Hydrology under changing conditions: process understanding, model improvement, and implications for future projections

Convener: Giulia BrunoECSECS | Co-conveners: August BjerkénECSECS, Matthew Armstrong, Gabrielle BurnsECSECS, Keirnan Fowler, Margarita SaftECSECS

In an era of climate uncertainty and evolving human influence on natural environments, understanding the dynamics of long-term hydrological change has become critical to properly simulate and predict the multifaceted implications of climate change on water availability and aquatic environments. Catchments are complex systems responding to changes in climate, among external factors, on a variety of timescales and with many interacting processes. The poor performance of models in representing these responses suggests they potentially misrepresent (or omit) important processes, timescales, or interactions. This session focusses on better understanding hydrological responses to changes in climatic forcing at multi-annual to multi-decadal timescales, on improving the representation of such responses in hydrological models, and on tangible examples of climate change impact assessments on hydrological and related socio-ecological systems. Submissions are encouraged across the full spectrum of available techniques, such as site-specific investigations or large-scale studies, using both in-situ and/or remotely sensed data or novel modelling frameworks. We hope to showcase research across diverse geographical regions and varied contexts to facilitate sharing of methods, insights and lessons learned. Therefore, this session covers themes such as (but not limited to):
1. Better understanding of hydrological and/or biophysical processes that govern hydrological response to multi-annual or longer climate shifts;
2. Studies of hydrological regularities (e.g. the Budyko hypothesis) for predictions under changing conditions;
3. Characterizations of catchment multi-annual “memory” and its representation in models;
4. Efforts to improve the realism and robustness of hydrological simulations under climatic variability and change;
5. So-called “bottom-up” approaches to decision making under deep uncertainty, novel modelling paradigms, innovative risk assessment frameworks, or characterisations of multiple (compound) sources of risk in future scenarios.