In today’s competitive energy market, water managers need optimized strategies for maximizing the profitability of their hydropower systems. Accurate and reliable inflow forecasting tools are critical for hydropower operators to balance competing interests and make informed operational decisions leading to efficient use of water resources. Over the past decades, a large number of inflow forecasting tools have been developed with varying degrees of complexity, accuracy and performance, depending on the application and forecasting situation. In current operational practice, much effort is devoted to data collection, application and use of inflow forecasting tools, but much less effort to the selection, review and evaluation of the tools. This report provides a systematic review of inflow forecasting tools according to the techniques they use and their position in the inflow forecasting system.
The information used in the review was collected from published literature, as well as from a survey of hydropower agencies from different parts of the world. From the collected information, a subset of promising forecasting tools was identified by a two-level selection procedure. The accuracy of these tools was then conceptually evaluated, and the results summarized in a decision matrix developed to assist hydropower operators in the selection of the most appropriate forecasting tools for a given watershed’s hydro-climatic settings and forecasting application.
The last section of the report is devoted to case study modelling. The aim of the modelling was to explore, in detail, specific inflow forecasting issues. The key issues considered were the effects of spatial detail and complexity of process-based hydrologic models on forecast accuracy, meteorological forecast errors, model updating issues, impacts of forecaster errors on forecast accuracy, and real short-term deterministic and long-term probabilistic forecasting. The scenarios were modelled in two case study watersheds, with contrasting geographic and hydro-climatic settings and forecasting conditions.
Keywords: Inflow forecasting, meteorological forecasting, downscaling, hydrologic forecasting, probabilistic forecasting, data assimilation, forecast accuracy, modelling.