Using Medium-Range Ensemble Inflow Scenarios for Decision Support on the Sediments Management of a Hydropower Dam

Forecasts of hydrological variables at a medium-range horizon, from one to two weeks, are useful to operate reservoirs, especially if these are used for hydropower generation and are constrained due to multiple water uses. In the present study we investigate the use of medium-range scenarios of reservoirs inflow for a decision making procedure related to a reservoir operation in the Doce River basin, in Brazil. The main location of interest for hydrological forecasting in the Doce River basin is the reservoir of the Aimorés Hydro Power Plant (HPP). The drainage area of the HPP is approximately 63,000km2. Aimorés HPP is owned by a consortium of CEMIG (Companhia Energética de Minas Gerais) and Vale (Mineradora Vale). It has an installed generation capacity of 330MW, and its reservoir has a total volume of approximately 184.66 million cubic meters. During the daily operations this reservoir acts as a “trap” to the large amount of sediments that originates from the upstream basin of the Doce River. This motivates a cleaning process called “pass through” to periodically remove the sediments from the upstream area of the reservoir and avoid greater problems in terms of backwater flooding, hydropower generation and dam safety. The “pass through” or “sediments flushing” process consists of a decrease of the reservoir’s water level to a certain flushing level when a determined reservoir inflow threshold is forecasted. Then, the water in the approaching inflow is used to flush the sediments from the reservoir through the spillway and to recover the original reservoir storage. To be triggered, the sediments flushing operation requires an inflow larger than 2500 m3/s in a forecast horizon of 7 days. This number of days is not only related to the reservoir volume, but also related to the time necessary to make all the preparations with the local authorities to authorize the procedures. The operation can only be aborted without major impacts within a 3 days lead time. A lead-time of 7 days is far beyond the basin’s concentration time (around 2 days), meaning that the forecasts for the pass-through procedure highly depends on Numerical Weather Predictions (NWP) models that generate Quantitative Precipitation Forecasts (QPF). This dependency on medium-range NWP creates an environment with a high amount of uncertainty to the operators, since the meteorological uncertainty of the QPF is usually a key factor in medium-range hydrological forecasting [1]. Fan et al. [2] also studied ensemble forecasts in a broader study that included the Doce river region and showed that forecasts with lead times over 3 days have increasing errors. To support the decision making related to executing the flushing process at Aimorés HPP, we developed a fully operational hydrological forecasting system to the basin. The forecasting system can generate ensemble streamflow forecasts scenarios when driven by QPF data from meteorological Ensemble Prediction Systems (EPS). This approach allows accounting for uncertainties in the NWP at a decision-making level. This research has the objective of verifying what is the added value of the ensemble scenarios (in comparison to a deterministic reference) and what are the conditions to trigger the flushing process provided by the medium-range ensemble forecasts for this decision-making problem. Volume 2 Issue 1 2018