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Since 2012, the "Mountain Excavation and City Construction" (MECC) project has been implemented extensively on the Loess Plateau of China, transforming gullies into flat land for urban sprawl by leveling loess hilltops to fill in valleys. However, this unprecedented human activity has caused widespread controversy over its unknown potential ecological impacts. Quantitative assessment of the impacts of the MECC project on the vegetation is key to ecological management and restoration. Taking the largest MECC project area on the Loess Plateau, Yan'an New District (YND), as the study area, this study investigated the spatiotemporal pattern of vegetation dynamics before and after the implementation of the MECC project using a multitemporal normalized difference vegetation index (NDVI) time series from 2009 to 2023 and explored the response of vegetation dynamics to the large-scale MECC project. The results showed that the vegetation dynamics in the YND exhibited significant spatial and temporal heterogeneity due to the MECC project, with the vegetation in the project-affected areas showing rapid damage followed by slow recovery. Vegetation damage occurred only in the project-affected area, and 84 % of these areas began recovery within 10 years, indicating the limited impact of the large-scale MECC project on the regional vegetation. The strong correlation between vegetation dynamics and the MECC project suggested that the destruction and recovery of vegetation in the project-affected areas was mainly under anthropogenic control, which highlights the importance of targeted ecological policies. Specifically, the MECC project induced local anthropogenic damage to the plant population structure during the land creation period, but regeneration and rational allocation of the vegetation were achieved through urbanization, gradually forming a new balanced ecological environment. These findings will contribute to a full understanding of the response of vegetation to such large-scale engineering activities and help local governments adopt projects or policies that facilitate vegetation recovery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The fragile Loess Plateau of China suffers substantial gully erosion. It is imperative to elucidate gully erosion patterns for implementing effective erosion control strategies. However, high spatiotemporal resolution quantification of gully dynamics remains limited across the Loess Plateau landscape. We utilized the small baseline subset interferometric synthetic aperture radar (SBAS InSAR) technique to investigate the phenomenon of gully erosion and deposition on the Dongzhiyuan tableland, which sits within the vast expanse of the Loess Plateau in China, over the period spanning 2020-2022. The tableland edges subsided while gully bottoms uplifted due to sedimentation. Low elevations underwent active deformation. Slope, aspect, and curvature modulated uplift and subsidence patterns by affecting runoff and sediment transport. Gentle downstream slopes displayed enhanced sedimentation. Southern gullies showed pronounced uplift compared to northern gullies. Heavy rainfall triggered extensive erosion followed by rapid uplift, reflecting an adaptive oscillation between erosion and deposition. Basin hydrology correlated with spatial patterns of deformation. Vegetation cover above 60 % of the maximum substantially increased InSAR error. Our study reveals intricate spatiotemporal behaviors of erosion and deposition in loess gullies using time-series InSAR. The findings provide new insights into gully geomorphology and evolution, and our study quantifies gully erosion and deposition patterns at high spatiotemporal resolution, enabling identification of the most vulnerable areas and prioritization of conservation efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Due to urban expansion and the rapid development of infrastructure in the loess area of China, artificial earth-fill embankments and excavated slopes are increasingly widespread in recent years. Erosion is typical in such loess slopes; however, quantitative statistical analyses of various counter-measures that affects rill erosion are still lacking. Here, we quantified rill morphology and rill erosion development in two newly constructed slopes with different engineering protection measures. We used high-resolution digital surface models (DSMs) acquired using an Unmanned Aerial Vehicle (UAV) to analyze the case areas during two-time periods. Our results from centimeter accuracy differential DSMs demonstrated that rapid rill erosion is prevalent in the study area, expressed as rill density varying between 2.03 km -2 and 8.81 km -2 at different slope surfaces (viz., erosion protected slopes [EPS], landslide protected slopes [LPS], and unprotected slopes [US]). The slope gradient responsible for rill erosion of the EPS, LPS and US are obviously different, and such information is essential for planning preventive measures in each slope type. At the EPS, the severity of erosion is maximum at the top of the ridges, whereas the gap between reinforced concrete lattice and loess deposits are of serious concern at the LPS. The current engineering measures employed in the study area are thus found ineffective for protection against rill erosion. We therefore propose an improved design by implementing an intercepting drain to the existing design for preventing further erosion., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)