SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN A REGION OF THE LOESS PLATEAU OF PR CHINA SUBJECT TO WIND AND WATER EROSION
ABSTRACT The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosi...
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Published in | Land degradation & development Vol. 24; no. 3; pp. 296 - 304 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.05.2013
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1085-3278 1099-145X |
DOI | 10.1002/ldr.1128 |
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Abstract | ABSTRACT
The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0·54 km2 watershed on the Loess Plateau. Topsoil samples (0–5 cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas KS had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p < 0·05). Geostatistical analyses revealed that the KS semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100‐m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright © 2011 John Wiley & Sons, Ltd. |
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AbstractList | ABSTRACT
The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0·54 km2 watershed on the Loess Plateau. Topsoil samples (0–5 cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas KS had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p < 0·05). Geostatistical analyses revealed that the KS semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100‐m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright © 2011 John Wiley & Sons, Ltd. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (K sub(S)), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0.54km super(2) watershed on the Loess Plateau. Topsoil samples (0-5cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas K sub(S) had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p<0.05). Geostatistical analyses revealed that the K sub(S) semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100-m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright [copy 2011 John Wiley & Sons, Ltd. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity ( K S ), total porosity ( TP ), capillary porosity ( CP ) and bulk density ( BD ) in relation to land use in a 0·54 km 2 watershed on the Loess Plateau. Topsoil samples (0–5 cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP , CP and BD had low variability whereas K S had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland ( p < 0·05). Geostatistical analyses revealed that the K S semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100‐m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright © 2011 John Wiley & Sons, Ltd. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0·54 km² watershed on the Loess Plateau. Topsoil samples (0–5 cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas KS had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p < 0·05). Geostatistical analyses revealed that the KS semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100‐m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0·54km2 watershed on the Loess Plateau. Topsoil samples (0-5cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas KS had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p<0·05). Geostatistical analyses revealed that the KS semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100-m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright © 2011 John Wiley & Sons, Ltd. [PUBLICATION ABSTRACT] |
Author | Shao, M. A. Wang, Y. Q. |
Author_xml | – sequence: 1 givenname: Y. Q. surname: Wang fullname: Wang, Y. Q. organization: College of Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR, China – sequence: 2 givenname: M. A. surname: Shao fullname: Shao, M. A. email: Correspondence to: M. A. Shao, No. 26, Xinong Road, Institute of Soil and Water Conservation, Chinese Academy of Science, Yangling, Shaanxi Province 712100, PR China., mashao@ms.iswc.ac.cn organization: State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Science and the Ministry of Water Resources, Yangling, 712100, Shaanxi, PR, China |
