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Spotlight |


Accounting for grey swans and butterfly effects


Predictive surprise and natural variability in hydrology and climate have begun to overwhelm those who manage and operate hydraulic infrastructures, and water and hydropower resources, but flexible, science-based, and data-driven planning can help manage disaster risks and ensure progress. Auroop R. Ganguly explains why dam and hydropower managers need to urgently account for the swan and butterfly effects.


THERE WAS A TIME in the not-too-distant past when insurance companies refused to pay for what they called “acts of God”, which in turn included almost all natural catastrophes, and which were considered rare enough to be unpredictable and beyond the ability of humans to prevent. Nowadays, based on probabilistic risk analysis methods, we know that no natural hazard turns into a disaster, much less a catastrophe, unless supplemented by human factors, specifically, by the infrastructural and societal vulnerabilities, as well as by the exposure of assets and human beings. Furthermore, weather extremes and hydrological


Above: Auroop Ratan Ganguly says that the amplification of threats and risks caused by grey swans, and the limits to predictability imposed by butterfly effects, needs to be addressed by a suite of tools and strategies. Photo by Matthew Modoono Northeastern University


hazards, which seem to be intensifying over the years, are at least partially human-caused, via climate and land use change. The latter situation has been occasionally providing an excuse for inaction: lack of investments in critical infrastructure and human development, as well as inadequate economic investments and financial instruments, are being brushed under the carpet by blaming all weather and hydrological disasters as “acts of climate change”. Other than effectively replacing “God” with “climate change”, it has become all too convenient for local governments and national agencies, which are usually charged with, and happen to be in the best position to invest in, disaster risk reduction and climate


adaptation, to blame climate-related disasters on the lack of mitigation and financing at international scales. The truth, meanwhile, is a bit more nuanced. In the


interests of this article, let us discuss if we can search for the elusive truth by examining three broad cases, specifically, dam construction, dam operations, and hydropower management. Dam constructors and operators, as well as


hydropower and river managers, fulfil critical societal responsibilities by saving lives and reducing property damage from flood and drought disasters, and by ensuring the supply of clean water and energy to homes and businesses. However, they are being increasingly challenged by relatively rare or even unprecedented extremes and stresses, as well as by the superposition of fluctuations and natural variability with long-term trends.


Swans and butterflies Nicholas Nasser Taleb, a Wall Street trader, introduced


About the author


Auroop Ratan Ganguly, a college of engineering distinguished professor at Northeastern University (NU) in Boston, MA, with a joint appointment as a chief scientist at the US Department of Energy’s Pacific Northwest National Laboratory in Richland, WA, has over 25 years of full-time professional experience in the US spanning the private industry, government research laboratory, and academia. Ganguly has published widely in water and climate science and engineering, critical infrastructure resilience, as well as machine learning, nonlinear dynamics, and extreme value statistics. He has co-founded or advised two successful startups in climate and weather analytics, led or supported community science related to climate action in the greater Boston area, and has been collaborating with scientists in US, Europe, India, Indonesia, Brazil, Tanzania, and around the world. At NU, Ganguly directs the Sustainability and Data Sciences Laboratory within Civil and Environmental Engineering, the Artificial Intelligence for Climate and Sustainability focus area within the Institute for Experiential AI and until recently, was one of two Co-Directors leading the Global Resilience Institute. He is a Fellow of the American Society of Civil Engineers, a Distinguished Member of the Association for Computing Machinery and obtained a PhD in hydrology from the CEE Department at the Massachusetts Institute of Technology (MIT) in Cambridge, MA.


the concept of swans in the assessments of risks and resilience. White swan events are not-too-unexpected minor shocks that do not disrupt human or societal functions. Black swan events are surprising and rare to the point of being unpredictable and out of bounds for probabilistic descriptions – although on hindsight they may appear inevitable – with deep and lasting impacts. Grey swans are predictive surprises: these events may be relatively rare, but they can be characterised probabilistically, and while they may be unprecedented in a region, the combination of process changes and data-driven understanding make them viable in the future. Thus, climate change may cause grey swan storms and cyclones, while a combination of climate change with lack of investments in techno-social readiness and high exposure in vulnerable regions may lead to grey swan flooding disasters. Ed Lorenz, an MIT meteorologist, introduced the concept of chaos or butterfly effects to weather prediction. The extreme sensitivity to initial conditions (with relatively abrupt decay in predictability beyond certain lead times) and the presence of what are called strange attractors in dynamic plots of weather variables (which in certain idealised situations look like butterfly wings), was paraphrased for non-specialists by Lorenz: “When a butterfly flutters its wings in one part of the world, it can eventually cause a hurricane in another.” This butterfly effect makes weather extremes and


10 | April 2024 | www.waterpowermagazine.com


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