Spatial Quantification of Cropland Soil Erosion Dynamics in the Yunnan Plateau Based on Sampling Survey and Multi-Source LUCC Data

Published: Jan. 17, 2024

Large scale cropland erosion rates mapping and dynamic monitoring are critical for agricultural planning but extremely challenging. In this study, by using field investigation data collected from 20,155 land parcels in 2,781 sample units the National Soil Erosion Survey, use change two decades Land Use/Cover Database of China (NLUD-C), we proposed a new point to surface approach quantitatively assess long-term based on CSLE model non-homogeneous voting. The results show that Yunnan suffers serious problem with unsustainable mean soil rate 40.47t/(ha·a) ratio 70.11%, which significantly higher than those other types. Engineering control measures (ECMS) have profound impact reducing erosion, without ESMs differs more five times. Over past decades, area continues decrease, net reduction 7461.83 km2 −10.55%, causes corresponding 0.32×108 t (12.12% ) decrease loss. We also quantified different LUCC scenarios extraordinarily high variability was found loss basins periods. Conversion forest contributes most reduction, while conversion grassland 56.18% increase erosion. Considering current speed regulation, it is sharp leads rather treatments. dilemma between Grain Green Policy Cropland Protecting Strategy mountainous areas should be treated carefully shared understanding collaborations roles.

Language: Английский

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Predicting Soil Erosion Using RUSLE and GeoSOS-FLUS Models: A Case Study in Kunming, China

Forests, Journal Year: 2024, Volume and Issue: 15(6), P. 1039 - 1039

Published: June 16, 2024

Revealing the relationship between land use changes and soil erosion provides a reference for formulating future strategies. This study simulated historical based on RULSE GeoSOS-FLUS models used random forest model to explain relative importance of natural anthropogenic factors erosion. The main conclusions are as follows: (1) From 1990 2020, significant in occurred Kunming, with continuous reduction woodland, grassland, cropland, being converted into construction land, which grew by 195.18% compared 1990. (2) During this period, modulus decreased from 133.85 t/(km²·a) 130.32 loss 74,485.46 t/a, mainly due conversion cropland ecological lands (woodland, grassland). (3) expansion will continue, it is expected that 2050, decrease 3.77 t/(km²·a), 4.27 3.27 under development, rapid protection scenarios, respectively. However, scenario, increased 0.26 2020. (4) spatial pattern influenced both factors, human activities intensify future, influence further increase. Traditionally, thought increase loss. Our may offer new perspective provide planning management Kunming.

Language: Английский

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A Spatiotemporal Dynamic Evaluation of Soil Erosion at a Monthly Scale and the Identification of Driving Factors in Hainan Island Based on the Chinese Soil Loss Equation Model

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2361 - 2361

Published: March 7, 2025

The damage caused by soil erosion to global ecosystems is undeniable. However, traditional research methods often do not consider the unique characteristics specific China and rainfall intensity variability in different periods on vegetation, relatively few efforts have addressed attribution analysis of changes tropical islands. Therefore, this study applied a modification Chinese Soil Loss Equation (CSLE) evaluate monthly mean modulus Hainan Island over past two decades, aiming assess potential risk. model demonstrated high R2, with validation results for three basins yielding R2 values 0.77, 0.64, 0.78, respectively. indicated that annual average was 92.76 t·hm−2·year−1, 7.73 t·hm−2·month−1. key months were May October, which coincided rainy season, having an 8.11, 9.41, 14.49, 17.05, 18.33, 15.36 t·hm−2·month−1, September marked most critical period erosion. High-erosion-risk zones are predominantly distributed central eastern sections area, gradually extending into southwest. increased rising elevation slope. variation trend erosivity factor had greater impact water than vegetation cover biological practice factor. identification dynamic factors crucial areas prone erosion, as it provides scientific underpinning monitoring implementing comprehensive management these regions.

Language: Английский

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Study on Class Imbalance in Land Use Classification for Soil Erosion in Dry–Hot Valley Regions

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(9), P. 1628 - 1628

Published: May 4, 2025

The inherent spatial heterogeneity of land types often leads to a class imbalance in remote sensing-based classification, reducing the accuracy minority detection. Consequently, current use datasets are inadequate for specific needs soil erosion studies. In response need conservation dry–hot valley regions, this study integrated multi-source sensing imagery and constructed three high-precision imbalanced sample on Google Earth Engine (GEE) platform perform classification. degree was quantified using ratio (IR), impact classification different typical analyzed. results show that (1) Feature selection significantly improved both computational efficiency. period from February April each year, between 2018 2023, identified as optimal time window valleys. (2) Constructing composite images over longer scales enhanced performance: 2020 annual image combined with Gradient Tree Boosting classifier yielded highest accuracy, indicating temporal synthesis improves results. (3) effect varied by type: woodland (the majority class) least affected imbalance, whereas classes such cultivated land, garden plantations, grassland were highly sensitive imbalance. scenarios, prone omission errors, leading notable declines; producer’s (PA) decreased 46%, 42%, 25% grassland, respectively, IR increased (with PA dropping faster than user’s UA). Cultivated especially frequently overlooked under high conditions compared gardens grasslands. Despite overall improving higher IR, these dropped significantly, underscoring importance addressing erosion-prone areas.

Language: Английский

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Impact of Land Use/Cover Change on Soil Erosion and Future Simulations in Hainan Island, China

Water, Journal Year: 2024, Volume and Issue: 16(18), P. 2654 - 2654

Published: Sept. 18, 2024

Soil erosion (SE) is a critical threat to the sustainable development of ecosystem stability, agricultural productivity, and human society in context global environmental climate change. Particularly tropical island regions, due expansion activities land use/cover changes (LUCCs), risk SE has been exacerbated. Combining RUSLE with machine learning methods, spatial patterns, their driving forces mechanisms how LUCCs affect SE, were illustrated. Additionally, potential impacts future on simulated by using PLUS model. The main results are as follows: (1) Due LUCCs, average soil modulus (SEM) decreased significantly from 108.09 t/(km2·a) 2000 106.75 2020, reduction 1.34 t/(km2·a), mainly transformation cropland forest urban land. (2) dominant factor affecting pattern LS (with relative contributions 43.9% 45.17%), followed (LUC) (the contribution 28.46% 34.89%) respectively. (3) Three kinds scenarios simulation indicate that SEM will decrease 2.40 under natural scenario 1.86 ecological protection 2060. However, scenario, there slight increase SEM, an 0.08 t/(km2·a). Sloping control remains primary issue for Hainan Island future.

Language: Английский

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Coupling the Rulse and Plus Models to Assess Past and Future Soil Erosion in Hainan Island, China

Published: Jan. 1, 2024

Language: Английский

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Coupling the Rulse and Plus Models to Assess Past and Future Soil Erosion in Hainan Island, China

Published: Jan. 1, 2024

Language: Английский

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