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Li YY, Shao MA. 2006. Change of soil physical properties under long-term natural vegetation restoration in the Loess Plateau of China. Journal of Arid Environments 64: 77-96. Sobieraj JA, Elsenbeer H, Cameron G. 2004. Scale dependency in spatial patterns of saturated hydraulic conductivity. Catena 55: 49-77. Zeleke TB, Si BC. 2005. Scaling relationships between saturated hydraulic conductivity and soil physical properties. Soil Science Society of America Journal 69: 1691-1702. Zhao PP, Shao MA, Wang TJ. 2010. Spatial distributions of soil surface-layer saturated hydraulic conductivity and controlling factors on dam farmlands. Water Resources Management 24: 2247-2266. Han FP, Hu W, Zheng JY, Du F, Zhang XC. 2010. Estimating soil organic carbon storage and distribution in a catchment of Loess Plateau, China. Geoderma 154: 261-266. Burrough P. 1981. Fractal dimensions of landscapes and other environmental data. Nature 294: 240-242. Li JW, Richter DD, Mendoza A, Heine P. 2010. Effects of land-use history on soil spatial heterogeneity of macro- and trace elements in the Southern Piedmont USA. Geoderma 156: 60-73. Bartoli F, Burtin G, Royer JJ, Gury M, Gomendy V, Philippy R, Leviandier T, Gafrej R. 1995. Spatial variability of topsoil characteristics within one silty soil type-Effects on clay migration. Geoderma 68: 279-300. Wang YQ, Shao MA, Gao L. 2010. Spatial variability of soil particle size distribution and fractal features in water-wind erosion crisscross region on the Loess Plateau of China. Soil Science 175: 579-585. Shaver TM, Peterson GA, Ahuja LR, Westfall DG, Sherrod LA, Dunn G. 2002. Surface soil physical properties after twelve years of dryland no-till management. Soil Science Society of America Journal 66: 1296-1303. Wu J, Norvell WA, Welch RM. 2006. Kriging on highly skewed data for DTPA-extractable soil Zn with auxiliary information for pH and organic carbon. Geoderma 134: 187-199. Burke IC, Lauenroth WK, Riggle R, Brannen P, Madigan B, Beard S. 1999. Spatial variability of soil properties in the shortgrass steppe: The relative importance of topography, grazing, microsite, and plant species in controlling spatial patterns. Ecosystems 2: 422-438. Fu XL, Shao MA, Wei XR, Horton R. 2010. Soil organic carbon and total nitrogen as affected by vegetation types in Northern Loess Plateau of China. Geoderma 155: 31-35. Peng L, Wang JZ, Yu CZ. 1995. Nutrient losses in soils on Loess Plateau. Pedosphere 5: 83-92. Falleiros MC, Portezan O, Oliveira JCM, Bacchi OOS, Reichardt K. 1998. Spatial and temporal variability of soil hydraulic conductivity in relation to soil water distribution, using an exponential model. Soil and Tillage Research 45: 279-285. Mandelbrot BB, Van Ness JW. 1968. Fractional Brownian motions, fractional noises and applications. SIAM Review 10: 422-437. Zhao PP, Shao MA. 2010. Soil water spatial distribution in dam farmland on the Loess Plateau, China. Acta Agriculturae Scandinavica. Section B: Soil and Plant Science 60: 117-125. Krasa J, Dostal T, Vrana K, Plocek J. 2010. Predicting spatial patterns of sediment delivery and Impacts of land-use scenarios on sediment transport in Czech Catchments. Land Degradation and Development 21: 367-375. Buttle JM, House DA. 1997. Spatial variability of saturated hydraulic conductivity in shallow macroporous soils in a forested basin. Journal of Hydrology 203: 127-142. Hu W, Shao MA, Wang QJ, Reichardt K. 2009a. Time stability of soil water storage measured by neutron probe and the effects of calibration procedures in a small watershed. Catena 79: 72-82. Moran PA. 1950. Notes on continuous stochastic phenomena. Biometrika 37: 17-23. Lopez-Granados F, Jurado-Exposito M, Atenciano S, Garcia-Ferrer A, de la Orden MS, Garcia-Torres L. 2002. Spatial variability of agricultural soil parameters in southern Spain. Plant and Soil 246: 97-105. Tang KL. 2004. Soil and water conservation in China. Science Press: Beijing (in Chinese). Gallardo A, Paramá R. 2007. Spatial variability of soil elements in two plant communities of NW Spain. Geoderma 139: 199-208. Sobieraj JA, Elsenbeer H, Coelho RM, Newton B. 2002. Spatial variability of soil hydraulic conductivity along a tropical rainforest catena. Geoderma 108: 79-90. Wang YQ, Zhang XC, Huang CQ. 2009b. Spatial variability of soil total nitrogen and soil total phosphorus under different land uses in a small watershed on the Loess Plateau, China. Geoderma 150: 141-149. Weindorf DC, Zhu Y. 2010. Spatial variability