Iterative integration of deep learning in hybrid Earth surface system modelling

Nature Reviews Earth & Environment, Journal Year: 2023, Volume and Issue: 4(8), P. 568 - 581

Published: July 11, 2023

Language: Английский

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Impacts of land use/land cover and soil property changes on soil erosion in the black soil region, China

Journal of Environmental Management, Journal Year: 2022, Volume and Issue: 328, P. 117024 - 117024

Published: Dec. 14, 2022

Language: Английский

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Mapping soil erodibility over India

CATENA, Journal Year: 2023, Volume and Issue: 230, P. 107271 - 107271

Published: June 6, 2023

Language: Английский

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Global soil water erosion responses to climate and land use changes

CATENA, Journal Year: 2024, Volume and Issue: 241, P. 108043 - 108043

Published: April 25, 2024

Language: Английский

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Future Soil Erosion Risk in China: Differences in Erosion Driven by General and Extreme Precipitation Under Climate Change

Earth s Future, Journal Year: 2025, Volume and Issue: 13(3)

Published: March 1, 2025

Abstract Soil erosion status is a comprehensive indicator reflecting the quality and stability of ecosystems. changes in China are becoming more unclear due to climate change intensified human activity. Within framework change, this study treats rainfall factor as dynamic examines three types contrasting precipitation—general, heavy, extreme—through integrates Revised Universal Loss Equation Geographic Information Systems reveal differences water driven by varying intensities precipitation. The results that over 63% China's land area has experienced soil during historical period (1980–2022), with slight being most common. Severe predominantly found Southwest Basin, Yangtze River Yellow basin. multi‐year average rate estimated at 2.46 t·ha −1 yr , R95P R99P contributing 26.50% 7.71%, respectively. Future projections (2023–2100) indicate PRCPTOT, R95P, could increase 22%–91% under SSP5‐RCP8.5 SSP2‐RCP4.5 scenarios. Overall, limited effect on spatial pattern China, mainly influencing intensity extent adversely impacting regions. Extreme precipitation sensitive making future risks associated it critical concern. These findings can guide decision‐makers resource managers regional planning enhance resilience secure food resources.

Language: Английский

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Spatio-temporal variation in soil erosion on sloping farmland based on the integrated valuation of ecosystem services and trade-offs model: A case study of Chongqing, southwest China

CATENA, Journal Year: 2023, Volume and Issue: 236, P. 107693 - 107693

Published: Nov. 27, 2023

Language: Английский

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Recent advancements in rainfall erosivity assessment in Brazil: A review

CATENA, Journal Year: 2022, Volume and Issue: 219, P. 106572 - 106572

Published: Aug. 26, 2022

Language: Английский

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An artificial intelligence-based assessment of soil erosion probability indices and contributing factors in the Abha-Khamis watershed, Saudi Arabia

Frontiers in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 11

Published: June 6, 2023

Soil erosion is a major problem in arid regions, including the Abha-Khamis watershed Saudi Arabia. This research aimed to identify soil erosional probability using various erodibility indices, clay ratio (CR), modified (MCR), Critical Level of Organic Matter (CLOM), and principle component analysis based index (SEI). To achieve these objectives, study used t -tests an artificial neural network (ANN) model best SEI for management. The performance models were then evaluated R 2 , Root Mean Squared Error (RMSE), (MSE), Absolute (MAE), with CLOM identified as predicting erodibility. Additionally, Shapley additive explanations (SHAP) values influential parameters erosion, sand, clay, silt, organic carbon (SOC), moisture, void ratio. information can help develop management strategies oriented parameters, which will prevent erosion. showed notable distinctions between CR CLOM, where 25–27% contribution explained over 89% overall diversity. MCR indicated that 70% area had low erodibility, while 20% moderate 10% high range from 40% showing moderate, high. Based on T -test results, significantly different MCR, principal (PCA), PCA, PCA. ANN implementation demonstrated highest accuracy ( 0.95 training 0.92 testing) SOC, being most important variables. SHAP confirmed importance variables each four models. provides valuable regions. identification effective promote agricultural production. be by policymakers stakeholders make informed decisions manage

Language: Английский

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Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 714 - 714

Published: Feb. 18, 2024

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil received continuous attention. Different conservation measures such restoring low-function forests, closing hillsides for afforestation, planting trees grass, constructing terraces slope land have implemented controlling problems promoting vegetation cover change. One important task is to understand effects of different problems. However, directly conducting evaluation reduction difficult. solution evaluate patterns magnitudes change due implementing these measures. Therefore, this selected Changting County, Fujian Province case study examine based time series Landsat images field survey data. between 1986 2021 were used produce data using Google Earth Engine. Sentinel-2 acquired 2010 separately develop maps random forest method. The spatial distribution was linked annual cover. results showed significant bare lands increase pine forests. coverage increased from 42% 79% region compared with an 73% 87% non-conservation during same period. Of measures, magnitude 0.44 forests afforestation 0.65 multiple control This provides new insights terms understanding taking proper scientific decisionmaking controls. strategy method are valuable other regions roles through employing remote sensing technologies.

Language: Английский

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Spatiotemporal dynamics of landslide susceptibility under future climate change and land use scenarios

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(12), P. 124016 - 124016

Published: Oct. 23, 2024

Abstract Mountainous landslides are expected to worsen due environmental changes, yet few studies have quantified their future risks. To address this gap, we conducted a comprehensive analysis of the eastern Hindukush region Pakistan. A geospatial database was developed, and logistic regression employed evaluate baseline landslide susceptibility for 2020. Using latest coupled model intercomparison project 6 models under three shared socioeconomic pathways (SSPs) cellular automata-Markov model, projected rainfall land use/land cover patterns 2040, 2070, 2100, respectively. Our results reveal significant changes in use patterns, particularly long-term (2070 2100). Future then predicted based on these projections. By high-risk areas increase substantially all SSP scenarios, with largest increases observed SSP5-8.5 (56.52%), SSP2-4.5 (53.55%), SSP1-2.6 (22.45%). will rise by 43.08% (SSP1-2.6), 40.88% (SSP2-4.5), 12.60% (SSP5-8.5). However, minimal compared baseline, 9.45% 1.69% 7.63% These findings provide crucial insights into relationship between risks support development climate risk mitigation, planning, disaster management strategies mountainous regions.

Language: Английский

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