Surface water sensitivity to climate variability

Global water security is known to depend on, among other things, the ability of societies to cope with hydrological risks. While there are several drivers that determine the severity of these risks, climatological mechanisms play an important role in describing their spatial and temporal characteristics. These mechanisms are often described as intra-annual and inter-annual sources of climate variability. Furthermore, anthropogenic climate change is understood to importantly perturb these mechanisms and in turn magnify hydrological risks. As such, understanding the way in which these mechanisms of climate variability influence hydrological processes has become a present and pressing scientific challenge. In particular, while existing methods look to explain the role of climate variability in hydrometeorological variables, namely precipitation and temperature, more research is required to explain how these mechanisms manifest in large-scale land surface hydrological processes and extremes.
The objective of this thesis is to increase our understanding of the way that climate sources of variability influence the spatial and temporal heterogeneity of hydrological flows. This objective is addressed in a systematic way, by first exploring how hydrological flow characteristics are influenced by land surface hydrological processes in areas, with traditional rudimentary runoff representations. Building on this, this thesis secondly analyses the direct link between natural sources of climate variability and land surface hydrological processes and risks at the global scale. Lastly, the repercussions of anthropogenic climate change, in the context of current global climate agreements, in influencing hydrological extremes are explored. By examining the impacts of such extremes on global hydropower availability, a part of the ultimate consequences of hydrological risks on human systems are subsequently explored.
In order to address these aims this thesis proposes a systemic framework that connects climate sources of variability and heterogeneity of flows, by combining various physical sub-models of a Land Surface Model (LSM) and other complementary tools. As such, this framework looks to link climate sources of variability, atmospheric responses, surface hydrological variables, hydrodynamics, hydrological extremes, and societal repercussions. To demonstrate the value of the framework, this thesis presents four case studies in which specific components and sub-models of this framework are utilized to address the mentioned objectives.
The framework proposed here has helped to unveil and quantify new drivers that control river flows and hydrological risks. This includes explaining the snowpack characteristics that determine timing and magnitude of river flow peaks in snow-dominated regions. Also, by quantifying the inter-annual variability driven by Atmospheric Rivers, this thesis found that this form of moisture transport contributes to 22% of total global annual runoff and their variability importantly drives hydrological extremes in various global locations. Furthermore, by applying this framework, this thesis found that committing to a 1.5oC level of warming, instead of 2.0°C, as agreed in Paris in 2015, may importantly decrease high flow occurrences in regions such central Asia or western Europe. Similarly, this thesis found that the intensification of future low flow events, resulted from future climate targets, may lead to important global water losses which in turn would make almost a quarter of current global GHP vulnerable, importantly affecting the energy share in various Asian and Sub-Saharan countries.

Keywords: Climate variability
Modelling Framework
Climate change
Global Hydrology
Advisor: Dadson, S