Spatial variability and influencing factors of soil catalase activity in grapevine fields in Huailai-Zhuolu Basin

2013 ◽  
Vol 21 (8) ◽  
pp. 992-997
Author(s):  
Kun MA ◽  
Cheng LI ◽  
Fan XIAO ◽  
Sheng-Dong FENG ◽  
Zhi-Xin YANG
Keyword(s):  
Spatial Variability ◽  
Influencing Factors ◽  
Catalase Activity

scholarly journals Characteristics of Soil Erodibility K Value and Its Influencing Factors in the Changyan Watershed, Southwest Hubei, China

Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 134
Author(s):  
Xiaofang Huang ◽  
Lirong Lin ◽  
Shuwen Ding ◽  
Zhengchao Tian ◽  
Xinyuan Zhu ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Variability ◽  
Influencing Factors ◽  
Soil Type ◽  
Soil Survey ◽  
Purple Soil ◽  
Soil Erodibility ◽  
K Value ◽  
K Factor

Soil erodibility K factor is an important parameter for evaluating soil erosion vulnerability and is required for soil erosion prediction models. It is also necessary for soil and water conservation management. In this study, we investigated the spatial variability characteristics of soil erodibility K factor in a watershed (Changyan watershed with an area of 8.59 km2) of Enshi, southwest of Hubei, China, and evaluated its influencing factors. The soil K values were determined by the EPIC model using the soil survey data across the watershed. Spatial K value prediction was conducted by regression-kriging using geographic data. We also assessed the effects of soil type, land use, and topography on the K value variations. The results showed that soil erodibility K values varied between 0.039–0.052 t·hm2·h/(hm2·MJ·mm) in the watershed with a block-like structure of spatial distribution. The soil erodibility, soil texture, and organic matter content all showed positive spatial autocorrelation. The spatial variability of the K value was related to soil type, land use, and topography. The calcareous soil had the greatest K value on average, followed by the paddy soil, the yellow-brown soil (an alfisol), the purple soil (an inceptisol), and the fluvo-aquic soil (an entisol). The soil K factor showed a negative correlation with the sand content but was positively related to soil silt and clay contents. Forest soils had a greater ability to resist to erosion compared to the cultivated soils. The soil K values increased with increasing slope and showed a decreasing trend with increasing altitude.

scholarly journals Spatial Variability and Influencing Factors of Cr, Ni, Cu, Zn and Pb in Five Mangroves Reserves of South China

2021 ◽  
Vol 690 (1) ◽  
pp. 012017
Author(s):  
Si Chen ◽  
Junxian Liao ◽  
Qijiong Zhang ◽  
Suli Ding ◽  
Mengyuan He ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Influencing Factors ◽  
South China

scholarly journals Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods

2021 ◽  
Vol 10 (6) ◽  
pp. 366
Author(s):  
Ping Yan ◽  
Kairong Lin ◽  
Yiren Wang ◽  
Xinjun Tu ◽  
Chunmei Bai ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Statistical Methods ◽  
Influencing Factors ◽  
Land Degradation ◽  
Ph Value ◽  
Southern China ◽  
Great Influence ◽  
Significant Negative Correlation ◽  
Crop Productivity ◽  
Soil Parameters

Understanding the spatial variability of soil organic matter (SOM) is crucial for implementing precise land degradation control and fertilization to improve crop productivity. Studying spatial variability provides a scientific basis for precision fertilization and land degradation control. In this study, geostatistics and classical statistical methods were used to analyze the spatial variability of SOM and its influencing factors under various degrees of land degradation in the red bed area of southern China. The results demonstrate a declining trend for SOM content with increasing land degradation. The SOM content differs profoundly under different land degradation degrees. The coefficient of variation ranges from 13.61% for extreme land degradation to 8.98% for mild land degradation, 7.96% for moderate land degradation, and 5.64% for severe land degradation. A significant positive correlation is displayed between the altitude and the SOM (p < 0.01) under mild and moderate land degradation conditions. Bulk density and pH value have a significant negative correlation with SOM (p < 0.01). It can be observed that terrain factors, as well as physical and chemical soil parameters, have a great influence on SOM.

Spatial variability of cropland lead and its influencing factors: A case study in Shuangliu county, Sichuan province, China

Geoderma ◽  
2011 ◽  
Vol 162 (3-4) ◽  
pp. 223-230 ◽  
Author(s):  
Su Pang ◽  
Ting-Xuan Li ◽  
Xian-Feng Zhang ◽  
Yong-Dong Wang ◽  
Hai-Ying Yu
Keyword(s):  
Spatial Variability ◽  
Influencing Factors ◽  
Sichuan Province

scholarly journals Spatial Distribution of Stony Desertification and Key Influencing Factors in Different Sampling Scales in Small Karst Watersheds

2018 ◽  
Author(s):  
Zhenming Zhang ◽  
Yunchao Zhou ◽  
Shijie Wang ◽  
Xianfei Huang
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Influencing Factors ◽  
River Basin ◽  
Original Data ◽  
Gis Technology ◽  
Soil Thickness ◽  
Grid Sampling ◽  
Average Value ◽  
Sampling Scale

In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in Karst areas in different sampling scales are studied using a grid sampling method based on geographic information system (GIS) technology and geo-statistics, with the rock bareness rate obtained through sampling with 150m &times; 150m grids in the Houzhai River Basin being taken as the original data and five grid scales (300m &times; 300m, 450m &times; 450m, 600m &times; 600m, 750m &times; 750m, and 900m &times; 900m) as the subsample sets. The results show that the rock bareness rate does not vary much from one sampling scale to another while average values of the five sub-samples all fluctuate around the average value of the entire set. As the sampling scale is expanding, the maximum value and the average value of rock bareness rate are decreasing gradually, with a gradual increase in the coefficient of variability. In the scale of 150m &times; 150m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification on small scales is influenced by many factors, and that on medium scales is jointly influenced by gradient, rock contents, and rock bareness rate. On large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock bareness rate.

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