Exploring the capabilities of electrical resistivity tomography to study subsea permafrost
Exploring the capabilities of electrical resistivity tomography to study subsea permafrost
复制标题
DOI：
10.5194/tc-16-4423-2022
复制
发表时间：
2022-10-20
期刊：
影响因子：
5.2
通讯作者：
Tronicke, Jens
中科院分区：
文献类型：
--
作者：
Arboleda-Zapata, Mauricio;Angelopoulos, Michael;Tronicke, Jens
海平面上升和海岸侵蚀淹没了北极大面积的永久冻土。与陆地上的陆上融化相比，温暖和盐水沃茨增加了淹没的永久冻土融化的速率。研究海床下未冻结和冻结沉积物之间的接触，也称为含冰永久冻土表（IBPT），为了解水下永久冻土的演变提供了有价值的信息，这是改进和了解海岸侵蚀预测模型和潜在温室气体排放的关键。在这项研究中，我们使用的数据来自2D电阻率层析成像（ERT）收集在近岸海岸带的两个北极地区，不同的环境条件（例如，海水深度和电阻率）来成像和研究海底永久冻土。2D ERT数据集的反演通常使用有利于平滑解的确定性方法来执行，该方法通常使用用户指定的电阻率阈值来解释以识别IBPT位置。相反，在反演过程中直接针对IBPT位置，我们使用基于层的模型参数化和全局优化方法来反演我们的ERT数据。这种方法的结果在合奏分层的2D模型的解决方案，我们用它来识别IBPT和估计电阻率的解冻和冻结沉积物，包括估计的不确定性。此外，我们在全球范围内反演一维合成电阻率数据，并进行敏感性分析，以更简单的方式研究我们的模型参数的相关性和影响。在这项研究中提供的一套方法可能有助于进一步利用在这样的永久冻土环境中收集的ERT数据，以及未来的现场实验的设计。
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.