伊朗克尔曼沙赫省GLDAS土壤水分产品评价

IF 1.5 Q4 WATER RESOURCES

H2Open Journal Pub Date : 2023-07-07 DOI:10.2166/h2oj.2023.057

A. Amini, M. K. Moghadam, A. A. Kolahchi, Mehrdad Raheli-Namin, K. O. Ahmed

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引用次数: 0

摘要

地表模拟和数据同化是生成地表状态和通量最佳场的先进技术。利用全球土地资料同化系统(GLDAS)的数据，对伊朗西北部克尔曼沙阿省的土壤水分变化和干旱进行了研究。利用GLDAS在不同深度的土壤湿度数据，并与逐月观测的土壤湿度数据进行比较。在地理信息系统(GIS)环境下对月、年湿度数据进行处理。为了计算标准化降水指数SPI，利用2000 - 2014年降水数据，研究干旱与土壤水分变化的关系。GLDAS的湿度数据与最严重的干湿季节有显著的相关性。2004年和2009年SPI的最小值和最大值分别为- 2.077和0.931，对应土壤水分的最高和最低标准化值分别为- 1.93和1.41。结果表明，GLDAS数据可用于重建时空湿度数据序列。

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Evaluation of GLDAS soil moisture product over Kermanshah province, Iran

Land surface modelling and data assimilation are advanced techniques for generating optimal fields of land surface states and fluxes. In this study, the Global Land Data Assimilation System (GLDAS) data were utilized to investigate the soil moisture variations and droughts in Kermanshah province, northwest Iran. The GLDAS soil moisture data were employed in various depths and compared with observed monthly soil moisture. The monthly and annual moisture data were processed in the Geographic Information System (GIS) environment. To compute the Standardized Precipitation Index, SPI, precipitation data from 2000 to 2014 were used, and the relationship between drought and soil moisture variation was studied. The moisture data from GLDAS had a significant correlation with the most severe wet and dry seasons. The minimum and maximum values of the SPI were determined as −2.077 and 0.931 in 2004 and 2009, respectively, which corresponded to the highest and lowest normalized soil moisture of −1.93 and 1.41. The results showed that GLDAS data can be used to reconstruct spatial and temporal moisture data series.

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来源期刊

H2Open Journal Environmental Science-Environmental Science (miscellaneous)

CiteScore

3.30

自引率

4.80%

发文量

审稿时长

24 weeks