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Drought monitoring using high spatial resolution soil moisture data over Australia in 2015–2019
Journal of Hydrology ( IF 5.9 ) Pub Date : 2021-01-08 , DOI: 10.1016/j.jhydrol.2021.125960
Bin Fang , Prakrut Kansara , Chelsea Dandridge , Venkat Lakshmi

Drought is one of the major hazards that could have a significant impact on agriculture. In this study, two drought indices at high spatial resolution: Soil Water Deficit Index (SWDI) and Soil Moisture Deficit Index (SMDI) were derived by 1 km downscaled Soil Moisture Active Passive (SMAP) soil moisture (SM), Global Land Data Assimilation System (GLDAS) long-term SM and soil attribute products, and used to analyze the drought conditions in Australia in 2015–2019. The SWDI was calculated from SMAP SM estimates and SM at field capacity/wilting point derived from soil attribute data, while the SMDI was calculated by integrating GLDAS and SMAP SM using a temporally incremental based method. We found that in the eastern and western coastal regions, the droughts occurred during spring and summer and were relieved in fall and winter. The temporal change pattern of drought conditions for the northern coastal regions was opposite of the eastern/western coasts. On the other hand, the inland regions always had more severe drought conditions. Additionally, the validation results for the 1 km SMAP SM using International Soil Moisture Network (ISMN) in situ data showed reliable accuracy and the Root Mean Square Deviation (RMSD) ranged from 0.02 to 0.09 m3/m3. Both SWDI and SMDI showed clear seasonal and interannual variability, and the drought conditions worsened in 2017–2019. From the 1 km SWDI/SMDI maps in the Murray-Darling River Basin, terrain and streamflow were found to be two deterministic factors for the drought conditions.



中文翻译:

使用2015-2019年澳大利亚高空间分辨率土壤湿度数据进行干旱监测

干旱是可能对农业产生重大影响的主要危害之一。在这项研究中,两个高分辨率的干旱指数:土壤水分亏缺指数(SWDI)和土壤水分亏缺指数(SMDI)通过缩小1 km的土壤水分主动被动(SMAP)土壤水分(SM),全球土地数据同化得出系统(GLDAS)的长期SM和土壤属性产品,用于分析2015-2019年澳大利亚的干旱状况。SWDI由SMAP SM估算值和田间容量/枯萎点的SM从土壤属性数据得出,而SMDI是通过使用基于时间增量的方法对GLDAS和SMAP SM进行积分来计算的。我们发现在东部和西部沿海地区,干旱发生在春季和夏季,秋季和冬季则减轻了。北部沿海地区干旱状况的时间变化模式与东部/西部沿海相反。另一方面,内陆地区总是有更严重的干旱条件。此外,使用国际土壤水分网络(ISMN)现场数据进行的1 km SMAP SM的验证结果显示出可靠的准确性,并且均方根偏差(RMSD)介于0.02至0.09 m之间3 /米3。SWDI和SMDI均显示明显的季节和年际变化,并且在2017–2019年期间干旱状况恶化。从墨累达令河流域的1 km SWDI / SMDI地图中,发现地形和水流是干旱条件的两个确定性因素。

更新日期:2021-01-20
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