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Developing a drought-monitoring index for the contiguous US using SMAP

机译:使用Smap开发邻接美国的干旱监测索引

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Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe (between 85.044 degrees N/S) using an L-band (1.4 GHz) microwave radiometer in 2-3 days depending on location. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for meaningful assessment of its indices. This study presents initial in-sights about using SMAP for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS). SMAP soil moisture data from April 2015 to December 2017 at both near-surface (5 cm) SPL3SMP, or Level 3, at similar to 36 km resolution, and root-zone SPL4SMAU, or Level 4, at similar to 9 km resolution, were fitted to beta distributions and were used to construct probability distributions for warm (May-October) and cold (November-April) seasons. To assess the data adequacy and have confidence in using short-term SMAP for a drought index estimate, we analyzed individual grids by defining two filters and a combination of them, which could separate the 5815 grids covering CONUS into passed and failed grids. The two filters were (1) the Kolmogorov-Smirnov (KS) test for beta-fitted long-term and the short-term variable infiltration capacity (VIC) land surface model (LSM) with 95% confidence and (2) good correlation (= 0.4) between beta-fitted VIC and beta-fitted SPL3SMP. To evaluate which filter is the best, we defined a mean distance (MD) metric, assuming a VIC index at 36 km resolution as the ground truth. For both warm and cold seasons, the union of the filters-which also gives the best coverage of the grids throughout CONUS -was chosen to be the most reliable filter. We visually compared our SMAP-based drought index maps with metrics such as the U.S. Drought
机译:自2015年4月以来,美国宇航局的土壤水分活跃被动(SMAP)特派团已经监测了近地表土壤水分,使用L波段(1.4GHz)微波辐射计在2-3天内使用L波段(1.4GHz)微波辐射计来映射地板(85.044度N / s)。地点。特别感兴趣的基于SMAP的农业应用是一种监测产品,其在干燥和湿润条件下评估概率百分比的液体近表面土壤水分。然而,短的SMAP记录长度为其指数有意义地评估了统计挑战。本研究介绍了使用SMAP进行监测的初始视线,用于监测干旱和普拉维地区,首先应用于连续的美国(Conus)。 2015年4月至2017年12月的SMAP土壤水分数据在近表面(5cm)SPL3SMP或3级,类似于36公里的分辨率和Root-Zone Spl4smau,或4级类似于9公里的分辨率适用于Beta分布,用于构建温暖(10月)和寒冷(4月至4月)季节的概率分布。为了评估数据充足性并对使用短期液体进行置信度进行干旱指数估计,我们通过定义两个过滤器和它们的组合来分析各个网格,这可以将覆盖康士群的5815网格分离成通过和失败的网格。这两个过滤器是(1)Kolmogorov-Smirnov(KS)试验,用于β-拟合的长期和短期可变渗透能力(VIC)陆地表面模型(LSM),置信95%和(2)良好的相关性( & = 0.4)β配合VIC和Beta安装的SPL3SMP。为了评估哪个过滤器是最好的,我们定义了一个平均距离(MD)度量标准,假设36公里的VIC索引作为地面真理。对于温暖和冷的季节来说,过滤器的联盟 - 这也给出了整个康塞斯的网格的最佳覆盖范围,选择是最可靠的过滤器。我们将我们的SMAP型干旱指数与美国干旱等度量进行了比较

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