Postdoctoral Fellowship: EAR-PF: Evaluating spatiotemporal dependence in groundwater-dependent ecosystem processes

Matthew Lurtz博士获得了美国国家科学基金会地球科学博士后奖学金，在科罗拉多州立大学Michael Ronayne博士的指导下，在悉尼科技大学Alfredo Huerte博士的指导下进行研究和专业发展活动。在整个美国西部和其他地方，内陆地下水依赖生态系统（GDEs）出现在地下水位接近陆地表面的许多河流和湖泊旁边。这些生态系统拥有各种原生和非原生植被，这些植被提供的好处包括：减少农业污染物，保护物种栖息地，稳定河流沉积物运输。植被群落利用水分（即植物蒸腾），是地表水-地下水综合系统的重要水分收支组成部分。因此，gde可用于识别与脆弱河流系统相关的地下水供应。在本研究中，将使用现场仪器、遥感方法和数值地下水模拟相结合的方法对不同气候区域的gde的吸水量进行量化。通过提高对gde的科学认识，可以提高地下水供应的知识基础，这是人类和环境可持续性的关键。这项工作的重要性将通过与科罗拉多州东南部和亚利桑那州水利地区的受益者接触来实现，实地研究将在那里进行。该项目将通过使用基于地点的教育和综合美国和澳大利亚领土居民采用的水资源保护策略，使下一代科学家受益。该项目将依靠科罗拉多州立大学（CSU）的教育推广计划来交流科学发现和保护方法，包括传统的土著方法。在研究期间获得的数据、模型和绘制的产品将在地方和国际范围内共享。依赖地下水的生态系统在支持植物和动物方面发挥着主导作用，但在不同时间、空间和气候尺度下，帮助量化GDE健康（即蒸散量）的信息很少。本研究的主要目的是利用遥感和数值模拟方法揭示gde的时空依赖性。本研究将利用假设检验来研究小规模GDE过程如何转化为更大的空间尺度，这将支持用于解决国家水挑战的预测模型。在时间基础上，将利用美国西部的数据，收集在不同地下水和气候条件下在GDE中发现的植物功能群的环境计量数据，调查GDE健康与地下水供应之间的趋势方向。对环境数据采用降维方法，推断地下水依赖生态系统随地下水供给量减少的变化轨迹。从空间尺度的角度来看，这项工作将首先利用贝叶斯回归框架在点尺度上推导出描述GDE健康与地下水可用性之间关系的函数形式。为了研究点尺度以外的GDEs的空间结构，本工作将使用派生函数作为空间分布参数建模方案中的子程序来构建一个尺度启发的数值模型。该项目将使用一个假设驱动的研究框架，以当前的科学状况为基础，并以可持续工程概念为依据，从而在水资源模型中更准确地表示gde。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Dr. Matthew Lurtz has been awarded an NSF Earth Sciences Postdoctoral Fellowship to carry out research and professional development activities at Colorado State University under the mentorship of Dr. Michael Ronayne and at the University of Technology Sydney under the mentorship of Dr. Alfredo Huerte. Throughout the western United States and elsewhere, inland groundwater dependent ecosystems (GDEs) occur alongside many rivers and lakes where the water table is close to the land surface. These ecosystems host a variety of native and nonnative vegetation that provide benefits such as: reduce agricultural-borne pollutants, protect species habitat, and stabilize stream sediment transport. The vegetation communities utilize water (i.e., plant transpiration), representing an important water budget component for the integrated surface-groundwater system. Therefore, GDEs can be used to identify the groundwater supply connected to vulnerable river systems. In this study, water uptake by GDEs in different climatic regions will be quantified using a combination of site instrumentation, remote sensing methods, and numerical groundwater modeling. By increasing the scientific understanding on GDEs, it is possible to enhance the knowledge base surrounding groundwater supply which is key to human and environmental sustainability. The importance of this work will be realized by engaging with beneficiaries in the water conservancy districts of southeastern Colorado and Arizona, where the field research will be conducted. This project will benefit the next generation of scientists by using place-based education and synthesizing water conservation strategies employed by inhabitants of American and Australian territories. The project will rely on Colorado State University’s (CSU) educational outreach programs to communicate scientific findings and conservation methodologies, including traditional indigenous methods. Data acquired, and models and mapped products created during the fellowship will be shared on local-to-international scales.Groundwater dependent ecosystems play a dominant role in supporting flora and fauna, but little information is available to help quantify GDE health (i.e., evapotranspiration) with varying time, space and climatic scales. The main goal of the study is to uncover temporal and spatial dependence in GDEs using remotely-sensed and numerical modeling methodologies. This study will utilize hypothesis testing to investigate how small scale GDE processes translates to larger spatial scales which will bolster predictive models used to address national water challenges. On a temporal basis, the trend direction between GDE health and groundwater availability will be investigated by collecting environmetrics on plant functional groups found in GDEs under varying groundwater and climatic conditions with data in the western United States. A dimension reduction method will be applied to the environmetric data to infer the trajectory of groundwater dependent ecosystems with reductions in groundwater supply. From a spatial-scale perspective, this work will begin by deriving the function form to describe the relationship between GDE health and groundwater availability at the point scale using a Bayesian regression framework. To examine spatial structure in GDEs beyond the point scale, this work will use the derived function as a subroutine in a spatially distributed parameter modeling scheme to build a scale-enlightened numerical model. This project will result in a more accurate representation of GDEs in water resource models using a research framework that is hypothesis-driven, based on the current state of science, and informed by sustainable engineering concepts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.