Xin Zhang, L. Cao, Yida Wang, Zhendong Yao, Shuling Li, Jiliang Han
{"title":"Comparative analysis of soil moisture based on model simulation and site observation data","authors":"Xin Zhang, L. Cao, Yida Wang, Zhendong Yao, Shuling Li, Jiliang Han","doi":"10.1109/ICMO49322.2019.9076593","DOIUrl":null,"url":null,"abstract":"It is of great significance to accurately and objectively evaluate the spatial and temporal variation characteristics of soil moisture in studies Heilongjiang Region. Combining model simulation and site observation is necessary to studying water and energy recycling at a regional scale especially. In this paper, Using the soil moisture observation at 0~10 cm layer from the automatic soil moisture monitoring stations and Manual observation data as a guide. Based on the surface soil moisture data of 10 cm provided by CLDAS-V2.0 ( CMA Land Data Assimilation System Version2.0 ) developed by the National Meteorological Information Center, the spatiotemporal difference of model simulated data in Heilongjiang province was compared and analyzed. The correlation coefficient(R), mean relative deviation, root-meansquare error (RMSE), mean relative error (MRE) and mean absolute error (MAE)of the simulated data and the observed data were calculated, Comprehensive evaluation the applicability of soil moisture data from simulated data in Heilongjiang Region. In this paper using soil data in the main growth period of crops, summer is selected as the research period for preliminary evaluation and analysis, The research period is from May to August,2018 to 2019, the time series length was 244days. Using the NetCDF toolbox of ArcGIS to get 0 ~ 10 cm soil moisture data of the grid where the observation station is located by CLDAS-V2.0. The results showed that: Although the data from model products were generally slightly higher than the observation data, station observation and model products data show a good consistency. The paper would help us make effective use of model products in soil moisture related studies with a view to testing CLDAS V2.0 for Ability to describe soil humidity.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Meteorology Observations (ICMO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMO49322.2019.9076593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is of great significance to accurately and objectively evaluate the spatial and temporal variation characteristics of soil moisture in studies Heilongjiang Region. Combining model simulation and site observation is necessary to studying water and energy recycling at a regional scale especially. In this paper, Using the soil moisture observation at 0~10 cm layer from the automatic soil moisture monitoring stations and Manual observation data as a guide. Based on the surface soil moisture data of 10 cm provided by CLDAS-V2.0 ( CMA Land Data Assimilation System Version2.0 ) developed by the National Meteorological Information Center, the spatiotemporal difference of model simulated data in Heilongjiang province was compared and analyzed. The correlation coefficient(R), mean relative deviation, root-meansquare error (RMSE), mean relative error (MRE) and mean absolute error (MAE)of the simulated data and the observed data were calculated, Comprehensive evaluation the applicability of soil moisture data from simulated data in Heilongjiang Region. In this paper using soil data in the main growth period of crops, summer is selected as the research period for preliminary evaluation and analysis, The research period is from May to August,2018 to 2019, the time series length was 244days. Using the NetCDF toolbox of ArcGIS to get 0 ~ 10 cm soil moisture data of the grid where the observation station is located by CLDAS-V2.0. The results showed that: Although the data from model products were generally slightly higher than the observation data, station observation and model products data show a good consistency. The paper would help us make effective use of model products in soil moisture related studies with a view to testing CLDAS V2.0 for Ability to describe soil humidity.