Modeling Climate Impacts on Glacier Evolution and Water Balance in the Issyk-Kul Basin, Kyrgyzstan

Abstract ID: 3.13017 | Accepted as Talk | Requested as: Talk | TBA | TBA

Phillip Schuster (1)
Alexandra, von der Esch (2, 3); Azamat, Osmonov (4); Tobias, Sauter (1); Christoph, Schneider (1)

(1) Humboldt-Universtität zu Berlin, Unter den Linden 6, 10099 Berlin, DE
(2) ETH Zurich, Rämistrasse 101, 8092, Zurich, Switzerland
(3) Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Rue de l’Industrie 23, 1950, Sion, Switzerland
(4) Central Asian Institute for Applied Geosciences, Timur Frunze Rd.73/2, 720027, Bishkek, Kyrgyz Republic

Categories: Cryo- & Hydrosphere, Water Resources
Keywords: Glacio-hydrological modeling, Central Asia, Google Earth Engine, GloGEM, MATILDA

Categories: Cryo- & Hydrosphere, Water Resources
Keywords: Glacio-hydrological modeling, Central Asia, Google Earth Engine, GloGEM, MATILDA

Abstract
The content was (partly) adapted by AI
Content (partly) adapted by AI

Climate change and glacial retreat are altering the hydrology of high mountain rivers, affecting water availability and management. In data-scarce regions such as Central Asia, accessible modeling tools are essential for decision making.
This study uses MATILDA, an open-source glacio-hydrological model, to assess climate impacts on the water balance of the Issyk-Kul basin (Kyrgyzstan) between 1982 and 2100. For a realistic representation of the more than 800 glaciers in the basin, MATILDA is coupled with the Global Glacier Evolution Model (GloGEM). A semi-distributed approach simulates the hydrology at the catchment scale for the tributaries of Issyk-Kul. Model calibration includes snow reanalysis data, geodetic and in-situ glacier mass balance data, and 31 historical discharge records, mainly from the Soviet era.
The study assesses the projected impacts of climate change on the basin’s water balance, the cryosphere’s contribution to runoff, and lake level changes. We explore methods for modeling ungauged catchments using a set of predictors derived from soil, terrain, climate, and glaciological datasets available through cloud services such as Google Earth Engine. We also evaluate the added value of dedicated glacier models compared to the simplified routines used in most hydrological models. The study integrates historical field observations with data from global and regional models and remote sensing to support water resource management in glacierized basins under climate change.