Doing Hydrology when no in-situ data exists: Surrogate River discharge Model (SRM)

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106334 - 106334

Published: Jan. 1, 2025

Language: Английский

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No-reference-image gap filling for Landsat-7 ETM + SLC-off images under unsupervised classification criteria

Signal Image and Video Processing, Journal Year: 2025, Volume and Issue: 19(7)

Published: May 8, 2025

Language: Английский

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Evaluation of ICESat-2 Laser Altimetry for Inland Water Level Monitoring: A Case Study of Canadian Lakes

Water, Journal Year: 2025, Volume and Issue: 17(7), P. 1098 - 1098

Published: April 6, 2025

This study evaluates the performance of ICESat-2 ATL13 altimetry product for estimating water levels in 182 Canadian lakes by integrating satellite-derived observations with situ gauge measurements and applying spatial filtering using HydroLAKES dataset. The analysis compares ATL13-derived lake surface elevations hydrometric data from national monitoring stations, providing a robust framework assessing measurement accuracy. Statistical metrics—including root mean square error (RMSE), absolute (MAE), bias (MBE)—are employed to quantify discrepancies between datasets. Importantly, application HydroLAKES-based reduces RMSE 1.53 m 1.40 m, further exclusion high-error lowers it 0.96 m. Larger deeper exhibit lower margins, while smaller complex shorelines show greater variability. Regression confirms excellent agreement satellite (R2 = 0.9999; Pearson’s r 0.9999, n lakes, p < 0.0001). Temporal trends reveal declining 134 increasing 48 2018 2024, potentially reflecting climatic variability human influence. These findings highlight potential utility large-scale inland when combined techniques such as HydroLAKES.

Language: Английский

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A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Dec. 16, 2024

Water depth, a fundamental characteristic of lake, is important for understanding climatic, ecological, and hydrological processes. However, lake water depth data are still scarce due to the high cost in-situ measurements limitations remote sensing observations. In this study, novel method was developed estimate time series pixel-wise depths lakes that have ever exposed their bottom by Lake were calculated as difference between elevations dynamic surface historical lakebed using optical images DEM data. The applied in Sahel-Sudano-Guinean region Africa where complex climatic conditions rare measurements. Experiments showed proposed could get consistent compared with HydroLAKES data, i.e. MAE 0.86 m RMSE 1.69 m, similar estimates derived from ICESat/ICESat-2 3.79 5.92 m. can provide information on at temporal frequency, expected an efficient solution gather essential lakes.

Language: Английский

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Monitoring reservoir water elevation changes using Jason-2/3 altimetry satellite missions: exploring the capabilities of JASTER (Jason-2/3 Altimetry Stand-Alone Tool for Enhanced Research)

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Sept. 23, 2024

Language: Английский

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Monitoring Water Level Fluctuations of Reservoirs in The Krishna River Basin Using Sentinel-3 and ICESat-2 Altimetry Data

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 183394 - 183409

Published: Jan. 1, 2024

Language: Английский

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