKE SHE. In: Singh VP, Frevert DK (Editors). Watershed models.CRC Press, New York. 25–40.

Gardner WR, 1970. Field measurement of soil water diffusivity. Soil Science Society of America Proceedings, 34(5): 832– 833.

Guo ZG, Cheng GD, Wang GX, 2004. Plant diversity of alpine meadow in the northern region of the Tibetan Plateau. Journal of Glaciology and Geocryology, 26(1): 95–100.

Han B, Wu QX, 2004. Study on the characteristics of soil infiltration ofPinus tabulaeformisstand in the loess hilly areas. Protection Forest Science and Technology, 5: 1–3.

Horton RE, 1940. An approach toward a physical interpretation of infiltration capacity. Proceedings of Soil Science Society of America, 5: 339–417.

Hua M, Wang J, 1993. Soil Physics. Beijing Agricultural University Press,Beijing. 12–21.

Jiang DS, 1997. Soil Erosion and Treatments Model in Loess Plateau. China Water Power Press, Beijing. 32–46.

Jiang DS, Huang GJ, 1986. Soil infiltration rate of the Loess Plateau Reasearch. Chinese Journal of Soil Science, 23(4): 299–304.

Lei ZD, 1988. Soil Water Dynamics. Tsinghua University Press, Beijing.10–18.

Li DF, Tian Y, Liu CM, 2004. Distribution hydrological simulation of the source regions of the Yellow River under environmental changes. Acta Geographica Sinica, 59(4): 265–273.

Liu GS, Wang GX, Hu HC, Li TB, Wang JF, Ren DX, Huang YJ, 2009.Influence of vegetation coverage on water and heat processes of the active layer in permafrost regions of the Tibetan Plateau. Journal Glaciology and Geocryology, 2(1): 89–95.

Liu XZ, Kang SZ, 1999. Some developments and review of rainfall-infiltration-runoff yield research. Bulletin of Soil and Water Conservation, 19(2): 57–62.

Niu YF, 1999. The study of environment in the Plateau of Qing-Tibet. Progress in Geography, 18(2): 163–171.

Peng KS, 1995. A study on the problems of environment degradation of China in the 21st century. Tropical Geography, 15(1): 1–9.

Philip J, 1957. The theory of infiltration. Soil Science, 83(5): 345－357.

Sun R, Liu CM, Zhu QJ, 2001. Relationship between the fractional vegetation cover change and rainfall in the Yellow River Basin. Acta Geographica Sinica, 56(6): 667–672.

Wang GX, Shen YP, Liu SY, 2001. The vegetation cover over last 20 years in Yellow River Basin. Journal of Glaciology and Geocryology, 23(1):16–21.

Wang GX, Shen YP, Qian J, Wang JD, 2003. Study on the influence of vegetation change on soil moisture cycle in alpine meadow. Journal Glaciology and Geocryology, 25(6): 653–659.

Wang JM, Wu QX, Han B, Dai XY, 2004. Distribution law on infiltration of Loess hilly region. System Science and Comprehensive Studies in Agriculture, 20(4): 288–290.

Yang ST, Liu CM, Sun R, 2002. The vegetation cover over last 20 years in Yellow River Basin. Acta Geographica Sinica, 57(6): 679–684.

Yao XL, Cheng YS, 1986. Soil Physics. Agriculture Press, Beijing. 17–30.

Zhan WH, Huang GH, 2000. A review of study on fractals of soil hydraulic properties. Advances in Water Science, 11(4): 457–462.

Zhao XN, Wu FQ, 2004. Developments and reviews of soil infiltration research. Journal of Northwest Forestry University, 19(1): 42–45.

10.3724/SP.J.1226.2011.00233

*Correspondence to: Dr. YiBo Wang, Associate Professor of College of Earth and Environment Science, Lanzhou University,No.222, South Tianshui Road, Lanzhou, Gansu 730000, China. Email: yibo_wang@163.com

7 January 2011 Accepted: 2 March 2011