Fengpeng Han

Application of the SCS-CN Model to Runoff Estimation in a Small Watershed with High Spatial Heterogeneity

For reasons of simplicity, the most commonly used hydrological models are based on the Soil Conservation Service Curve Number (SCS-CN) model, which is probably a good choice for the estimation of runoff on the Loess Plateau of China; however, the high spatial heterogeneity, mainly caused by a fragmented landform and variations in soil type, may limit its applicability to this region. Therefore, applicability of the SCS-CN model to a small watershed, Liudaogou on the plateau, was evaluated and the most appropriate initial abstraction ratio (Ia/S) value in the model was quantified by the inverse method. The results showed that the standard SCS-CN model was applicable to the estimation of runoff in the Liudaogou watershed and the model performance was acceptable according to the values of relative error and Nash-Sutcliffe efficiency. The most appropriate Ia/S value for the watershed was 0.22 because with this modified Ia/S value, the model performance was slightly improved. The model performance was not sensitive to the modification of the Ia/S value when one heavy rainfall event (50.1 mm) was not considered, which implied that the model, using a standard Ia/S value, can be recommended for the Liudaogou watershed because single rainfall events exceeding 50 mm seldom occurred in that region. The runoff amount predicted for the Liudaogou watershed by the SCS-CN model, using the modified Ia/S value, increased gradually with increasing rainfall when rainfall values were lower than 50 mm, whereas the predicted amount increased rapidly when the rainfall exceeded 50 mm. These findings may be helpful in solving the problem of serious soil and water loss on the Loess Plateau of China.

The Combined Effects of Moss-Dominated Biocrusts and Vegetation on Erosion and Soil Moisture and Implications for Disturbance on the Loess Plateau, China

Biological soil crusts (BSCs, or biocrusts) have important positive ecological functions such as erosion control and soil fertility improvement, and they may also have negative effects on soil moisture in some cases. Simultaneous discussions of the two-sided impacts of BSCs are key to the rational use of this resource. This study focused on the contribution of BSCs while combining with specific types of vegetation to erosion reduction and their effects on soil moisture, and it addressed the feasibility of removal or raking disturbance. Twelve plots measuring 4 m × 2 m and six treatments (two plots for each) were established on a 15° slope in a small watershed in the Loess Plateau using BSCs, bare land (as a control, BL), Stipa bungeana Trin. (STBU), Caragana korshinskii Kom. (CAKO), STBU planted with BSCs (STBU+BSCs) and CAKO planted with BSCs (CAKO+BSCs). The runoff, soil loss and soil moisture to a depth of 3 m were measured throughout the rainy season (from June to September) of 2010. The results showed that BSCs significantly reduced runoff by 37.3% and soil loss by 81.0% and increased infiltration by 12.4% in comparison with BL. However, when combined with STBU or CAKO, BSCs only made negligible contributions to erosion control (a runoff reduction of 7.4% and 5.7% and a soil loss reduction of 0.7% and 0.3%). Generally, the soil moisture of the vegetation plots was lower in the upper layer than that of the BL plots, although when accompanied with a higher amount of infiltration, this soil moisture consumption phenomenon was much clearer when combining vegetation with BSCs. Because of the trivial contributions from BSCs to erosion control and the remaining exacerbated consumption of soil water, moderate disturbance by BSCs should be considered in plots with adequate vegetation cover to improve soil moisture levels without a significant erosion increase, which was implied to be necessary and feasible.

Effects of Pisha sandstone content on solute transport in a sandy soil.

In sandy soil, water, nutrients and even pollutants are easily leaching to deeper layers. The objective of this study was to assess the effects of Pisha sandstone on soil solute transport in a sandy soil. The miscible displacement technique was used to obtain breakthrough curves (BTCs) of Br(-) as an inert non-adsorbed tracer and Na(+) as an adsorbed tracer. The incorporation of Pisha sandstone into sandy soil was able to prevent the early breakthrough of both tracers by decreasing the saturated hydraulic conductivity compared to the controlled sandy soil column, and the impeding effects increased with Pisha sandstone content. The BTCs of Br(-) were accurately described by both the convection-dispersion equation (CDE) and the two-region model (T-R), and the T-R model fitted the experimental data slightly better than the CDE. The two-site nonequilibrium model (T-S) accurately fit the Na(+) transport data. Pisha sandstone impeded the breakthrough of Na(+) not only by decreasing the saturated hydraulic conductivity but also by increasing the adsorption capacity of the soil. The measured CEC values of Pisha sandstone were up to 11 times larger than those of the sandy soil. The retardation factors (R) determined by the T-S model increased with increasing Pisha sandstone content, and the partition coefficient (K(d)) showed a similar trend to R. According to the results of this study, Pisha sandstone can successfully impede solute transport in a sandy soil column.

