An improved modeling of precipitation phase and snow in the Lancang River Basin in Southwest China

Precipitation phase(e.g., rainfall and snowfall) and snow(e.g., snowpack and snowmelt runoff) in high-mountain regions may largely affect runoff generation, which is critical to water supply, hydropower generation, agricultural irrigation, and ecosystems downstream. Accurately modeling precipitation phase and snow is therefore fundamental to developing a better understanding of hydrological processes for high-mountain regions and their lower reaches. The Lancang River(LR, or the Upper Mekong River)in China, among the most important transboundary rivers originating from the Tibetan Plateau, features active dam construction and complex water resources allocation of various stakeholders in Southeast Asian countries under climate change. This study aims to improve precipitation phase and snow modeling for the LR basin with a hydrological model and multisource remotely sensed data. Results show that joint use of the Moderate Resolution Imaging Spectroradiometer(MODIS) land surface temperature product with high spatial resolution(1 km×1 km) and an air temperature product can more precisely distinguish precipitation phase than air and wet-bulb temperature products in the LR basin. Snowfall and snowmelt were found to be controlled primarily by rainfall and snowfall temperature thresholds in snow modeling. The rainfall and snowfall temperature thresholds derived from the hydrological model through calibration with remotely sensed snowpack at basin scales were considerably lower than those derived from in situ observations. Rainfall and snowfall temperature thresholds derived from in situ observations could lead to the overestimation of snowmelt runoff due mostly to the lack of representation of point-based measurements at basin scales. This study serves as a basis for better modeling and predicting snow for the LR basin and potentially other similar basins globally.