摘要
利用新安江模型对无资料地区径流预报方法进行研究。以澳大利亚东南地区的210个流域为例,首先利用距离相近法、属性相似法和回归法进行预报,并对3种方法进行比较,结果表明,距离相近法精度最高,属性相似法次之,回归法效果较差。然后在距离相近法和属性相似法的基础上提出了综合相似法,使得模拟结果进一步提高。此方法可对中国无资料或者资料缺乏流域进行水文预报。
This paper uses a conceptual rainfall-runoff model, the Xinanjiang model, to evaluate regionalization approaches using 210 catchments in south-east Australia as examples. Three regionalization approaches are compared： spatial proximity, physical similarity and regression. The results show that： spatial proximity provides the best regionalization solution; the physical similarity approach is intermediary; the regression approach is the least satisfactory. A new method, integrated similarity, is proposed by combining the spatial proximity and physical similarity. It turns out the integrated similarity further improves runoff prediction in free of observational data catchments. It is likely that taking into account the parameter uncertainty will improve the performance of predictions in free of observational data catchments.
出处
《长江科学院院报》
CSCD
北大核心
2010年第2期11-15,共5页
Journal of Changjiang River Scientific Research Institute
基金
国家自然科学基金项目(50979062)
国家科技重大水专项(008ZX07526-004-T007)
关键词
新安江模型
无资料地区
径流预报
区域化
Xinanjiang model
runoff prediction
free of observational data catchments
regionalization
