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

Abstract

The development and availability of climate forecasting systems have allowed the implementation of seasonal hydroclimatic services at the continental scale. User guidance and quality of the forecast information are key components to ensure user engagement and service uptake, yet forecast quality depends on the hydrologic model setup. Here, we address how seasonal forecasts from continental services can be used to address user needs at the catchment scale. We compare a continentally calibrated process‐based model (E‐HYPE) and a catchment‐specific parsimonious model (GR6J) to forecast streamflow in a set of French catchments. Results show that despite expected high performance from the catchment setup against observed streamflow, the continental setup can, in some catchments, match or even outperform the catchment‐specific setup for 3‐month aggregations and threshold exceedance. Forecast systems can become comparable when looking at statistics relative to model climatology, such as anomalies, and adequate initial conditions are the main source of skill in both systems. We highlight the need for consistency in data used in modeling chains and in tailoring service outputs for use at the catchment scale. Finally, we show that the spread in internal model states varies largely between the two systems, reflecting the differences in their setups and calibration strategies, and highlighting that caution is needed before extracting hydrologic variables other than streamflow. We overall argue that continental hydroclimatic services show potential on addressing needs at the catchment scale, yet guidance is needed to extract, tailor and use the information provided.

Advances in the Definition of Needs and Specifications for a Climate Service Tool Aimed at Small Hydropower Plants’ Operation and Management

“…SEAS5 is based on a global climate model, which, since the oceanic circulation is a major source of predictability in the seasonal scale, is based on coupled ocean-atmosphere integrations [17]. E-HYPE is the European setup of the HYPE model, which calculates hydrological variables on a daily time step at an average sub-basin resolution of 120 km 2 over the entire continent [17][18][19]. Figure 1 shows the location of the sub-basin where seasonal forecast data are produced, which has a size of 527 km 2 .…”

A Vision for Hydrological Prediction

“…Continental and global systems can address various user needs, notably in areas of sparse observational networks. Since they are based on global climate datasets, they also offer consistency among the meteorological data used in the setup and running of catchment-based hydrological models, even though they may lack accuracy at local scales due to local anthropogenic influences that are not usually taken into account in global models [14].…”

“…Once fuzzy logic systems were trained and validated for all subbasins, they were then applied (via a fuzzy inference) to the pan-European seasonal forecasts of the Jucar River Basin in order to obtain bias corrected discharge forecasts that could be applied to local models of reservoir optimization [27]. In another IMPREX study, we highlighted how the differences and the specificities of local and continental models raise the question of how useful large-scale models can be for local decision-making and how to optimally use the information from these different sources [14].…”

Lessons learnt from checking the quality of openly accessible river flow data worldwide

“…In hydrological modelling, datasets used throughout model delineation, parametrization, calibration, and validation, are essential and integral parts of the modelling, which will later influence model performance and may limit model applications (e.g. Arheimer et al 2012, 2019, Crochemore et al 2019.…”