Improved parameterization of groundwater flow models using interferograms and adjoint sensitivity analysis

使用干涉图和伴随灵敏度分析改进地下水流模型的参数化NSF #0943415雷达干涉测量法提供了盆地范围内高精度垂直形变数据的采集，这些数据揭示了大量抽水的沉积盆地中地面沉降的空间复杂性和结构依赖性。例如，在拉斯维加斯山谷，干涉合成孔径雷达干涉图描绘了以盆地填充断层为边界的分隔沉降碗。已知地裂缝发生在许多这样的断层附近，从干涉图中可以观察到这些断层的差异沉降。恢复水位与减少地下水抽水在夏季和严格的ASR计划在冬季的几个月导致了季节性模式的沉降和反弹，反映在干涉合成孔径雷达时间序列数据。提出了一种新的建模策略，使这些季节性的变形模式与观测到的水位数据相结合，以量化的存储特性的含水层和封闭单元在一个像素分辨率的干涉图，或约40米。使用这些观测结果的逆模型受到以下事实的阻碍，即用于存储和水力传导率的参数区域分布通常是用户定义的，并且通常以特别的方式制定。这项研究的目的是开发一种基于伴随的参数估计模型，系统地产生最佳的存储和导电区的分布，导致一个上级概念模型，并产生不仅是最好的参数分布，但提供必要的细节，以反映在拉斯维加斯谷观察到的复杂的故障有界的存储碗。这项拟议的研究的更广泛的影响是显着的，因为他们解决了社会经济和水文地质问题所面临的拉斯维加斯谷使用多学科的方法。拉斯维加斯谷的经济福祉取决于可开发土地的长期增长和管理。这项研究将提供一个高分辨率的地下水和沉降模型，可在未来用作水管理工具。伴随为基础的参数估计模型（APE）在这项研究中开发的自动化区域中使用的反模型。这种新的模型提供了一个明显的优势，技术需要分析的许多替代模型。这个新的建模包将提供给所有建模从业者。一名外联协调员将利用佛蒙特州地球科学博物馆向包括PK-12学生、教师、本科生和公众在内的受众提供地下水和水资源教育。在计划的讲习班期间，将使用一个地下水物理模型来指导教师和示范安全用水做法。将为高中教室和博物馆制作一张海报和工作表，以突出弗吉尼亚理工大学的地下水研究，以吸引更多未来的地下水科学家。

Improved Parameterization of Groundwater Flow Models using Interferograms and Adjoint Sensitivity AnalysisNSF #0943415 Radar interferometry provides for the acquisition of basin wide high precision vertical deformation data that reveal the spatially complex and structurally dependent nature of land subsidence in heavily pumped sedimentary basins. In Las Vegas Valley, for example, InSAR interferograms portray compartmentalized subsidence bowls bounded by basin-fill faults. Earth fissures are known to occur adjacent to many such faults where differential subsidence is observed from interferograms. Recovering water levels associated with reduced groundwater pumping during summer months and a rigorous ASR program during winter months have resulted in seasonal patterns of subsidence and rebound that are reflected in the InSAR time-series data. A new modeling strategy is proposed whereby these seasonal deformation patterns are coupled with observed water-level data to quantify the storage characteristics of the aquifer and confining units at a pixel resolution of the interferogram, or about 40m. Inverse models that use these observations are hindered by the fact that parameter zone distributions for storage and hydraulic conductivity are typically user defined and often formulated in an ad-hoc fashion. The objective of this proposed research is to develop an adjoint-based parameter estimation model that systematically produces the optimal storage and conductivity zone distributions that leads to a superior conceptual model and yields not only the best parameter distribution, but provides the details necessary to reflect the intricacies of the fault-bounded storage bowls observed in Las Vegas Valley. The broader impacts of this proposed research are significant because they address the socioeconomic and hydrogeologic problems facing Las Vegas Valley using a multi-disciplinary approach. The economic well being of Las Vegas Valley is dependent on long-term growth and management of developable land. This research will provide a high-resolution groundwater and subsidence model that can be used as a water-management tool well into the future. The adjoint-based parameter estimation model (APE) developed in this research automates zones used in inverse modeling. This new model provides a distinct advantage over techniques requiring analysis of numerous alternative models. This new modeling package will be made available to all modeling practitioners. An Outreach Coordinator will use the VT Museum of Geosciences to provide groundwater and water resources education to audiences that include pK-12 students, teachers, undergraduates and the general public. A physical groundwater model will be used during planned workshops to instruct teachers and demonstrate safe water practices. A poster and worksheet will be developed for high school classrooms and for the Museum to highlight Virginia Tech groundwater research in an effort to attract more future groundwater scientists.