Precipitation assessment and hydrological implications of climate change in the high-altitude Indus basin

The high-altitude Indus basin is one of the most complex and underexplored mountain regions in the World. Scarcity and directional biases of the observed precipitation coupled with measurement errors, high orographic influences and effects of multiple weather systems have prevented a comprehensive and reliable assessment of precipitation distribution in this region. Quantitative and spatiotemporal distributions of precipitation estimated by the previous studies and global/regional scale gridded datasets for this region are highly contrasting and extremely uncertain. Consequently, the studies using these estimates often lead to suboptimal and misleading outcomes regarding hydrometeorological assessments.This PhD research study integrated precipitation observations from multiple sources with the indirect estimates at the accumulation zones of major glaciers, adjusted these observations for measurement errors and derived spatially distributed fields of mean monthly precipitation using the standard and well-recognized techniques. The resultant reference estimates of precipitation distribution are cross-validated by the corresponding observed river inflows, which were adjusted for contribution of net mass balance. The reference climatologies of mean monthly maximum and minimum temperature are derived through elevation and latitude dependent lapse rates at sub-regional scale. Performance of 27 widely used gridded precipitation products is evaluated against the observational based reference dataset at sub-regional scale. The best performing gridded dataset is statistically downscaled and bias-corrected with respect to the reference datasets to develop long-term historical dataset of precipitation and temperature. Similarly, precipitation estimates of 75 CMIP5 GCM outputs for the historical period are evaluated against the bias-corrected historical dataset. Top 24 ranked GCM outputs are further analysed based on the changes in their climatic means between 1971–2000 and 2071–2100. Four corners of warm-dry, warm-wet, cold-dry and cold-wet spectrum are determined from the range of projected changes in mean annual air temperature and annual precipitation using the 10th and 90th percentile values. Precipitation and temperature data of two GCMs representing warm-wet and cold-dry extremes under three RCPs (2.6, 4.5 & 8.5) are statistically downscaled and bias-corrected against the historical datasets. A fully-distributed physically-based energy-balance hydrological model is forced with these datasets at daily timestep to model the sub-basin scale hydrologic regime for the historical as well as six scenarios of future climates.The altitudinal analysis of precipitation distribution in the study domain demonstrated strong orographic influence. However, the available observations are insufficient to infer an accurate relationship of precipitation with altitude. Rather nonlinear trends of precipitation increase with altitude are evident. Generally, precipitation tends to decrease with increasing latitude (from south to north), while longitude has seasonal influence, positive in monsoon and negative in winter season. Monthly distribution of precipitation largely indicates a bimodal weather system, reflecting influence of winter westerlies and summer monsoon. In contrast to previous studies, the results of this study reveal substantially higher precipitation in most of the sub-basins indicating two distinct rainfall maxima; 1st in the western Himalaya along southern and lower most slopes of Chenab, Jhelum, Indus main and Swat basins, and 2nd around north-west corner of Shyok basin in the central Karakoram. Adjustments of measurement errors in precipitation observation and net snow accumulations indicated significant improvements in the quantitative and spatio-temporal distribution of precipitation over the unadjusted case, while adjustment of river flows revealed only a marginal contribution of net glacier mass balance to river flows. The study recognized that the higher river flows than the corresponding precipitation estimates by the previous studies are mainly due to underestimated precipitation. The study demonstrated that the gridded precipitation products are prone to significant errors and their direct (uncorrected) use in climate change and hydrological studies will imply erroneous inferences. Gauge-based and merged products performed relatively better in dry regions and during monsoon season, while reanalyses products provided better estimates in wet areas, at higher-altitudes and during winter months. Overall, ERA5 precipitation product provided relatively better and equally acceptable estimates for all sub-regions. Precipitation projections by the GCMs are more uncertain and generally fail to efficiently reflect the bimodal weather system prevailing in the study area. Nevertheless, MIROC5 and MPI-ESM-LR provided better skill scores to reproduce the past climate of the study area.In the presence of significant interannual variability, the mean annual air temperature has increased by 0.6 oC during the last 40 years and is projected to increase further by 1.3-2.6 oC during mid-century and between 0.8-5.7 oC by the end-century. Compared to temperature, precipitation remains much more variable and uncertain in both space and time. Mean annual precipitation experienced considerable decline during the famous and prolonged drought of recent time (1999-2003). It tried to recover thereafter but still fell short by 11.9% of the mean annual precipitation for the 1st half of the baseline period (1981-2020). Compared to the baseline historical period, the interannual variability of the projected precipitation by all GCM runs is even more pronounced throughout the 21st century. Definite and strong increasing trend in mean annual precipitation is only evident for MIROC5_RCP8.5, while MPI-ESM-LR shows declining trends for RCP4.5 & RCP8.5. The remainder of GCM runs show mixed trends. River flows are largely modulated by timing, intensity, duration, and form of precipitation; snow and glacial ice reserves; and amount of energy available for melting of seasonal and perennial snow and glacial ice. The basin-scale projections of water availability show an overall increase of river inflows but exhibit significant spatiotemporal variability. MIROC5 outputs generally depict positive changes, while MPI-ESM-LR outputs result in negative changes. Late spring and pre-monsoon (Apr-Jun) river inflows will be significantly increased, while considerable reduction in late summer flows is very likely due to early melting of seasonal snow cover. Similarly, slight increments are also projected for wintertime baseflows due to increasing temperature. Hydrologic extremes of floods and drought are projected to be more intensive and frequent under all scenarios.Although, there are still significant uncertainties, this PhD research attempted to minimize the underlying uncertainties and added to the current knowledge and understanding of hydrometeorology of the high-altitude Indus basin. The results will serve as the basis for design and operation of hydropower plants and hydraulic structures and provide guidelines for planning and management of water resources