Collaborative Research: A new classification system for karst springs using storm hysteresis

合作研究：利用风暴磁滞的岩溶泉水新分类系统

• 批准号: 1417401
• 负责人: Ellen Herman
• 金额: $ 8.35万
• 依托单位: Bucknell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1417401&HistoricalAwards=false
• 关键词: Collaborative; Research; new; classification; system

Karst aquifers are an important groundwater resource, but they are vulnerable to contamination because of fast and complex flow paths arising from subsurface caves and large fractures. The complexity of karst aquifers has for a long time imposed challenges for researchers to characterize the groundwater flow system. This project will develop a new classification method for karst springs that will guide monitoring and pollution prevention strategies. Based on water chemistry variability in response to storms, this classification will identify different sources of water and improve water capture area delineation. The new classification system will be tested by revisiting a well-known set of karst springs that show variations in flow paths. Educational opportunities for students and for the general public are incorporated into the project. Classification will be based on the shape of hysteresis plots and changes in hysteresis plots from storm to storm. Storm hysteresis, defined as the difference in chemical trends at the beginning versus the end of a storm, offers opportunities to identify changes over time in water movement and storage in karst networks. The project will test two hypotheses. (1) During a storm, hysteresis occurs as the water flows through the matrix and conduits, and (2) from storm to storm, the hysteresis pattern changes as the water capture area and storage zones change. For example, Mg:Ca ratios in spring water increase with diffusive recharge but decrease with more focused recharge through conduits, and hysteresis plots can show the timing of each type of recharge. Automatic samplers and data loggers will be used during storms to provide data for hysteresis plots. In addition to Mg:Ca ratios, Sr:Ca ratios, rare earth elements, stable isotopes, and carbonate equilibria will be examined and potential flow paths will be evaluated using groundwater models. The combination of multiple natural tracers, modeling, and capture area calculations will help quantify behavior of karst springs and karst aquifers. Ultimately, the new classification system will improve understanding of contaminant transport in karst systems.

岩溶含水层是一种重要的地下水资源，但由于地下洞穴和大裂缝产生的快速和复杂的流动路径，它们很容易受到污染。长期以来，岩溶含水层的复杂性给研究人员描述地下水流系统带来了挑战。该项目将开发一种新的岩溶泉分类方法，以指导监测和污染预防战略。 根据水化学变化对风暴的反应，这种分类将确定不同的水源，并改善水捕获区的划定。 新的分类系统将通过重访一组著名的岩溶泉来测试，这些泉显示出流动路径的变化。学生和公众的教育机会被纳入该项目。 分类将基于滞后图的形状和风暴之间滞后图的变化。 风暴滞后被定义为风暴开始与结束时化学趋势的差异，为确定岩溶网络中水的运动和储存随时间的变化提供了机会。该项目将测试两个假设。 (1)在风暴期间，滞后发生在水流过基质和管道时，以及（2）从风暴到风暴，滞后模式随着水捕获区域和存储区域的变化而变化。 例如，镁：钙在泉水中的比例增加扩散补给，但减少更集中的补给通过导管，滞后图可以显示每种类型的补给的时间。 在风暴期间将使用自动取样器和数据记录器，为滞后图提供数据。 除了镁钙比，锶钙比，稀土元素，稳定同位素和碳酸盐平衡将被检查和潜在的流动路径将使用地下水模型进行评估。 多种天然示踪剂、建模和捕获面积计算的组合将有助于量化岩溶泉和岩溶含水层的行为。 最终，新的分类系统将提高岩溶系统中污染物传输的理解。