TY - JOUR
T1 - A century of Sudd wetland's water storage dynamics using reconstructed and downscaled GRACE/GRACE-FO Data
AU - Kudagama, Dinuka
AU - Awange, Joseph
AU - Wang, Jielong
AU - Zerihun, Ayalsew
AU - Luna, Leidy
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/6
Y1 - 2025/6
N2 - Although the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have provided valuable Total Water Storage Anomaly (TWSA) observations for understanding the stored water changes in the Ramser Sudd wetland, their coarse resolution (∼300 km) and relatively short records (<30 years) limit their applicability to study long-term water storage variations over this wetland, one of the largest (tropical) wetlands in the world that has so far received little attention. Random Forest (RF) modeling is used to downscale the Sudd wetland's TWSA from 0.5°to 0.1°for the period 2003–2023 for the evaluation of the short-term TWSA dynamics, whereas the centenary precipitation-driven TWSA product is employed to elucidate the long-term climate impacts on the Sudd wetland's TWSA. Our findings show that the downscaled TWSA exhibits a significant correlation with the Global Land Data Assimilation System (correlation coefficient of 0.72) and the WaterGAP Global Hydrology Model (0.65), indicating its potential utility in climate variability analysis. Time series analysis of precipitation/potential evapotranspiration with the downscaled TWSA reveals a higher influence of precipitation-driven runoff from the upstream sub-basins. Our analysis also shows that El Niño–Southern Oscillation (ENSO) is the predominant climate driver, influencing the Sudd's TWSA in both short-term and long-term periods; however, Indian Ocean Dipole (IOD) is found to augment the effect of ENSO over the wetland. Wavelet coherence analysis identifies significant coherence between climate patterns and the Sudd wetland's TWSA over periods of 8–16 months and 4–7 years, indicating the recurrent and cyclic nature of the ENSO/IOD and their influence on TWSA in the Sudd over time.
AB - Although the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have provided valuable Total Water Storage Anomaly (TWSA) observations for understanding the stored water changes in the Ramser Sudd wetland, their coarse resolution (∼300 km) and relatively short records (<30 years) limit their applicability to study long-term water storage variations over this wetland, one of the largest (tropical) wetlands in the world that has so far received little attention. Random Forest (RF) modeling is used to downscale the Sudd wetland's TWSA from 0.5°to 0.1°for the period 2003–2023 for the evaluation of the short-term TWSA dynamics, whereas the centenary precipitation-driven TWSA product is employed to elucidate the long-term climate impacts on the Sudd wetland's TWSA. Our findings show that the downscaled TWSA exhibits a significant correlation with the Global Land Data Assimilation System (correlation coefficient of 0.72) and the WaterGAP Global Hydrology Model (0.65), indicating its potential utility in climate variability analysis. Time series analysis of precipitation/potential evapotranspiration with the downscaled TWSA reveals a higher influence of precipitation-driven runoff from the upstream sub-basins. Our analysis also shows that El Niño–Southern Oscillation (ENSO) is the predominant climate driver, influencing the Sudd's TWSA in both short-term and long-term periods; however, Indian Ocean Dipole (IOD) is found to augment the effect of ENSO over the wetland. Wavelet coherence analysis identifies significant coherence between climate patterns and the Sudd wetland's TWSA over periods of 8–16 months and 4–7 years, indicating the recurrent and cyclic nature of the ENSO/IOD and their influence on TWSA in the Sudd over time.
KW - Climate variability
KW - Random forest machine learning
KW - Sudd wetland
KW - Total water storage anomalies
UR - https://www.scopus.com/pages/publications/105005790005
U2 - 10.1016/j.srs.2025.100232
DO - 10.1016/j.srs.2025.100232
M3 - Journal article
AN - SCOPUS:105005790005
SN - 2666-0172
VL - 11
JO - Science of Remote Sensing
JF - Science of Remote Sensing
M1 - 100232
ER -