Knowledge Resource Center for Ecological Environment in Arid Area
| 由AMSR-E和CMORPH数据制作稿时间分辨率土壤湿度产品 | |
| 其他题名 | Research of high time resolution soil moisture product generated from AMSR-E and CMORPH |
| 席家驹 | |
| 出版年 | 2014 |
| 学位类型 | 硕士 |
| 导师 | 文军 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 土壤湿度是陆面水文和气象过程的重要影响因子和环境参量，影响着陆-气间水分与能量的交换，在许多方面都有着重要的研究和应用价值。但土壤湿度受到地形、植被覆盖及降水分布等因素的影响，有着较大的空间异质性。而当今中尺度气象模式、水文模式、天气气候预报以及作物长势监测等实际应用对于土壤湿度资料的时空分辨率有着较高的要求。为了获得高时间分辨率（1h）和高空间分辨率（10km）的土壤湿度产品,本文以中国科学院寒区旱区环境与工程研究所2010年的野外土壤湿度观测网为依托，进行了高级微波扫描辐射计/地球观测系统(Advanced Micro-wave Scanning Radiometer/Earth Observation System, AMSR-E)土壤湿度产品在青藏高原的适用性研究及玛曲地区前期降水估算土壤湿度(Antecedent Precipitation Index for Soil Moisture, API4SM)模型的建立、发展和验证等两方面的研究工作，最终获取了玛曲地区高时间分辨、高空间分辨率，同时具有一定精度的土壤湿度产品。\n 首先，本文对比分析了三种目前国际上比较广泛关注的AMSR-E土壤湿度产品。首先，利用实验观测数据评价了三种土壤湿度产品的精度，分析了不同植被覆盖和降水对被动微波遥感反演土壤湿度精度的影响。结果表明：被动微波卫星遥感反演土壤湿度在平坦裸露地表具有较高精度，卫星降轨观测数据估算土壤湿度与实测资料相关系数大于0.7，均方根误差小于0.16，但在高密度植被区域误差较大，相关系数小于0.7，均方根误差最大可达到0.2；之后，分析了降水发生时土壤湿度的变化，结果表明：三种产品精度均有不同程度下降，但NASA产品的相关系数仍然能够达到0.69。在此基础上，本研究制作了青藏高原地区土壤湿度时空分布图，分析了三种产品在青藏高原地区的时空分布特征及其适应性，发现这三种土壤湿度产品在土壤湿度值的变化范围上均存在较大误差。\n 然后，本文建立、发展了API4SM模型，并运用玛曲地区的中国气象局制作的基于美国气候预测中心(CPC Morphing Technique, CMORPH)卫星反演降水数据的融合降水产品，通过API4SM模型计算得到了玛曲地区高时空分辨率的土壤湿度产品。结果表明：局地土壤水分平衡原理能够用于估算空间分布土壤湿度，并且获得较好的估算结果。但土壤温度、前期土壤水分及地形对于估算过程有较大的影响。验证发现：API4SM模型在玛曲地区能够较好的模拟土壤湿度的变化，实测点验证相关系数大于0.68，平坦区域相关系数大于0.78，并且具有小于0.1m3/m3的均方根误差。7月份降水量的增加使得降水对土壤湿度的影响增大，各验证点估算值与实测值的相关系数基本都大于夏季半年的相关系数。但由于模型对于地形因素考虑不足，使得降水量的增加会放大地形因素所带来的误差，导致了7月份各验证点的均方根误差也明显高于夏季半年。为了减小地形因素所带来的系统误差，本文将API4SM模型的估算结果与AMSR-E土壤湿度产品进行融合，结果显示：最终的土壤湿度产品的湿度值范围处于0.2至0.5m3/m3的合理区间，能够准确描述玛曲地区土壤湿度的时空特征及其变化趋势。\n综上所述，本文运用AMSR-E土壤湿度产品和CMORPH融合降水产品，通过API4SM模型获得了玛曲地区高时间分辨率、高空间分辨率的土壤湿度产品。能够为气象模式、气候预测和农作物监测等应用提供土壤湿度数据支持。 |
| 英文摘要 | Soil moisture is an important factor and environmental parameter that affects the land surface hydrological and meteorological processes. It has important application value in many aspects. The terrain of Maqu in the Yellow River source is complex because of staggered flat areas and hills. The temporal and spatial variability of soil moisture in Maqu is strong. In order to get the high time resolution(1H) and high space resolution (10km)soil moisture products of the Yellow River source region, data of field soil moisture observation network and precipitation data offered by Cold and Arid Regions Environmental and Engineering Research Institute of Chinese Academy of Sciences was used to evaluate the applicability of the AMSR-E(Advanced Microwave Scanning Radiometer/Earth Observation System) soil moisture products in the Qinghai-Tibet plateau and build Antecedent Precipitation Index for Soil Moisture(API4SM) model which can generate a high time resolution and high space resolution soil moisture product.\n In the first place, to evaluate the accuracy of soil moisture estimated by passive microwave remote sensing, three kinds of Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture products have been inter-compared and analyzed. Firstly, the ground measured soil moisture data was used for evaluating the precision of three kinds of soil moisture products and analyzing the effects of different vegetation coverage and precipitation on passive microwave soil moisture estimates. For this purpose, four soil moisture observation networks, which were displayed in the Qinghai-Tibet Plateau, were taken into account to ensure that this experiment considered most Land cover types. The results showed that the estimated soil moisture in flat and bare soil area is more accurate with its correlation coefficient above 0.7 and RMSE below 0.16, while in the