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Validation and assessment of SPoRT-LIS surface soil moisture estimates for water resources management applications

机译:水资源管理应用运动 - LIS表面土壤水分估算的验证与评估

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Evaluation of surface soil moisture is necessary to understand spatiotemporal soil moisture trends and their implications on water resources management. This research evaluated a real-time instantiation of NASA's Land Information System (LIS) for water resources management applications at a higher spatial and temporal resolution than is currently available with remotely-sensed satellite estimates or in situ measurements of the same product. Managed by NASA's Short-term Prediction Research and Transition (SPoRT) Center, the "SPoRT-LIS" is an observation-driven, real-time simulation of the Noah land surface model at a 3-km resolution over the full continental United States. Surface soil moisture estimates from SPoRT-LIS (0-10 cm layer) were validated against in situ soil moisture from the International Soil Moisture Network in the Missouri and Arkansas-Red-White River Basins. Validation was conducted at in situ measurement depths of 5-cm and 10-cm, and performance was evaluated across varying soil types, land cover, depth, slope, aspect, and pixel heterogeneity to determine conditions under which SPoRT-LIS surface soil moisture had excellent estimation capability. Results demonstrate that 53% of data at a depth of 5-cm and 51% of the data at a depth of 10-cm were significantly correlated with a Spearman's p greater than 0.5 on a daily basis. Based upon validation results, it is evident that the SPoRT-LIS surface soil moisture estimate is satisfactory for research and operational water resources management applications.
机译:表面土壤水分评估是理解时尚土壤水分趋势及其对水资源管理的影响。该研究评估了NASA的土地信息系统(LIS)的实时实例化,用于水资源管理应用,其空间和时间分辨率比目前可用的卫星估计或原位测量相同的产品。由美国宇航局的短期预测研究和过渡(Sport)中心管理,“Sport-Lis”是一个观察驱动的,实时模拟Noah Land Surface Model,以3公里的美国的大陆分辨率为3公里。 Sport-Lis(0-10cm层)的表面土壤水分估算验证了密苏里州和阿肯色州红白河流盆地国际土壤水分网络的原位土壤水分。验证在原位测量深度为5-cm和10厘米,并且在不同的土壤类型,陆地覆盖,深度,坡度,方面和像素异质方面进行了评估性能,以确定运动-LIS表面土壤水分的条件出色的估计能力。结果表明,53%的数据深度为5-cm的深度和51%的数据,深度为10厘米的数据与每日大于0.5的Spearman的P显着相关。基于验证结果,显然是研究和运营水资源管理应用令人满意的运动-LIS表面土壤水分估计。

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