Abstract: 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.