冰川冻土 ›› 2016, Vol. 38 ›› Issue (1): 211-221.doi: 10.7522/j.isnn.1000-0240.2016.0024

• 寒旱区水文与水资源 • 上一篇    下一篇


闫玉娜1,2,3, 车涛1,3, 李弘毅1,3, 秦越4   

  1. 1. 中国科学院 寒区旱区环境与工程研究所, 甘肃 兰州 730000;
    2. 中国科学院大学, 北京 100049;
    3. 中国科学院 黑河遥感试验研究站, 甘肃 兰州 730000;
    4. 清华大学 水利水电工程系 水沙科学与水利水电工程重点实验室, 北京 100084
  • 收稿日期:2015-10-23 修回日期:2015-11-25 出版日期:2016-02-25 发布日期:2016-05-30
  • 通讯作者: 车涛,
  • 作者简介:闫玉娜(1990-),女,山东菏泽人,2012年毕业于曲阜师范大学,现为中国科学院寒区旱区环境与工程研究所在读硕士研究生,从事积雪遥感与寒区水文模拟研究
  • 基金资助:

Using snow remote sensing data to improve the simulation accuracy of spring snowmelt runoff: take Babao River basin as an example

YAN Yuna1,2,3, CHE Tao1,3, LI Hongyi1,3, QIN Yue4   

  1. 1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Heihe Remote Sensing Experimental Research Station, Chinese Academy of Sciences, Lanzhou 730000, China;
    4. State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
  • Received:2015-10-23 Revised:2015-11-25 Online:2016-02-25 Published:2016-05-30

摘要: 随着寒区水文模拟研究的深入,春季融雪径流模拟误差大这一问题越来越明显.针对此问题,以八宝河流域为研究区,利用积雪衰减曲线将MODIS积雪面积比例产品转化为雪水当量,并用其更新分布式水文模型GBHM(Geomorphology-Based Hydrological Model)中模拟的雪水当量,达到提高春季融雪径流模拟精度的目的.利用GBHM模型对八宝河流域2005-2007年进行了模型预热,参数率定,同时选择2008年进行模型检验.结果表明:GBHM模型在八宝河流域有较好的径流模拟精度,年均纳什效率系数(NSE)达到0.64.但模型对春季融雪过程的模拟效果较差,通过引入积雪遥感数据,这一问题得到很大改善.加入积雪遥感数据后,2008年3-6月径流模拟精度NSE和相对偏差Bias分别由-1.0、-0.45改进为0.58、0.06,单点雪水当量模拟精度获得提高,流域水量平衡也更加合理.

关键词: 积雪遥感数据, 春季融雪径流, 积雪衰减曲线, GBHM模型

Abstract: With the development of hydrologic simulation in cold regions, the large simulation error of spring snowmelt runoff has become one of the largest uncertainties. In this study, Babao River basin was selected as the study area which is regarded as the representative alpine catchment and GBHM (Geomorphology Based Hydrological Model) was established to simulation the watershed hydrological process. Then, the maneuverability of the GBHM was discussed and analyzed. On this basis, the snow cover extent (SCE) product with cloud reducing which retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to update GBHM snow water equivalent(SWE) for a more accurate description of the spring snowmelt runoff process. A simple snow depletion curve model was used for the necessary SWE-SCE inversion. And, the model's calibration period (2005-2007) and validation period (2008) was chosen. The results show that: the model can basically reflect the trend of the runoff and achieve good simulation accuracy with the average annual Nash-Sutcliffe coefficient(NSE) reached 0.64. However, the model doesn't work well during spring snowmelt process. After applying snow remote sensing data into GBHM, this situation has been improved. The NSE and Bias of spring snowmelt runoff respectively from -1.0, -0.45 become 0.58, 0.06, the SWE of grid gets more accurate, and water balance is more reasonable after adding remote sensing data between March and June 2008.

Key words: snow remote sensing data, spring snowmelt runoff, snow depletion curve, GBHM model


  • P407.8