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

基于干涉图和伴随灵敏度分析的地下水流模型参数化改进雷达干涉测量技术可获取全盆地高精度垂直变形数据，揭示了重抽水沉积盆地地面沉降的空间复杂性和结构依赖性。例如，在拉斯维加斯谷，InSAR干涉图描绘了以盆地填充断层为界的分区下沉碗。我们知道，在许多这样的断层附近会出现地裂缝，从干涉图中可以观察到不同的沉降。在夏季减少地下水抽水和在冬季实施严格的ASR计划后，水位得以恢复，这导致了InSAR时间序列数据中反映的季节性下沉和反弹模式。提出了一种新的建模策略，将这些季节性变形模式与观测到的水位数据相结合，以干涉图的像素分辨率（约40米）量化含水层和围封单元的储存特征。利用这些观测数据建立的逆模型受到以下事实的阻碍：存储和水力导电性的参数区域分布通常由用户定义，并且通常以特别的方式制定。本研究的目的是开发一种基于伴随的参数估计模型，该模型系统地产生最佳存储和电导率区分布，从而产生优越的概念模型，不仅产生最佳参数分布，而且提供必要的细节，以反映在拉斯维加斯谷观察到的断层边界存储碗的复杂性。这项拟议研究的更广泛影响是重要的，因为它们使用多学科方法解决了拉斯维加斯谷面临的社会经济和水文地质问题。拉斯维加斯山谷的经济繁荣依赖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，可以作为未来的水管理工具。本研究建立的基于伴随的参数估计模型（APE）实现了逆建模中所用区域的自动化。与需要分析众多备选模型的技术相比，这种新模型具有明显的优势。这个新的建模包将提供给所有建模从业者。外联协调员将利用VT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观众提供地下水和水资源教育。在计划的讲习班期间，将使用物理地下水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.