An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical mode decomposition

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 620, P. 129460 - 129460

Published: April 1, 2023

Language: Английский

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Disentangling Ecological Restoration's Impact on Terrestrial Water Storage

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(4)

Published: Feb. 12, 2025

Abstract Large‐scale ecological restoration (ER) in semiarid regions is often associated with substantial terrestrial water storage (TWS) depletion. This study challenged previous estimates by demonstrating the critical importance of considering other human activities when assessing ER impacts on TWS. Using a novel analytical framework integrating GRACE satellite data and ground observations, we analyzed TWS changes China's Mu Us Sandyland under two scenarios: without mining farming activities. Our results show that consumed at an average rate 11.7 ± 12.2 mm yr −1 from 2003 to 2022. Neglecting led 251% overestimation ER's effect provided more nuanced understanding resource dynamics restored ecosystems, emphasizing need for comprehensive approaches assessments informing sustainable land management strategies globally.

Language: Английский

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Divergent Changes in Vegetation Greenness, Productivity, and Rainfall Use Efficiency Are Characteristic of Ecological Restoration Towards High-Quality Development in the Yellow River Basin, China

Engineering, Journal Year: 2023, Volume and Issue: 34, P. 109 - 119

Published: Sept. 14, 2023

Globally, vegetation has been changing dramatically. The vegetation–water dynamic is key to understanding ecosystem structure and functioning in water-limited ecosystems. Continual satellite monitoring detected global greening. However, a greenness increase does not mean that functions increase. intricate interplays resulting from the relationships between precipitation must be more adequately comprehended. In this study, data, for example, leaf area index (LAI), net primary production (NPP) rainfall use efficiency (RUE), were used quantify dynamics their relationship with different reaches of Yellow River Basin (YRB). A sequential regression method was detect trends NPP sensitivity rainfall. results showed 34.53% YRB exhibited significant greening trend since 2000. Among them, 20.54%, 53.37%, 16.73% upper, middle, lower reach areas positive trend, respectively. similar LAI reaches. notable difference noted distributions RUE across Moreover, there vegetation–rainfall 16.86% YRB's middle reaches—14.08% negative 2.78% trends. total 8.41% marked LAI, NPP, RUE. Subsequently, strategic locations reliant on correlation identified designated restoration planning purposes propose future ecological efforts. Our analysis indicates most variation productivity. present study underscores significance examining within context high-quality development strategy YRB. outcomes our proposed framework can provide decision-makers valuable insights executing rational basin pattern optimization sustainable management.

Language: Английский

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Analysis of Vegetation Restoration Potential and Its Influencing Factors on the Loess Plateau: Based on the Potential Realization Model and Spatial Dubin Model

Land, Journal Year: 2025, Volume and Issue: 14(1), P. 138 - 138

Published: Jan. 10, 2025

Improvements in vegetation coverage are driven by both resource endowment conditions and policy behaviors. To accurately reflect the restoration effect after ecological policies, this study used potential realization model to calculate degree of on Loess Plateau assess Grain for Green Program from 2000 2020. Then, influencing factors were explored using spatial Dubin model. The results reveal that (1) EVI value northern Shaanxi increased below 0.25 at beginning approximately 0.35 end, indicating green territory gradually expanded northwest over period, east west key areas cover further improvement; (2) compared traditional indicator, can more evaluate policies; (3) intensity is positively correlated with growth rate 0.183 significant 1% level, making it primary factor restoration. Additionally, annual average precipitation sunshine percentage have positive contributions improvement Plateau. study’s findings expected contribute development a scientific basis adjusting enhancing efforts.

Language: Английский

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Revealing joint evolutions and causal interactions in complex ecohydrological systems by a network-based framework

Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(2), P. 361 - 379

Published: Jan. 20, 2025

Abstract. There is evidence that climate change and human activities are changing ecohydrological systems, yet the complex relationships among ecological (normalized difference vegetation index, gross primary productivity, water use efficiency) hydrological variables (runoff, soil storage, groundwater etc.) remain understudied. This study develops a novel framework based on network analysis alongside satellite data in situ observations to delineate joint evolutions (phenomena) causal interactions (mechanisms) systems. The former employs correlations, latter uses physically constrained causality construct relationships. applied Yellow River basin, region undergoing profound changes. Results suggest controlled by compound drivers direct causality. Different types of found – namely, evolution with weak causality, high asynchronous upstream alpine subregions, for example, where subsystem more influenced temperature, while one driven precipitation, show relatively synchronization but lagged between two subsystems. On other hand, can be masked intensive (revegetation, withdrawals, reservoir regulation), leading distinct trends. Other mechanisms also deduced. Reductions efficiency growing season directly caused control evapotranspiration, strength decreases greening land surface some subregions. Overall, proposed provides useful insight into within systems basin has applicability broader geographical contexts.

Language: Английский

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Global inequities in population exposure to urban greenspaces increased amidst tree and nontree vegetation cover expansion

Communications Earth & Environment, Journal Year: 2023, Volume and Issue: 4(1)

Published: Dec. 8, 2023

Abstract Cities worldwide are expanding greenspaces, including parks, urban forests, and grasslands. However, population exposure to tree nontree vegetation is less well understood. Here, we use multiple satellite-derived datasets on vegetation, climate, socioeconomic factors examine the variations of cover, drivers changes, impacts global between 2000 2020. We find that approximately 90% cities experienced an ascending trend in 49% showed growth ( p < 0.05). The increase cover most evident high-latitude areas, such as Eastern Russia Northern Europe. Human considerably declined Global South, widening disparity North South. Our study underscores persistent inequalities human green space calls for evidence-based strategies reduce increasing disparities.

Language: Английский

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Satellite observed dryland greening in Asian endorheic basins: Drivers and implications to sustainable development

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 922, P. 171216 - 171216

Published: Feb. 25, 2024

Language: Английский

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Changes in terrestrial water storage in the Three-North region of China over 2003–2021: Assessing the roles of climate and vegetation restoration

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 637, P. 131303 - 131303

Published: May 9, 2024

Language: Английский

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Dynamic monitoring and drivers of ecological environmental quality in the Three-North region, China: Insights based on remote sensing ecological index

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102936 - 102936

Published: Dec. 1, 2024

Language: Английский

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Discriminating the impacts of vegetation greening and climate change on the changes in evapotranspiration and transpiration fraction over the Yellow River Basin

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 904, P. 166926 - 166926

Published: Sept. 7, 2023

Language: Английский

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