Hydropower Portfolio Site and Design using a Simulation - Optimisation Model incorporating High Resolution Hydraulic Modelling in Data Scarce Regions

Development of hydropower in developing countries carries economic development rewards, particularly for storage hydropower which can be used to balance fluctuating supply of other renewables. Yet, dams and reservoirs carry significant environmental impacts, e.g., network fragmentation and flow alteration. While flood control has often been a motivator for reservoir construction, one environmental impact of storage hydropower on tropical rivers is the reduction of peak flows resulting in less hydraulic connectivity between floodplains and channels. In many tropical rivers, where most future dams are planned, this reduced lateral connectivity will create negative impacts on biodiversity, the biophysical functioning of floodplains, and human uses such as recession agriculture. Determining the optimal siting, design, and operation (SDO) of dam portfolios which maximises power generation and minimises this environmental impact, e.g., in terms of maintaining lateral connectivity, is a complex problem.

Simulation - Optimisation models of hydropower portfolios have often included impact on annual flood peak as a proxy objective for floodplain impacts, but have rarely explicitly included inundated area as an objective. Furthermore, when this type of analysis is done, it is usually performed at a monthly timescale, which underestimates flood peaks and neglects in-channel and floodplain hydraulics.

This work presents a multi-dam simulation - optimisation framework which uses a high-resolution hydrodynamic modelling framework (LISFLOOD-FP) to explicitly model the impact of SDO of many different dam portfolios on inundated floodplain extent, and to include this modelled extent as an optimisation objective. This incorporates channel and floodplain hydraulics at a fine time resolution, allowing a more realistic representation of the impact of hydropower development on biodiversity.

The optimisation framework is applied to the data scarce Pungwe Basin in Mozambique / Zimbabwe, and identifies significant trade-offs from mainstem damming between power production and downstream hydraulic connectivity between rivers and floodplains. It identifies Pareto Optimal combinations of site and design (large dam, small dam, and run-of-the-river installations) for these two objectives. The inclusion of hydraulically modelled inundated area represents a step forward for increasing the ability of simulation - optimisation frameworks to model complex downstream impacts of hydropower development and operation related to changing discharge and channel hydraulics.