Glaciohydrology of the Himalaya-Karakoram

Abstract

Waters of high Asia How the rivers of the Himalaya-Karakoram region of Asia respond to climate change is critical for the billion-plus people who depend on the water that they provide. In a Review, Azam et al. discuss recent progress in understanding the importance of glacier and snow melt in the hydrological budget there, which is driven largely by advances in remote sensing and modeling. Observational data remain sparse and challenging to collect. Science, abf3668, this issue p. eabf3668 A Review discusses how climate change is affecting the glacial hydrology of high mountain Asia. BACKGROUND The Himalayan-Karakoram (HK) region in south Asia is one of the most heavily glacierized and vulnerable mountainous regions on Earth. The Indus, Ganges, and Brahmaputra river systems, which originate from HK glaciers and snowfields, support the water requirements of 1 billion people. HK river basins have the largest irrigated area (~577,000 km2) and the largest installed hydropower capacity (~26,000 MW) worldwide. Optimum planning for management of water demand and supply for agriculture, hydropower, domestic needs, and sanitation requires a consensus on the region’s glaciohydrology. Understanding the uncertainties in glaciohydrological modeling, climate change projections, and their impacts on the availability of water and its transboundary nature in HK rivers is thus critical for sustainable water resource management and regional geopolitics. ADVANCES Glaciohydrological models have been used to investigate contributions of glacier and snow melt, impacts of climate change on melt runoff, and future runoff evolution in HK rivers. Recent efforts to map and measure glacier extents, mass balance, and velocity, as well as the growth of glacial lakes, have filled several major gaps in glaciohydrology that existed a decade ago. This progress has been achieved primarily through remote sensing and modeling, yet field-based studies remain limited. The combined result of improved models and observations suggests that snow and ice melt are important but spatially variable runoff components in HK rivers. Meltwater contributions are highest closest to the snow and ice sources, and the meltwater contribution in the Indus is greater than in the Ganges and Brahmaputra basins. Meltwater contributions vary widely between catchments as a result of orographic microclimates and the relative proportions of summer and winter precipitation. However, the contributions of runoff components estimated for the same catchments vary between studies, highlighting discrepancies in model approaches and assumptions. Projected 21st-century trends in the seasonality of runoff and the increasing intensity and frequency of extreme runoff events are consistent across a range of climate change scenarios. Total river runoff, glacier melt, and seasonality of flow are projected to increase until the 2050s and then decrease, with some exceptions and large uncertainties. Uncertain future water availability, including glacier and snow melt, hinders policymakers from developing adequate water resource plans that include bilateral cooperation for irrigation, hydropower generation, industrial use, and water-induced hazard mitigation in HK countries. OUTLOOK We underline the major research gaps that, if filled, can reduce large uncertainties in glaciohydrological modeling. These research gaps include accurate representations of glacier volumes, precipitation distribution, permafrost, sublimation, and impacts of debris cover, black carbon, dust, and glacier dynamics. Comprehensive field observation–based and remote sensing–based methods and models are needed to fill the knowledge gaps and reduce uncertainties in runoff projections. As a first step (Tier 1), we recommend the development of monitoring networks that measure hydrology and meteorology across the full range of elevations in targeted basins that span a variety of climate regimes. These networks should include fully automatic weather stations situated on selected glaciers, and would provide detailed information for calibration and testing of process-based models, downscaling approaches, and hydrological models. We also recommend developing comparison projects for glacier area and volume, glacier dynamics, permafrost thaw, and snow and ice sublimation studies. Satellite and airborne remote sensing offers a potential for rapid advances in Tier-1 objectives, and includes platforms such as InSAR, GRACE, Icesat-2, high-resolution digital elevation models, and geophysical surveys. Tier-2 recommendations include the development of catchment-wide glaciohydrological models for the selected reference catchments identified in Tier 1 and a strengthened process-based understanding of high-elevation hydrology and meteorology to reduce the uncertainties in projections of runoff components, runoff volumes, and shifts in runoff seasonality. Lastly, the development of collaborative research groups and data-sharing policies among HK countries, combined with integrated and interdisciplinary studies of water access and water vulnerabilities, are strongly recommended to understand the impacts of changing river runoff on economic, agricultural, and human productivity. Simplified hydrological cycle. Representation of major Earth surface system processes, each of which carries a research gap in the glaciohydrology of the Himalaya-Karakoram region. IWM, Indian winter monsoon; ISM, Indian summer monsoon. Understanding the response of Himalayan-Karakoram (HK) rivers to climate change is crucial for ~1 billion people who partly depend on these water resources. Policy-makers tasked with sustainable water resources management require an assessment of the rivers’ current status and potential future changes. We show that glacier and snow melt are important components of HK rivers, with greater hydrological importance for the Indus basin than for the Ganges and Brahmaputra basins. Total river runoff, glacier melt, and seasonality of flow are projected to increase until the 2050s, with some exceptions and large uncertainties. Critical knowledge gaps severely affect modeled contributions of different runoff components, future runoff volumes, and seasonality. Therefore, comprehensive field observation–based and remote sensing–based methods and models are needed.