Spatiotemporal changes and influencing factors of ecosystem services in the Nanchang metropolitan area, China DOI Creative Commons
Ting Zhang, Yuzhu Hu, Shengyu Guan

et al.

Frontiers in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 12

Published: Nov. 12, 2024

Ecosystem services (ES) such as carbon storage (CS), soil conservation (SC), habitat quality (HQ), and water yield (WY) play a crucial role in maintaining ecological balance supporting sustainable regional development. With increasing environmental changes, understanding the spatiotemporal dynamics of these their driving factors has become essential science. This study focuses on Nanchang metropolitan area, quantifying CS, SC, HQ, WY from 2000 to 2020. It explores impacts major factors, including climate, topography, social aspects, spatial heterogeneity ES. The results reveal that between 2020, CS HQ decreased by 0.1385×108 tons/ha 0.0507, respectively, while SC increased 2.4754×10 9 1.6668×10 10 m 3 , respectively. Notable exists correlation changes distribution ESs is higher mountainous regions compared central plains. Among human population (POP) gross domestic product (GDP) predominantly influenced whereas climate POP drove SC. Changes were primarily affected topography. These findings suggest need focus key formulate targeted land policies aimed at enhancing ES value area.

Language: Английский

Drivers and characteristics of groundwater drought under human interventions in arid and semiarid areas of China DOI
Xiaofei Ren, Peiyue Li, Dan Wang

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 631, P. 130839 - 130839

Published: Feb. 2, 2024

Language: Английский

Citations

13
Downscaled‐GRACE Data Reveal Anthropogenic and Climate‐Induced Water Storage Decline Across the Indus Basin DOI Creative Commons
Arfan Arshad, Ali Mirchi, Saleh Taghvaeian

et al.

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(7)

Published: July 1, 2024

Abstract GRACE (Gravity Recovery and Climate Experiment) has been widely used to evaluate terrestrial water storage (TWS) groundwater (GWS). However, the coarse‐resolution of data limited ability identify local vulnerabilities in changes associated with climatic anthropogenic stressors. This study employs high‐resolution (1 km 2 ) generated through machine learning (ML) based statistical downscaling illuminate TWS GWS dynamics across twenty sub‐regions Indus Basin. Monthly anomalies obtained from a geographically weighted random forest (RF gw model maintained good consistency original at 25 grid scale. The downscaled 1 resolution illustrate spatial heterogeneity depletion within each sub‐region. Comparison in‐situ 2,200 monitoring wells shows that significantly improves agreement data, evidenced by higher Kling‐Gupta Efficiency (0.50–0.85) correlation coefficients (0.60–0.95). Hotspots highest decline rate between 2002 2023 were Dehli Doab (−442, −585 mm/year), BIST (−367, −556 Rajasthan (−242, −381 BARI (−188, −333 mm/year). Based on general additive model, 47%–83% was stressors mainly due increasing trends crop sown area, consumption, human settlements. lower (i.e., −25 −75 mm/year) upstream (e.g., Yogo, Gilgit, Khurmong, Kabul) where factors (downward shortwave radiations, air temperature, sea surface temperature) explained 72%–91% TWS/GWS changes. relative influences varied sub‐regions, underscoring complex interplay natural‐human activities basin. These findings inform place‐based resource management Basin advancing understanding vulnerabilities.

Language: Английский

Citations

13
Downscaled GRACE/GRACE-FO observations for spatial and temporal monitoring of groundwater storage variations at the local scale using machine learning DOI
Shoaib Ali, Jiangjun Ran, Behnam Khorrami

et al.

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 25, P. 101100 - 101100

Published: Jan. 23, 2024

Language: Английский

Citations

11
Filling the data gap between GRACE and GRACE-FO based on a two-step reconstruction method DOI Creative Commons
Fengmin Hu, Beibei Yang, Zushuai Wei

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: Feb. 23, 2025

Language: Английский

Citations

1
Monitoring spatio-temporal variations of terrestrial water storage changes and their potential influencing factors in a humid subtropical climate region of Southeast China DOI Creative Commons
Haijun Deng, Yang Li, Yuqing Zhang

