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Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts

Wang, Jielong, Awange, Joseph, Shen, Yunzhong, Yang, Ling, Feng, Tengfei, and Song, Yongze, 2024. Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts. Journal of Hydrology, 645:132272, doi:10.1016/j.jhydrol.2024.132272.

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@ARTICLE{2024JHyd..64532272W,
       author = {{Wang}, Jielong and {Awange}, Joseph and {Shen}, Yunzhong and {Yang}, Ling and {Feng}, Tengfei and {Song}, Yongze},
        title = "{Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts}",
      journal = {Journal of Hydrology},
     keywords = {GRACE, Deep learning, Data reconstruction, Nile River Basin, Total water storage anomalies},
         year = 2024,
        month = dec,
       volume = {645},
          eid = {132272},
        pages = {132272},
     abstract = "{While the Gravity Recovery And Climate Experiment (GRACE) and its
        Follow-On (GFO) missions have offered valuable observations for
        monitoring total water storage anomalies (TWSA), their short
        record constrains our ability to study the complete range and
        long-term variability of TWSA in the Nile River Basin (NRB).
        Previous studies reconstructing TWSA in this region either
        relied on specific hydrological models or did not consider
        spatial correlations among the TWSA grids. Here, we employ
        RecNet, a deep learning model capable of providing independent
        TWSA observations without relying on hydrological models while
        considering spatial correlations, to reconstruct precipitation-
        driven TWSA in the NRB from 1923 to 2022. The reconstructed data
        are validated by comparisons with the Global Land Data
        Assimilation System (GLDAS), the WaterGAP Global Hydrology Model
        (WGHM), the water balance budget, long-term runoff data, and
        GRACE-REC (i.e., a global reconstruction dataset freely
        available online). Subsequently, the suitability of the
        reconstructed data for studying El Ni{\~n}o Southern Oscillation
        (ENSO) and Indian Ocean Dipole (IOD) impacts within the NRB is
        assessed. Dividing the NRB into four sub-regions, i.e., the Lake
        Victoria Basin (LVB), the Bahr el Jebel and Bahr el Ghazal
        basins (BJBG), Ethiopian Highlands region (EH), and the Lower
        Nile River Basin (LNRB), it is shown that RecNet successfully
        reconstructs precipitation-driven TWSA over BJBG and EH,
        achieving correlation coefficient (CC), normalized root mean
        square error (NRMSE), and Nash{\textendash}Sutcliffeefficiency
        (NSE) of 0.94/0.11/0.88 and 0.96/0.09/0.91 during the testing
        period, respectively. Additionally, RecNet's reconstruction
        shows better agreement with GLDAS and WGHM than GRACE-REC,
        correlating well with runoff and the water balance budget in
        these regions. The relatively poor performance in the LVB and
        LNRB regions could be attributed to the substantial influence of
        Lake Victoria and the arid climate, respectively. Correlation
        analysis and wavelet coherence analysis identify significant
        coherence between ENSO/IOD and the reconstructed TWSA in BJBG
        and EH, with CC values of ‑0.68/0.34 and ‑0.82/0.56,
        respectively. This study provides centennial reconstructed TWSA
        data that could be useful in climate change/variability studies
        and water resource management within the NRB.}",
          doi = {10.1016/j.jhydrol.2024.132272},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024JHyd..64532272W},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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