Cycles of wildfire and rainfall produce sediment-laden floods that pose a hazard to development and may clog or overtop protective infrastructure, including debris basins and flood channels. The compound, post-fire flood hazards associated with infrastructure overtopping and clogging are challenging to estimate due to the need to account for interactions between sequences of wildfire and storm events and their impact on flood control infrastructure over time. Here we present data sources and calibration methods to estimate infrastructure clogging and channel overtopping hazards on a catchment-by-catchment basis using the Post-Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous simulation to resolve the effects of antecedent conditions and system memory. Publicly available data sources provide parameter ranges needed for stochastic modeling, and several performance measures are considered for model calibration. With application to three catchments in southern California, we show that PF2HazMo predicts the median of the simulated distribution of peak bulked flows within the 95% confidence interval of observed flows, with an order of magnitude range in bulked flow estimates depending on the performance measure used for calibration. Using infrastructure overtopping data from a post-fire wet season, we show that PF2HazMo accurately predicts the number of flood channel exceedances. Model applications to individual watersheds reveal where infrastructure is undersized to contain present-day and future overtopping hazards based on current design standards. Model limitations and sources of uncertainty are also discussed.

中文翻译：

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估计火灾后洪水基础设施堵塞和漫溢的危险


野火和降雨的循环会产生富含沉积物的洪水，对发展造成危害，并可能堵塞或淹没保护性基础设施，包括碎片盆地和洪道。由于需要考虑野火和风暴事件序列之间的相互作用及其对防洪基础设施随时间的影响，因此与基础设施漫溢和堵塞相关的复合火灾后洪水灾害难以估计。在这里，我们介绍了数据源和校准方法，以使用火灾后洪水危险模型 (PF2HazMo) 逐个流域地估计基础设施堵塞和渠道漫溢危险，这是一种随机建模方法，利用连续模拟来解决先行因素的影响条件和系统内存。公开可用的数据源提供了随机建模所需的参数范围，并且模型校准考虑了多种性能测量。通过应用于南加州的三个集水区，我们表明 PF2HazMo 可以预测观测流量 95% 置信区间内峰值散装流量的模拟分布中值，散装流量估计的数量级范围取决于所使用的性能指标用于校准。使用火灾后雨季的基础设施超标数据，我们表明 PF2HazMo 可以准确预测洪水通道超标数量。各个流域的模型应用表明，根据当前的设计标准，基础设施的规模不足以容纳当前和未来的漫溢灾害。还讨论了模型的局限性和不确定性的来源。