顾及环境物理因子的时序InSAR冻土形变建模与分析

Recently, under the effects of global climate warming and human activities, the permafrost in Qinghai-Tibet Plateau degrade significantly, which leads to remarkable environmental problems, such as water and soil loss, grasslands degeneration and environment deterioration, and threatens the safety of important projects and facilities in the Plateau. Wide-range and high-resolution permafrost deformation monitoring can provide important information for permafrost active layer thickness inversion and degradation assessment. However, currently using InSAR to monitor permafrost deformation adopts pure mathematics model, ignoring the effects of surrounding physical factors, which not only limits the accuracy of monitoring results, but also poses difficulty to the subsequent parameters inversion. .This project will firstly investigate the relevance between permafrost deformation and surrounding physical factors (e.g., ground temperature, air temperature, precipitation and solar radiation, etc.), followed by selection of surrounding physical factors that are highly related to permafrost deformation. Then we develop a new Multi-temporal InSAR (MT-InSAR) observation model that accounts for surrounding physical factors, and design a strict method to solve it. Finally, we invert the permafrost physical parameter (such as freezing and thawing depth, active layer thickness) and assess the permafrost status and variation, based on the monitored deformation. This project will improve our understanding on the process of widespread permafrost freezing and thawing, and the accuracy and reliability of MT-InSAR. In addition, it will benefit the exact and rapid detection of destruction caused by permafrost deformation, and the assessment and prevention of potential geohazard.

近年来，在全球气候变暖和人类活动干扰下，青藏高原冻土出现了严重退化，引起了水土流失、草场退化和环境恶化，还威胁着高原上重点工程和设施的安全。大范围、高分辨率的冻土形变监测可以为活动层厚度反演和冻土退化评估提供重要信息。但是，目前InSAR监测冻土形变时采用的基本上是纯数学模型，没有考虑环境物理因子的影响，不仅限制了监测精度，也给后续参数反演带来了困难。.本项目拟从分析冻土形变与环境物理因素（如地温、气温、降水、太阳辐射等）的关联性入手，甄选出与冻土形变密切相关的环境物理因素，建立顾及环境物理因素的时序InSAR观测模型及严密解算方法，并基于冻土形变结果反演冻土物理参数（如冻融深度、活动层厚度），评估冻土现状及变化。本项目对提高人类对大面积冻土冻融过程的认识、改善时序InSAR的精度和可靠性具有重要的科学意义，对准确、快速探测冻土引发的地表破坏，以及进行潜在的治理和评价具有重要的社会意义。

目前InSAR监测冻土形变时采用的基本上是纯数学模型，没有考虑环境物理因子的影响，不仅限制了监测精度，也给后续参数反演带来了困难。鉴于此，本项目从分析冻土形变与环境物理因素的关联性入手，甄选出与冻土形变密切相关的环境物理因素(气温和降水)，建立顾及环境物理因素(气温和降水量)的时序InSAR观测模型，并在引入参数的同时，采用了考虑观测精度的加权最小二乘方法进行参数的解算；在进行InSAR数据处理时，为减少误差对形变结果的影响，提出了潮汐模型改正算法，提高形变监测结果的精度。在此基础上，分析了获取的冻土区地表形变与环境物理因素的相关性，定量的揭示了它们之间的内在关联性。并且建立了根据土壤一维热传导方程或简化的冻土沉降模型及InSAR冻土形变结果反演高空间分辨率的活动层厚度的理论和方法，拓宽了InSAR技术在冻土监测中的应用。本项目对提高人类对大面积冻土冻融过程的认识、改善时序InSAR的精度和可靠性具有重要的科学意义，对准确、快速探测冻土形变引发的地表破坏，以及进行潜在地质灾害的评价和治理具有重要的社会意义。项目发表期刊和会议论文16篇。