high vegetation density area, the correlation coefficient is less than 0.7 and RMSE can reach to 0.2. In general, NASA’s soil moisture product performs well in all Land cover types with stable relativity. VUA’s soil moisture product has less RMSE in high soil moisture areas. Otherwise JAXA’s soil moisture product’s relativity rises in low soil moisture areas. Especially in the area where soil moisture less than 0.12m3/m3, JAXA’s soil moisture product has highest correlation coefficient in three kinds of soil moisture products. It shows potential for drought monitoring. When precipitation occurs, the accurate of three kinds of soil moisture products all decrease in different degrees. But NASA’s product sustains preferable stability with a 0.69 correlation coefficient. Based on this, the soil moisture maps of the Qinghai-Tibet Plateau are generated to analyze space-temporal distributed characteristics of the three kinds of soil moisture products. It proves that NASA’s and VUA’s soil moisture products are in well agreement with actual situation. In addition, monthly variations of NASA’s and VUA’s soil moisture are basically the same with monitoring results of China Meteorological Administration. But the magnitudes of these two kinds of soil moisture products have a great difference with actual situation. While JAXA’s soil moisture product is not in accordance with the reality in spatial distribution in the northwest and southeast of Qinghai-Tibet Plateau.\n In the second place, the soil moisture products of Maqu were calculated through API4SM model using CMORPH satellite precipitation data. The results show that: the soil water balance principle can be used to estimate the local spatial distribution of soil moisture and obtain good results. But the soil temperature, initial soil moisture and topography have significant effects on the estimation process. The API4SM model can simulate the change of soil moisture well in Maqu area. The correlation coefficient with the measured soil moisture is greater than 0.68.In the flat region, the correlation coefficient is greater than 0.78, while the root mean square error is less than 0.1m3/m3. In July, increased precipitation has a greater influence on soil moisture. The estimated soil moisture with has a higher correlation coefficient in July than the half year in summer. But because of the less consideration of terrain factor, the increase of precipitation will amplify the error caused by terrain, which makes the root mean square error in July are higher than those in half year of summer. In order to reduce the system error caused by terrain factors, the estimation results of API4SM model and AMSR-E soil moisture products were used to make a fusion. The results show that: the fusion result has a reasonable range of 0.2 to 0.5m3/m3. The temporal and spatial change trend of soil moisture in Maqu area can be described accurately.\n In summary, through the API4SM model，soil moisture products with high time resolution and high spatial resolution in Maqu area were generated using the AMSR-E soil moisture products and the CMORPH fusion precipitation products, Which can provide the soil moisture data for the meteorological model, prediction of climate and crop monitoring . |
| 中文关键词 | 微波遥感 ; 降水 ; 土壤湿度 ; 时间分辨率 |
| 英文关键词 | Microwave Remote Sensing Precipitation Soil Moisture Time Resolution |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 环境工程 |
| 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/2XILL650/287404 |
| 推荐引用方式 GB/T 7714 | 席家驹. 由AMSR-E和CMORPH数据制作稿时间分辨率土壤湿度产品[D]. 中国科学院大学,2014. |
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