Collaborative Research: Predicting post-wildfire sedimentation of reservoirs: probabilistic modeling of debris flow generation and downstream sediment routing

在美国，林地为三分之二的人口提供水源。然而，自从大多数水利基础设施在美国西部建成以来的几十年里，野火的烧毁面积、频率和严重程度都有了相当大的提高。虽然野火可能会对供水的数量和质量产生短期影响，但严重烧伤后发生的侵蚀也会将大量泥沙输送到河流和下游水库，降低供水的长期储存能力。此外，随着预计未来野火的增加，河流沉积物也将增加。因此，在这个项目中，研究人员将开发新的基于计算机的建模工具，能够识别和量化野火后的侵蚀对下游水利基础设施构成的风险。这个模型框架的第一个应用将是整个犹他州的供水水库，犹他州是美国最干旱的州之一，每个水库的脆弱性将被量化，以确定野火带来的侵蚀和沉积风险。与全国各地的堤坝水库类似，犹他州水库的泥沙淤积已经成为人们对日益老化的水利基础设施的日益担忧，甚至在考虑未来野火预计会增加的原因之前。最后，研究人员将把他们的模型整合到在线开源项目中，让任何有兴趣将该模型应用于其他州或地区的个人或机构都可以使用这些资源。该项目的成果将为改进和更有针对性的森林管理提供关键信息和工具，帮助确定和保护脆弱的水资源，并解决预测野火后侵蚀对下游影响的关键知识缺口。该项目将通过两所大学的合作，为一名博士后研究员(Pi Murphy)、两名博士生和至少六名本科生提供支持，以培训和发展他们在水文学、地貌学、数据分析和管理以及科学交流方面的技能。该项目将推进对预测野火后向下游水利基础设施输送泥沙的地点和时间至关重要的基础知识。研究人员将把新的和现有的模型联系起来：1)预测野火后侵蚀的位置和程度，2)以基于物理和水文地貌敏感的方式通过河网向下游输送野火后的沉积物输入，以及3)确定在一系列野火条件下向下游水库输入的潜在体积泥沙的范围。将这个新的建模框架应用于犹他州的133个主要水库，该项目将回答四个关键研究问题：1)犹他州的哪些供水水库最容易受到野火后的侵蚀？2)野火发生和下游水库蓄水损失之间的时间间隔是多少？3)哪个景观、火灾、水文和植被特征对上游蓄水和火灾后向水库输送泥沙的控制最强？4)什么景观、火灾和河网属性控制着野火后沉积物产量的相对增加高于背景产量？通过这一分析，研究人员将具体评估沉积物连通性对水库脆弱性的影响，以及粗泥沙投入对较长运输时间尺度上的水库储存量减少的贡献。鉴于大坝的所有权和管理复杂，他们将聘请一个利益相关者咨询小组，该小组涵盖不同的所有权范围，包括公用事业部门、州和联邦森林管理机构以及大坝运营商。此外，他们将与社区表面动力学建模系统(CSDMS)合作，将他们的模型集成到开源平台中，并创建一个公共平台来托管项目数据集、教育材料、技术报告和出版物。该项目代表了综合地球科学前沿的研究，这一新的建模框架填补了在评估有关野火和水安全的紧迫社会关切所需工具方面的关键空白。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In the United States, forested lands provide water supply for two-thirds of the population. However, in the decades since most water infrastructure was constructed in the western U.S., the burned area, frequency, and severity of wildfires has increased considerably. While wildfires can have short-term impacts on the quantity and quality of water supply, the erosion that occurs after severe burns can also deliver significant amounts of sediment to rivers and downstream reservoirs, reducing the long-term storage capacity of water supplies. Further, with projected future increases in wildfire, there will be increases in river sediment. Thus, in this project the researchers will develop new computer-based modeling tools capable of identifying and quantifying the risk that post-wildfire erosion poses to downstream water infrastructure. The first application of this modeling framework will be the water supply reservoirs throughout Utah, one of the driest states in the U.S., where the vulnerability of each reservoir will be quantified as to the erosion and sedimentation risk posed by wildfire. Similar to dammed reservoirs across the nation, sedimentation in Utah reservoirs is a growing concern for aging water infrastructure, even before accounting for the projected increases in future wildfire. Finally, the researchers will integrate their model into online, open-source programs, making these resources available to any person or agency interested in applying the model to other states or regions. The deliverables of this project will provide critical information and tools for improved and more targeted forest management, help identify and protect vulnerable water resources, and address crucial knowledge gaps for predicting downstream impacts from post-wildfire erosion. Collaborating across two universities, this project will provide support for one post-doctoral researcher (PI Murphy), two PhD students, and a minimum of six undergraduate students to train and develop their skills in hydrology, geomorphology, data analysis and management, and science communication. This project will advance fundamental knowledge critical for predicting the locations and timing of post-wildfire sediment delivery to downstream water infrastructure. The researchers will link new and existing models that: 1) predict the locations and magnitudes of post-wildfire erosion, 2) route post-wildfire sediment inputs downstream through river networks in a physics-based and hydro-geomorphically sensitive manner, and 3) determine a range of potential volumetric sediment inputs to downstream reservoirs under a range of wildfire conditions. Applying this new modeling framework to the 133 major reservoirs throughout Utah, this project will answer four key research questions: 1) Which water supply reservoirs in Utah are most vulnerable to post-wildfire erosion? 2) What is the time lag between occurrence of a wildfire and loss of reservoir storage downstream? 3) Which landscape, fire, hydrologic, and vegetation characteristics exert the strongest control on the upstream storage vs. delivery of post-fire sediment to reservoirs? 4) What landscape, fire and river network attributes control the relative increase in post-wildfire sediment yields above background yields? Through this analysis, the researchers will specifically assess the influence of sediment connectivity on reservoir vulnerability, as well as the contribution of coarse sediment inputs to the reductions in reservoir storage over longer transport timescales. Given the complex ownership and management of dams, they will engage a stakeholder advisory group that spans the diverse range of ownership and includes public utilities departments, state and federal forest management agencies, and dam operators. Further, they will work with the Community Surface Dynamics Modeling System (CSDMS) to integrate their models into open-source platforms, and create a public platform to host the project datasets, educational materials, technical reports, and publications. This project represents research at the frontier of integrated geosciences, and this new modeling framework fills a critical gap regarding the tools needed to assess urgent societal concerns regarding wildfire and water security.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.