Hydrological consistency in modeling - Improving model structure and parameter estimation with temporal diagnostic analyses

建模中的水文一致性 - 通过时间诊断分析改进模型结构和参数估计

• 批准号: 246416625
• 负责人: Dr. Björn Guse
• 金额: --
• 依托单位: Abteilung für Hydrologie und Wasserwirtschaft
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/246416625?language=en
• 关键词: Hydrological; consistency; modeling; Improving; model

Catchment models reproduce the hydrological processes and their temporal dynamic in a catchment. Seeing models as learning tools in contrast to application studies, these models are used for an improved understanding of processes and their representation in models. In a consistent model concept, the hydrological processes are appropriately represented in the model structure. Each model parameter is used for the related process and its dominant periods coincide with the temporal process patterns. Temporal diagnostic analyses investigate the relation of model structure and real-world processes in a high temporal resolution. In this project, temporal variations in dominant processes are detected by a temporal analysis of parameter sensitivity for each model time step. The temporal analysis of parameter sensitivities is related to total discharge and to the corresponding process to identify temporal process patterns. In combination with a temporal analysis of model performance, dominant parameters in phases of poor model performance are detected. Based on this, failures in model components are derived. Temporal diagnostic information is also included in the model calibration. For the estimation of the parameter values, only the periods of high sensitivity of this parameter are used.This project aims to develop new methods to achieve hydrologic consistency in model structure and calibration based on the temporal patterns of dominant processes. The main research objectives aim to achieve hydrologic consistency1) in the temporal process patterns by analyzing the temporal variations in dominant model parameters in relation to the corresponding hydrological process2) in the model structure by detecting structural model failures with a joined temporal analysis of parameter sensitivity and model performance3) in the estimation of model parameters by developing a new innovative calibration method based on periods of high parameter sensitivity.

流域模型再现了流域内的水文过程及其时间动态。将模型视为与应用研究相反的学习工具，这些模型用于改进对过程及其在模型中的表示的理解。在一个一致的模型概念，水文过程中适当地表示在模型结构。每个模式参数用于相关的过程，其优势周期与时间过程模式相吻合。时间诊断分析研究模型结构和现实世界的过程在高时间分辨率的关系。在这个项目中，在主导过程的时间变化检测的时间分析参数的敏感性，为每个模型的时间步。参数敏感性的时间分析与总流量和相应的过程，以确定时间过程模式。结合模型性能的时间分析，检测模型性能差的阶段中的主导参数。在此基础上，模型组件的故障推导。时间诊断信息也包括在模型校准中。对于参数值的估计，仅使用该参数的高敏感性时期。本项目旨在开发新的方法，以根据主导过程的时间模式在模型结构和校准中实现水文一致性。主要研究目标是：1）通过分析主要模型参数与相应水文过程的时间变化，实现时间过程模式中的水文一致性; 2）通过对参数敏感性和模型性能进行联合时间分析，检测模型结构故障，实现模型结构中的水文一致性; 3）通过开发一种基于高参数敏感性周期的新的创新校准方法来估计模型参数。

项目成果

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

• DOI: 10.1111/1752-1688.12524
• 发表时间: 2017-06
• 期刊: JAWRA Journal of the American Water Resources Association
• 作者: M. Pfannerstill;K. Bieger;B. Guse;D. Bosch;N. Fohrer;J. Arnold

Process verification of a hydrological model using a temporal parameter sensitivity analysis

使用时间参数敏感性分析对水文模型进行过程验证

• DOI: 10.5194/hess-19-4365-2015
• 发表时间: 2015
• 期刊: Hydrology and Earth System Sciences
• 影响因子: 6.3
• 作者: Pfannerstill;Reusser;Fohrer
• 通讯作者: Fohrer

Detection of dominant nitrate processes in ecohydrological modeling with temporal parameter sensitivity analysis

• DOI: 10.1016/j.ecolmodel.2015.07.009
• 发表时间: 2015-10-24
• 期刊: ECOLOGICAL MODELLING
• 影响因子: 3.1
• 作者: Haas, Marcelo B.;Guse, Bjoern;Fohrer, Nicola
• 通讯作者: Fohrer, Nicola

On characterizing the temporal dominance patterns of model parameters and processes

• DOI: 10.1002/hyp.10764
• 发表时间: 2016-06
• 期刊: Hydrological Processes
• 影响因子: 3.2
• 作者: B. Guse;M. Pfannerstill;M. Strauch;D. Reusser;S. Lüdtke;M. Volk;H. Gupta;N. Fohrer

A joined multi-metric calibration of river discharge and nitrate loads with different performance measures

• DOI: 10.1016/j.jhydrol.2016.03.001
• 发表时间: 2016-05
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: M. Haas;B. Guse;M. Pfannerstill;N. Fohrer