地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (12): 1661-1669.doi: 10.3724/SP.J.1047.2017.01661

• 山洪/泥石流灾害监测技术与方法 • 上一篇    下一篇

昆仑山提孜那甫河流域雨雪分离的温度条件分析

段永超1,2(), 孟凡浩1,2, 刘铁1*(), 罗敏1,2, 张军峰1, 包安明1   

  1. 1. 中国科学院新疆生态与地理研究所 荒漠与绿洲生态国家重点实验室,乌鲁木齐 830011
    2. 中国科学院大学,北京 100049
  • 收稿日期:2017-06-27 修回日期:2017-08-31 出版日期:2017-12-25 发布日期:2017-12-25
  • 作者简介:

    作者简介:段永超(1990-),男,博士生,主要从事遥感水文研究。E-mail: duanyongchao_1@163.com

  • 基金资助:
    “千人计划”——新疆项目(374231001);中国科学院国际伙伴关系计划项目(131551KYSB20160002);中国科学院项目(TSS-2015-014-FW-2-1);2016年“创新人才国际合作培训计划”项目(201604910973)

Analysis of Temperature Conditions for Rain and Snow Separation in Tizinafu River Basin of Kunlun Mountains

DUAN Yongchao1,2(), MENG Fanhao1,2, LIU Tie1*(), LUO Min1,2, ZHANG Junfeng1, BAO Anming1   

  1. 1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-06-27 Revised:2017-08-31 Online:2017-12-25 Published:2017-12-25

摘要:

气候变暖背景下高海拔山区融雪(冰)以及强降水引发的洪水愈加难以预测,通过山区雨雪分离可判定引发洪水的温度条件,从而为山洪准确预报提供简单而科学的参考依据。本研究以昆仑山提孜那甫河流域为例,基于流域内不同海拔气象站2012-2016年的降水以及温度数据,结合MOD10A2积雪数据,采用温度积分法和概率统计方法,利用研究期内的平均温度,确定出不同降水形态对应的温度条件,以达到雨雪分离的目的。研究结果表明,莫木克站最大温和积温分别达到20.91 ℃和51.82 ℃时,降水可判定为降雨,最大温和积温分别低于18.13 ℃,43.69 ℃时,降水可判定为降雪;库地站最大温和积温分别达到14.51 ℃,33.17 ℃时,降水可判定为降雨,最大温和积温分别低于13.57 ℃,31.68 ℃时,降水可判定为降雪;西合休站最大温和积温分别达到9.43 ℃,19.53 ℃时,降水可判定为降雨,最大温和积温分别低于8.22 ℃,19.4 ℃时,降水可判定为降雪。利用流域内气象站点附近乡镇的气象统计数据对温度条件及分离结果进行验证,在海拔2000 m以下、2000~3000 m以及3000 m以上不同海拔地区的准确率分别为92.86%、79.49%以及88.3%。本研究可为判别洪水类型和洪水预报提供科学参考。

关键词: 山区, 山洪预报, 雨雪分离, 温度积分, 概率统计

Abstract:

Under the context of global climate change, the heavy flood caused by the snow melting (glacier melting) as well as heavy rainfall in the high altitude mountainous areas in Xinjiang Uygur Autonomous Region was becoming more unpredictable. Therefore, clarifying the relationship between the temperature and the rainfall types is the prerequisite step to predict the flood effectively in these mountainous regions. Fortunately, the approach of rainfall and snowfall separation in mountainous regions is capable of determining the temperature conditions which may cause the heavy flood. It is also able to provide important and scientific references to the accurately prediction for the heavy flood in the mountainous regions. In this study, temperature and precipitation data were collected from ground-based meteorological stations located in different altitude in a case study area: the Tizinafu River Basin in Kunlun Mountains. This study was conducted on a daily basis during 2012 to 2016. The MODIS10A2 snow cover data with 8-day temporal resolution were also applied as the valid reference data. For the purpose of rainfall and snow separation, we adopted the temperature integral and probability statistics methods to analyze the temperature conditions for different rainfall types in the research region. The remote sensing snow cover data combined with the average temperature over the latest past few years are used to determine the different temperature conditions with different precipitation patterns. The results were summarized as follows. If the maximum temperature and accumulated temperature reaches 20.91 ?C and 51.82 ?C, respectively, the precipitation can be predicted as rainfall in the Momuke station. In contrast, if maximum and accumulated temperature are below 18.13 ?C and 43.69 ?C, respectively, the precipitation can be predicted as snowfall. Similarly, for Kudi station, if the maximum and accumulated temperature reaches 14.51 ?C and 33.17 ?C, respectively, the precipitation can be judged as rainfall. While the precipitation will be recognized as snowfall when the maximum and accumulated temperature are below 13.57 ?C and 31.68 ?C, respectively. In the same way, when the maximum temperature and accumulated temperature in the Xihexiu meteorological station are above 9.43 ?C and 19.53 ?C, respectively, the precipitation will be recognized as rainfall and the precipitation will be recognized as snowfall once maximum temperature and accumulated temperature are below 8.22 ?C and 19.4 ?C, respectively. For validating and evaluating the credibility of this rainfall and snowfall separation method as well as the reasonability of the reference temperature conditions, the meteorological data from the nearby villages of the study catchment were used to assess rainfall and snow separation results. From the results, we can conclude that in different elevation bands, the rainfall and snow separation results are always acceptable with different levels. The precisions are 92.86%, 79.49% and 88.3% in the elevation bands below 2000 m, 2000-3000 m, and 3000 m above sea level, respectively. The results is capable of providing a scientific evidence for monitoring flood types and flood forecasting, which is of great significance and is related to create new water resource management guidelines and planning schemes for local people and decision makers.

Key words: mountainous region, flash flood forecasting, rainfall and snow separation, temperature integral, probability statistics