Yongqiu Wu

Using contour lines to generate digital elevation models for steep slope areas: a case study of the Loess Plateau in North China

In soil erosion models digital elevation models (DEMs) play an important role. Most interpolations from contour lines fail to address multi-value cells (MVCs) problems and therefore find it difficult to deal with steep slopes. These interpolation methods randomly assign a single value for MVCs and use this value in interpolation for nearby cells. This approach is very inaccurate. The frequency of MVCs and the problem caused by them was investigated, and the errors created by using the random values for MVCs was analyzed in this paper. A special treatment for MVCs and practical solution to create more accurate interpolation cell values in DEM building was developed. The new approach involves storing additional information of contour lines that go through the MVCs, such as maximum height and minimum height values, and the cardinal orientation relationship of the contour lines. A special MVC filter kernel was developed to decide the appropriate elevation value for interpolation. The computation method is based on raster data. An area on the Loess Plateau in North China was selected as an example to demonstrate the problems of the previously common used approach and to show results of the new method.

Crop characteristics and their temporal change on the Loess Plateau of China

Abstract Crop characteristics with obvious seasonal changes strongly influence soil loss. The purpose of this study is to measure and analyze the plant characteristics and their seasonal change in the Loess Plateau. A small watershed, Danangou in the Loess Plateau of north China, was selected for this study. Crop characteristics including plant cover, plant height and leaf area index (LAI) were measured every 2 weeks in 1998, 1999 and 2000. In Danangou watershed, half of the lands used as cropland for maize, foxtail millet, pearl millet, potato, buckwheat and soybean. The remainder of the land included wasteland, fallow, shrub, woodland and orchard. The woodlands have high leaf area index (LAI) with the value of 3–7, and high cover of 40–80% in wet year and 30–50% in dry year. For shrub, the maximum height is about 1 m, 1–2 LAI, and cover 50–90% in wet year, 40–50% in dry year. The characteristics of fallow and wasteland were similar with the height of 30–50 cm in wet year and 10–20 cm in dry year. For wasteland, LAI was 1–2 in wet year and 0.3–0.5 in dry year, and cover was 30–40% in wet year and 20–30% in dry year. For fallow, LAI was 0.5–1 in wet year and 0.2–0.5 in dry year, and cover was 10–20% both in wet and dry years. For cropland, LAI, height and coverage changed greatly during the measurement season. For different crops, the range of height, LAI and cover was 0.5–2 m, 0–4.5 and 10–90%, respectively. For non-cropland, cover increased from April, reached maximum in May or June, and remained high until September or October. For croplands, cover increased later and slowly during spring, and reached highest in August. Annual precipitation has large influences on the crop characteristics, especially for crops. The individual rainfall event also has an important effect on crop characteristics. Because cropland comprises of half of the watershed, hence land use in the Danangou is not very good for soil and water conservation.

Cogitation on developing a dynamic model of soil wind erosion

Studies on soil wind erosion began with single factors affecting soil wind erosion; with increasing quantities of data being accumulated, the wind erosion equation (WEQ), the revised wind erosion equation (RWEQ), the wind erosion prediction system (WEPS), and other soil wind erosion models have been successively established, and great advances have been achieved. Here we briefly review the soil wind erosion research course and analyze the advantages and disadvantages of the current soil wind erosion models. From the perspective of the dynamics of wind erosion, we classified the factors affecting soil wind erosion into three categories, namely, wind erosivity factors (WEF), soil antierodibility factors (SAF), and roughness interference factors (RIF). We proposed the concept of a standard plot of soil wind erosion to solve the problem of uncertainty of the soil wind erosion modulus on a spatial scale, and provided methods to set similarity conditions in wind tunnel simulation experiments and to convert the spatial scale of the wind erosion modulus from the standard plot to a large scale field. We also proposed a conceptual model on the basis of the dynamics of soil wind erosion with the theoretical basis that wind produces a shear force on the soil surface. This shear force is partitioned by barely erodible soil surfaces and roughness elements on the ground, and the amount of soil loss by wind should be calculated by comparing the shear force of the wind on barely erodible soil surfaces with the anti-erosion force of the surface soil. One advantage of this conceptual model is that the calculated soil wind erosion modulus is not subject to changes of spatial scale. Finally, we recommended continual improvement of the existing models while also establishing new models.

