Land surface modeling informed by earth observation data: Toward understanding blue–green–white water fluxes in High Mountain Asia

Mountains are important suppliers of freshwater to downstream areas, affecting large populations in particular in High Mountain Asia (HMA). Yet, the propagation of water from HMA headwaters to downstream areas is not fully understood, as interactions in the mountain water cycle between the cryo-, hydro- and biosphere remain elusive. We review the definition of blue and green water fluxes as liquid water that contributes to runoff at the outlet of the selected domain (blue) and water lost to the atmosphere through vapor fluxes, that is evaporation from water, ground, and interception plus transpiration (green) and propose to add the term white water to account for the (often neglected) evaporation and sublimation from snow and ice. We provide an assessment of models that can simulate the cryo-hydro-biosphere continuum and the interactions between spheres in high mountain catchments, going beyond disciplinary separations. Land surface models are uniquely able to account for such complexity, since they solve the coupled fluxes of water, energy, and carbon between the land surface and atmosphere. Due to the mechanistic nature of such models, specific variables can be compared systematically to independent remote sensing observations – providing vital insights into model accuracy and enabling the understanding of the complex watersheds of HMA. We discuss recent developments in spaceborne earth observation products that have the potential to support catchment modeling in high mountain regions. We then present a pilot study application of the mechanistic land surface model Tethys & Chloris to a glacierized watershed in the Nepalese Himalayas and discuss the use of high-resolution earth observation data to constrain the meteorological forcing uncertainty and validate model results. We use these insights to highlight the remaining challenges and future opportunities that remote sensing data presents for land surface modeling in HMA.