Abstract

AbstractSnowmelt water is a vital freshwater resource in the Altai Mountains of northwestern China. Yet its seasonal hydrological cycle characteristics could change under a warming climate and more rapid spring snowmelt. Here, we simulated snowmelt runoff dynamics in the Kayiertesi River catchment, from 2000 to 2016, by using an improved hydrological distribution model that relied on high‐resolution meteorological data acquired from the National Centers for Environmental Prediction (Fnl‐NCEP) that were downscaled using the Weather Research Forecasting model. Its predictions were compared to observed runoff data, which confirmed the simulations' reliability. Our results show the model performed well, in general, given its daily validation Nash–Sutcliffe efficiency (NSE) of 0.62 (from 2013 to 2015) and a monthly NSE score of 0.68 (from 2000 to 2010) for the studied river basin of the Altai Mountains. In this river basin catchment, snowfall accounted for 64.1% of its precipitation and snow evaporation for 49.8% of its total evaporation, while snowmelt runoff constituted 29.3% of the annual runoff volume. Snowmelt's contribution to runoff in the Altai Mountains can extend into non‐snow days because of the snowmelt water retained in soils. From 2000 to 2016, the snow‐to‐rain ratio decreased rapidly, however, the snowmelt contribution remained relatively stable in the study region. Our findings provide a sound basis for making snowmelt runoff predictions, which could be used prevent snowmelt‐induced flooding, as well as a generalizable approach applicable to other remote, high‐elevation locations where high‐density, long‐term observational data are currently lacking. How snowmelt contributes to water dynamics and resources in cold regions is garnering greater attention. Our proposed model is thus timely perhaps, enabling more comprehensive assessments of snowmelt contributions to hydrological processes in those alpine regions characterized by seasonal snow cover.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call