{"title":"Decreasing soil erosion in South China with uncertainties driven by NDVI estimates","authors":"Xinqing Lu , Yulian Liang , Tongtiegang Zhao , Xudong Zhu , Zhangcai Qin","doi":"10.1016/j.ecolind.2025.113422","DOIUrl":null,"url":null,"abstract":"<div><div>Investigating soil erosion in South China, one of China’s most populous coastal regions, is crucial for understanding regional soil and water conservation, preventing soil degradation, and safeguarding food security. However, significant discrepancies persist among existing estimates of soil erosion, calling for further evaluation of long-term trends in its magnitude and spatial–temporal dynamics. This study utilized the Revised Universal Soil Loss Equation (RUSLE) model to assess soil erosion dynamics over 35 years, and further evaluated the influence of the Normalized Difference Vegetation Index (NDVI). Our findings revealed a general decline in soil erosion across South China, dominated by slight and mild erosion. However, the spatiotemporal patterns exhibited marked variations depending on NDVI datasets, particularly in interannual fluctuations and spatial discrepancies. The soil erosion modulus estimated from AVHRR NDVI demonstrated higher values and greater variability than those based on GIMMS NDVI. Spatially, three out of five datasets indicated a consistent reduction in erosion intensity, while two AVHRR datasets showed an initial decline followed by a resurgence over the past decade. Variations in NDVI data can lead to order-of-magnitude differences in soil erosion estimates, highlighting the need for careful dataset selection for soil erosion analysis. A comprehensive analysis and understanding of these differences are needed to provide valuable insights into the applicability of various NDVI datasets in future soil erosion modeling and risk assessment.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"173 ","pages":"Article 113422"},"PeriodicalIF":7.0000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25003528","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Investigating soil erosion in South China, one of China’s most populous coastal regions, is crucial for understanding regional soil and water conservation, preventing soil degradation, and safeguarding food security. However, significant discrepancies persist among existing estimates of soil erosion, calling for further evaluation of long-term trends in its magnitude and spatial–temporal dynamics. This study utilized the Revised Universal Soil Loss Equation (RUSLE) model to assess soil erosion dynamics over 35 years, and further evaluated the influence of the Normalized Difference Vegetation Index (NDVI). Our findings revealed a general decline in soil erosion across South China, dominated by slight and mild erosion. However, the spatiotemporal patterns exhibited marked variations depending on NDVI datasets, particularly in interannual fluctuations and spatial discrepancies. The soil erosion modulus estimated from AVHRR NDVI demonstrated higher values and greater variability than those based on GIMMS NDVI. Spatially, three out of five datasets indicated a consistent reduction in erosion intensity, while two AVHRR datasets showed an initial decline followed by a resurgence over the past decade. Variations in NDVI data can lead to order-of-magnitude differences in soil erosion estimates, highlighting the need for careful dataset selection for soil erosion analysis. A comprehensive analysis and understanding of these differences are needed to provide valuable insights into the applicability of various NDVI datasets in future soil erosion modeling and risk assessment.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.