When timing matters-misdesigned dam filling impacts hydropower sustainability

Abstract

Decades of sustainable dam planning efforts have focused on containing dam impacts in regime conditions, when the dam is fully filled and operational, overlooking potential disputes raised by the filling phase. Here, we argue that filling timing and operations can catalyze most of the conflicts associated with a dam's lifetime, which can be mitigated by adaptive solutions that respond to medium-to-long term hydroclimatic fluctuations. Our retrospective analysis of the contested recent filling of Gibe III in the Omo-Turkana basin provides quantitative evidence of the benefits generated by adaptive filling strategies, attaining levels of hydropower production comparable with the historical ones while curtailing the negative impacts to downstream users. Our results can inform a more sustainable filling of the new megadam currently under construction downstream of Gibe III, and are generalizable to the almost 500 planned dams worldwide in regions influenced by climate feedbacks, thus representing a significant scope to reduce the societal and environmental impacts of a large number of new hydropower reservoirs.

Fig. 1. Geography of the Omo-Turkana Basin (OTB).

The Omo river collects the abundant rainfalls of the Ethiopian highlands and flows southwards through the Omo valley contributing about 90% of the annual inflow to Lake Turkana, where its outlet forms a complex delta across the Ethiopian-Kenyan border. About 500 thousand pastoralists and farmers inhabit the area depending on the Omo or Turkana waters for their livelihood. The Gibe-Koysha dam cascade regulates the river hydrology, comprising Gibe I and II, the recently completed Gibe III, and the Koysha dam currently under construction. Marker size is proportional to the installed hydropower capacity. Basemap: Google Satellite, Map data ©2015 Google.

Fig. 2. Reconstructed historical filling strategy.

a Gibe III reservoir reached its normal operating level within its first two years of operations by impounding the near totality of the 2015 Kiremt season inflow, and a significant fraction of 2016’s. b In the two following years, Gibe III level oscillates around its operational level as a consequence of a release pattern that increases low flows and reduces high flows with respect to natural Omo hydrology. c Simultaneously, Lake Turkana suffered a 2-m level drop with respect to a simulation of a scenario in which Gibe III was not built. While the Lake Turkana level trajectory estimated from satellite altimetry is publicly available, we reconstructed the Gibe III level trajectory from Sentinel 2 image classification (see “Methods”).

Fig. 3. Climatic oscillations can inform a favorable timing for filling.

A pattern of harmonic climatic oscillations governs the magnitude of annually cumulated rainfall occurring on the OTB, shown at a monthly time step (a). Panels (b–e) contrast the historical 2015 filling performance (black bar) with alternative filling timings (colored bars) with respect to relevant indicators. The bar labels report the percentage change in the value of the indicator with respect to the historical performance. Filling Gibe III reservoir during an upwards phase of water availability (e.g., 2013), instead of a downwards phase as historically, could have resulted in a more efficient, and less conflictual filling. By projecting the harmonic trends into the future, we advise to delay Koysha filling by one year and begin in 2022 instead of the planned 2021, as the additional stress caused by a bad timed filling stress could have detrimental consequences on the fragile social and ecological balances of the region.

Fig. 4. Adaptive filling strategies can reduce filling impacts.

The seasonal forecasts of Standardized Precipitation and Evaporation Index expressed in terms of dry, normal, and wet conditions with respect to seasonal average (a) inform the designed adaptive filling strategies (b, c). Different colors correspond to adaptive strategies with different tradeoffs between upstream and downstream competing interests, blues for more environmental inclined, and reds for hydropower inclined strategies, while the historical strategy is represented in black. Adaptive strategies demonstrate the ability to significantly reduce downstream impacts on Lake Turkana (d) and average river hydrology (e, where the shaded areas refer to the interannual variability) while remaining within a contained range of historically produced hydropower. The numerical labels in the barplot of f quantifies the percentage difference in hydropower production associated with adaptive strategies normalized to the historical production. This figure illustrates 4 representative adaptive solutions, compared to the historical solution in black. The complete set of adaptive policies resulted from the optimization is reported in Supplementary Fig. 4.

Fig. 5. Future dams overlap regions with a strong ENSO influence.

The red points indicate the locations of medium-to-large future hydropower reservoirs and dams, extracted from the FHReD database. Dam height is generally employed to discern between small, medium, and large dams, but in the absence of this information, we consider as medium-to-large the hydropower projects with an installed capacity grater than 150 MW, retaining a total of 642 dams of the over 3700 reported in the database. A blue shade highlights the regions of the globe that are most affected by El Niño and La Niña oscillations. Over 70% of medium-to-large future dams are located in areas affected by the ENSO teleconnection.