Monitoring and forecasting water erosion in response to climate change effects using the integration of the global RUSLE/SDR model and predictive models

Applied Soil Ecology, Journal Year: 2025, Volume and Issue: 206, P. 105910 - 105910

Published: Jan. 28, 2025

Language: Английский

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Analysis and early warning management of resource and environmental carrying capacity in agricultural provinces: A case study of Henan Province

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0318848 - e0318848

Published: Feb. 12, 2025

Resources and Environmental Carrying Capacity (RECC) is a comprehensive concept that encompasses the interactions between resources, environment, human activities, serving as foundation for social development strategies. To adequately reflect this complex relationship, multi-level, multi-dimensional evaluation indicator system must be developed. This paper constructs regional soil environmental incorporating PM2.5 indicators, which in line with relevant protection policies planning orientations our country from 2014 to 2023. It analyzes level trend of RECC Henan Province proposes measures effective management. The results indicate following: (1) demonstrates downward trajectory, marked by temporary fluctuations over time. hit its nadir 2019, subsequently undergoing gradual resurgence; (2) Analysis individual dimension indicators reveals natural carrying capacity has declined medium relatively weaker level. Meanwhile, shown slight but generally remained stable. In contrast, socio-economic demonstrated an upward trend, rising strong terms early warning measures, it essential establish red zone, implement credit record accountability system, develop monitoring database along information technology platform. evaluating across different dimensions holds significant reference value assessing similar regions.

Language: Английский

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Groundwater quality assessment for drinking and irrigation uses within the vicinities of Volta Lake and Akosombo Dam in Ghana: a multi-methodological approach

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(7)

Published: March 26, 2025

Language: Английский

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Assessing cropping system dynamics over three decades: remote sensing and GIS insights in Murshidabad-Jiaganj Block

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(2)

Published: Jan. 11, 2025

Language: Английский

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Prediction of spatial-temporal flood water level in agricultural fields using advanced machine learning and deep learning approaches

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Language: Английский

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Dynamics and impacts of monsoon-induced geological hazards: a 2022 flood study along the Swat River in Pakistan

Natural hazards and earth system sciences, Journal Year: 2025, Volume and Issue: 25(3), P. 1071 - 1093

Published: March 11, 2025

Abstract. This study examines the impacts of unprecedented 2022 monsoon season in Pakistan's Swat River basin, where rainfall exceeded historical averages by 7 %–8 %. extreme weather led to catastrophic debris flows and floods, worsening challenges for low-income communities. The resulting financial instability affected millions, causing significant damage homes, crops, transportation. employs a multidisciplinary approach, combining field investigations, remote sensing data interpretation, numerical simulations identify factors contributing flow incidents. Analysis land cover changes reveals decrease grasslands an increase barren land, indicating adverse effects deforestation on region. Topography gully morphology are crucial initiating flows, with steep gradients shallow-slope failures predominant. Numerical show that reached high velocities 18 m s−1 depths 40 within 45 min. Two resulted formation dams along River, intensifying subsequent floods. emphasizes interplay during rainy season, rendering region susceptible hindering restoration efforts. Recommendations include climate change mitigation, reforestation initiatives, discouraging construction activities flood-prone debris-flow-prone regions. advocates enhanced early warning systems rigorous use planning protect environment local communities, highlighting imperative proactive measures face escalating challenges. Additionally, investigates spatial distribution various events their consequences, including potential hydrometeorological triggers, how such initiate processes mountain landscapes. It also assesses extent which can be classified as abnormal. combination empirical evidence practical insights presented this highlights research gaps proposes routes toward deeper understanding monsoon-triggered geological hazards consequences.

Language: Английский

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Assessing the Environmental, Health, and Food Security Implications of Heavy Metals in Irrigation Water: A Multi-Index Analytical Framework

Analytical Letters, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 36

Published: April 1, 2025

Language: Английский

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Mitigating Coastal Flood Risks in the Sundarbans: A Combined InVEST and Machine Learning Approach

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2025, Volume and Issue: 138, P. 103855 - 103855

Published: Jan. 6, 2025

Language: Английский

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Predicting the Dynamic of Debris Flow Based on Viscoplastic Theory and Support Vector Regression

Water, Journal Year: 2025, Volume and Issue: 17(1), P. 120 - 120

Published: Jan. 4, 2025

The prediction of debris flows is essential for safeguarding infrastructure and minimizing the economic losses associated with hazards. Traditional empirical theoretical models, while providing foundational insights, often struggle to capture complex nonlinear behaviors inherent in flows. This study aims enhance flow by integrating modeling data-driven approaches. We model as a viscoplastic fluid, employing Herschel–Bulkley rheological describe its behavior. By combining kinematic wave lubrication theory, we develop comprehensive framework that encapsulates mechanical physics identifies key governing parameters. Numerical solutions this are utilized generate an extensive training dataset, which subsequently used train support vector regression (SVR) model. SVR targets slide depth velocity upon impact, using explanatory variables including yield stress, material density, source area length, slope length. demonstrates high predictive accuracy, achieving coefficients determination R2 0.956 0.911 at impact. Additionally, relative residuals σ primarily distributed within range −0.05 0.05 both These results indicate proposed hybrid not only incorporates fundamental physical mechanisms but also significantly enhances performance through optimization. underscores critical advantage merging models machine learning techniques, offering robust tool improved risk assessment, can inform development more effective early warning systems mitigation measures.

Language: Английский

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Increasing landslide deformation and activity in a changing local environment: a case study of Zhouqu County in the Bailong River Basin

Bulletin of Engineering Geology and the Environment, Journal Year: 2025, Volume and Issue: 84(2)

Published: Feb. 1, 2025

Language: Английский

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