Articles | Volume 13, issue 10
Hydrol. Earth Syst. Sci., 13, 1897–1906, 2009
https://doi.org/10.5194/hess-13-1897-2009

Special issue: Cold region hydrology: improved processes, parameterization...

Hydrol. Earth Syst. Sci., 13, 1897–1906, 2009
https://doi.org/10.5194/hess-13-1897-2009

  15 Oct 2009

15 Oct 2009

A snowmelt runoff forecasting model coupling WRF and DHSVM

Q. Zhao1,2, Z. Liu2,3,4, B. Ye1, Y. Qin2,3, Z. Wei2,3, and S. Fang2,3 Q. Zhao et al.
  • 1The States Key Laboratory of Cryospheric Sciences, Cold & Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China
  • 2College of Resources and Environment Science, Xinjiang University, Urumqi, China
  • 3Oasis Ecology Key laboratory of Xinjiang Uygur Autonomous region, Xinjiang University, Urumqi, China
  • 4International Centers for Desert Affairs-Research on Sustainable Development in Arid and Semi-arid Lands, Urumqi, China

Abstract. This study linked the Weather Research and Forecasting (WRF) modelling system and the Distributed Hydrology Soil Vegetation Model (DHSVM) to forecast snowmelt runoff. The study area was the 800 km2 Juntanghu watershed of the northern slopes of Tianshan Mountain Range. This paper investigated snowmelt runoff forecasting models suitable for meso-microscale application. In this study, a limited-region 24-h Numeric Weather Forecasting System was formulated using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. Using the WRF forecasts, the DHSVM hydrological model was used to predict 24 h snowmelt runoff at the outlet of the Juntanghu watershed. Forecasted results showed a good similarity to the observed data, and the average relative error of maximum runoff simulation was less than 15%. The results demonstrate the potential of using a meso-microscale snowmelt runoff forecasting model for forecasting floods. The model provides a longer forecast period compared with traditional models such as those based on rain gauges or statistical forecasting.