摘要
构建了一种基于网格计算流域蒸散发及产汇流的分布式格林-安普特降雨径流模型,并选择陕北黄土高原地区两个半干旱流域为研究区域,研究该模型在半干旱地区的应用效果。结果表明:在两个半干旱流域,分布式格林-安普特降雨径流模型的应用效果好于GA-PIC模型和格林-安普特模型,尤其对于洪峰的模拟精度更高;分布式格林-安普特降雨径流模型中基于网格的坡面汇流与河道汇流模块能够更准确地计算出径流汇集到流域出口断面的时间;分布式格林-安普特降雨径流模型能更精确地计算出流域不同位置的产流过程,并准确地模拟流域产流面积分布情况;半干旱地区降雨时空分布不均,超渗产流主要受降雨强度的影响,降雨观测精度对径流预报精度影响较大。
A distributed Green-Ampt rainfall-runoff model based on orthogonal grids was built and applied to two semi-arid basins in the Loess Plateau of Northern Shaanxi Province to test its performance.The results show that in the two semi-arid basins,the distributed Green-Ampt model performs better than the GA-PIC model and the traditional Green-Ampt model,especially in the flood peak simulating.The distributed Green-Ampt model has higher accuracy in simulating the time from the confluence to outlet section of basin with the grid-based slope confluence and river confluence module.In addition,the distributed Green-Ampt model is able to calculate the runoff process at different locations of the basin more accurately,and also able to simulate the runoff area distribution of the basin more accurately.The spatial and temporal distribution of rainfall in the semi-arid area is uneven and the infiltrated-excess runoff is mainly affected by the rainfall intensity,therefore the rainfall observation accuracy has a great impact on the runoff forecasting accuracy.
作者
霍文博
李致家
张珂
杨明祥
金双彦
张萍
HUO Wenbo;LI Zhijia;ZHANG Ke;YANG Mingxiang;JIN Shuangyan;ZHANG Ping(China Institute of Water Resource and Hydropower Research,Beijing 100038,China;Hydrology Bureau of Yellow River Conservancy Commission,Zhengzhou 450004,China;College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)
出处
《河海大学学报（自然科学版）》
CAS
CSCD
北大核心
2022年第3期47-54,共8页
Journal of Hohai University(Natural Sciences)
基金
国家自然科学基金(52079035,51679061)
国家重点研发计划(2018YFC1508100)
流域水循环模拟与调控国家重点实验室自由探索课题(SKL2020TS01)。
关键词
分布式格林-安普特降雨径流模型
降雨径流
半干旱流域
超渗产流模型
洪水预报
陕北地区
distributed Green-Ampt rainfall-runoff model
rainfall-runoff
semi-arid basin
infiltrated-excess runoff model
flood forecasting
Northern Shaanxi Province
