Linking Inca Terraces with Landslide Occurrence in the Ticsani Valley, Peru DOI Creative Commons
Gonzalo Ronda, Paul M. Santi, Isaac E. Pope

et al.

Geosciences, Journal Year: 2024, Volume and Issue: 14(11), P. 315 - 315

Published: Nov. 18, 2024

Since the times of Incas, farmers in remote Andes Peru have constructed terraces to grow crops a landscape characterized by steep slopes, semiarid climate, and landslide geohazards. Recent investigations concluded that terracing irrigation techniques could enhance risk due increase water percolation interception surface flow unstable leading failure. In this study, we generated an inventory 170 landslides terraced areas assess spatial coherence, causative relations, geomechanical processes linking presence Inca 250 km2 area located Ticsani valley, southern Peru. To tool was developed based on confusion matrix approach. Performance parameters were quantified for close main rivers communities yielding precision recall values between 64% 81%. On larger scale, poor performance obtained pointing existence additional linked presence. investigate role other natural variables prediction, logistic regression analysis performed. The results showed terrace is statistically relevant factor bolsters predictions, apart from first-order like distance rivers, curvature, geology. explore potential slope failures, FEM numerical modeling conducted. Results suggested both decreased permeability increased irrigation, at 70% average annual rainfall, are capable inducing Overall, irrigated appear further promote instability infiltration fluvial erosion, high relief, geologic materials, exposing local risk.

Language: Английский

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

Belhaj Fatima,

Hlila Rachid,

Abdeldjalil Belkendil

et al.

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

Published: Jan. 28, 2025

Language: Английский

Citations

9
Groundwater quality assessment for drinking and irrigation uses within the vicinities of Volta Lake and Akosombo Dam in Ghana: a multi-methodological approach DOI
Mahamuda Abu, Johnbosco C. Egbueri, Johnson C. Agbasi

et al.

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

Published: March 26, 2025

Language: Английский

Citations

2
Assessing cropping system dynamics over three decades: remote sensing and GIS insights in Murshidabad-Jiaganj Block DOI
Lal Mohammad, Jatisankar Bandyopadhyay, Ismail Mondal

et al.

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

Published: Jan. 11, 2025

Language: Английский

Citations

1
Prediction of spatial-temporal flood water level in agricultural fields using advanced machine learning and deep learning approaches DOI

Adisa Hammed Akinsoji,

Bashir Adelodun, Qudus Adeyi

et al.

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

Published: Jan. 17, 2025

Language: Английский

Citations

1
Dynamics and impacts of monsoon-induced geological hazards: a 2022 flood study along the Swat River in Pakistan DOI Creative Commons
Nazir Ahmed Bazai, Mehtab Alam, Peng Cui

et al.

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

Citations

1
Assessing the Environmental, Health, and Food Security Implications of Heavy Metals in Irrigation Water: A Multi-Index Analytical Framework DOI
Johnbosco C. Egbueri, Johnson C. Agbasi, Mohd Yawar Ali Khan

et al.

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

Published: April 1, 2025

Language: Английский

Citations

1
Mitigating Coastal Flood Risks in the Sundarbans: A Combined InVEST and Machine Learning Approach DOI
Ismail Mondal, Vikas Mishra, SK Ariful Hossain

et al.

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

Citations

0
Predicting the Dynamic of Debris Flow Based on Viscoplastic Theory and Support Vector Regression DOI Open Access
Xinhai Zhang,

Hanze Li,

Yazhou Fan

et al.

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

Citations

0
Increasing landslide deformation and activity in a changing local environment: a case study of Zhouqu County in the Bailong River Basin DOI
Zijing Liu, Haijun Qiu, Ya Liu

et al.

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

Published: Feb. 1, 2025

Language: Английский

Citations

0
Coastal Dynamics: Assessing Erosion and Progradation Patterns in Campeche Coastal Region Using Machine Learning Techniques for Geological Insights DOI

D Palanikkumar,

Eatedal Alabdulkreem,

Nuha Alruwais

et al.

Journal of South American Earth Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 105406 - 105406

Published: Feb. 1, 2025

Language: Английский

Citations

0