Aeolian creeping mass of different grain sizes over sand beds of varying length

Creep is an important mode of aeolian sand transport, but it has received little attention in previous studies due to experimental difficulties and insufficient theory. In this study, we conducted 116 groups of experiments with three repeats for each group in a wind tunnel to measure the creeping mass of four different mean grain sizes (152, 257, 321, and 382 µm) over six bed lengths (2.0, 3.5, 5.0, 6.5, 8.0, and 10.0 m) at six different friction velocities (0.23, 0.35, 0.41, 0.47, 0.55, and 0.61 m/s). We attempted to develop a comprehensive model of the aeolian creeping mass by analyzing the effect of wind velocity, the particle size, and the sand bed length based on the experimental data. The primary conclusions are as follows: (1) the complex relationship among the wind velocity, the grain size, the length of the bed, and the surface shape determines sand creep. There was no unified formula to express the effect of particle sizes and the sand bed length on aeolian creeping masses, and their effects appeared to depend on each other and wind velocity, whereas the creeping mass increases with increasing wind velocity for any particle size with any length of sand bed. (2) This paper presented a predicting model to determine the aeolian creeping mass, whose calculating results can match to experimental data with correlation coefficients (R2) of 0.94 or higher. (3) The effect of grain size on creeping mass can be classified into three categories: the creeping mass increases with increasing grain size, the creeping mass initially decreases and subsequently increases with increasing grain size, and the creeping mass fluctuates with the grain size. (4) The effect of increasing bed length appears to depend on the grain size. For mean grain sizes of 152, 257, and 321 µm, creep initially increases with increasing bed length before decreasing above a certain value, while for a mean grain size of 382 µm, the creeping mass gradually increased with increasing bed length. The results help to elucidate aeolian creep and provide an intense foundation for advanced study.

Investigation of Soil Shear-Strength Parameters and Prediction of the Collapse of Gully Walls in the Black Soil Region of Northeastern China

The collapse of gully walls is an important mode of gully erosion, and it depends strongly on two soil shear-strength parameters: cohesion and the internal friction angle. However, little research has examined these parameters in Chinas black soil region. In the present study, we sampled six groups of surface soils from four different land uses, and two groups of soils at depths of 30 cm and 60 cm. The cohesion (c) and internal friction angle (φ) of each group were determined at 10 levels of water content. The results show that c increased with increasing water content until a certain level (12% for the surface soils, and 14% for the deeper soils), after which c decreased. Internal friction angle generally decreased with increasing water content. We developed a model predicting collapse of gully walls based on four parameters: dry bulk density, water content, crack depth, and the width of the soil collapse. The model predicts that soil collapse would occur at two levels of water content: dry and wet conditions. Field data showed that collapse only occurred under the wet condition; the critical mass water content given by the model is between 31.0% and 33.8% moisture.

Evolution of Peatlands in the Mu Us Desert, Northern China, Since the Last Deglaciation

(1) State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, PR China. (xiaokangliu@mail.bnu.edu.cn), (2) Engineering Center of Desertification and Blown-Sand Control of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing, PR China.(ruijielu@bnu.edu.cn), (3) Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing, PR China.

Blown sand motion within the sand-control system in the southern section of the Taklimakan Desert Highway

Although scientists have performed many studies in the Taklimakan Desert, few of them have reported the blown sand motion along the southern edge of the Taklimakan Desert Highway, which differs significantly from the northern region in terms of aeolian sand geomorphology and formation environment. Based on the field observation data of airflow and aeolian sand transport, continuous monitoring data of erosional and depositional processes between 14 April 2009 and 9 April 2011 and data of surface sand grains from the classical section along the southern edge of the Taklimakan Desert Highway, this paper reported the blown sand motion within the sand-control system of the highway. The main results are as follows: 1) The existing sand-control system is highly effective in preventing and controlling desertification. Wind velocities within the sand-control system were approximately 33%–100% of those for the same height above the mobile sand surface. Aeolian sand fluxes were approximately 0–31.21% of those of the mobile sand surface. Sand grains inside the system, with a mean diameter of 2.89 φ, were finer than those (2.15 φ) outside the system. In addition, wind velocities basically followed a logarithmic law, but the airflow along the classical section was mainly determined by topography and vegetation. 2) There were obvious erosional and depositional phenomena above the surface within the sand-control system, and these phenomena have very consistent patterns for all observation points in the two observed years. The total thicknesses of erosion and deposition ranged from 0.30 to 14.60 cm, with a mean value of 3.67 cm. In contrast, the deposition thicknesses were 1.90–22.10 cm, with a mean value of 7.59 cm, and the erosion thicknesses were 3.51–15.10 cm, with a mean value of 8.75 cm. The results will aid our understanding of blown sand within the sand-control system and provide a strong foundation for optimizing the sand-control system.

Application of Empirical Orthogonal Function (EOF) method to detect the spatial grain-size fractionation of aeolian sediment and comparison with other methods in case studies from northwestern China

Abstract A grain-size fraction/population of sediment can reflect a specific transport process. Use of this potential grain-size fraction is more meaningful than that of a single grain-size value for analysis of grain-size fractionation over space, so identifying the potential grain-size fraction is key in analyzes of grain-size fractionation. Our aim was to test the applicability of Empirical Orthogonal Function (EOF) analysis for sediment grain-size fractionation. We performed EOF analysis on grain-size data of aeolian sediment to identify the potential grain-size fraction and detect its grain-size fractionation over space. Two other methods, the grain-size-class standard deviation (GSC-std) method and end-member analysis (EMA) were conducted for comparison. The results show that the EOF method is not only able to identify the potential grain-size fraction, but also to simultaneously determine the spatial change of the potential grain-size fraction. The GSC-std method provides the potential grain-size fraction, but fails to exhibit its spatial change at the same time. EMA end members resemble a grain-size distribution that differs from the potential grain-size fraction; thus, the EMA method fails to identify the potential grain-size fraction directly. Our results suggest that EOF analysis is suitable for detecting grain-size fractionation over space.