PREEVENTS TRACK 2: Integrated Modeling of Hydro-Geomorphic Hazards: Floods, Landslides and Sediment

洪水夺去了许多人的生命，摧毁了财产，每年造成数十亿美元的损失，这促使人们需要改进预测工具。洪水通常与降水增加有关，但越来越多的证据表明，泥沙沉积导致河道输送洪水能力的降低，可能导致洪水更频繁，洪水危害增加。目前的洪水模型不能充分解决河网中的泥沙动力学和河道运输的相关后果。本研究的总体目标是通过定位泥沙输入系统中滑坡、泥石流和泥沙动力学的关键不确定性，提高我们对洪水和滑坡风险的理解和预测能力。研究人员将开发基于过程的模型，这些模型将直接与现有的操作洪水模型进行比较，从而使研究水平的进步和创新能够迅速转向操作模型。两名博士生和两名博士后将在教师和政府科学家的支持下接受多学科研究环境的培训。该项目将使用Landlab，一个最近开发的用于模拟地表过程的工具包，来模拟河道网络中的高地沉积物输入和沉积物动力学。Landlab将被整合到一个集成的洪水建模框架中，该框架包括分布式水文学（DHSVM）、河流地貌学和水动力学（Delft3D）模型。DHSVM将为Landlab提供水文强迫，后者将被DHSVM用于模拟流经流域的泥沙通量，并被纳入Delft3D用于洪水预测。这个建模框架将被应用于斯卡吉特河和普雅鲁普河，它们流经华盛顿州的两个不同的沉积物层状火山——冰川峰和雷尼尔山。斯卡吉特河和普雅鲁普河都有产生与沉积过程有关的破坏性洪水的悠久历史。建模框架将通过现有观测和遥感数据进行广泛验证，以解决以下问题：(1)在研究系统中，导致泥沙供应和河道变化的主要地貌过程是什么？如何在综合洪水模型中表示这些过程？(2)包括滑坡、泥石流和河道蓄积在内的地貌过程如何影响洪水风险？(3)考虑到地貌过程的预期变化，未来洪水风险将如何变化？综合建模框架将评估在洪水事件期间和之间的时间和空间尺度上的过程如何相互作用，形成泥沙动力学，河流输送和洪水频率。提高对这些系统中洪水和滑坡风险的了解将为管理决策提供有价值的信息，以应对未来的洪水风险，并将通过利益相关者研讨会进行交流。

Floods claim many lives, destroy property, and cost billions of dollars annually, motivating the need for improved tools for making predictions. Flooding is typically related to higher precipitation, but there is growing evidence that reduction of a river channel's ability to convey floodwaters as a result of sediment deposition can lead to more frequent floods and increased flood hazards. Current flood models do not sufficiently resolve sediment dynamics in river networks and related consequences for channel conveyance. The overarching objective of this research is to improve our understanding and ability to forecast flood and landslide risks by targeting key uncertainties of sediment inputs to the system from landslides and debris flows and sediment dynamics in channels. The investigators will develop process-based models, which will be directly compared with existing operational flood models, so that advancements and innovations at the research level can be moved toward operational models rapidly. Two PhD students and two postdoctoral associates will receive training with faculty and government scientist support in a multi-disciplinary research environment. This project will use Landlab, a recently developed toolkit for modeling earth surface processes, to model upland sediment input and sediment dynamics in channel networks. Landlab will be incorporated into an integrated flood modeling framework that includes distributed hydrology (DHSVM), and fluvial geomorphology and hydrodynamics (Delft3D) models. DHSVM will provide hydrologic forcing to Landlab, which will be used to model sediment flux that is routed through the watershed by DHSVM and incorporated into Delft3D for flood prediction. This modeling framework will be applied to Skagit and Puyallup Rivers draining two different sediment-laden stratovolcanos, Glacier Peak and Mount Rainier, in the State of Washington. The Skagit and Puyallup Rivers both have long histories of generating damaging floods linked to sedimentation processes. The modeling framework will be extensively validated with existing observations and remote sensing data to address the following questions: (1) What are the dominant geomorphic processes that lead to sediment supply and channel change in the study systems, and how they can be represented in an integrated flood model? (2) How do geomorphic processes, including landslides, debris flows and channel storage affect flood risk? (3) How will flood risk change in the future given expected changes in geomorphic processes? The integrated modeling framework will evaluate how processes interact over a range of temporal and spatial scales during and between flood events, shaping sediment dynamics, river conveyance, and flood frequency. Improved understanding of flood and landslide risks in these systems will provide valuable information for management decisions to address future flood risks and will be communicated via stakeholder workshops.