This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come. ARTICLE HISTORY

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[1] The impact of climate change upon groundwater has an increasing profile in the literature but there is little guidance on selecting Global Climate Models (GCMs), downscaling methods or hydrological models. This paper quantifies the relative uncertainties inherent in projections of future recharge contributed by multiple GCMs, downscaling methods and hydrological models at three locations across southern Australia. Results highlight that the choice of GCM is the largest source of uncertainty, with a median range between the highest and lowest GCM of 53% of the historical recharge for a given downscaling method and hydrological model. The downscaling method is the next largest source of uncertainty with a median range of 44% and the choice of hydrological model is the source of the least uncertainty with a median range of 24%. These results strongly suggest that impact studies should use multiple GCMs and give careful consideration to the choice of downscaling methods.

[1] An investigation into landscape saturation has been carried out analytically using similarity parameters derived from topographic, soil, and climatic attributes. Three parameters (an input index (q/Z)(L/KS), convergence ratio (CR), and profile factor (B)) define the extent of hillslope saturation. From these, a single dimensionless parameter has been derived to describe the occurrence of saturation in planar, concave, and convex profile hillslope shapes, and with parallel, convergent, and divergent planforms. The relationship can be represented by a single dimensionless curve. The theory derived in this paper provides a basis for combining the individual parameters into a similarity criterion for saturation in landscapes. The theory and ensuing similarity hypothesis are applied to three natural catchments near Canberra, Australia, and are tested against observed rainfallrunoff data. The results support the validity of the similarity approach. There is a clear link between the distribution of hillslope similarity parameters and catchment saturation behavior.