Topographic response to the transition from snowmelt- to rainfall- triggered extremes

2013年9月，科罗拉多州博尔德市附近的山脚下发生了一场1000年一遇的风暴，引发了大范围的山体滑坡和洪水。然而，从极端降雨到洪水再到河流侵蚀和山体滑坡的因果链条是复杂的。例如，这一事件在当地造成了“25年至200年”的洪水和山体滑坡，造成了100‘S到1000’S的泥沙产生量。本项目重点研究山区地貌中两种主要的径流产生模式(融雪和降雨径流)如何导致侵蚀过程的速度和模式的诊断差异。我们以美国科罗拉多前锋山脉为例，由于积雪融化程度的增加，平均径流量随着海拔的增加而系统地增加，而峰值径流在由大而强烈的降雨事件引起的中等海拔处最高。更好地考虑与海拔有关的径流产生对水资源管理、洪水和侵蚀风险评估以及景观演变建模具有重要意义。为此，该项目促进了科罗拉多大学博尔德分校(Boulder Creek临界区天文台、地球实验室和社区地表动力学建模系统)的三个研究所之间的合作，通过向研究人员、决策者和公民提供开放、可重复的工作流程，更好地整合数据收集、分析和模型开发。该项目的主要目标是开发一个河流切割的量化框架，该框架解释了科罗拉多前锋山脉的两个有充分记录的属性：(1)从融雪到降雨引发的极端事件的地形过渡；(2)高海拔、低地形、侵蚀面的形成和持续，基岩河峡谷被切割成的地方。虽然科罗拉多锋山脉是重点，但这种方法也可以转移到事件尺度径流变率具有强烈地形梯度的其他环境(例如安第斯山脉；喜马拉雅山脉)。为实现目标，研究任务由三个主要部分组成：(A)水文气候数据分析；(B)地形数据分析；(C)河流切割数值模拟。水文气候数据分析的重点是降雨和融雪事件的分日至日(即强度、持续时间)和空间(即风暴大小)属性如何影响洪水频率。地形数据分析侧重于基于实地调查和摄影测量、Boulder Creek和堡垒山脉沿线的高分辨率机载激光雷达地形以及中等分辨率区域地形的数据，量化河道陡度、河道宽度和粒度分布在地形中的变化。河道切割的数值模拟建立在一维基岩切割随机阈值模型的基础上，通过增加更多的随机参数(即产流的位置和空间足迹)，目前仅包括随机径流强度。对降雨和融雪统计中的地形梯度及其在设定河流响应基准面下降的时间尺度中的作用进行了明确的核算，这是对气候、地形和侵蚀之间以前未被认识到的反馈的首次测试。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 September of 2013, a "1000-yr" storm occurred in the foothills of the mountains near Boulder, CO, triggering widespread landslides and floods. However, the causal chain from extreme rainfall to flooding to river erosion and landslides is complex. For example, this event produced "25- to 200- yr" floods and landslides locally removed 100's to 1000's of years of sediment production. This project focuses on how the two main modes of runoff generation (snowmelt and rainfall runoff) in mountain landscapes can lead to diagnostic differences in the rates and patterns of erosional processes. We use the Colorado Front Range, USA as a case study where mean runoff systematically increases with elevation due to increased snowmelt, while peak runoff is highest at intermediate elevations caused by large, intense rainfall events. Better accounting for elevation-dependent runoff generation has implications for water resource management, flood and erosion hazard assessment, and landscape evolution modeling. To this end, this project fosters collaboration among three institutes at the University of Colorado, Boulder (the Boulder Creek Critical Zone Observatory, Earth Lab, and the Community Surface Dynamics Modeling System) to better integrate data collection, analysis, and model development via open, reproducible workflows made available to researchers, decision-makers, and citizens.The main goals of this project are to develop a quantitative framework for river incision that accounts for two well-documented attributes of the Colorado Front Range: (1) an orographic transition from snowmelt- to rainfall- triggered extreme events, and (2) the formation and persistence of high elevation, low relief, erosion surfaces, into which bedrock river canyons have incised. While the Colorado Front Range is the focus, the approach is transferable to other settings with strong orographic gradients in event-scale runoff variability (e.g., Andes; Himalayas). To accomplish objectives, research tasks consist of three main components: (A) Hydroclimatic data analysis; (B) Topographic data analysis; (C) Numerical modeling of river incision. Hydroclimatic data analysis focuses on how sub-daily to daily (i.e., intensity, duration) and spatial (i.e., storm size) attributes of rainfall and snowmelt events imprint into flood frequencies. Topographic data analysis focuses on quantifying how channel steepness, channel width, and grain size distributions vary in the landscape based on data from field surveys and photogrammetry, high-resolution airborne lidar topography along Boulder Creek and the Rampart Range, and moderate-resolution regional topography. Numerical modeling of river incision builds on a 1-D stochastic-threshold model of bedrock incision, that currently only includes stochastic runoff intensity, by adding more stochastic parameters (i.e., the location and spatial footprint of runoff generation). Explicit accounting for orographic gradients in rainfall and snowmelt statistics and their role in setting the timescale of river response to base level fall provides a first test of a previously unrecognized feedback between climate, topography, and erosion.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.