天山地区典型流域雪粒径与融雪过程的遥感定量研究

Snow in mountainous areas is a major source of surface water and groundwater recharge in the world. The water balance in mountainous regions is controlled by the interactions between the climate, cryospheric, and hydrological systems. Surface snow grain is a sensitive thermodynamic indicator of snowpack and plays an important role in the snow albedo. The snowmelt hydrologic process depends on the heat input, surrounding temperature, melting cycle and new snowfall superposition, etc. To obtain the spatial and temporal distribution of the snow parameters accurately is the key to the study of the hydrological process of river basin scale snow melting. Snow grain size is one of the key variables in cryosphere, since it influences the earth's surface energy budget and characterizes the hydrothermal status of snowpack. Snow grain size data at large scales can be retrieved from space-borne optical observations, which are significant to research on climate/weather modelling and hydrological processes in alpine mountainous regions. The quantitative expression of the snow status in the snowmelt process is the research objective. Taking the mountainous area in Kaidu river watershed on the south slope of Tianshan Mountains as the study area. this study aims to: 1) optimize retrieval parameters based on the snowpack status identified using optical remote sensing techniques and control the retrieval procedure and assess the retrieval accuracy, using field experiments data; 2) model the interaction mechanism between snow grain size and environmental parameters in complicated terrain conditions in the snow melting period; 3) obtain the spatio-temporal characteristics of snow grain size and the progress of snow melting. The developed model and resultant could benefit to retrieval theory, provide evidence for research on eco-climate change at watershed scales, and have practical meaning for regional water resource management.

积雪是冰冻圈的重要组成部分，是全球气候变化的显著因子和指示器；积雪又是全球水循环的关键一环，雪冰融水是干旱与半干旱地区宝贵的淡水资源。融雪水文过程依赖于热量输入、环境温度、融冻循环和新降雪叠加等因素，融雪过程中涉及的参数远比降雨径流复杂，准确获取相关积雪参数的时空分布，是进行流域尺度融雪水文过程研究的关键。故本项目拟选择天山中部开都河流域上源为典型示范区，以融雪过程中积雪状态的时空定量表达为研究目标，通过高时空分辨率的雪表层粒径信息和雪面温度信息，定量研究天山地区典型流域的融雪过程，揭示复杂地形条件下雪粒径与环境参数的相互作用机制，得到积雪状态的空间差异、积雪场年内消融的时空特征以及年际波动的变化规律。项目的实施可为天山地区内陆河流域融雪过程的定量分析提供科学依据，为融雪过程研究提供新的思路与方法，研究成果可为山区积雪和融雪过程的遥感定量研究提供借鉴。

雪冰融水是干旱与半干旱地区宝贵的淡水资源。融雪过程所涉及的参数复杂，准确获取相关积雪参数的时空分布，是进行流域尺度融雪水文过程研究的关键。本项目以天山中部开都河流域为典型示范区，以融雪过程中积雪状态的时空定量表达为研究目标，通过高时空分辨率的积雪参数信息获取，定量研究了天山地区典型流域的融雪过程，揭示了复杂地形条件下积雪参数与环境参数的相互作用机制，得到了积雪状态的空间差异、积雪场年内消融的时空特征以及年际波动的变化规律。本项目的主要研究成果如下：1)以雪粒径在流域尺度的分布为基础，发展了基于雪粒径填补的积雪去云算法；2)构建了基于雪粒径的降雪频次估算方法，提升对于高海拔地区降雪观测的能力；3)发展了适用于天山地区的降尺度雪深反演算法，将山区雪深数据集的空间分辨率提升到500m；4)从站点、区域和全国的尺度研判了积雪的时空分布及趋势变化。研究成果提高了天山地区融雪过程监测能力，为山区积雪和融雪过程的遥感定量研究提供理论支撑与应用示范。