Knowledge Resource Center for Ecological Environment in Arid Area
| 基于热惯量法和BBH模型的黑河流域土壤水分反演与模拟研究 | |
| 其他题名 | Study on Soil Moisture Retrieval and Simulation in Heihe River Basin Based on Thermal Inertia Method and BBH Model |
| 马春锋 | |
| 出版年 | 2012 |
| 学位类型 | 硕士 |
| 导师 | 王维真 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 黑河流域地处中国西北河西走廊，是典型的中国西北干旱区。水资源问题一直是该地区经济社会发展的障碍。近年来，随着工农业的快速发展，这一问题更加突出。土壤水分是黑河流域陆表水中极其重要的组成部分，是连接地气之间水分交换、能量平衡的纽带，更是农作物和牧草生长的关键因子。因此，在黑河流域开展土壤水分研究具有重要的科学意义和应用价值。\n 本论文以黑河流域表层土壤水分为研究目标，分别以热惯量遥感反演和BBH模型模拟为研究方法，以MODIS地表温度和地表反射率产品、黑河中上游自动气象站观测资料、土壤质地数据（HWSD）等为基础，分别获取了站点尺度和流域尺度上的土壤热惯量、土壤水分。主要的研究工作包括以下三个方面：\n 1）以MODIS地表温度产品和地表反射率数据为基础，从土壤热传导方程出发，建立真实热惯量模型，在反演了模型中昼夜最大温差、地表反照率等关键参数的基础上，反演得到了黑河流域的土壤热惯量，为研究流域土壤水分提供了可靠方法和数据。利用地面站点的四分量辐射、土壤温度、土壤热通量等数据估算了地表温度、反照率、土壤热传导率和土壤热容等，验证了各反演结果。在此基础上，分析了地表昼夜最大温差、地表反照率及土壤热惯量的季节变化规律和空间分布特征，对比了真实热惯量模型与表观热惯量模型的反演结果与土壤水分的相关性。结果表明：地表昼夜最大温差、地表反照率及土壤热惯量都具有明显的季节变化特征；土壤热惯量受土壤水分等控制，呈现出中上游相对较高，下游很低的空间分布格局；真实热惯量较表观热惯量与土壤水分更相关，因此真实热惯量模型更适合土壤水分的反演。\n 2）在黑河流域土壤热惯量反演的基础上，利用土壤质地数据，提取土壤含沙量、孔隙率、容重等参数，根据经验模型计算土壤热传导率、土壤热容等参数，再分别根据经验公式和土壤热惯量的定义计算了干土和饱和土的热惯量。将计算出的土壤热惯量与遥感反演的土壤热惯量进行归一化处理，得到归一化函数，根据土壤收缩曲线，推算了土壤含水量，从而达到反演土壤水分的目的。利用站点观测的土壤水分对遥感反演结果进行了验证，结果表明，真实热惯量模型反演的土壤水分与实测的土壤水分有一定的相关性，两者具有一致的变化趋势。土壤水分的趋势变化分析表明：黑河流域土壤水分受降雨、蒸发、灌溉、径流等因素影响，具有明显的季节性变化特征；土壤水分还呈现中上游含量较高，下游含量低的空间分布格局。\n 3）利用黑河中上游两个自动气象站的观测资料，采用BBH（Bucket with a Bottom Hole）模型模拟计算了中游农田和上游草地下垫面的土壤水分，并与实测数据进行了对比，模拟误差不超过5%，模拟值的变化趋势和实测值趋势一致。表明该模型模拟流域土壤水分有一定的精度，能够满足农田水分预测和灌溉需水分析的要求，而且该模型需要的参数较少，计算过程简单，获取数据容易，能够满足不同下垫面的土壤水分的模拟要求，具有一定的实用意义。采用参数同定法对模型的参数进行了敏感性分析，确定了模型参数的适用范围和敏感程度。并在结合模型模拟与实际观测的基础上，探讨了农田和草地土壤水分的变化规律，结果发现，土壤水分冬春两季变化平缓，夏秋两季变化剧烈。 |
| 英文摘要 | Heihe River Basin (HRB) lies in Gansu Corridor of northwest China, which is a typical arid-semiarid district. The water issue has been an obstacle to economic and social development of the region，Especially in recent years with the rapid development of agriculture and industry , this problem is more prominent. Soil water content is one of the utmost components of land surface water in Heihe River; it is the link of energy balance between land and atmosphere; it is also the key factor of crop and grass. Thus, it is of scientific significance and applied value to study the soil moisture in this district.\n In this study, soil moisture of Heihe River Basin was taken as the study objective, thermal inertia remote sensing retrieval and simulation with BBH model as the methods, MODIS LST and Reflectance products, AWS data, soil texture data as the basic data, ArcGIS, ENVI/IDL, ERDAS software as the basic tools. Soil thermal inertia and soil moisture of stations scales and basin scales were obtained respectively. The principal research contents include the follows:\n Real thermal inertia model was established with the start of the thermal conduct equation basing the MODIS LST and reflectance data. After the retrieval of diurnal temperature difference, land surface albedo and other key parameters in the model, we retrieved the soil thermal inertia of HRB. Thus, we could supply means and data for the study of soil moisture. Besides, land surface temperature, albedo, soil heat conductivity and soil heat capacity estimated by four-component