KMS XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY，CAS
| 古尔班通古特沙漠南缘典型沙地土壤水分动态及模拟 | |
| 董义阳 | |
| Subtype | 硕士 |
| Thesis Advisor | 赵成义 |
| 2017-05-01 | |
| Degree Grantor | 中国科学院大学 |
| Place of Conferral | 新疆乌鲁木齐 |
| Degree Discipline | 理学硕士 |
| Keyword | Laio 土壤水分动态随机模型 土壤水分动态 土壤水力学参数 古尔班通古特沙漠 Stochastic model of soil moisture of Laio Dynamics of soil moisture,Soil hydraulic parameters Gurbantunggut Desert |
| Abstract | Soil moisture is the mainly limiting factor for the plant growth, vegetation succession and pattern change in arid desert area. The dynamics of soil moisture is affected by kinds of uncertainties, e.g., physical-chemical-biological processes,climate change, soil and vegetation differences. With randomness, it is more practical to simulate soil moisture evolution throughout time and space using a model based on probabilistic framework. Here, we selected the typical interdune at the southern edge of Gurbantunggut Desert as the study area in this thesis. This study was designed to investigate the soil moisture dynamics based on the field monitoring, laboratory experiment and model simulation. The relationship between the soil moisture dynamics and the precipitation characteristics was also analyzed. Using the measured soil moisture movement parameters, long-term soil moisture datasets and precipitation datasets, we simulated the soil moisture probability density function by stochastic Laio Model. The main conclusions are listed as follows.(1) Soil hydraulic parameters conformed to soil moisture dynamic chracteristics. Our results found that both the two models(VG and G) fit well with the measured soil water characteristic curves in this region. The saturated hydraulic conductivity of aeolian sandy soil in interdune was 1424.16 mm/d, which was determined using the one-dimensional horizontal infiltration method. There presented a monotonically increasing relationship between the unsaturated soil water diffusivity D(θ) and the soil water content θ.(2) Precipitation in the study area was dominated by small precipitation events(0-5 mm), accounted for 85.2% of the total events, and up to 44.7% of the total precipitation amount. The precipitation interval was dominated by 0-5 days,accounted for 53.2% of the total days without rainfall. And there showed 29.0% and 24.4% of intervals between precipitation events were from 11 days to 20 days and from 6 days to 10 days, respectively. As the precipitation intervals increased, the frequency of precipitation events decreased. (3) Soil moisture was relatively high at root-zone(0-100 cm) in the early growing season. With the temperature rising gradually, soil moisture decreased and reached the lowest basically(0.025 cm3 /cm3) at the end of the growing season. There were two distinct soil layers in the 400 cm depth. Soil water contents was significant variability in the upper 0-50 cm, and remained stable in 50-400 cm. (4) The soil moisture in sandy root-zone layer probability obeyed the T distribution with scale parameter and positional parameter in growing season. The distribution of probability density was basically unimodal, with a narrower width compared to the humid area. The peak value, position and scope of p(s) obtained by Laio model were similar to that of the measured values. Laio model had a good applicability in our study areas. For the thirteen parameters of Laio model, soil porosity, root depth, amount of precipitation intercepted by canopy cover for each rainfall event, soil moisture level below which plants begin closing their stomata, average daily evapotranspiration rate under unrestricted siol moisture conditions, average daily evaporation rate at permanent wilting point, mean of depth of rainfall events, arrival rate of rainfall events, soil moisture level below which water can not be extracted from the soil through evaporation and permanent wilting point were more sensitively, and mainly impacted the peak value of p(s) than paramater defining, along with saturated hydraulic conductivity, the relationship between soil moisture and hydraulic conductivity when an exponential law was used, saturated hydraulic conductivity, soil field capacity. |
| Other Abstract | 土壤水分是干旱荒漠地区植物生长、植被演替和格局等主要生态过程的控制因子。土壤水分动态变化受到多种物理、化学和生物过程、气候、土壤及植被等不确定性因素影响，具有随机性。论文用基于概率统计模型模拟土壤水分动态更符合实际。以古尔班通古特沙漠南缘典型丘间地为例，通过野外监测、室内实验与模型模拟相结合的方法，研究了沙地土壤水分运动以及与降水特征的关系，采用 Laio 土壤水分动态随机模型模拟了古尔班通古特沙漠南缘典型丘间地土壤水分动态随机过程。主要结论如下：（1）丘间地沙土土壤水力学参数符合土壤水分动态特征，VG 模型和 G 模型均能很好地拟合实测土壤水分特征曲线；采用一维水平入渗试验测定丘间地风沙土的饱和导水率为 1424.16 mm/d；土壤水分扩散率 D(θ)与土壤含水率 θ 呈单调递增关系。（2）研究区 0-5 mm 降水占全部降水事件的 85.2%，占全部降水量的 44.7%；0-5d 降水间隔期出现的频数最高，占降水事件的 53.2%，11-20 d 为主要间隔期，占无降水期的 29.0%，6-10 d 的降水间隔期占无降水期的 24.4%，随着间隔时间的延长，其出现的频数逐渐减少。（3）生长季初期植物根系层土壤湿度相对较高，随着气温逐渐升高，土壤水分处于衰减状态，生长季末期土壤含水率基本达到最低（0.025 cm3/cm3）。0-50 cm 土壤含水率变化明显；50-400 cm 土壤含水率基本保持稳定。（4）沙地根系层土壤水分基本服从含有尺度参数和位置参数的 t 分布，概率分布直方图呈单峰状，土壤水分的变化范围较窄。Laio 模型在古尔班通古特沙漠南缘丘间地荒漠生态系统的适用性较好。Laio 模型涉及的 13 个参数中土壤孔隙度、土壤根系层深度、植被截留阈值、水分胁迫开始点、日最大蒸散量、凋萎点对应日蒸发量、降水事件的平均降水量、降水事件的日平均降水频率、吸湿系数和凋萎系数敏感性较强，土壤孔隙大小分布参数、土壤饱和导水率和田间持水率的敏感性较弱。 |
| Subject Area | 自然地理学 |
| Language | 中文 |
| Document Type | 学位论文 |
| Identifier | http://ir.xjlas.org/handle/365004/14869 |
| Collection | 研究系统_荒漠环境研究室 |
| Affiliation | 中国科学院新疆生态与地理研究所 |
| First Author Affilication | 中国科学院新疆生态与地理研究所 |
| Recommended Citation GB/T 7714 | 董义阳. 古尔班通古特沙漠南缘典型沙地土壤水分动态及模拟[D]. 新疆乌鲁木齐. 中国科学院大学,2017. |
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