基于SAR的多数据源呼伦湖地下水补给与水文过程研究

Hulun Lake is located in semi-arid Hulun Buir Prairie central region of north China with high latitudes, which is one of the most sensitive lakes responding to global climate change. Groundwater resource for Hulun Lake is hot issue in arid inland district. However, as Hulun Lake basin is located in the junction of China, Mongolia, and Russian, depth research and convincing conclusions is deficient because of lack of systemic ground measurement information. Aiming at this background, a set of technique based on synthetic aperture radar(SAR) is now proposed and will be carried out in this project. Firstly, topographic structure and water change model is established based on SAR image, while filtering, enhancement, recognition, segmentation, and extraction technology in SAR image is developed for Hulun Lake. Secondly, the amount of groundwater recharge in Hulun Lake is determined, by utilizing the balance between amount of water, as well as remote sensing and ground measurements, such as precipitation, evaporation and runoff. Thirdly，position of groundwater spring in Hulun Lake will be found, by cyanobacteria observation in summer and lake ice monitoring in winter through SAR technique. Finally, sources of Hulun groundwater recharge will be investigated by environmental isotope tracer technique, with deuterium, oxygen, tritium, strontium and carbon sampling and analysis for related peripheral area of Hulun Lake. This project will improve the existing Hulun hydrological model, while important theoretical and engineering application values can be also expected from these researches.

呼伦湖位于中国北方高纬度半干旱的呼伦贝尔草原中心区，属于对全球变化响应最敏感的湖泊之一。呼伦湖地下水资源属于干旱内陆流域湖泊环境热点问题，但由于呼伦湖流域跨中、蒙、俄边界，相关资料的系统性较差，导致研究深度和可信服结论性认识有限。本项目以SAR技术为基础：1)发展适用于呼伦湖的SAR图像滤波、增强、识别、分割、提取等技术，并结合呼伦湖地形结构，建立基于SAR图像的呼伦湖水量变化模型。2)运用遥感及地面测量手段，确定呼伦湖流域降水量、蒸发量及径流量，利用水量平衡关系，确定呼伦湖地下水补给量。3)在夏季、冬季分别以蓝藻和湖冰作为标识物，通过SAR技术观测呼伦湖中的蓝藻变化和结冰过程，确定呼伦湖地下水泉眼位置。4)利用环境同位素示踪技术，对呼伦湖周边及相关区域进行采样及环境同位素氘、氧、氚、锶、碳等分析，研究呼伦湖地下水补给来源。本项目将完善现有呼伦湖水文水循环模型，并为未来相关研究提供借鉴。

呼伦湖位于中国北方高纬度半干旱的呼伦贝尔草原中心区，属于对全球变化响应最敏感的湖泊之一。呼伦湖地下水资源属于干旱内陆流域湖泊环境热点问题，但由于呼伦湖流域跨中、蒙、俄边界，相关资料的系统性较差，导致研究深度和可信服结论性认识有限。本项目以SAR技术为基础：1)发展适用于呼伦湖的SAR图像滤波、增强、识别、分割、提取等技术，并结合呼伦湖地形结构，建立基于SAR图像的呼伦湖水量变化模型。2)运用遥感及地面测量手段，确定呼伦湖流域降水量、蒸发量及径流量，利用水量平衡关系，确定呼伦湖地下水补给量。3)通过SAR技术观测呼伦湖中的蓝藻变化和结冰过程，对呼伦湖水环境进行监测。4)利用环境同位素示踪技术，对呼伦湖周边及相关区域进行采样及环境同位素氘、氧、氚、锶、碳等分析，研究呼伦湖地下水补给来源。科研主要贡献如下：.1）基于高分辨遥感影像及水文测量数据，通过深度学习算法建立湖泊、林地及农田演化的时间序列，结合土壤水渗透测试、水化学和同位素特征分析，揭示了呼伦湖蓝藻爆发原因及外源地下水的重要补给作用。.2）提出一种基于夜光遥感和互联网链接索引的区域间联系指数模型，深度解析长时间尺度下城市群空间扩展特征，定量计算各城市间相关性，为城市群的时空变化研究提供了遥感—互联网大数据交互框架。.3）提出基于集合卡尔曼滤波对流域长短时降水进行同化的方法，明显改善了降水卫星的降雨估计值，可为进一步提高水文预报、洪水预警的准确性提供可靠数据基础。本项目将完善现有呼伦湖水文水循环模型，并为未来相关研究提供借鉴。