Department of Geography, State University of New York, SUNY at Binghamton, Vestal, NY, USA.
Hydrometrology and Remote Sensing (HyDROS) laboratory, University of Oklahoma, Norman, OK, USA.
Sci Rep. 2019 Aug 23;9(1):12327. doi: 10.1038/s41598-019-48813-x.
GRACE Terrestrial Water Storage (TWS) provides unique and unprecedented perspectives about freshwater availability and change globally. However, GRACE-TWS records are relatively short for long-term hydroclimatic variability studies, dating back to April 2002. In this paper, we made use of Noah Land Surface Model (LSM), and El Niño-Southern Oscillation (ENSO) data in an autoregressive model with exogenous variables (ARX) to reconstruct a 66-year record of TWS for nine major transboundary river basins (TRBs) in Africa. Model performance was evaluated using standard indicators, including the Nash Sutcliffe Efficiency criteria, cumulative density frequency, standardized residuals plots, and model uncertainty bounds. Temporally, the reconstruction results were evaluated for trend, cycles, and mode of variability against ancillary data from the WaterGAP Model (WGHM-TWS) and GPCC-based precipitation anomalies. The temporal pattern reveals good agreement between the reconstructed TWS, WGHM-TWS, and GPCC, (p-value < 0.0001). The reconstructed TWS suggests a significant declining trend across the northern and central TRBs since 1951, while the southern basins show an insignificant trend. The mode of variability analysis indicates short storage periodicity of four to sixteen-month in the northern basins, while strong intra-annual variability in the central and southern basins. The long-term TWS records provide additional support to Africa's water resources research on hydroclimatic variability and change in shared transboundary water basins.
GRACE 陆地水储量(TWS)提供了关于全球淡水资源可用性和变化的独特而前所未有的视角。然而,对于长期水文气候变异性研究来说,GRACE-TWS 记录相对较短,可追溯到 2002 年 4 月。在本文中,我们利用 Noah 陆面模型(LSM)和厄尔尼诺-南方涛动(ENSO)数据,在自回归模型中引入外生变量(ARX),对非洲九个主要跨界流域(TRBs)的 TWS 进行了 66 年的重建。采用标准指标对模型性能进行了评估,包括纳什-苏特克里夫效率准则、累积密度频率、标准化残差图和模型不确定性界限。从时间上看,根据 WaterGAP 模型(WGHM-TWS)和基于 GPCC 的降水异常的辅助数据,对重建 TWS 的趋势、周期和变异性模式进行了评估。时间模式显示,重建的 TWS、WGHM-TWS 和 GPCC 之间具有良好的一致性(p 值<0.0001)。重建的 TWS 表明,自 1951 年以来,北部和中部 TRBs 的 TWS 呈显著下降趋势,而南部流域则没有明显的趋势。变异性模式分析表明,北部流域的存储周期性为四到十六个月,而中部和南部流域则具有强烈的年内变异性。长期 TWS 记录为非洲在共享跨界水域的水文气候变异性和变化方面的水资源研究提供了额外的支持。