Advancing Sustainable Groundwater Resource Management

地下水资源是加拿大和世界大部分地区供水的重要组成部分。在许多地方，由于过度开采，地下水位已经降到危险的低点，水井已经干涸。地下水可持续管理的一个必要条件是存在能够定量预测含水层对抽水响应的工具。对于简单的含水层，已有精确预测所需的数学模型和工具。然而，有些含水层是复杂的，因为含水层不同部分之间的连接是复杂的。评价复杂含水层并预测其对抽水和补给变化的响应仍然是水文地质学的重大挑战之一。

Groundwater resources are an important part of water supply in Canada and much of the world. In many places, groundwater levels have dropped dangerously low or wells have gone dry due to over exploitation. A necessary condition for sustainable groundwater management is the existence of tools that can quantitatively predict the response of aquifers to pumping. The mathematical models and tools required for accurate predictions exist for simple aquifers. However some aquifers are complex because the connection between different parts of the aquifer are complex. It remains one of the great challenges in hydrogeology to evaluate complex aquifers and predict their response to pumping and changes in recharge. These aquifers are too complicated for us to map exactly with current technology. Consequently, we cannot know with certainty exactly how they are constructed. However, we often understand how they were deposited and evolved geologically and have a general idea about what types of structures that we can anticipate. So, we do have some knowledge about their general characteristics. It is the objective of this research proposal to convert that knowledge into a statistical description of the aquifers and then to use a body of statistical techniques known as stochastic methods to build models that can be used to calculate the range of possible responses to changes in pumping and recharge. This will give groundwater managers the ability to project the most likely response to pumping as well as worst and best case scenarios and improve our ability to sustainably manage water resources. This research proposal has several interrelated parts. Geological and geophysical studies will determine the types of aquifer geometries that we can anticipate. Stochastic hydrogeologic studies will use hydrogeologic observations and stochastic methods to build the groundwater models. The results of the geologic and geophysical studies will be used to assure that the statistical models are consistent with what we know about the geology.