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Cryosphere and Hydrology


This project seizes the opportunity offered by ESA and NRSCC to access high resolution satellite observations of Earth’s surface to provide novel understanding of the cryosphere and water cycle of key water towers of High Mountain Asia (HMA). Using a hyper-resolution ecohydrological model, fed by Earth System Observations, we will bridge the modelling gap between snow and glaciers, which generate the runoff that ultimately feeds major rivers, and downstream water cycle components such as vegetation, which buffer, delay or amplify that runoff. We will focus on blue (runoff) and green (evapotranspiration) water interactions in HMA, which are often examined separately, and integrate water supply changes due to a vanishing cryosphere with the effect of vegetation to dampen or amplify those changes, especially in periods of droughts. This new perspective will enable us to assess the vulnerability of selected High Asian water towers. The new model will afford a thorough assessment of all water budget components in 10 benchmark catchments representative of the climatic differences of HMA. This unprecedented synthesis effort is possible through the combined expertise in remote sensing (Chinese PI) and modelling (European PI), with synergies due to existing projects and support from partners in the region. Our main aim is to understand how green water processes affect the availability of blue water from glaciers, snow and precipitation across High Mountain Asia High-resolution satellite data of land-cover, surface albedo, vegetation phenology, surface water, glacier velocities, surface lowering and mass balance will guide model developments and support model calibration and validation in a systematic manner to ensure comparability across case studies, providing a holistic assessment of how ecosystems and vegetation can enhance or reduce glacier response to climate change in HMA. The 10 glacierized sites span a variety of climates, glacier conditions and mass balance regimes. For each catchment, field measurements of glacier melt, mass balance, runoff and meteorological variables are available. These will be used in combination with the diverse remote sensing observations generated by the Chinese PI group to drive the model and validate results. This key synergy is further strengthened by a partnership with Dr Tobias Bolch and his team. Dr Bolch leads a companion proposal to develop records of glacier shrinkage, thinning and motion for some of the same sites that we propose to study, maximising synergies. Our multidisciplinary team of European and Chinese scientists will thus collaborate to: i) provide an advanced characterisation of the main glacier and hydrological processes from remote sensing observations in the high elevation catchments of HMA; ii) resolve the altitudinal surface mass balance for all study glaciers; iii) apply a novel hyper-resolution earth-surface model to simulate the complexity of the high mountain water budget and quantify changes in streamflow. The proposed work is supported by, for the European PI: (1) ERC Consolidator Grant “RAVEN: Rapid mass loss of debris covered glaciers in High Mountain Asia”; (2) Royal Society Grant “Understanding glaciers and hydrological changes in the Tibetan Plateau using high resolution monitoring and modelling”; (3) Swiss National Science Foundation (SNSF) project “High Elevation Precipitation in High Mountain Asia (HOPE)”; (4) SNSF project “Understanding snow, glacier and rivers response to climate in High Mountain Asia (ASCENT)”; and (5) NERC Grant “Peruvian Glacier Retreat and its Impact on Water Security (Peru GROWS)”. For the Chinese PI, work is supported by: (1) Natural Science Foundation of China, grant number 91737205; (2) Strategic Priority Research Program of the Chinese Academy of Sciences (CAS), grant numbers XDA19030203 and XDA19070102; and (3) MOST High Level Foreign Expert program, grant number G20190161018.


PI Europe
Dr. Francesca Pellicciotti, Swiss Federal Institute for Forest, Snow and Landscape Research,WSL, SWITZERLAND
PI China
Prof.. Massimo Menenti, Aerospace Information Research Institute - CAS, CHINA