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首页> 外文期刊>Journal of the American Water Resources Association >A STATISTICAL SEDIMENT YIELD PREDICTION MODEL INCORPORATING THE EFFECT OF FIRES AND SUBSEQUENT STORM EVENTS
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A STATISTICAL SEDIMENT YIELD PREDICTION MODEL INCORPORATING THE EFFECT OF FIRES AND SUBSEQUENT STORM EVENTS

机译：统计含沙量和暴风雨影响的产量预测模型

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摘要

Alluvial fans are continuously being developed for residential, industrial, commercial, and agricultural uses in southern California. Development and alteration of alluvial fans need to consider the possibility of mud and debris flows from upstream mountain watersheds affected by fires. Accurate prediction of sediment yield (or hyper-concentrated sediment yield) is essential for the design, operation, and maintenance of debris basins to safeguard properly the general populace. This paper presents a model for the prediction of sediment yields that result from a combination of fire and subsequent storm events. The watersheds used in this analysis are located in the foothills of the San Gabriel Mountains in southern California. A multiple regression analysis is first utilized to establish a fundamental statistical relationship for sediment yield as a function of relief ratio, drainage area, maximum 1-h rainfall intensity and fire factor using 45 years of data (1938-1983). In addition, a method for multi-sequence sediment yield prediction under fire conditions was developed and calibrated using 17 years of sediment yield, fire, and precipitation data for the period 1984-2000. After calibration, this model was verified by applying it to provide a prediction of the sediment yields for the 2001-2002 fire events in southern California. The findings indicate a strong correlation between the estimated and measured sediment yields. The proposed method for sequence sediment yield prediction following fire events can be a useful tool to schedule cleanout operations for debris basins and to develop an emergency response strategy for the southern California region where plentiful sediment supplies exist and frequent fires occur.
机译：加州南部正在不断开发冲积扇，用于住宅，工业，商业和农业用途。冲积扇的开发和改造需要考虑泥土和碎屑从大山上游流域受火灾影响的可能性。泥沙量的准确预测（或高浓度泥沙量）对于泥石流域的设计，操作和维护至关重要，以适当保护普通民众。本文提出了一个模型，用于预测由于火灾和随后的暴风雨事件而产生的沉积物产量。此分析中使用的分水岭位于加利福尼亚南部的圣盖博山的山麓。首先使用45年的数据（1938-1983年），利用多元回归分析来建立沉积物产量与溢流率，流域面积，最大1-h降雨强度和着火因子的函数的基本统计关系。此外，还开发了一种在火灾条件下预测多序列沉积物产量的方法，并使用1984-2000年期间17年的沉积物产量，火灾和降水数据进行了校准。校准后，通过应用此模型验证了该模型，以便为加利福尼亚南部2001-2002年火灾的沉积物产量提供预测。调查结果表明，估计的和测得的沉积物产量之间有很强的相关性。所提出的火灾事件发生后顺序沉积物产量预测的方法，对于安排泥石流域的清理作业并为存在大量沉积物供应且经常发生火灾的南加州地区制定应急策略，是一种有用的工具。

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