An Ensemble Modelling Framework for Prediction in Ungauged Catchments

用于未测量流域预测的集成建模框架

• 批准号: DP0879218
• 负责人: Prof Ashish Sharma
• 金额: $ 24.84万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-03-31 至 2012-03-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0879218
• 关键词: Ensemble; Modelling; Framework; Prediction; Ungauged

An important issue facing the water sector is a rationale for modeling flows in catchments having no prior measurements. Current approaches for modeling flow in ungauged catchments assume a rigid specification which is adopted for all catchments, irrespective of differences in regions and soil types. We propose here a modeling philosophy that better characterises the variability in the flow generation mechanism, with different mechanisms being represented through different models in a probabilistic sense. We expect our approach to address the limitations of current schemes, and provide a much improved basis for estimating flows for design and management applications.

水务部门面临的一个重要问题是在没有事先测量的情况下对流域流量进行建模的基本原理。当前对未计量流域流量进行建模的方法假设了所有流域均采用的严格规范，无论地区和土壤类型有何差异。我们在这里提出了一种建模理念，可以更好地表征流生成机制的可变性，不同的机制在概率意义上通过不同的模型来表示。我们希望我们的方法能够解决当前方案的局限性，并为设计和管理应用程序的流量估计提供一个大大改进的基础。