EAPSI:Aquifer System Storage Response to Canterbury Earthquake Sequence using Satellite Radar and Observation Well Time Series Data

EAPSI：使用卫星雷达和观测井时间序列数据对坎特伯雷地震序列的含水层系统存储响应

• 批准号: 1614031
• 负责人: Megan Miller
• 金额: $ 0.54万
• 依托单位: Miller Megan M
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1614031&HistoricalAwards=false
• 关键词: EAPSI; Aquifer; System; Storage; Response

The 2010-2011 Canterbury, New Zealand earthquake sequence prompted a significant hydrologic response in the form of groundwater level variations due to ground shaking. It is important to understand the extent to which the storage capacity of aquifers is affected, given the reliance of local populations on groundwater for drinking water supply. This award funds research to investigate the spatial extent and amplitude of the change in aquifer storativity due to the seismic activity. The research will be conducted in collaboration with Dr. Simon Cox, Principal Scientist at GNS Science and renowned expert in structural and hydrogeology. By analyzing seasonal patterns in ground uplift and well head levels, the fellow will estimate and compare elastic aquifer storativity before, during, and after the seismic sequence. This project will use the abundant satellite radar and well data available for the region, which acts as a natural laboratory to study aquifer-earthquake interactions. The findings will impact other earthquake prone regions with active groundwater usage, including Southern California and Tennessee, to enhance water management plans following major seismic events. Understanding the spatiotemporal extent of the interaction between aquifer systems and seismic faults is a key factor for mitigating hazards associated with liquefaction and enhancing water management plans. To this end imaging surface deformation with sufficient precision, spatiotemporal resolution, and spatial accuracy is integral to this effort. The fellow will use Interferometric Synthetic Aperture Radar (InSAR) datasets from two SAR satellites, ENVISAT and TerraSAR-X, in both ascending and descending acquisition geometries. The overlapping areas allow for calculating the vertical and horizontal displacement time series, capturing pre-, co-, and post-seismic deformation in two dimensions including both tectonic and hydrological signals. In addition, observation wells with dense temporal measurements are abundant in the Canterbury and Christchurch region. The elastic storage coefficient is estimated by comparing the isolated seasonal component of the vertical displacement and the observation well time series. To isolate these seasonal components in the signals, wavelet power spectra analysis is applied, and the desired seasonal time series is identified, isolated and reconstructed. To determine if any increase or decrease in storativity occurred during the earthquake sequence, a best-fit linear value relating the inputs is chosen within a 95% confidence interval. This study will use Christchurch and the Canterbury Plains as a case study that will ultimately help other regions prone to seismic hazards that rely on groundwater resources. This award under the East Asia and Pacific Summer Institutes program supports summer research by a U.S. graduate student and is jointly funded by NSF and the Royal Society of New Zealand.

2010-2011年新西兰坎特伯雷地震序列引发了重大的水文响应，其形式是地下水位因地面震动而发生变化。鉴于当地居民的饮用水供应依赖地下水，必须了解含水层的储存能力受到多大程度的影响。该奖项资助研究，以调查地震活动引起的含水层储存量变化的空间范围和幅度。这项研究将与GNS Science首席科学家、著名结构和水文地质专家西蒙·考克斯博士合作进行。通过分析地面隆起和井口水位的季节模式，估计和比较地震序列之前、期间和之后的弹性含水层储水量。该项目将使用该区域丰富的卫星雷达和钻井数据，该区域充当研究含水层-地震相互作用的天然实验室。这一发现将影响其他地下水使用活跃的地震多发地区，包括南加州和田纳西州，以加强重大地震事件后的水管理计划。了解含水层系统与地震断层之间相互作用的时空范围，是减轻与液化有关的灾害和加强水管理计划的关键因素。为此，具有足够精度、时空分辨率和空间精度的成像表面变形是这项工作不可或缺的一部分。该研究员将使用来自两颗合成孔径雷达卫星ENVISAT和TerraSAR-X的干涉合成孔径雷达(InSAR)数据集，在上行和下行捕获几何形状上都是如此。重叠区域可以计算垂直和水平位移时间序列，捕捉包括构造和水文信号在内的两个维度的地震前、同震和震后变形。此外，坎特伯雷和克赖斯特彻奇地区还有大量具有密集时间测量的观测井。通过比较竖直位移的孤立季节分量和观测井时间序列，估算了弹性存储系数。为了分离信号中的这些季节性成分，应用小波功率谱分析，识别、分离和重构所需的季节性时间序列。为了确定在地震序列期间是否发生了存储能力的增加或减少，在95%的置信度区间内选择与输入相关的最佳拟合线性值。这项研究将以克赖斯特彻奇和坎特伯雷平原作为案例研究，最终将帮助依赖地下水资源的其他容易发生地震灾害的地区。该奖项由东亚和太平洋夏季学院项目资助一名美国研究生的暑期研究，由NSF和新西兰皇家学会共同资助。