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 634, P. 131095 - 131095

Published: March 28, 2024

Identifying the changes in terrestrial water storage is essential for a comprehensive understanding of regional hydrological mass balance under global climate change. This study used partial least square regression model to fill observation gaps between GRACE and GRACE-FO obtained complete series anomaly data from April 2002 December 2020 southeast China. We investigated variations anomalies region influencing factors. The revealed that (TWS) have been increasing region, with an average increase 0.33 cm/yr (p < 0.01). intra-annual variation showed positive March September negative other months. Terrestrial increased most regions (especially central northern parts), whereas they decreased southern parts. In terms components, soil moisture (SMS) contributes 58.3 % surface (SWS, especially reservoirs storage) 41.4 TWS. also found precipitation explain approximately 71.7 variation, remaining 28.3 %. These results are cycle developing strategies management Southeast

Language: Английский

Citations

4
A machine learning downscaling framework based on a physically constrained sliding window technique for improving resolution of global water storage anomaly DOI
Gangqiang Zhang, Tongren Xu, Wenjie Yin

et al.

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 313, P. 114359 - 114359

Published: Aug. 10, 2024

Language: Английский

Citations

4
Combining machine learning algorithms for bridging gaps in GRACE and GRACE Follow-On missions using ERA5-Land reanalysis DOI Creative Commons
Jaydeo K. Dharpure, I. M. Howat, Saurabh Kaushik

et al.

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

Published: Jan. 1, 2025

Language: Английский

Citations

0
A Comparative Study of Downscaling Methods for Groundwater Based on GRACE Data Using RFR and GWR Models in Jiangsu Province, China DOI Creative Commons
Rong Yang, Yuqing Zhong, Xiaoxiang Zhang

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 493 - 493

Published: Jan. 31, 2025

The Gravity Recovery and Climate Experiment (GRACE) introduces a new approach to accurately monitor, in real time, regional groundwater resources, which compensates for the limitations of traditional hydrological observations terms spatiotemporal resolution. Currently, storage changes Jiangsu Province face issues such as low spatial resolution, limited applicability downscaling models, insufficient water resource observation data. This study based on GRACE employs Random Forest Regression (RFR) Geographically Weighted (GWR) methods order obtain high-resolution information change. results indicate that among established 66 × 158 local GWR coefficient determination (R2) ranges from 0.39 0.88, with root mean squared error (RMSE) approximately 2.60 cm. proportion models an R2 below 0.5 was 18.52%. Similarly, RFR trained above time series grid data achieved 0.50, RMSE fluctuating around 1.59 In validation, monthly correlation coefficients between measured stations ranged 0.37 0.66, 53.33% having greater than 0.5. seasonal 0.41 0.62, 60% exceeding 0.44 ranging 0.49 0.84. Only one station had both results. validation accuracy levels, model demonstrated better predictive performance, offers distinct advantages improving resolution Province.

Language: Английский

Citations

0
A novel generative adversarial network and downscaling scheme for GRACE/GRACE-FO products: Exemplified by the Yangtze and Nile River Basins DOI
Jielong Wang, Yunzhong Shen, Joseph L. Awange

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 969, P. 178874 - 178874

Published: Feb. 24, 2025

Language: Английский

Citations

0
Ecosystem Service Trade-Offs and Synergies in a Temperate Agricultural Region in Northeast China DOI Creative Commons
Yuhong Li, Yu Cong, Zhang Jin

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 852 - 852

Published: Feb. 28, 2025

Ecosystem services (ESs) are essential for balancing environmental sustainability and socio-economic development. However, the of ESs their relationships increasingly threatened by global climate change intensifying human activities, particularly in ecologically sensitive agriculturally-intensive regions. The Songnen Plain, a crucial agricultural region Northeast China, faces considerable challenges sustaining its due to overexploitation land, degradation, variability. This study assessed five key Plain from 2000 2020 across multiple scales: habitat quality (HQ), soil conservation (SC), water yield (WY), food production (FP), windbreaking sand fixing (WS). We evaluated trade-offs synergies between these ESs, as well driving factors main ES trade-offs. Our findings indicate that provisioning (WY FP) regulating (SC WS) improved over time, with FP exhibiting most significant increase at 203.90%, while supporting (HQ) declined 32.61%. primary ecosystem service multifunctionality areas were those provided FP, SC, WY, accounting 58% total. varied spatial scales, stronger being observed pixel scale more pronounced county scale. Climate factors, precipitation temperature, played role shaping than anthropogenic factors. provides valuable insights into restoration sustainable management temperate regions, implications protection northeastern black safeguarding national security.

Language: Английский

Citations

0