文章摘要
张相芝, 周 剑, 文 磊.时空变源混合产流模型及其在小流域洪水模拟中的应用——以四川省、甘肃省的4个小流域为例Journal of Water Resources and Water Engineering[J].,2021,32(3):80-90
时空变源混合产流模型及其在小流域洪水模拟中的应用——以四川省、甘肃省的4个小流域为例
Application of spatio-temporal variable source mixed runoff model to flood simulation of small watersheds:A Case study of four small watersheds in Sichuan and Gansu Province
  
DOI:10.11705/j.issn.1672-643X.2021.03.12
中文关键词: 山洪模拟  时空变源混合产流模型  主导产流成份  敏感性参数  下垫面信息
英文关键词: flash flood simulation  spatio-temporal variable source mixed runoff model  dominant runoff component  sensitivity parameter  underlying surface information
基金项目:国家重点研发计划项目(2018YFC1508105); 全国山洪灾害防治项目(Y990BQ1001)
Author NameAffiliation
ZHANG Xiangzhi1,2, ZHOU Jian1, WEN Lei3 (1.中国科学院 西北生态环境资源研究院 甘肃 兰州 730000 2.中国科学院大学 北京 100049 3.河海大学 水文水资源学院 江苏 南京 210098) 
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中文摘要:
      近年来山洪灾害造成的人员伤亡和财产损失不断增加,基于GIS和遥感数据的水文模型为山洪预报提供了新的思路。利用DEM和遥感数据提取小流域基础属性并划分地貌水文响应单元,利用垂向混合产流计算产流量,采用包气带非饱和土壤计算下渗,建立垂向上的时空变源混合产流模型。利用时空变源混合产流模型,模拟四川省和甘肃省4个流域多场次洪水过程,通过SCE算法进行参数率定和产流分析。结果表明:模型模拟与实测数据基本吻合,纳什效率系数均超过0.8;四川和甘肃两省小流域受到下垫面信息影响,主导产流成分不同。模型能够提供较为精确的山丘区流域洪水预报。
英文摘要:
      In recent years, the casualties and property losses caused by flash flood disasters have been on the rise. Hydrological models based on GIS and remote sensing data can provide a new perspective for flash flood forecasting. Here, DEM and remote sensing data were adopted to extract basic attributes of small watersheds and to divide them into geomorphological and hydrological response units, then the discharge was calculated using vertical mixed runoff, and the infiltration was calculated using unsaturated soil in vadose zone, based on which the vertical spatio-temporal variable source mixed runoff model was established. Then the spatio-temporal variable source mixed runoff model (SVSM) was used to simulate multiple flood processes in four river basins of Gansu and Sichuan Province. The parameter calibration and runoff analysis were carried out using the shuffled complex evolution (SCE) algorithm. The results showed that the simulation results are consistent with the measured data, and the Nash efficiency coefficients are all over 0.8. Because small watersheds in Gansu and Sichuan Provinces are affected by the underlying surface information, their dominant runoff components are different. The proposed model can provide more accurate forecasting results for flash floods in hilly areas.
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