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水力发电学报 ›› 2024, Vol. 43 ›› Issue (5): 68-79.doi: 10.11660/slfdxb.20240507

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基于径向基网络的堰塞体溃决峰值流量预测研究

  

  • 出版日期:2024-05-25 发布日期:2024-05-25

Radial basis function model for predicting peak outflow caused by landslide dam failure

  • Online:2024-05-25 Published:2024-05-25

摘要: 堰塞体由天然滑坡堆积而成,受上游来流冲刷和渗透极易发生溃决,给下游人们生命财产造成严重威胁。快速、准确地预测溃决峰值流量是堰塞体抢险工作的重中之重。现有研究基于数据库—统计回归—溃决模型的思想,提出了一系列堰塞体溃决峰值流量预测模型,但均未综合考虑堰塞体冲蚀特性和颗粒组成对溃决流量的影响,且随着数据的不断扩充,预测模型难以取得预期效果。因此,本研究基于国内外2060例堰塞体溃决信息数据库,通过考虑堰塞体几何特征、冲蚀特性和颗粒组成,提炼出堰塞体高度(Hd)、堰塞体宽度(Wd)、堰塞体体积(Vd)、水库库容(Vl)、溃口深度(Hw)、溃口平均宽度(Wb)、堰塞体中值粒径(d50)7个影响参数,并将堰塞体冲蚀程度分为5类,构建了考虑冲蚀特性的堰塞体溃决峰值流量预测模型。选取数据齐全的120座堰塞体溃决案例对模型进行验证,均方根误差(RMSE)和相关系数(R2)分别为9581 m3/s与0.965,并和国内外已有典型参数模型进行比较。结果表明,考虑堰塞体冲蚀特性和d50参数的模型可以更好地预测溃决峰值流量,能够为堰塞体溃决抢险进程中的溃决洪水演进、下游受灾区域划分等工作内容提供合理参考。

关键词: 堰塞体, 冲蚀特性, 溃决流量, 参数模型

Abstract: A landslide dam is formed by natural landslide and is extremely vulnerable to dam failure due to flow scour and seepage, thereby posing a severe threat to human lives and property downstream. Rapid and accurate prediction of the peak flow rate through the breach is the most important task in the rescue work of landslide dam breaching. In previous studies, a series of landslide dam peak flow prediction models were developed based on the idea of the database-statistical regression-breaching model, but none of them took into account the effects of dam erosion characteristics or particle composition on the breaching flow. With continuous expansion of the data, it is difficult yet for these prediction models to achieve the expected results. This study is based on a database of 2060 cases of landslide dam failure in China and abroad, and takes into account the landslide dam geometrical characteristics, erosive characteristics and particle composition, through extracting seven parameters-weir height (Hd), weir width (Wd), weir volume (Vd), reservoir capacity (Vl), failure depth (Hw), average width of failure (Wb), and median particle size (d50). We classify the degree of dam erosion into five categories, and establish a peak flow prediction model of landslide dam failure that includes a factor of erosion characteristics. Then, we validate the model by selecting 120 cases with complete data from the database, and achieve a root mean square error (RMSE) of 9581 m3/s and a correlation coefficient (R2) of 0.965, with a comparison with the typical parameter models available in China and abroad. The results show that considering the landslide dam erosion characteristics and the d50 parameter improves the model significantly in predicting the peak breaching flow, and our model is satisfactory in accuracy and applicable to the peak flow predictions aimed at rescue and relief work. It would also help the routing of such outburst floods and the division of the affected areas downstream.

Key words: landslide dam, erosion characteristics, outburst flow, parametric model

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