CAREER: Alluvial-river dynamics through watershed networks

河流及其支流形成了一个网络，将地球上遥远的风景整合在一起，连接着我们的家园、农场、城市和荒野地区。这些河流是不断变化的，有时几乎不被察觉，有时戏剧性地调整它们的形式，以携带雨水、冰雪融化和周围景观侵蚀提供的水和沉积物。自然和人类活动都可以改变进入河流的水和沉积物的平衡，当供水量超过沉积物供应时，导致河流向下侵蚀到河床，或者当沉积物供应增加到超过水的承载能力时，沉积沉积物并提高河床的水位。威克特和他的团队将开发一种理论来预测这些河流系统的变化，并将其纳入一个包括降雨和径流、湖泊和湿地以及形成河流的过程的计算机模型。他们将使用来自美国明尼苏达州和阿根廷萨尔塔的河流数据来测试这一理论和模型。在过去的冰川周期中，这些河流的河床高度变化了几十到几百米，在过去的200年里，由于气候和土地利用的变化，这些河流的河床高度变化了几米。在圣安东尼瀑布实验室进行的小规模河流控制实验将补充这些实地试验。这项工作提出的结果是一个有效的、基于物理的预测模型，以模拟气候和土地利用变化对河网演变的响应。该项目将培养本科生、研究生和博士后学者。该小组将与Ojibwe人民合作，扩大对科学的参与。威克特和他的团队将开发和测试理论和模型，以模拟河网对水和沉积物供应变化的反应。他们将把河流支流网络编纂成数学网络，并将山谷、湖泊和周围的山坡纳入其中。然后，他们将对这些网络中描述冲积-河流动力学的方程进行耦合和求解，以预测河流对外部扰动的复杂响应。这些方程式将构成一个新的数值模型的基础，该模型将根据实地和实验室数据进行测试，并由沉积物输入和水排放的记录和模拟驱动。该模型将使我们能够快速模拟冲积河流对地貌变化驱动因素的响应，从而提高我们重建过去河流动态和预测未来环境变化对河流影响的能力。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。

Rivers and their tributaries form networks that integrate the far reaches of Earth's landscapes, linking our homes, farms, cities, and wilderness areas. These rivers are ever-changing, sometimes near-imperceptibly and sometimes dramatically adjusting their forms to carry the water and sediment supplied by rainfall, snow/ice melt, and erosion of the surrounding landscape. Both natural and human activities can alter the balance of water and sediment entering rivers, causing them to erode downwards into their beds when water supply outweighs sediment supply, or to deposit sediments and raise the level of their beds when sediment supply increases beyond what the water can carry. Wickert and his team will develop a theory to predict these river-system changes, and incorporate it into a computer model that includes rainfall and runoff, lakes and wetlands, and processes that shape rivers. They will test this theory and model using data from rivers in Minnesota, USA, and Salta, Argentina. These rivers' bed elevations have changed by tens to hundreds of meters during past glacial cycles and by several meters over the past 200 years in response to changing climate and land use. Controlled experiments on small-scale rivers conducted at the Saint Anthony Falls Laboratory will supplement these field-based tests. The proposed outcome of this work is an efficient, physics-based, predictive model to simulate river-network evolution in response to climate and land-use change. The project will train undergraduate students, graduate students, and postdoctoral scholars. The team will work with the Ojibwe people to broaden participation in science.Wickert and his group will develop and test theory and models to simulate river-network response to changes in water and sediment supply. They will codify river-tributary networks into mathematical networks that additionally incorporate valleys, lakes, and the surrounding hillslopes. They will then couple and solve equations describing alluvial-river dynamics across these networks to predict the complex response of rivers to external perturbations. These equations will underlie a new numerical model, to be tested against field and laboratory data and driven by records and simulations of sediment inputs and water discharge. This model will enable us to rapidly simulate alluvial-river response to drivers of geomorphic change, thereby improving our ability to both reconstruct past river dynamics and forecast the impacts of environmental change on rivers into the future.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.