Research progresses and prospects of catchment hydrological forecasting driven by global climate forecasts

Global climate models and emerging artificial intelligence models generate big climate forecasts data for catchment hydrological forecasting at daily, sub-seasonal and seasonal timescales. The utilization of global climate forecasts to drive catchment hydrological models are confronted with the technical issues of climate forecast data retrieval, hydrological forecasting model set-up and verification of hydro-climatic forecasts. Starting with international collaborative research projects on global climate forecasting, this paper conducts a survey of short-term weather forecasts for the next 1 day to 2 weeks, sub-seasonal climate forecasts for the next 1 to 60 days, seasonal climate forecasts for the next 1 to 12 months and artificial intelligence-based climate forecasts. Furthermore, the processes of catchment hydrological forecasting driven by global climate forecasts are illustrated by detailing the technical aspects on the calibration of climate forecasts, the setting-up of hydrological models and the verification of predictive performance. By generating real-time and retrospective catchment hydrological forecasts from global climate forecasts, the efficacy of forecasting models can be quantitatively examined by verifying forecast skill at different lead times, laying a solid basis for practical forecasts-based operations of hydraulic infrastructure.