• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >Application of snowmelt runoff model (SRM) in upper Songhuajiang Basin using MODIS remote sensing data
【24h】

Application of snowmelt runoff model (SRM) in upper Songhuajiang Basin using MODIS remote sensing data

机译：MODIS遥感数据在融雪径流模型（SRM）在松花江流域上空的应用

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The snowmelt runoff model (SRM) is used to simulate streamflow from snowmelt in the Er'dao-Songhua basin of upper Songhuajiang basin from March to August in 2010. The basin is divided into three elevation zones based on SRTM DEM data. MODIS flexible snow cover products (MODISMC) are generated form daily Terra/Aqua products and used as snow cover area input for SRM model. The precipitation and temperature data from climate station are interpolated by Kriging methods to calculate daily average precipitation and temperature for each zone. SRM model is forced by three variables and eight parameters considering the physical and hydrological feature of study area. Results show that the peak of snowmelt runoff comes in the middle of April and the end of May. The Nash-Sutcliffe coefficient of determination (R2) and deviation of the runoff volumes (Dv) is 0.57 and 25.59% respectively. The model errors are mainly caused by ignoring the physical process of snowmelt and lacking enough in-situ materials.
机译：融雪径流模型（SRM）用于模拟2010年3月至8月松花江流域上游二道-松花盆地融雪的径流。根据SRTM DEM数据，该流域分为三个高程区。每天从Terra / Aqua产品中生成MODIS柔性积雪产品（MODISMC），并用作SRM模型的积雪面积输入。通过Kriging方法对来自气候站的降水和温度数据进行插值，以计算每个区域的每日平均降水和温度。考虑到研究区的物理和水文特征，SRM模型由三个变量和八个参数组成。结果表明，融雪径流的高峰出现在四月中旬和五月底。 Nash-Sutcliffe的确定系数（R2）和径流量的偏差（Dv）分别为0.57％和25.59％。模型误差主要是由于忽略融雪的物理过程和缺乏足够的原位材料引起的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号