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首页> 外文期刊>Journal of Hydrology >Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States
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Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States

机译:陆地储水异常的气候驱动预测:在孔雀石美国的水资源监测前景

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The conterminous United States (CONUS) extends over a region of contrasting climates with an uneven distribution of freshwater resources. Under climate change, most predictions concur on critical disturbances in the terrestrial hydrological cycle with consequences on freshwater resources availability. In the case of the US, an exacerbation of the contrast between dry and wet regions is expected and could drastically affect local ecosystems, agriculture practices, and communities. Hence, efforts to better understand long-term spatial and temporal patterns of freshwater resources are needed to plan and anticipate responses. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite observations provide estimates of large-scale land water storage changes with an unprecedented accuracy. However, the limited lifetime and observation gaps of the GRACE mission have sparked research interest for GRACE-like data reconstruction. Hence, this study developed a predictive modeling approach to quantify monthly land liquid water equivalence thickness anomaly (LWE) using climate variables including total precipitation (PRE), number of wet day (WET), air temperature (TMP), and potential evapotranspiration (PET). The approach builds on the achievements of the GRACE mission by determining LWE footprints using a multivariate regression on principal components model with lag signals. The performance evaluation of the model with a lag signals consideration shows 0.5 <= R-2 <= 0.8 for 41.2% of the CONUS. However, the model's predictive power is unevenly distributed. The model could be useful for predicting and monitoring freshwater resources anomalies for the locations with high model performances.
机译:孔雀石美国(康明斯)延伸到一个对比气候的区域,淡水资源的分布不均匀。在气候变化下,大多数预测对陆地水文循环中的关键干扰同意淡水资源可用性的影响。在美国的情况下,预计干燥和湿地区之间的对比度会发生较大,并且可能会大大影响当地生态系统,农业实践和社区。因此,需要努力更好地了解淡水资源的长期空间和时间模式来计划和预测反应。自2002年以来,重力恢复和气候实验(Grace)和Grace跟进(Grace-Fo)卫星观察提供了大规模土地储存变化的估计,具有前所未有的准确性。然而,恩典特派团的有限寿命和观察差距引起了恩典数据重建的研究兴趣。因此,本研究开发了一种预测建模方法,可以使用气候变量量化每月土地液体水当量厚度异常(LWE),包括总沉淀(前),湿日(湿),空气温度(TMP)和潜在蒸散量(PET )。该方法通过在具有滞后信号的主成分模型上使用多变量回归来确定LWE脚印来构建恩典使命的成就。具有滞后信号考虑的模型的性能评估显示为41.2%的锥形的0.5 <= R-2 <= 0.8。然而,模型的预测力是不均匀的分布。该模型可用于预测和监测具有高模型性能的地点的淡水资源异常。

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