The effect of weighting hydrological projections based on the robustness of hydrological models under a changing climate

Journal of Hydrology: Regional Studies

Paul Royer-Gaspard¹  Christiana Photiadou²  Javier Aparicio-Ibañez²  Rafael Pimentel³  María José Pérez-Palazón⁴  Ernesto Pastén-Zapata⁴  Jens Christian Refsgaard⁵  Raphael Schneider⁵  Torben O. Sonnenborg⁵  Guillaume Thirel⁶  Anthony Lemoine⁶ 

[1] Corresponding author at: Department of Hydrology, Geological Survey of Denmark and Greenland, Copenhagen, Denmark.;Department of Agronomy, Unit of Excellence María de Maeztu (DAUCO), University of Córdoba, Córdoba, Spain;Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, Finland;Department of Hydrology, Geological Survey of Denmark and Greenland, Copenhagen, Denmark;Fluvial Dynamics and Hydrology Research Group. Andalusian Institute for Earth System Research, University of Cordoba, Córdoba, Spain;Université Paris-Saclay, INRAE, HYCAR Research Unit, Antony, France;

关键词: Uncertainty;    Climate change impacts;    Model weighting;    Differential split sampling test, Bayesian model averaging;   

DOI  :  

来源: DOAJ

【 摘 要 】

Study region: This study is developed in three catchments located in Denmark, France and Spain, covering different climate and physical conditions in Europe. Study focus: The simulation skill of hydrological models under contrasting climate conditions is evaluated using a Differential Split Sample Test (DSST). In each catchment, three different hydrological models are given a weight based on their simulation skill according to their robustness considering the DSST results for traditional and purpose-specific metrics. Four weighting approaches are used, each including a different set of evaluation metrics. The weights are applied to obtain reliable future projections of annual mean river discharge and purpose-specific metrics. New hydrological insights: Projections are found to be sensitive to model weightings in cases where the models show significantly different skills in the DSST. However, when the skills of the models are similar, there is no significant change when applying different weighting schemes. Nevertheless, the methodology proposed here increases the reliability of the purpose-for-fit hydrological projections in a climate change context.

【 授权许可】

Unknown