Hydropower, a leading renewable energy source, is cheap, reliable, and sustainable. Small
hydropower plants (SHPs) under 10 MW offer an eco-friendly alternative to traditional dams,
yet only 36 % of their capacity is exploited globally. This research focuses on run-of-river
(RoR) plants, having (sub-daily) storage capacity, making them the predominant type of
SHPs. Over 2,000 RoRs are planned or under construction in emerging economies over the
next three decades despite challenges posed by climate change and socio-economic uncertainties. Traditional designs rely on cost-benefit analyses, ignore hydroclimatic variations,
operational considerations and future-proofing investments. The primary goal of this thesis is to propose a robust framework for designing RoR hydropower plants, with secondary
objectives to ensure computational efficiency and integration of optimized operations into
design. These aims have been achieved through three core papers, all led by me. First, I
developed a novel statistical generation method for generating plausible streamflow futures,
enabling robust hydropower assessment without rainfall-runoff models. I used this method
to represent climatic uncertainty in the rest of this thesis. I then proposed a Multi-Objective
Robust Decision-Making approach to RoR design in response to the limitations of traditional
approaches. This study pioneers integrating variable turbine efficiency into a framework for
multi-objective hydropower design, assessing its financial viability under uncertain futures.
Application to five cases challenges fundamental design assumptions, advocating for smaller
designs with varying turbine capacities and high benefit-cost ratios as robust solutions across
diverse plausible futures. Finally, to address the computational expense of the above framework, I developed the HYPER-FORD toolbox. It proposes approximations to slash the
computational requirements associated with the robust design by over 92%, without compromising accuracy and in fact, by explicitly incorporating optimised operations into design
for the first time. These contributions collectively advance RoR design, benefiting real-world
decision-making and promoting effective, sustainable water resource management.
