A feasible quantitative hydrological forecasting service is a combination of technological elements, qualified personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation. The process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here we present an operational assessment and lessons from the implementation and first year of operation of the recently released Operational Forecast Service for the Betania’s Hydropower Reservoir – PRONOS, located at the Upper-Magdalena River Basin (Colombia). PRONOS was developed under the Flexible, Adaptive, Simple and Transient Time forecasting approach, or FAST-T, a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time and operational forecast and automatic model adjustment in case of failures in the data real-time transmission or assimilation. The PRONOS service is designed specifically to support the hydropower operation, therefore, produces forecasts of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. At its current configuration, the PRONOS performance objectives are fulfilled for 90% of the forecasts with lead times up to +2 days and +15 hours (using the predictability criteria) and the average accuracy is in the range 70-99% ( criteria). However, longer lead times are at present not satisfactory in terms of forecasts accuracy. System reliability was also evaluated in terms of forecast performance consistency over time (65%), and the percentage of time offline (7%).
Domínguez, Efraín; Angarita, Hector; Méndez, Zulma; Angulo, Gustavo; Motavita, Diego; and Rosmann, Thomas, "The PRONOS Hydrological Forecast System: Assessment And Learned Lessons From The First Year Of Operation At The Betania Hydropower Reservoir" (2014). CUNY Academic Works.