考虑产流模式空间分布的流域-城市复合系统洪水预报模型

Study on flood forecasting model of watershed-urban complex system considering the spatial distribution of runoff generation pattern

为解决流域-城市复合系统洪水协同预报问题,本文将流域和城市纳入统一空间范畴,在提出易发生产流模式辨析框架的基础上,耦合网格产流计算模型(GRGM)和长短时记忆神经网络(LSTM)构建了GRGM-LSTM洪水预报混合模型。以贾鲁河中牟站控制流域为例,基于18场实测洪水进行模型检验,同时将预报结果与暴雨洪水管理模型(SWMM)、GRGM-SWMM模型进行对比分析。研究表明:①GRGM模型模拟产流量相对误差、决定性系数平均值分别为8.41%、0.976,考虑产流模式空间分布的产流计算更为准确;②预见期小于6 h时,GRGM-LSTM混合预报模型纳什效率系数大于0.8,比GRGM-SWMM、SWMM等物理机制模型具有更好的模拟性能;③预见期大于6 h时,GRGM-LSTM混合模型出现一定的精度损失,预见期增至12 h时,GRGM-SWMM模拟精度高于GRGMLSTM模型。研究成果可为流域-城市防洪减灾协同管理提供科学依据。

Current study incorporates both the watershed and urban areas into a unified spatial context in order to address the problem of coordinated flood forecasting in watershed-urban compound systems.Based on the proposed framework for distinguishing easily generated runoff patterns,a hybrid forecasting model,called GRGM-LSTM,and is developed by coupling the Grid-based Runoff Generation Model(GRGM)with Long Short-Term Memory neural networks(LSTM).The model is tested using 18 observed flood events in the control basin of the Jialu River at Zhongmou station.In addition,the forecast results are compared and analyzed against the Storm Water Management Model(SWMM)and GRGM-SWMM model.The study reveals that:①The relative error and coefficient of determination obtained from the GRGM for simulating runoff are 8.41%and 0.976,respectively.This indicates that considering the spatial distribution of runoff patterns results in more accurate runoff calculations.②For forest period of less than 6 hours,the GRGM-LSTM hybrid model outperforms physical mechanism models such as GRGM-SWMM and SWMM,yielding Nash-Sutcliffe efficiency coefficients greater than 0.8,indicating superior simulation performance.③However,for a forest period exceeding 6 hours,the GRGM-LSTM hybrid model experiences some accuracy loss,and when the forest period increases to 12 hours,the simulation accuracy of GRGM-SWMM surpasses that of GRGM-LSTM.The research findings can serve as a scientific basis for coordinated management of flood prevention and disaster reduction in watershed-urban areas.