The GWR model-based regional downscaling of GRACE/GRACE-FO derived groundwater storage to investigate local-scale variations in the North China Plain

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 908, P. 168239 - 168239

Published: Nov. 4, 2023

Language: Английский

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Remote Sensing Technologies for Unlocking New Groundwater Insights: A Comprehensive Review

Journal of Hydrology X, Journal Year: 2024, Volume and Issue: 23, P. 100175 - 100175

Published: March 19, 2024

This study examined recent advances in remote sensing (RS) techniques used for the quantitative monitoring of groundwater storage changes and assessed their current capabilities limitations. The evolution analyses spans from empirical reliance on sparse point data to assimilation multi-platform satellite measurements using sophisticated machine learning algorithms. Key developments reveal enhanced characterisation localised measurement by integrating coarse-resolution gravity with high-resolution ground motion observations radar imagery; Notable include improved accuracy achieved Gravity Recovery Climate Experiment (GRACE) Interferometric Synthetic Aperture Radar (InSAR) data. Cloud computing now facilitates intensive analysis large geospatial datasets address quantification challenges. While significant progress has been made, ongoing constraints coarse spatial temporal resolutions limiting basin-scale utility, propagation uncertainties sensor calibrations merging, a lack systematic validation impeding operational readiness. Addressing these limitations is critical continued improvement techniques. review identifies promising pathways overcome limitations, emphasising standardised fusion frameworks gravimetry, interferometry, hydrogeophysical development robust cloud-based modelling platforms multi-source subsurface information key recommendation, highlighting potential significantly advance accuracy. comprehensive serves as valuable resource water experts, providing insights into evolving landscape methodologies paving way future advancements tools.

Language: Английский

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The analysis on groundwater storage variations from GRACE/GRACE-FO in recent 20 years driven by influencing factors and prediction in Shandong Province, China

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 9, 2024

Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as example, data from Gravity Recovery Climate Experiment (GRACE) GRACE Follow-On (GRACE-FO) used to invert GWS January 2003 December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ volume level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), impact factors, such precipitation human activities, which also analyzed. To predict short-time changes of GWS, Support Vector Machines (SVM) adopted three commonly methods Long Short-Term Memory (LSTM), Singular Spectrum (SSA), Auto-Regressive Moving Average (ARMA), comparison. results show that: (1) loss intensity western significantly greater than those in coastal areas. From 2006, increased sharply; during 2007 2014, there exists a rate - 5.80 ± 2.28 mm/a GWS; linear trend change 5.39 3.65 2015 2022, may be mainly due effect South-to-North Water Diversion Project. correlation coefficient between WGHM 0.67, consistent level. (2) has higher positive monthly Precipitation Climatology Project (GPCP) considering time delay after moving average, similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, influencing facotrs annual analyzed, including consumption mining, farmland irrigation 0.80, 0.71, respectively. (3) For prediction, SVM method analyze, training samples 180, 204 228 months established goodness-of-fit all 0.97. coefficients 0.56, 0.75, 0.68; RMSE 5.26, 4.42, 5.65 mm; NSE 0.28, 0.43, 0.36, performance model better other short-term prediction.

Language: Английский

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Assessing wildfire impact on Trigonella elliptica habitat using random forest modeling

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 353, P. 120209 - 120209

Published: Jan. 30, 2024

Language: Английский

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Reinterpreting Global GRACE Trends Based on Century‐Long GRACE‐REC Data

Water Resources Research, Journal Year: 2023, Volume and Issue: 59(12)

