Assessing future flood vulnerabilities in lower vellar basin: a remote sensing approach for sustainable flood management

Journal of Building Pathology and Rehabilitation, Journal Year: 2024, Volume and Issue: 10(1)

Published: Nov. 11, 2024

Language: Английский

Reconstructing Long-Term, High-Resolution Groundwater Storage Changes in the Songhua River Basin Using Supplemented GRACE and GRACE-FO Data

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(23), P. 4566 - 4566

Published: Dec. 5, 2024

The Gravity Recovery and Climate Experiment (GRACE) enables large-scale monitoring of terrestrial water storage changes, significantly contributing to hydrology related fields. However, the coarse resolution groundwater anomaly (GWSA) data limits local-scale research utilizing GRACE GRACE-FO missions. In this study, we develop a regional downscaling model based on linear regression relationship between GWSA environmental variables, reducing grid obtained from approximately 25 km 1 km. First, estimate missing values monthly continuous (TWSA) for period 2003 2020 using interpolated multi-channel singular spectrum analysis (IMSSA). Next, apply balance equation separate TWSA, which is provided jointly by Global Land Data Assimilation System (GLDAS) distributed ecohydrological ESSI-3. We then employ partial least squares (PLSR) identify most significant variables GWSA. Precipitation (Prec), normalized difference vegetation index (NDVI), actual evapotranspiration (AET), with variable importance in projection (VIP) greater than 1.0, are recognized as effective reconstructing long-term, high-resolution changes. Finally, downscale reconstruct long-term (2003–2020), (1 × km) Songhua River Basin fused supplemented GRACE/GRACE-FO data, employing either geographically weighted (GWR) or random forest (RF) models. results demonstrate superior performance GWR (CC = 0.995, NSE 0.989, RMSE 2.505 mm) compared RF downscaling. downscaled not only achieves high spatial but also exhibits improved accuracy when situ observation records. This enhances understanding spatiotemporal variations due local agricultural industrial use, providing scientific basis resource management.

Language: Английский

Anthropogenic coal mining reducing groundwater storage in the Yellow River Basin

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 178120 - 178120

Published: Dec. 18, 2024

Language: Английский