Snow Hydrology in the Upper Yellow River Basin Under Climate Change: A Land Surface Modeling Perspective

Abstract

Snow has been widely recognized as a crucial component of water resources and is expected to be vulnerable to climate change in cold and mountainous regions. Here we projected climate change impacts on snow hydrology in the upper Yellow River (UYR) basin through a distributed biosphere hydrological model with improved snow physics, forced with Inter‐Sectoral Impact Model Intercomparison Project climate model outputs under two emission scenarios (representative concentration pathways, RCP4.5 and RCP8.5) during the period of 1996–2025. The results indicated that the climate in the UYR basin is turning warmer and wetter. In this context, more precipitation would occur as rain (snow‐to‐precipitation ratio would decrease accordingly). The total runoff generation would increase slightly with increased precipitation. The simulated snow depth and snow water equivalent would decrease by 33% and 19% per 1 °C warming under the RCP4.5. These declined rates would further enlarge under the RCP8.5. Accordingly, the multimodel ensemble mean snowmelt‐to‐runoff ratio decreases by 9% and 7% per 1 °C warming under the two emission scenarios. The projected responses of snow hydrology (e.g., snow depth, snow water equivalent, and snowmelt) to the changing climate in the UYR basin are consistent among different climate models and RCP scenarios, which would provide valuable insights for water resources management, environmental protection, and climate change adaption in high mountainous basins and their downstream regions.

Projected hydrologic changes over the north of the Iberian Peninsula using a Euro-CORDEX multi-model ensemble

“…This downward tendency driven by a warmer climate has being previously identified for the mountainous areas in Spain (López-Moreno et al, 2009;Morán-Tejeda et al, 2017;Collados-Lara et al, 2019) and other parts of the world (e.g. Bhatti et al, 2016;Majone et al, 2016;Coppola et al, 2018;Ishida et al, 2018Ishida et al, , 2019Liu et al, 2018), thus suggesting a critical role of the snowmelt component for the future management of mountain water resources (Viviroli et al, 2011;Mankin et al, 2015).…”

Observation‐Constrained Projection of Global Flood Magnitudes With Anthropogenic Warming

“…We apply global daily gridded runoff ( R SIM , mm, 0.5° × 0.5°) simulated by five GHMs, that is, DBH (Tang et al., 2007), H08 (Hanasaki et al., 2008a, 2008b), LPJmL (Bondeau et al., 2007), PCR‐GLOBWB (Wada et al., 2010; Sutanudjaja et al.,2018), and VIC (Liang et al., 1994) under the VARSOC dynamic‐social economic scenario (considering time‐varying water abstraction, dam constructions, and land cover change; Zaherpour et al., 2018), forced by atmospheric reanalysis in ISIMIP2a and bias‐corrected meteorological outputs from five GCMs (GFDL‐ESM2M, HadGEM2‐ES, IPSL‐CM5A‐LR, MIROC‐ESM‐CHEM and NorESM1‐M; 5 GCMs × 5 GHMs = 25 combinations) in ISIMIP Fast‐track (ISIMIP‐FT) data archive (Table 1). The bias correction is conducted using a method initially developed for the ISIMIP simulation protocol to ensure the long‐term statistical characteristics of climate model outputs coincide with the WATCH (WATer and global CHange data; Weedon et al., 2011)/WFDEI (WATCH forcing data by making use of the ERA‐Interim reanalysis data; Warszawski et al., 2014) meteorological forcing data during the historical period and to preserve their relative and absolute trends over the historical and future periods (W. B. Liu, Wang et al., 2018; Warszawski et al., 2014). Moreover, the ISIMIP has released five datasets including the ISIMIP‐FT, ISIMIP2a, ISIMIP2b, ISIMIP3a, and ISIMIP3b.…”

Soil Moisture to Runoff (SM2R): A Data‐Driven Model for Runoff Estimation Across Poorly Gauged Asian Water Towers Based on Soil Moisture Dynamics

“…Based on glacier mask data sets from the Randolph Glacier Inventory (RGI 6.0; RGI Consortium, 2017), the glacierized area accounts for ∼9% (Indus), ∼7% (Ganges), and ∼3% (Brahmaputra) of the water tower area. In addition, snowpack stores cold‐season precipitation to meet warm‐season water demand in the high‐mountain regions, and snowfall together with snowmelt plays a vital role in runoff generation (Liu, Wang, et al., 2018). Particularly, snowfall at high elevations (e.g., the Himalayas) often freezes in the cold seasons, resulting in a lag of several months before it melts into liquid water and causes changes in soil moisture or translates into outgoing fluxes as it gets warmer.…”