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

预防轨道 2：水文地貌灾害综合建模：洪水、山体滑坡和沉积物

• 批准号: 1663859
• 负责人: Erkan Istanbulluoglu
• 金额: $ 169.97万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1663859&HistoricalAwards=false
• 关键词: PREEVENTS; TRACK; Integrated; Modeling; Hydro

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.

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。洪水通常与降水量增加有关，但越来越多的证据表明，由于沉积物沉积，河道输送洪水的能力降低，可能导致洪水更加频繁，洪水危害增加。 目前的洪水模型不能充分解决河流网络中的泥沙动力学和相关后果的渠道输送。这项研究的总体目标是提高我们的理解和能力，预测洪水和滑坡的风险，针对泥沙输入系统的滑坡和泥石流和泥沙动态渠道的关键不确定性。 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业务洪水模型进行比较，以便研究层面的进步和创新能够迅速转向业务模型。两名博士生和两名博士后将在多学科研究环境中接受教师和政府科学家支持的培训。该项目将使用最近开发的模拟地球表面过程的工具包Landlab来模拟渠道网络中的高地沉积物输入和沉积物动力学。Landlab将被纳入一个集成的洪水建模框架，其中包括分布式水文（DHSVM），河流地貌和水动力学（Delft3D）模型。DHSVM将为Landlab提供水文强迫，该强迫将用于模拟DHSVM通过流域的沉积物通量，并将其纳入Delft3D进行洪水预测。这个模型框架将被应用到Skagit和Puyallup河流排水两个不同的沉积物负载成层火山，冰川峰和雷尼尔山，在华盛顿州。斯卡吉特河和普亚卢普河都有产生与沉积过程有关的破坏性洪水的悠久历史。模型框架将广泛验证现有的观测和遥感数据，以解决以下问题：（1）什么是主导的地貌过程，导致沉积物供应和渠道的变化，在研究系统中，以及如何将它们表示在一个综合的洪水模型？(2)地貌过程，包括滑坡、泥石流和河道蓄水，如何影响洪水风险？(3)在地貌过程预期变化的情况下，未来洪水风险将如何变化？综合建模框架将评估过程如何在洪水事件期间和之间的时间和空间尺度范围内相互作用，形成沉积物动力学，河流输送和洪水频率。对这些系统中洪水和滑坡风险的进一步了解将为管理决策提供宝贵信息，以应对未来的洪水风险，并将通过利益攸关方研讨会进行交流。

项目成果

Elevation distributed micro-climatology data in a coastal glaciated watershed

沿海冰川流域的高程分布微气候数据

• DOI: 10.1016/j.dib.2020.105578
• 发表时间: 2020
• 期刊: Data in Brief
• 影响因子: 1.2
• 作者: Bandaragoda, Christina;Beaulieu, Jezra;Cristea, Nicoleta;Beveridge, Claire
• 通讯作者: Beveridge, Claire

Survival of the Strong and Dense: Field Evidence for Rapid, Transport‐Dependent Bed Material Abrasion of Heterogeneous Source Lithology

强而密的生存：非均质源岩性快速、传输依赖的床层物质磨损的现场证据

• DOI: 10.1029/2021jf006455
• 发表时间: 2022
• 期刊: Journal of Geophysical Research: Earth Surface
• 作者: Pfeiffer, Allison M.;Morey, Susannah;Karlsson, Hannah M.;Fordham, Edward M.;Montgomery, David R.
• 通讯作者: Montgomery, David R.

Frequent Mass Movements From Glacial and Lahar Terraces, Controlled by Both Hillslope Characteristics and Fluvial Erosion, are an Important Sediment Source to Puget Sound Rivers

受山坡特征和河流侵蚀控制的冰川和泥沙台地频繁的大规模运动是普吉特湾河流的重要沉积物来源

• DOI: 10.1029/2020wr028389
• 发表时间: 2021
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Scott, Daniel N.;Collins, Brian D.
• 通讯作者: Collins, Brian D.

Channel Conveyance Variability can Influence Flood Risk as Much as Streamflow Variability in Western Washington State

• DOI: 10.1029/2021wr031890
• 发表时间: 2022-06
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: S. Ahrendt;A. Horner‐Devine;B. Collins;J. Morgan;E. Istanbulluoglu

Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields

• DOI: 10.1016/j.geomorph.2023.108805
• 发表时间: 2023-10
• 期刊: Geomorphology
• 影响因子: 3.9
• 作者: Eli Schwat;E. Istanbulluoglu;A. Horner‐Devine;Scott Anderson;F. Knuth;D. Shean