Development and Evaluation of a Pan-European Multimodel Seasonal Hydrological Forecasting System

Abstract

Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.

Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?

“…User needs beyond the local and regional scales have led to the development of hydroclimate services at the continental and global scales (e.g., Arnal et al, 2018;Emerton et al, 2018;Thiemig et al, 2015;Wanders et al, 2018). The aim in developing these services is twofold: to bridge the gap between user needs and the current state of climate knowledge (van den Hurk et al, 2016) and to tailor climate information to be readily available to local users (e.g., in hydropower production; Foster et al, 2018).…”

A Vision for Hydrological Prediction

“…There has been an increasing interest in the implementation of large-scale months-ahead hydrological forecasting systems to serve the water sector. Further examples at the European scale are the pan-European hydroclimatic seasonal forecasting service from the Swedish Meteorological and Hydrological Institute (SMHI; based on the hydrological model E-Hype [5]), and the EDgE project end-to-end demonstrator for improved decision-making in the water sector [6,7] (based on the Mesoscale Hydrologic Model (mHM) [8], PCR-GLOBWB [9], Variable Infiltration Capacity (VIC) [10] and Noah-MP [11]), both developed under the Copernicus Climate Change Service (C3S) to support society and European authorities with consistent climate data and enhanced information on impacts. At the global scale, the global operational seasonal hydrometeorological forecasting system, GloFAS-Seasonal (based on the one-way coupled HTESSEL and Lisflood models) [12] and the global system based on the North American Multimodel Ensemble (NMME) [13] are examples of recent developments.…”

Evaluating skill and robustness of seasonal meteorological and hydrological drought forecasts at the catchment scale – Case Catalonia (Spain)

“…The difference between skill in meteorological and hydrological drought forecasts can be explained by catchment memory, that is, prevailing catchment storage capacity (soil water, groundwater). Soil water and groundwater explain over 50% of the variance in discharge forecasts for short LTs (1-2 months) and remains about 40% up to LT = 3-4 months (Wanders et al, 2019).…”

“…The early projects were set up to decrease the impact of flooding, but later these projects also included hydrological forecasts and drought projections under different climate change scenarios at the pan-European scale (e.g. Marx et al, 2018;Thober et al, 2018;Wanders et al, 2019). However, none of them addresses hydrological drought forecasts.…”

“…Hence, skills of hydrological forecasts, which are known (e.g. Wanders et al, 2019), and skills of hydrological drought forecasts are anticipated to be different.…”