of soil properties at Capulin Volcano, New Mexico, USA: Implications for sampling strategy. Pedosphere 20: 185-197. Hu W, Shao MG, Wang QJ, Fan J, Horton R. 2009b. Temporal changes of soil hydraulic properties under different land uses. Geoderma 149: 355-366. Iqbal J, Thomasson JA, Jenkins JN, Owens PR, Whisler FD. 2005. Spatial variability analysis of soil physical properties of alluvial soils. Soil Science Society of America Journal 69: 1338-1350. Sauer TJ, Clothier BE, Daniel TC. 1990. Surface measurements of the hydraulic properties of a tilled and untilled soil. Soil and Tillage Research 15: 359-369. Jia XH, Li XR, Zhang JG, Zhang ZS. 2009. Analysis of spatial variability of the fractal dimension of soil particle size in Ammopiptanthus mongolicus' desert habitat. Environmental Geology 58: 953-962. Nyamadzawo G, Shukla MK, Lal R. 2008. Spatial variability of total soil carbon and nitrogen stocks for some reclaimed minesoils of Southeastern Ohio. Land Degradation and Development 19: 275-288. Zhao Y, Peth S, Krummelbein J, Horn R, Wang ZY, Steffens M, Hoffmann C, Peng XH. 2007. Spatial variability of soil properties affected by grazing intensity in Inner Mongolia grassland. Ecological Modelling 205: 241-254. Price K, Jackson CR, Parker AJ. 2010. Variation of surficial soil hydraulic properties across land uses in the southern Blue Ridge Mountains, North Carolina, USA. Journal of Hydrology 383: 256-268. Wang HJ, Shi XZ, Yu DS, Weindorf DC, Huang B, Sun WX, Ritsema CJ, Milne E. 2009a. Factors determining soil nutrient distribution in a small-scaled watershed in the purple soil region of Sichuan Province, China. Soil and Tillage Research 105: 300-306. Mallants D, Mohanty BP, Vervoort A, Feyen J. 1997. Spatial analysis of saturated hydraulic conductivity in a soil with macropores. Soil Technology 10: 115-131. 2004; 169 1990; 15 2000; 45 1997; 41 2010; 383 1973 2009a; 79 1998; 45 2006; 134 2001; 41 2005; 69 2010; 60 2007; 137 1950; 37 2009; 58 2010; 21 2010; 20 2006; 64 2007; 139 2010; 24 2001 1997; 10 2009a; 105 1995; 68 2010; 156 2010; 154 1986 2010; 155 1985 2002; 108 1968; 10 2009b; 150 2009; 24 2009b; 149 2007; 205 2008; 19 2004 1999; 2 2005; 82 2003 1991 1995; 5 1983; 34 1999 2004; 55 1981; 294 1997; 203 1994; 163 2002; 246 2002; 66 1994; 58 2010; 175 e_1_2_6_51_1 e_1_2_6_53_1 Cliff AD (e_1_2_6_9_1) 1973 e_1_2_6_32_1 e_1_2_6_30_1 Nielsen DR (e_1_2_6_33_1) 1985 e_1_2_6_19_1 e_1_2_6_13_1 e_1_2_6_11_1 e_1_2_6_34_1 e_1_2_6_17_1 e_1_2_6_55_1 e_1_2_6_15_1 e_1_2_6_38_1 e_1_2_6_43_1 e_1_2_6_20_1 e_1_2_6_41_1 Lal R (e_1_2_6_25_1) 2001 e_1_2_6_5_1 e_1_2_6_7_1 e_1_2_6_24_1 e_1_2_6_49_1 e_1_2_6_3_1 e_1_2_6_22_1 e_1_2_6_28_1 e_1_2_6_26_1 e_1_2_6_47_1 e_1_2_6_52_1 e_1_2_6_54_1 e_1_2_6_10_1 e_1_2_6_31_1 e_1_2_6_50_1 Klute A (e_1_2_6_23_1) 1986 e_1_2_6_14_1 e_1_2_6_35_1 e_1_2_6_12_1 e_1_2_6_18_1 e_1_2_6_39_1 e_1_2_6_16_1 e_1_2_6_37_1 e_1_2_6_42_1 e_1_2_6_21_1 Peng L (e_1_2_6_36_1) 1995; 5 e_1_2_6_40_1 e_1_2_6_8_1 e_1_2_6_4_1 e_1_2_6_6_1 e_1_2_6_48_1 e_1_2_6_2_1 Tang KL (e_1_2_6_45_1) 2004 e_1_2_6_29_1 e_1_2_6_44_1 e_1_2_6_27_1 e_1_2_6_46_1 |
References_xml | – reference: Shukla MK, Slater BK, Lal R, Cepuder P. 2004. Spatial variability of soil properties and potential management classification of a chernozemic field in lower Austria. Soil Science 169: 852-860. – reference: Peng L, Wang JZ, Yu CZ. 1995. Nutrient losses in soils on Loess Plateau. Pedosphere 5: 83-92. – reference: Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal 58: 1501-1511. – reference: Tang KL. 2004. Soil and water conservation in China. Science Press: Beijing (in Chinese). – reference: Wang J, Fu BJ, Qiu Y, Chen LD, Wang Z. 2001. Geostatistical analysis of soil moisture variability on Da Nangou catchment of the loess plateau, China. Environmental Geology 41: 113-120. – reference: Jia XH, Li XR, Zhang JG, Zhang ZS. 2009. Analysis of spatial variability of the fractal dimension of soil particle size in Ammopiptanthus mongolicus' desert habitat. Environmental Geology 58: 953-962. – reference: Sobieraj JA, Elsenbeer H, Coelho RM, Newton B. 2002. Spatial variability of soil hydraulic conductivity along a tropical rainforest catena. Geoderma 108: 79-90. – reference: Mallants D, Mohanty BP, Vervoort A, Feyen J. 1997. Spatial analysis of saturated hydraulic conductivity in a soil with macropores. Soil Technology 10: 115-131. – reference: Bartoli F, Burtin G, Royer JJ, Gury M, Gomendy V, Philippy R, Leviandier T, Gafrej R. 1995. Spatial variability of topsoil characteristics within one silty soil type-Effects on clay migration. Geoderma 68: 279-300. – reference: Moran PA. 1950. Notes on continuous stochastic phenomena. Biometrika 37: 17-23. – reference: Zeleke TB, Si BC. 2005. Scaling relationships between saturated hydraulic conductivity and soil physical properties. 