Evaluating Modified Soil Erodibility Factors with the Aid of Pedotransfer Functions and Dynamic Remote-Sensing Data for Soil Health Management

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 657 - 657

Published: March 20, 2025

Soil erosion is a critical factor impacting soil health and agricultural productivity, with erodibility often quantified using the K-factor in models such as universal loss equation (USLE). Traditional estimation lacks spatiotemporal precision, particularly under varying moisture land cover conditions. This study introduces modified pedotransfer functions (Kmlr) integrating dynamic remotely sensed data on use to enhance accuracy for diverse management applications. The Kmlr from multiple approaches, including crop (Cdynamic), high resolution satellite data, downscaled were evaluated across spatial temporal scales within Fish River watershed Alabama, coastal significant soil–water interactions. results highlighted that model provided more accurate sediment yield (SY) predictions, areas, where traditional overestimated by upto 59.23 ton/ha. SY analysis 36 hydrological response units (HRUs) showed captured estimates, especially regions use. (Kmlr-c) Cdynamic high-resolution surface outperformed USLE K-factors predicting SY, strong correlation observed (R² = 0.980 versus R² 0.911). total predicted Kmlr-c (525.11 ton/ha) was notably lower than of USLE-based estimates (828.62 ton/ha), highlighting overestimation conventional models. identification erosive hotspots revealed 6003 ha at risk (K-factor > 0.25), an average 24.2 categorization areas erosion, underscoring need targeted conservation practices. research underscores improvement data-based perfects them application assessments thus promoting development

Language: Английский

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UAV-Based Soil Water Erosion Monitoring: Current Status and Trends

Drones, Journal Year: 2025, Volume and Issue: 9(4), P. 305 - 305

Published: April 14, 2025

Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional monitoring methods are often time-consuming, labor-intensive, resource-demanding, while unmanned aerial vehicles (UAVs) provide high-resolution, near-real-time data, improving accuracy. This study conducts a bibliometric analysis of UAV-based soil research to explore trends, technologies, challenges. A systematic review Web Science Scopus articles identified 473 relevant studies after filtering for terms that refer types erosion. Analysis using R’s bibliometrix package shows is concentrated in Asia, Europe, the Americas, with 304 publications following surge. Multi-rotor UAVs RGB sensors most common. Gully studied form issue, followed by landslides, rills, interrill piping Significant gaps remain rill research. The integration satellite laser surveys, properties limited but crucial. While challenges such as data accuracy persist, offer cost-effective, capabilities, enabling rapid responses changes. Future work should focus on multi-source fusion enhance conservation strategies.

Language: Английский

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Gully-ERFNet: a novel lightweight deep learning model for extracting erosion gullies in the black soil region of Northeast China

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

Published: April 21, 2025

Language: Английский

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Soil loss estimation in Ethiopia: a comprehensive review of the RUSLE model integrated with geospatial technologies

Discover Sustainability, Journal Year: 2025, Volume and Issue: 6(1)

Published: April 28, 2025

Language: Английский

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