Ph. D. ThesisWater resources in the Indus basin are under acute and growing stress. How climate change
will affect this situation in the coming decades depends substantially on responses in the datasparse
mountains of the upper basin. However, model projections of changes in the
cryosphere-dominated hydrology here are highly uncertain. Integral to this uncertainty are
challenges in: characterising near-surface climate fields needed for model input; selecting
appropriate model structures to balance process fidelity with data availability; and
understanding the wide spread in climate model projections used in impact assessments. As
such, this thesis aims to identify pathways for refined hydrological projections in the upper
Indus basin through in-depth evaluation of climate, cryospheric and hydrological models.
Firstly, using the High Asia Refined Analysis (HAR), the study assesses how relatively high
resolution regional climate modelling can help describe spatiotemporal variability in nearsurface
climate. The HAR exhibits substantial skill in many respects, but particularly in
capturing the complex patterns of precipitation in the basin. Some seasonally varying biases
in temperature and incoming radiation suggest deficiencies in snow and cloud representations
that are likely resolvable. Secondly, the Factorial Snowpack Model (FSM) is driven with the
HAR to examine the feasibility and required structure of process-based snowpack modelling.
Model correspondence with local observations and remote sensing is good for a subset of
FSM configurations using a prognostic albedo parameterisation, as well as a representation of
liquid water retention, drainage and melt/refreezing cycles in the snowpack. The multiphysics
approach additionally highlights the inputs and processes needing further
investigation, which include the atmospheric stability adjustment. Thirdly, using an adapted
FSM program and TOPKAPI-ETH, simplified representations of cryospheric processes are
compared with more process-based approaches. This helps to identify where systematic
differences in hydrological response occur and their connection with spatial and temporal
scales. It is found that an enhanced temperature index (ETI) model exhibits behaviour and
climate sensitivity more akin to energy balance formulations than a classical temperature
index model. However, there may be structural limits to the fidelity of the ETI formulation
under cloudy conditions, while further attention is needed on the translation of surface melt to
runoff, especially at high elevations.
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The study then moves to examine controls on regional trends and variability simulated by
climate models, focusing on temperature in CMIP5 GCMs. While the models partly
reproduce key regional atmospheric circulation influences, variation in summer temperature
responses depends on differing snow and albedo representations. Ultimately this may offer
some potential to constrain temperature projections. Finally, using CMIP5 and HAPPI GCM
outputs, the study explores climate and hydrological projections under selected global
warming stabilisation scenarios. This shows that shifts in the timing of runoff are discernible
even for low warming targets. Overall water availability may depend particularly on natural
variability in precipitation, but in dry years the pressures on water resources in the basin could
worsen in future. Further efforts to constrain the range of projections using observations and
process-based reasoning are required, but effective water resources management in the basin
is likely to depend on increasing resilience to a wide range of climatic and hydrological
variability