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Spatial variability of total soil carbon and nitrogen stocks for some reclaimed minesoils of Southeastern Ohio. Land Degradation and Development 19: 275-288. – reference: Weindorf DC, Zhu Y. 2010. Spatial variability of soil properties at Capulin Volcano, New Mexico, USA: Implications for sampling strategy. Pedosphere 20: 185-197. – reference: Li JW, Richter DD, Mendoza A, Heine P. 2010. Effects of land-use history on soil spatial heterogeneity of macro- and trace elements in the Southern Piedmont USA. Geoderma 156: 60-73. – reference: Shi H, Shao MG. 2000. Soil and water loss from the Loess Plateau in China. Journal of Arid Environments 45: 9-20. – reference: Wang YQ, Shao MA, Gao L. 2010. Spatial variability of soil particle size distribution and fractal features in water-wind erosion crisscross region on the Loess Plateau of China. Soil Science 175: 579-585. – reference: Gonzalez OJ, Zak DR. 1994. Geostatistical Analysis of Soil Properties in a Secondary Tropical Dry Forest, St-Lucia, West-Indies. Plant and Soil 163: 45-54. – reference: Burrough P. 1981. Fractal dimensions of landscapes and other environmental data. Nature 294: 240-242. – reference: Moreno F, Pelegrin F, Fernandez JE, Murillo JM. 1997. Soil physical properties, water depletion and crop development under traditional and conservation tillage in southern Spain. Soil and Tillage Research 41: 25-42. – reference: Fu XL, Shao MA, Wei XR, Horton R. 2010. Soil organic carbon and total nitrogen as affected by vegetation types in Northern Loess Plateau of China. Geoderma 155: 31-35. – reference: Wu J, Norvell WA, Welch RM. 2006. Kriging on highly skewed data for DTPA-extractable soil Zn with auxiliary information for pH and organic carbon. Geoderma 134: 187-199. – reference: Han FP, Hu W, Zheng JY, Du F, Zhang XC. 2010. Estimating soil organic carbon storage and distribution in a catchment of Loess Plateau, China. Geoderma 154: 261-266. – reference: Iqbal J, Thomasson JA, Jenkins JN, Owens PR, Whisler FD. 2005. Spatial variability analysis of soil physical properties of alluvial soils. Soil Science Society of America Journal 69: 1338-1350. – reference: Cliff AD, Ord JK. 1973. Spatial Autocorrelation. Pion: London. – reference: Li YY, Shao MA. 2006. Change of soil physical properties under long-term natural vegetation restoration in the Loess Plateau of China. Journal of Arid Environments 64: 77-96. – reference: Falleiros MC, Portezan O, Oliveira JCM, Bacchi OOS, Reichardt K. 1998. Spatial and temporal variability of soil hydraulic conductivity in relation to soil water distribution, using an exponential model. Soil and Tillage Research 45: 279-285. – reference: Burrough P. 1983. Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levels of soil variation. 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The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The... The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of... |
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SubjectTerms | Agricultural land Agricultural practices bulk density China Environmental management fractal dimensions geostatistic analysis Geostatistics Grasslands Land land degradation Land management Land use Loess Mathematical models ordinary kriging Physical properties Porosity PR China precision agriculture Precision farming saturated hydraulic conductivity semivariogram shrublands Soil (material) Soil physical properties Spatial analysis spatial structure Statistical analysis summer Topsoil water erosion Watersheds Wind erosion Woodlands |
Title | SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN A REGION OF THE LOESS PLATEAU OF PR CHINA SUBJECT TO WIND AND WATER EROSION |
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