大范围土壤含水率数据融合并行计算方法研究

土壤含水率是研究水文循环和旱情监测等的重要数据基础,通过多源数据融合能够获取高质量、大范围的土壤含水率资料,但该方法数据量大、计算耗时长。为了快速获取土壤含水率融合数据,提高计算速度,基于并行计算技术,对土壤含水率VIC模型模拟和站点观测数据的融合过程进行并行化设计,并测试了相应程序的计算性能。结果表明,该方法能有效加快融合计算过程,可更高效地获取高精度、高分辨率的土壤含水率数据。

Study on Parallel Computing Method of Data Merging for Large Scale Soil Moisture

Soil moisture data is the basis for the research of hydrological cycle and drought monitoring. High-quality and large-scale soil moisture data can be obtained through multi-source data merging. However, when dealing with multi-source data, the calculation of soil moisture merging required large amount of computing time. In order to improve the accuracy and computational speed, a parallel method was established to fuse the data of variable infiltration capacity model simulation and station observation. Based on the results of performance test, this method can speed up the process of soil moisture merging computation and obtain high-quality and high-resolution soil moisture data more efficiently.