RAPID: Monitoring and modeling watershed-scale post-wildfire streamflow response through space and time

RAPID：通过空间和时间监测和模拟流域规模的野火后水流响应

• 批准号: 2051762
• 负责人: Belize Lane
• 金额: $ 4.98万
• 依托单位: Utah State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-11-15 至 2022-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051762&HistoricalAwards=false
• 关键词: RAPID; Monitoring; modeling; watershed; scale

Wildfires alter hydrologic processes, accelerate erosion and increase sediment transport rates. In the western U.S, these changes pose considerable risks to downstream infrastructure and ecosystems, and natural resource managers urgently need practical and reliable predictive tools to support post-wildfire management. The active Grizzly Creek wildfire in Glenwood Canyon, CO, presents a unique, time-sensitive opportunity to collect necessary field data to monitor these processes and develop transferable analytical tools. The watershed has active long-term USGS gauges both up and downstream from the study area as well as highly variable topography, land cover and burn severity, making the Grizzly Creek fire an ideal candidate to capture a range of post-wildfire hydrologic responses within the same watershed. Ultimately, this data will directly support and inform post-wildfire management and restoration, which costs tens of millions of dollars across the western U.S. each year. Data collection is in coordination with the USGS Post-Fire Debris-Flow Hazards team to ensure efforts are complementary and support larger hydrologic and geomorphic research efforts. Results will be conveyed to the post-wildfire research and management community through presentations to major stakeholder groups, such as the USFS, NRCS, Utah Division of Natural Resources, water conservation districts, dam operators, and other relevant groups.Hydrologic field data collected for this project will support evaluation and improvement of post-wildfire hydrology and sediment dynamics models, as well as advances in fundamental understanding of hydrologic processes. Reasonable hydrologic forcing remains a major limitation of network-scale modeling frameworks to assess post-wildfire sediment dynamics. To fill this gap and improve our understanding of post-wildfire hydrologic response across a watershed requires rapid mobilization to capture the initial response in a recently burned watershed with long-term streamflow records and variable watershed and burn characteristics. Monitoring sites capture similar watershed characteristics (e.g., slope, land cover) along a burn severity gradient, and are paired with nearby analog unburned catchments. Precipitation, streamflow and hillslope infiltration rates will be monitored through time throughout the burned area. This perishable data will be used within a novel analytical framework to answer critical research questions related to variability in the post-wildfire rainfall-runoff response through space and time, beginning immediately following a burn. The research will help determine how the spatial distribution and severity of burned areas within a watershed impact post-wildfire runoff, distributed streamflow response and, ultimately, sediment flux rates. This research will advance long-term sediment transport and storage predictions in this and other emerging modeling efforts that inform resource management.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.

野火改变了水文过程，加速了侵蚀，增加了泥沙输移率。在美国西部，这些变化对下游基础设施和生态系统构成了相当大的风险，自然资源管理者迫切需要实用和可靠的预测工具来支持野火后的管理。科罗拉多州格伦伍德峡谷活跃的灰熊溪野火提供了一个独特的、对时间敏感的机会，可以收集必要的现场数据来监测这些过程并开发可转移的分析工具。该分水岭在研究区域的上下游都有活跃的美国地质勘探局长期测量，以及高度可变的地形、土地覆盖和烧伤严重程度，使灰熊小溪火灾成为捕捉同一分水岭内一系列野火后水文反应的理想人选。最终，这些数据将直接支持和指导野火后的管理和恢复，这在美国西部每年要花费数千万美元。数据收集与美国地质勘探局火灾后泥石流灾害小组协调，以确保努力是相辅相成的，并支持更大规模的水文和地貌研究工作。结果将通过向主要利益相关者团体，如美国科学基金会、自然资源研究中心、犹他州自然资源部、水源涵养区、大坝运营商和其他相关团体的演讲，传达给野火后的研究和管理界。为该项目收集的水文实地数据将支持对野火后水文和沉积物动力学模型的评估和改进，以及对水文过程的基本理解的进步。合理的水文强迫仍然是评估野火后沉积物动力学的网络规模模拟框架的主要限制。为了填补这一空白，并提高我们对整个流域的野火后水文反应的了解，需要快速动员，以捕捉最近被烧毁的流域的初始反应，该流域具有长期的径流记录和可变的流域和燃烧特征。监测点沿着烧伤严重程度梯度捕捉类似的分水岭特征(例如，坡度、土地覆盖)，并与附近的模拟未焚烧集水区配对。随着时间的推移，将监测整个烧毁地区的降雨量、径流量和山坡入渗率。这些易腐烂的数据将在一个新的分析框架内用于回答与野火后降雨-径流响应在空间和时间上的可变性有关的关键研究问题，从燃烧后立即开始。这项研究将有助于确定分水岭内烧毁区域的空间分布和严重程度如何影响野火后的径流、分布的径流响应，并最终影响沉积物通量。这项研究将推进长期泥沙运移和储存预测，为资源管理提供信息。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。