Spatial variability of soil organic carbon in a catchment of the Loess Plateau

Abstract The issue of soil organic carbon (SOC) is of increasing concern. Because SOC, as an important soil component in farming systems, is essential for improving soil quality, sustaining food production and quality, and maintaining water quality and as a major part of the terrestrial carbon reservoir, it plays an important role in the global carbon cycle. In this paper, a total of 665 soil samples from different depths were collected randomly in the autumn of 2007, and the spatial variability of SOC content at a small catchment of the Loess Plateau was analysed using classical statistics and geo-statistical analysis. In nonsampled areas classical kriging was utilized for interpolation of SOC estimation. The classic statistical analysis revealed moderate spatial variability with all five layers of SOC-content. In addition, the average SOC content decreased with soil depth and the relationship can be modelled by an exponential equation (y=3.1795x −1.2015, R 2=0.9866) and all of the SOC-content data in the different depth were normally distributed. The geo-statistical analysis indicated a moderate spatial dependence in 0–60 cm, while in the 60–80 cm depth spatial dependence was strong. The semi-variogram could be fitted by an exponential model for 0–10 cm depth; by a spherical model for 10–20 cm depth and 60–80 cm depth; and by a Gaussian model for 20–60 cm depth. The range increases with increasing depth. In addition, classical kriging could successfully interpolate SOC content in the catchment. In general, the geo-statistics method on a watershed scale could be accurately used to evaluate spatial variability of the SOC content in the Loess Plateau, China.

Spatial variability and distribution of soil nutrients in a catchment of the Loess Plateau in China

Abstract Inappropriate land use is one of the main reasons for soil erosion and nutrient loss in the hilly loess area of the Liudaogou catchment of the Loess Plateau, a typical topography area of hills and gullies. Good management practices, such as the nutrient variability for the different land uses (woodland, grassland, shrub land, farmland, and gully), would help the farmers. One study of the use of Geographic Information System (GIS) spatial analysis and geostatistic analysis was carried out in the catchment. The results showed that the trend of the content of clay and silt in the different soil ranks was: farmland < grassland < shrub land < gully soil. The sandy soil contained fewer nutrients than did the other soils. The farmland contains fewer total phosphorus (TP) and . The spatial dependence of the total nitrogen (TN) and the organic matter (OM) in the sandy soil is strong, but is only moderate in the other types of land use except for OM in farmland. The spatial dependence of TP in the different types of land use patterns is strong too, except in woodland, and the dependence of TP is moderate in grassland. The spatial dependence of and is not strong, especially in woodland, shrub land, and farmland. The dependence of is weak in grassland, gully, and farmland. In the catchment scale, the degree of spatial dependence (GD) is moderate for soil nutrients especially for TN and , but the different nutrients were modelled in different stationary models. The spatial variability of OM, TP, and was modelled by a Gaussian model, and the spatial variability of TN and was modelled by an exponential equation. The nutrients’ distribution in the catchment has been mapped by GIS. From the results, it was seen that annual grass played an important role in the conservation and improvement of soil quality in the Loess Plateau. In addition, the farmland should be given more fertilizer.

Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km2. A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g·kg−1. The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0–10 and 10–20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.

The WEPP Model Application in a Small Watershed in the Loess Plateau

In the Loess Plateau, soil erosion has not only caused serious ecological and environmental problems but has also impacted downstream areas. Therefore, a model is needed to guide the comprehensive control of soil erosion. In this study, we introduced the WEPP model to simulate soil erosion both at the slope and watershed scales. Our analyses showed that: the simulated values at the slope scale were very close to the measured. However, both the runoff and soil erosion simulated values at the watershed scale were higher than the measured. At the slope scale, under different coverage, the simulated erosion was slightly higher than the measured. When the coverage is 40%, the simulated results of both runoff and erosion are the best. At the watershed scale, the actual annual runoff of the Liudaogou watershed is 83m3; sediment content is 0.097 t/m3, annual erosion sediment 8.057t and erosion intensity 0.288 t ha-1 yr-1. Both the simulated values of soil erosion and runoff are higher than the measured, especially the runoff. But the simulated erosion trend is relatively accurate after the farmland is returned to grassland. We concluded that the WEPP model can be used to establish a reasonable vegetation restoration model and guide the vegetation restoration of the Loess Plateau.