Regional Adaptability of Global and Regional Hydrological Forecast System

Abstract

Our paper aims to improve flood forecasting by establishing whether a global hydrological forecast system could be used as an alternative to a regional system, or whether it could provide additional information. This paper was based on the operational Global Flood Awareness System (GloFAS) of the European Commission Copernicus Emergency Management Service, as well as on a regional hydrological forecast system named RHFS, which was created with observations recorded in the Wangjiaba river basin in China. We compared the discharge simulations of the two systems, and tested the influence of input. Then the discharge ensemble forecasts were evaluated for lead times of 1–7 d, and the impact on the forecasts of errors in initialization and modelling were considered. We also used quantile mapping (QM) to post-process the discharge simulations and forecasts. The results showed: (1) GloFAS (KGE of 0.54) had a worse discharge simulation than RHFS (KGE of 0.88), mainly because of the poor quality of the input; (2) the average forecast skill of GloFAS (CRPSS about 0.2) was inferior to that of RHFS (CRPSS about 0.6), because of the errors in the initialization and the model, however, GloFAS had a higher forecast quality than RHFS at high flow with longer lead times; (3) QM performed well at eliminating errors in input, the model, and the initialization.

Advancing Medium-Range Streamflow Forecasting for Large Hydropower Reservoirs in Brazil by Means of Continental-Scale Hydrological Modeling

“…However, there are currently several techniques that can improve the accuracy of flow prediction from local information, ranging from simple bias correction methods (e.g., [44]) to more complex methods such as ensemble calibration, statistical postprocessing (e.g., [14,18,45]), and data assimilation (e.g., [13,28,46]), although simple methods are generally more attractive because of their efficiency and ease of operational application [47]. In this sense, Lozano et al [48] showed that a simple bias correction on the outputs of a global-scale system was able to effectively transform historical runoff simulations and forecasts for local-scale use in Brazil, while Wang et al [49] found that a global forecast system (GloFAS) outperformed a regional system in predicting high runoff and even performed reasonably well in predicting low to moderate runoff after bias correction on forecast runoff. Combining simple bias correction with autoregressive models that can use newly available local information [50,51] also proved suitable for hydrological forecasting.…”

Assessment of the Feasibility of Implementing a Flash Flood Early Warning System in a Small Catchment Area

“…Flood early warning systems are widely used for real-time flood forecasting, especially for river basins, stream flows and urban drainage systems [51,52]. For planned real-time flood forecasting, the unique features of the protected urban or non-urban area and its microclimate should be considered [53][54][55][56]. The usefulness of a real-time flood forecasting model depends mainly on the quality of the collected data used to develop the model and the evaluation of its performance.…”