Morphological characteristics and influencing factors of permanent gully and its contribution to regional soil loss based on a field investigation of 393 km2 in Mollisols region of northeast China

Zhang, Shengmin; Han, Xiao; Cruse, Richard M.; Zhang, Xingyi; Hu, Wei; Yue, Yan; Guo, Mingming

doi:10.1016/j.catena.2022.106467

Cited by 36 publications

(12 citation statements)

References 82 publications

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“…The gully coordinates were determined by walking along the gully boundary and then the coordinates were imported into ArcGIS to show the gully position in the study area. Detailed information about the specific gully investigation method and process could be found in Zhang et al (2022). Gully density (GD), gully lacerative degree (GLD) and gully erosion intensity (GEI) were calculated based on the morphology parameters to analyse the effect of gully erosion on the spatial distribution of SOC, TN and TP.…”

Section: Methodsmentioning

confidence: 99%

“…The Mollisol region of Northeast China is one of the world's four largest Mollisol regions, accounting for over one‐third of China's national commodity grain and grain transfer output (Duan et al, 2009). However, soil loss is a major issue with soil erosion being mainly (65%) associated with gully erosion (Dong et al, 2019; Zhang et al, 2022), resulting in surface Mollisol loss at a rate of 0.3–2 mm per year (Yang et al, 2011). Topsoil erosion causes the depletion of soil nutrients, which in turn reduces soil fertility and productivity.…”

Section: Introductionmentioning

confidence: 99%

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Spatial heterogeneity of soil organic carbon and soil nutrients and their controlling factors in a small watershed in Northeast China

Lixin,

Zhuoxin,

Mingming

et al. 2023

Soil Use and Management

Self Cite

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Understanding the spatial distribution of soil organic carbon (SOC) and soil nutrients is crucial for optimizing land management in watersheds. This study explored the spatial distribution of SOC, total nitrogen (TN), and total phosphorus (TP) in topsoil (0‐20 cm) at a hilly small watershed site in Northeast China, and identified the controlling factors. The Gaussian mixture model optimally described SOC and TN with the ratio of nugget to sill variance (C0/ (C+C0)) indicating moderate spatial dependence for SOC (63.7%) and TN (59.3%). TP was best modelled by the spherical model and demonstrated weak spatial autocorrelation and strong human influence, with a nugget to sill variance of 0.841. Land use significantly affected SOC, TN, and TP contents, with the highest values recorded in woodland, followed by farmland and shrubland. Soil properties including bulk density (BD), gravel content (GC), moisture content (MC), soil porosity (SP), and the mean weight diameter (MWD) of water‐stable aggregates significantly correlated with SOC and TN content, but not with TP. Redundancy analysis revealed that soil properties (BD, GC, and SP), topography (slope and aspect), and gully erosion contributed 55.7%, 24.7%, and 4.3% of the spatial variation in SOC, TN, and TP, respectively. Hence, these are the dominant factors shaping the spatial variation of SOC and soil nutrients at the site. These results can aid the further development of optimized land management strategies.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial heterogeneity of soil organic carbon and soil nutrients and their controlling factors in a small watershed in Northeast China

Lixin,

Zhuoxin,

Mingming

et al. 2023

Soil Use and Management

Self Cite

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“…These areas not only have an impact on crop growth but also act as the origins of erosion gullies. Significant soil and water loss occurs as fine gullies, shallow gullies, and rills arise as a result of the ongoing erosion in these places by water flow [1,2].…”

Section: Introductionmentioning

confidence: 99%

Waterlogged Area Identification Models Based on Object-Oriented Image Analysis and Deep Learning Methods in Sloping Croplands of Northeast China

Xie,

Wang,

Wang

et al. 2024

Sustainability

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Drainage difficulties in the waterlogged areas of sloping cropland not only impede crop development but also facilitate the formation of erosion gullies, resulting in significant soil and water loss. Investigating the distribution of these waterlogged areas is crucial for comprehending the erosion patterns of sloping cropland and preserving black soil resource. In this study, we built varied models based on two stages (one using only deep learning methods and the other combining object-based image analysis (OBIA) with deep learning methods) to identify waterlogged areas using high-resolution remote sensing data. The results showed that the five deep learning models using original remote sensing imagery achieved precision rates varying from 54.6% to 60.9%. Among these models, the DeepLabV3+-Xception model achieved the highest accuracy, as indicated by an F1-score of 53.4%. The identified imagery demonstrated a significant distinction in the two categories of waterlogged areas: sloping cropland erosion zones and erosion risk areas. The former had obvious borders and fewer misclassifications, exceeding the latter in terms of identification accuracy. Furthermore, the accuracy of the deep learning models was significantly improved when combined with object-oriented image analysis. The DeepLabV3+-MobileNetV2 model achieved the maximum accuracy, with an F1-score of 59%, which was 6% higher than that of the model using only original imagery. Moreover, this advancement mitigated issues related to boundary blurriness and image noise in the identification process. These results will provide scientific assistance in managing and reducing the impact in these places.

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“…Currently, gully erosion is a serious problem in the black soil area of Northeast China. The formation of gullies affects mechanical operation, which results in nutrient loss and grain production reduction [17]. Tang et al [18] found that the gully erosion of Hebei Catchment in Heilongjiang Province reduced SOC and STN contents by 9.04 g/kg and 0.92 g/kg, respectively.…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of Soil Organic Carbon and Total Nitrogen in a Micro-Catchment of Northeast China and Their Influencing Factors

et al. 2023

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This study aimed to analyze the spatial distribution of soil organic carbon (SOC) and total nitrogen (STN) in a micro-catchment area comprising farmland and a gully with vegetation restoration (artificial forest and grassland) and their influencing factors. We surveyed a total of 52 topsoil sampling sites to measure the SOC and STN content, as well as topographical factors (elevation, curvature, slope gradient, and aspect), soil properties (bulk density, aggregate distribution, soil texture, and soil moisture), and land use and management. We used traditional statistical and geostatistical methods to analyze the spatial variability of SOC and STN. The results of this study indicate that SOC and STN content varied moderately across the entire micro-catchment area, with greater values in the west (gully head area) than in the east (gully mouth area). Additionally, SOC and STN were significantly positively correlated with soil water content, >2 mm size aggregate fraction, and elevation, but negatively correlated with <0.053 mm size fraction. Land use types also influenced the spatial distribution of SOC and STN contents, with the highest averages of SOC and STN content found at the edge of farmland road and grassland, respectively, and the lowest values in bare land. This study provides a valuable supplement to the understanding of SOC and STN in micro-catchment areas, and the research results also support the evaluation of the impact of gully erosion control on SOC and STN dynamics after vegetation restoration. Overall, vegetation restoration should be adopted for gully erosion control and sustainable agricultural development in the Mollisols region of Northeast China.

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Morphological characteristics and influencing factors of permanent gully and its contribution to regional soil loss based on a field investigation of 393 km2 in Mollisols region of northeast China

Cited by 36 publications

References 82 publications

Spatial heterogeneity of soil organic carbon and soil nutrients and their controlling factors in a small watershed in Northeast China

Spatial heterogeneity of soil organic carbon and soil nutrients and their controlling factors in a small watershed in Northeast China

Waterlogged Area Identification Models Based on Object-Oriented Image Analysis and Deep Learning Methods in Sloping Croplands of Northeast China

Spatial Distribution of Soil Organic Carbon and Total Nitrogen in a Micro-Catchment of Northeast China and Their Influencing Factors

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