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Abstract
Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himalayan river basins, focusing on their utility to analyse the impacts of future climate and socio-economic changes on water resource availability in the region. Results show that the latter are only represented by land use change. Distributed, process-based hydrological models coupled with temperature-index melt models are predominant. The choice of spatial discretisation is critical for model performance due to the strong influence of elevation on meteorological variables and snow/ice accumulation and melt. However, the sparsity and limited reliability of point weather data, and the biases and low resolution of gridded datasets, hinder the representation of the meteorological complexity. These data limitations often limit the selection of models and the quality of the outputs by forcing the exclusion of processes that are significant to the local hydrology. The absence of observations for water stores and fluxes other than river flows prevents multi-variable calibration and increases the risk of equifinality. The uncertainties arising from these limitations are amplified in climate change analyses and, thus, systematic assessment of uncertainty propagation is required. Based on these insights, transferable recommendations are made on directions for future data collection and model applications that may enhance realism within models and advance the ability of global change impact assessments to inform adaptation planning in this globally important region.
Highlights
The Himalayas are the source of many major rivers of South Asia [1,2]
Distributed, process-based hydrological models coupled with temperature-index melt models are predominant
These issues lead to potentially high uncertainty in model outputs which is aggravated in studies of global change impacts where the inherent uncertainty in future changes in climate [54,55] and socio-economic [56,57] factors are amplified through a cascade of uncertainties [58,59]
Summary
The Himalayas are the source of many major rivers of South Asia [1,2]. They act both as orographic barriers, influencing monsoonal precipitation [3,4], and as natural water reservoirs that store the largest volumes of ice and snow outside of the polar regions [5,6]. Intercomparison Project-5 (CMIP5) models (25 to 75 percentiles of the ensemble) [26] Such changes in climate will impact future hydrology in Himalayan catchments, modifying flow extremes and seasonal discharge patterns due to changes in rainfall amounts and seasonality, as well as snow and glacier accumulation and melt [28]. Securitisation of water hampers data accessibility as certain types of data such as river flows in some locations, glacier data, water management and consumption are restricted, generating (geo-political) uncertainty [14] These issues lead to potentially high uncertainty in model outputs which is aggravated in studies of global change impacts where the inherent uncertainty in future changes in climate [54,55] and socio-economic (e.g., land use and water abstractions/diversions) [56,57] factors are amplified through a cascade of uncertainties [58,59].
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