Catchments as non-linear filters: understanding catchment similarities for the regionalisation of rainfall-runoff transformation processes using wavelets

流域作为非线性滤波器：使用小波了解流域相似性以进行降雨径流转换过程的区域化

• 批准号: 35039866
• 负责人: Professorin Dr. Bettina Schaefli
• 金额: --
• 依托单位: Geographisches Institut
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2006
• 资助国家: 德国
• 起止时间: 2005-12-31 至 2007-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/35039866?language=en
• 关键词: Catchments; non; linear; filters; understanding

Discharge prediction in catchments with no or only a few discharge measurements - so-called ungauged catchments - is emerging as a major scientific and socioeconomic challenge. Currently available hydrological models are difficult to transfer from gauged to ungauged catchments due to an insufficient understanding of the hydrological processes underlying the discharge formation at the catchment scale. Such a spatial transfer of hydrological models is possible under the assumption that similar landscape units produce similar hydrological processes. The objective of the present research is to investigate this assumption and to propose a new approach for the quantification of hydrological landscape similarity. This similarity measure will be based on the assumption that different landscapes have different non-linear filtering characteristics during the rainfall-runoff transformation process and that these characteristics can be quantified. The filtering effects will be identified through signal processing techniques, namely wavelet analysis. Wavelets enable a quantitative analysis of how certain frequency features of a system input time series are filtered in the system output time series. In the present research, this main property will be exploited for the investigation of the filtering characteristics of different landscape units. A similarity measure based on such dynamic characteristics has the main advantage of connecting directly the hydrological response of a catchment or landscape unit to the processes that condition this response. It contributes therefore not only to the modelling of the hydrological response but to its understanding. The efficiency of the new approach and the gained insights will be validated through a discharge regionalisation study with data sets from the German part of the Rhine catchment.

没有或仅有少量流量测量的流域（即所谓的未测量流域）的流量预测正在成为一项重大的科学和社会经济挑战。由于对流域尺度流量形成背后的水文过程了解不足，目前可用的水文模型很难从计量流域转移到非计量流域。假设相似的景观单元产生相似的水文过程，这种水文模型的空间转移是可能的。本研究的目的是调查这一假设并提出一种量化水文景观相似性的新方法。这种相似性度量将基于这样的假设：不同景观在降雨-径流转化过程中具有不同的非线性过滤特性，并且这些特性可以量化。过滤效果将通过信号处理技术（即小波分析）来识别。小波可以定量分析系统输入时间序列的某些频率特征如何在系统输出时间序列中被过滤。在本研究中，将利用这一主要特性来研究不同景观单元的过滤特性。基于这种动态特征的相似性测量的主要优点是将流域或景观单元的水文响应直接连接到调节该响应的过程。因此，它不仅有助于水文响应的建模，而且有助于对其的理解。新方法的效率和所获得的见解将通过使用莱茵河流域德国部分数据集的排放区域化研究来验证。