Combining machine learning algorithms for bridging gaps in GRACE and GRACE Follow-On missions using ERA5-Land reanalysis

Science of Remote Sensing, Journal Year: 2025, Volume and Issue: unknown, P. 100198 - 100198

Published: Jan. 1, 2025

Language: Английский

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Detection and characterization of scale-invariant behaviour and stochastic downscaling of terrestrial water storage anomalies from GRACE and GPS

International Journal of Remote Sensing, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 31

Published: Jan. 26, 2025

Language: Английский

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Declining Groundwater Storage in the Indus Basin Revealed Using GRACE and GRACE‐FO Data

Water Resources Research, Journal Year: 2025, Volume and Issue: 61(2)

Published: Feb. 1, 2025

Abstract Snow and glacier melt provide freshwater to millions of people in the Indus basin. However, unprecedented increase demand for depleting resources due climate warming has put region's water at risk. Therefore, quantifying mass variation anticipating changes hydrological regimes that affect downstream supply are utmost importance. To address this, we used Gravity Recovery Climate Experiment (GRACE) GRACE Follow‐On derived terrestrial storage anomaly (TWSA) data from April 2002 May 2023 over Several gaps these data, totaling 33 months, significantly impact regional trends predictions changes. We apply a machine learning‐based MissForest algorithm fill compare our results with four previous studies. Annual TWSA shows declining trend (−0.65 cm/yr) before 2015/16, higher (−2.16 after 2015/16. Based on estimate annual groundwater (GWSA), major portion (83.7%) basin is experiencing significant (>−0.15 cm/yr, p < 0.05). Glaciated region less severe decreasing (−0.78 compared non‐glaciated (−1.44 cm/yr). Among sub‐basins, upper lowest decline (−0.42 cm/yr), while Panjnad exhibits highest (−1.70 precipitation runoff decreasing, temperature no trend. evapotranspiration increasing might be vegetation (0.23%/yr) The hydroclimatic variables, vegetation, anthropogenic factors, indicate consistently GWSA region.

Language: Английский

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A technical framework for determining water consumption thresholds in the semi-arid Xiliao River Plain based on terrestrial water balance

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102261 - 102261

Published: Feb. 26, 2025

Language: Английский

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Multi-model ensemble mapping of irrigated areas using remote sensing, machine learning, and ground truth data

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 312, P. 109416 - 109416

Published: March 9, 2025

Language: Английский

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Groundwater Storage Response to Extreme Hydrological Events in Poyang Lake, China’s Largest Fresh-Water Lake

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(6), P. 988 - 988

Published: March 12, 2025

Groundwater systems are important for maintaining ecological balance and ensuring water supplies. However, under the combined pressures of shifting climate patterns human activities, their responses to extreme events have become increasingly complex. As China’s largest freshwater lake, Poyang Lake supports critical resources, health, adaptation efforts. Yet, relationship between groundwater storage (GWS) hydrological in this region remains insufficiently studied, hindering effective management. This study investigates GWS response by downscaling Gravity Recovery Climate Experiment (GRACE) data validating it with five years observed daily levels. Using GRACE, Global Land Data Assimilation System (GLDAS), ERA5 data, a convolutional neural network (CNN)–attention mechanism (A)–long short-term memory (LSTM) model was selected downscale high resolution (0.1° × 0.1°) estimate recovery times return baseline. Our analysis revealed seasonal fluctuations that phase precipitation, evapotranspiration, runoff. durations flood (2020) drought (2022) ranged from 0.8 3.1 months 0.2 4.8 months, respectively. A strong correlation meteorological droughts, while agricultural significantly weaker. These results indicate precipitation runoff more sensitive than evapotranspiration influencing changes. findings highlight significant sensitivity GWS, despite improved management

Language: Английский

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Downscaling GRACE-scale groundwater storage variations to aquifer scales: A linear regression approach based on the water balance concept

Hydrogeology Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

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Snow cover variability assessment and its interplay with hydro-climatic characteristics in data scarce region of Gilgit-Baltistan, Pakistan

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 382, P. 125375 - 125375

Published: April 16, 2025

Language: Английский

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Remote Sensing-Based Multiscale Analysis of Total and Groundwater Storage Dynamics over Semi-Arid North African Basins

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(19), P. 3698 - 3698

Published: Oct. 4, 2024

This study evaluates the use of remote sensing data to improve understanding groundwater resources in climate-sensitive regions with limited availability and increasing agricultural water demands. The research focuses on estimating reserve dynamics two major river basins Morocco, characterized by significant local variability. employs from Gravity Recovery Climate Experiment satellite (GRACE) ERA5-Land reanalysis. Two GRACE terrestrial storage (TWS) products, CSR Mascon JPL (RL06), were analyzed, along auxiliary datasets generated ERA5-Land, including precipitation, evapotranspiration, surface runoff. results show that both TWS products exhibit strong correlations reserves, correlation coefficients reaching up 0.96 Oum Er-rbia River Basin 0.95 Tensift (TRB). root mean square errors (RMSE) 0.99 cm 0.88 cm, respectively. GRACE-derived (GWS) demonstrated a moderate observed levels OERRB (R = 0.59, RMSE 0.82), but weaker TRB 0.30, 1.01). On other hand, ERA5-Land-derived GWS showed stronger 0.72, 0.51) 0.63, 0.59). findings suggest may provide more accurate assessments anomalies, particularly local-scale variability land use. High-resolution like ERA5-land are, therefore, recommended for addressing heterogeneity contrasted complexities characteristics.

Language: Английский

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Assessing the impact of 2022 extreme drought on the Yangtze River basin using downscaled GRACE/GRACE-FO data obtained by partitioned random forest algorithm

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 29

Published: Dec. 4, 2024

The Gravity Recovery and Climate Experiment (GRACE) GRACE Follow-On (GRACE-FO) data have been widely used to monitor analyze extreme hydrological events globally. However, their coarse spatial resolution limits application in small- medium-scale regions. In this study, we proposed a partitioned random forest downscaling (PRFD) strategy improve the of GRACE/GRACE-FO quantitatively assessed performance using closed-loop simulation experiment. Our enhanced approach improved from 1°to 0.1°, downscaled were characterize 2022 drought Yangtze River basin (YRB), with particular on smaller (i.e. Wu basin, WRB). findings show that PRFD reduced root mean square error by 39.29% compared traditional over RF (ORFD), 27.8% grid points showed significantly accuracy improvements. results provided more detailed depiction YRB, allowing for precision identification onset, extent severity, accurate assessment impacts WRB. originated northern WRB, gradually extending southward across severe conditions north than south. High temperatures low precipitation primary drives, while elevated high human water use also contributed. This study provides valuable technique understanding regional-scale areas.

Language: Английский

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