Published: Dec. 1, 2023

Abstract Assessing changes in freshwater availability accurately is crucial for societal development. Previous studies have examined long‐term variations basin‐scale terrestrial water storage (TWS) using Gravity Recovery and Climate Experiment (GRACE) mission data. However, different basins exhibit distinct spatial temporal TWS variation patterns. To better interpret the trends each basin during GRACE era (2003–2016), this study proposes a novel criterion based on century‐long GRACE‐REC data set. This assesses (Trend G ), precipitation‐induced PI non‐precipitation‐induced NPI ) over period. By calculating upper lower bound values climate‐driven data, an indicator provided to evaluate range of trend under natural conditions. Results reveal that among 266 global analyzed study, , Trend or 115 exceed maximum minimum associated with climate variability. includes 20 large basins, 34 medium 61 small indicating significant Furthermore, we analyze driving mechanisms multi‐source The identified through method align well both our analysis previous studies, confirming reliability approach assessing trends.

Language: Английский

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Challenges in applying water budget framework for estimating groundwater storage changes from GRACE observations

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 639, P. 131600 - 131600

Published: July 1, 2024

The application of a water budget framework to isolate Gravity Recovery and Climate Experiment (GRACE) groundwater storage anomalies (GRACE-GWA) from GRACE terrestrial (GRACE-TWSA) is hindered by the lack direct observations components. In studies, components are frequently applied changes in component various auxiliary methods (e.g., land surface or hydrology models, reanalysis, remote sensing) used as supplement to, substitute for, in-situ measurements when sparse unavailable. contribution select datasets GRACE-GWA GRACE-TWSA an enduring quandary, attributed assumptions resemble hydrologic processes model formulations. This study systematically allocates assorted sources demonstrate bias distortion resulting simply data selection. Whereas previous studies combinations with uncertainty derived variance combined components, this applies single estimates for each measure variability. An initial comparative analysis focused on three basins suitable complex stores large lakes seasonal snow cover), correlation coefficients ranging 0.32 0.89. Our systematic was extended 12 additional that capture range characteristics highlight inconsistency estimates. variability evident highlights selection carries risk misleading outcomes disaggregating into GRACE-GWA. intercomparison provides important assessment limitation extraction GRACE-GWA, highlighting usefulness comprehensive appraisal studies.

Language: Английский

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A non-stationary downscaling and gap-filling approach for GRACE/GRACE-FO data under climatic and anthropogenic influences

Applied Water Science, Journal Year: 2025, Volume and Issue: 15(5)

Published: April 7, 2025

Language: Английский

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Innovative application of the composite Bezier GSXG hybrid machine learning model for daily evapotranspiration Estimation implementing satellite image data

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(9)

Published: April 18, 2025

Language: Английский

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Hydrogeochemical evaluation with emphasis on nitrate and fluoride in urban and rural drinking water resources in western Isfahan province, central Iran

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(50), P. 108720 - 108740

Published: Sept. 26, 2023

Language: Английский

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Incorporating Spatio-Temporal Changes of Well Irrigation into a Distributed Hydrologic Model to Improve Groundwater Anomaly Estimations for Basins with Expanding Agricultural Lands

Water Resources Management, Journal Year: 2024, Volume and Issue: 38(9), P. 3471 - 3487

Published: March 22, 2024

Abstract This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating changes groundwater storage Konya Endorheic Basin (KEB), a basin experiencing considerable land use cover (LULC) change, primarily agricultural expansion. Cereal cultivation has slight decreasing trend, however, crops with high consumption, such as maize sunflower, is increasing substantially. And total areas are increasing. GRACE-GLDAS approach does not accurately give long-term decline basin, mainly because surface models employed cannot realistically simulate variations they do consider LULC possess an elaborated irrigation scheme. Here, we used fully-distributed mesoscale hydrologic model, mHM, that can handle multiple maps from different years. The model was modified incorporate spatio-temporal fields KEB explicit scheme since hypothesized depletion caused by well irrigation. mHM calibrated against streamflow for period 2004–2019. simulations show incorporated features gives more consistent well-based than those obtained approach. On other hand, simulation static map, but better representation irrigated fields, provides anomaly results, further justification insufficiency GLDAS-based basins landscape change.

Language: Английский

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