A hydrologic signature approach to analysing wildfire impacts on overland flow

被引:2
作者
Bolotin, L. A. [1 ]
McMillan, H. [1 ]
机构
[1] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA
基金
美国国家科学基金会;
关键词
debris flows; flooding; hydrologic signatures; machine learning; overland flow; post-fire; SOIL-HYDRAULIC-PROPERTIES; WATER REPELLENCY; STREAMFLOW RESPONSE; STORM RUNOFF; DATA SET; INFILTRATION; CLIMATE; FLOODS;
D O I
10.1002/hyp.15215
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Post-fire flooding and debris flows are often triggered by increased overland flow resulting from wildfire impacts on soil infiltration capacity and surface roughness. Increasing wildfire activity and intensification of precipitation with climate change make improving understanding of post-fire overland flow a particularly pertinent task. Hydrologic signatures, which are metrics that summarize the hydrologic regime of watersheds using rainfall and runoff time series, can be calculated for large samples of watersheds relatively easily to understand post-fire hydrologic processes. We demonstrate that signatures designed specifically for overland flow reflect changes to overland flow processes with wildfire that align with previous case studies on burned watersheds. For example, signatures suggest increases in infiltration-excess overland flow and decrease in saturation-excess overland flow in the first and second years after wildfire in the majority of watersheds examined. We show that climate, watershed and wildfire attributes can predict either post-fire signatures of overland flow or changes in signature values with wildfire using machine learning. Normalized difference vegetation index (NDVI), air temperature, amount of developed/undeveloped land, soil thickness and clay content were the most used predictors by well-performing machine learning models. Signatures of overland flow provide a streamlined approach for characterizing and understanding post-fire overland flow, which is beneficial for watershed managers who must rapidly assess and mitigate the risk of post-fire hydrologic hazards after wildfire occurs. Hydrologic signatures are metrics that describe the hydrologic regime of a catchment. We leveraged signatures specific to overland flow and large-sample hydrometeorological datasets to investigate (1) whether signatures of overland flow change significantly to reflect shifts in runoff generation mechanisms after wildfire, (2) the timescale of wildfire impacts on signatures of overland flow and (3) the most important predictors of post-fire overland flow signatures. image
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页数:18
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