radiation, soil temperature and soil heat flux of the AWS data were used to validate the results. Under this condition, we analyzed the temporal variation character and spatial distribution character of diurnal temperature differences, surface albedo and soil thermal inertia. We contrasted the correlations of soil moisture between real thermal inertia (RTI) model and the apparent thermal inertia (ATI) model. The result showed that: diurnal temperature differences, surface albedo and soil thermal inertia had apparent seasonal variation features; under the control of soil moisture, soil thermal inertia was relatively high at the upper and middle reaches, low in the down reaches;\n RTI was more relative to soil moisture than ATI, thus, it was more suitable for soil moisture inversions.\n Under the basis of retrieval of remote sensing, soil texture data were used to get sand content, porosity, bulk density and so on. The thermal inertia of dry soil and saturated soil were computed according to empirical formula and definition of thermal inertia respectively. Then computed the Kp function with the thermal inertia by remote sensing inversion and computed above. Soil water content computed according to soil shrinkage curve, to as to achieve the purpose of the soil moisture retrieval. At the same time, the soil moisture retrieved by remote sensing was validated using the stations data. The result showed that soil moisture retrieved by RTI and measured in stations had certain correlations, both of which had consistent trend. The analysis of soil moisture trend showed it varied seasonally depending on the precipitation, evaporation, irrigation and running off. Soil moisture showed high in the upper reaches higher and low in the down reaches.\n Automatic Weather Station (AWS) data of Yingke station in middle reaches and Arou station in upper reaches of Heihe River were used to simulate the surface soil moisture. Comparing with the observations, the results showed that the model which simulated soil moisture content with high accuracy can meet the requirements of farmland water prediction and analysis of irrigation water demand. In addition, the model has the advantages of requiring fewer parameters, simple calculation process and easily data acquisition. So we can get a conclusion that the model is of practical significance in the region. Besides, parameters’ sensitivity was analyzed with the titration of the parameters, and then the applicable range and sensitivities of model parameters were determined. Variation of soil water content was also discussed on the basis of combination of simulations and observations. The result shows that soil moisture changes slowly during spring and winter, while sharply during summer and autumn. |
| 中文关键词 | 黑河流域 ; 土壤水分 ; 土壤热惯量 ; BBH模型 ; 参数敏感性分析 |
| 英文关键词 | Heihe River Basin Soil moisture Soil thermal inertia BBH model Sensitivity analysis of parameters |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 地图学与地理信息系统 |
| 来源机构 | 中国科学院西北生态环境资源研究院 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287072 |
| 推荐引用方式 GB/T 7714 | 马春锋. 基于热惯量法和BBH模型的黑河流域土壤水分反演与模拟研究[D]. 中国科学院大学,2012. |
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