Simulation of coupled transport of soil moisture and heat in a typical karst rocky desertification area, Yunnan Province, Southwest China

Xiong, Xiaofeng; Li, Jianhong; Zuyi, Tao; Wang, Sainan; Huo, Weijie

doi:10.1007/s11356-020-10784-2

Cited by 6 publications

(4 citation statements)

References 67 publications

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“…In this study, MODIS data was used to generate the rocky desertification level map at 250 m resolution, which was consistent with the continuous distribution scale of rocky desertification in nature, though there may still be mixed pixels [68]. In the future, more attention should be paid on the mixture pixel problem by using the linear spectral unmixing method to further improve the performance of the rocky desertification mapping.…”

Section: Discussionmentioning

confidence: 62%

Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic

et al. 2021

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Building a high-precision, stable, and universal automatic extraction model of the rocky desertification information is the premise for exploring the spatiotemporal evolution of rocky desertification. Taking Guizhou province as the research area and based on MODIS and continuous forest inventory data in China, we used a machine learning algorithm to build a rocky desertification model with bedrock exposure rate, temperature difference, humidity, and other characteristic factors and considered improving the model accuracy from the spatial and temporal dimensions. The results showed the following: (1) The supervised classification method was used to build a rocky desertification model, and the logical model, RF model, and SVM model were constructed separately. The accuracies of the models were 73.8%, 78.2%, and 80.6%, respectively, and the kappa coefficients were 0.61, 0.672, and 0.707, respectively. SVM performed the best. (2) Vegetation types and vegetation seasonal phases are closely related to rocky desertification. After combining them, the model accuracy and kappa coefficient improved to 91.1% and 0.861. (3) The spatial distribution characteristics of rocky desertification in Guizhou are obvious, showing a pattern of being heavy in the west, light in the east, heavy in the south, and light in the north. Rocky desertification has continuously increased from 2001 to 2019. In conclusion, combining the vertical spatial structure of vegetation and the differences in seasonal phase is an effective method to improve the modeling accuracy of rocky desertification, and the SVM model has the highest rocky desertification classification accuracy. The research results provide data support for exploring the spatiotemporal evolution pattern of rocky desertification in Guizhou.

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Section: Discussionmentioning

confidence: 62%

Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic

et al. 2021

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“…The process of rocky desertification creates specific hydrogeological structures in this area, which lead to the obvious transfer of natural precipitation from the surface to the underground and the serious loss of water resources [6,7]. Preferential flow at the rock and soil interface is an extraordinarily important mechanism of soil water loss to the subsurface in this karst region, which is significantly different from that in nonkarst areas [8,9]. Therefore, preventing the preferential flow at the rock-soil interface and reducing soil water loss through this technique can alleviate agricultural soil drought and increase crop yields in karst areas.…”

Section: Introductionmentioning

confidence: 99%

“…The infiltration process and redistribution of rainwater in rocky karst environments are strongly affected by rock outcrops [8,22,23]. The rocks extend from the surface to the underlying bedrock and will strongly induce the vertical infiltration of soil water and then inevitably reduce the soil's water-holding capacity due to their role in accelerating the conversion of surface water and groundwater [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Effects of Film-Mulched Rock Outcrops on Rainwater Redistribution and Maize Growth in the Cropland of a Rocky Karst Area

Zhao,

Deng,

Zhang

et al. 2024

Water

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Film-mulched rock outcrops are a proven way to effectively prevent preferential flow at the rock–soil interface in rocky karst areas, but the impact on rainwater redistribution and maize growth in farmland areas has never been studied. This paper used the dye tracer method at a sprinkling intensity of 1 mm min−1 to study the rainwater redistribution in soils for three different treatments: away from rock (AR), close to rock (CR), and close to film-mulched rock (CFMR). The growth situation of maize (Zea mays L.) according to the different treatments was also studied. It was shown in the study that the rainwater gathered by rock outcrops was mainly confined only within a narrow flow path at the rock–soil interface in the CR treatment, with a preferential flow fraction of 35.78~55.54% and dyeing depth of 15.37~20.00 cm across the three dye application amounts (850 mL, 1700 mL, and 3400 mL) in contrast to the uniform distribution of the rainwater in the soil of the AR treatment, with a preferential flow fraction of 12.31~37.15% and dyeing depth of 6.93~14.00 cm. Interestingly, in the CFMR treatment, there was no preferential flow at the rock–soil interface benefiting from the film’s blocking action, and the redistribution of rainwater was mainly based on the matrix flow, with a preferential flow fraction of 24.93~39.62% and dyeing depth of 10.27~18.00 cm, indicating that the film-mulched rock outcrops improved the rock’s output capability for gathering rainwater into the surrounding soil. In addition, film-mulched rock outcrops can promote the growth of maize, as indicated by the results for plant height, stem diameter, maximum leaf area, SPAD value, and floral development of maize, which increased in order from AR, CR, to CFMR. Our study suggests that film-mulched rock outcrops have important implications for the efficient use of rainwater and the growth of crops in rocky karst areas, as well as in regions with similar geological characteristics.

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“…The karst areas of Southwest China experience a subtropical, humid monsoon climate, and climate change significantly affects the soil moisture [20][21][22][23][24]. This region is typically characterized by a thin soil layer, severe rocky desertification, and fragile ecological environment [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Temporal Variation of Soil Moisture and Its Influencing Factors in Karst Areas of Southwest China from 1982 to 2015

Xin

Gao

Liu

et al. 2022

Water

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Climate change and human activities are two dominating factors affecting soil moisture temporal variation trends, whereas their individual contributions to soil moisture trends still remain uncertain in the karst areas of Southwest China. Based on the linear regression trend analysis, Mann–Kendall mutation detection, and residual analysis methods, we quantified the contributions of climate change and human activities to soil moisture temporal variation trends in the karst areas of Southwest China. The results showed that the soil moisture in the study area experienced a drying trend from 1982 to 2015. The mutated year was 1999, and the soil moisture decreasing trend was more evident from 2000 to 2015 than from 1982 to 1999. Human activities and climate change accounted for 59% and 41%, respectively, of soil moisture drying trends. Owing to the spatial heterogeneity of geomorphic features, the individual contributions of climate change and human activities to soil moisture trends exhibited regional differences. Although remarkable regional vegetation restoration was found since applying the Grain for Green Project, the negative impact of vegetation restoration on soil moisture cannot be neglected. This study is a quantitative analysis of the relative impacts of climate change and human activities on soil moisture trends, and our findings provide a theoretical reference for the sustainable use of soil water resources in the karst areas of Southwest China.

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Simulation of coupled transport of soil moisture and heat in a typical karst rocky desertification area, Yunnan Province, Southwest China

Cited by 6 publications

References 67 publications

Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic

Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic

Effects of Film-Mulched Rock Outcrops on Rainwater Redistribution and Maize Growth in the Cropland of a Rocky Karst Area

Temporal Variation of Soil Moisture and Its Influencing Factors in Karst Areas of Southwest China from 1982 to 2015

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