Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products
Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products
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DOI：
10.1016/j.jag.2015.06.009
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
Abdolaziz Rahmani;S. Golian;L. Brocca
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文献类型：
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作者：
Abdolaziz Rahmani;S. Golian;L. Brocca
土壤湿度 (SM) 对于许多水文应用（包括水资源、干旱分析、农业以及气候变化和极端情况）发挥着重要作用。伊朗大部分地区没有测量 SM，有限的测量无法满足足够的时间和空间分辨率。因此，由于操作简便、覆盖全球且准确性高，遥感 SM 产品几乎是伊朗获取 SM 信息的唯一途径。在本研究中，从两个卫星被动（SMOSL3）和主动+被动（ESA CCI SM）微波观测以及两个再分析（ERA-Interim和ERA-Interim/Land）产品中提取了伊朗六个不同气候条件次区域的地表SM（SSM）数据集。每个分区的平均月平均 SSM 产品以及实地地面降水和温度测量的时间序列。结果显示，总体而言，所有SSM产品彼此吻合良好，相关系数高于0.5。东北地区和西南地区的一致性较好，平均相关值分别为0.88和0.91。值得注意的是，SSM 数据集的特点是不同的周期和长度。因此，应谨慎评估结果。此外，大多数 SSM 产品与最高、最低和平均温度以及月总降水量具有很强的相关性。此外，趋势分析显示，1980-1999 年和 2000-2014 年两个时期所有次区域的月度 SSM 时间序列没有趋势。唯一的例外是 ERA-Interim 的东南次区域以及 ESA CCI SM 的中部和西北次区域，在 2000 年至 2014 年期间检测到负趋势。最后，根据 ERA-Interim、ERA-I/Land 和 ESA CCI SM 数据集计算的标准化土壤湿度指数（SSI）显示，中部和东南部地区遭受了过去十年来最严重和持续时间最长的干旱事件。
Soil moisture (SM) plays a fundamental role for many hydrological applications including water resources, drought analysis, agriculture, and climate variability and extremes. SM is not measured in most parts of Iran and limited measurements do not meet sufficient temporal and spatial resolution. Hence, due to ease of operation, their global coverage and demonstrated accuracy, use of remote sensing SM products is almost the only way for deriving SM information in Iran. In the present research, surface SM (SSM) datasets at six subregions of Iran with different climate conditions were extracted from two satellite-based passive (SMOSL3) and active + passive (ESA CCI SM) microwave observations, and two reanalysis (ERA-Interim and ERA-Interim/Land) products. Time series of averaged monthly mean SSM products and in situ ground precipitation and temperature measurements were derived for each subregion. Results revealed that, generally, all SSM products were in good agreement with each other with correlation coefficients higher than 0.5. The better agreement was found in the Northeast and Southwest region with average correlation values equal to 0.88 and 0.91, respectively. It should be noted that the SSM datasets are characterized by different periods and lengths. Hence, results should be assessed with cautious. Moreover, most SSM products have strong correlations with maximum, minimum and average temperature as well as with total monthly precipitation. Also, trend analysis showed no trend for time series of monthly SSM over all subregions in the two periods 1980–1999 and 2000–2014. The only exceptions were the Southeast subregion for ERA-Interim and Center and Northwest subregions for the ESA CCI SM for which a negative trend was detected for the period 2000–2014. Finally, the Standardized Soil Moisture Index (SSI) calculated from ERA-Interim, ERA-I/Land and ESA CCI SM datasets showed that the Center and Southeast regions suffered from the most severe and longest-lasting drought events in the last decade.