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Journal of Arid Land
Journal of Arid Land  2019, Vol. 11 Issue (2): 228-240    DOI: 10.1007/s40333-019-0051-4
Orginal Article     
Spatial distribution of water-activesoil layer along the south-north transect in the Loess Plateau of China
Chunlei ZHAO1,2, Ming'an SHAO1,2,3, Xiaoxu JIA1,2, Laiming HUANG1,2, Yuanjun ZHU3,4,*()
1 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
3State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China;
4 College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China;
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Abstract  

Soil water is an important compositionof water recyclein the soil-plant-atmosphere continuum. However, intense water exchange between soil-plant and soil-atmosphereinterfacesonly occurs in a certain layer of the soil profile. For deep insight into wateractive layer (WAL, defined as the soil layer with a coefficient of variation in soil water content>10% in a given time domain)inthe Loess Plateau of China,we measuredsoil water content (SWC)in the 0.0-5.0 m soil profile from 86 sampling sites along an approximately 860-kmlong south-north transect during the period 2013-2016. Moreover, a datasetcontainedfourclimatic factors (mean annual precipitation, mean annual evaporation, annual mean temperature and mean annual dryness index) andfivelocalfactors (altitude, slope gradient, land use, clay content and soil organic carbon)ofeachsampling sitewasobtained.Inthisstudy, three WAL indices (WAL-T (the thickness of WAL), WAL-CV (the mean coefficient of variation in SWC within WAL) and WAL-SWC (themean SWC within WAL)) were used to evaluate the characteristics of WAL. The results showed that with increasing latitude, WAL-T and WAL-CV increased firstly and then decreased. WAL-SWC showed an oppositedistribution pattern along the south-north transect compared with WAL-T and WAL-CV. Average WAL-T of the transect was 2.0 m, suggesting intense soil water exchange in the0.0-2.0 m soil layer in the study area. Soil water exchange was deeper and more intense in the middle region than in the southern and northern regions, with the values of WAL-CV and WAL-Tbeing27.3% and 4.3 m in the middle region, respectively. Both climatic (10.1%) and local (4.9%) factors influenced the indices of WAL, with climatic factors having a more dominant effect.Compared with multiple linear regressions, pedotransfer functions (PTFs) from artificial neural network can better estimate theWAL indices. PTFs developed byartificial neural network respectivelyexplained 86%, 81% and 64% of the total variations in WAL-T, WAL-SWC andWAL-CV. Knowledge of WAL iscrucial for understanding the regional water budgetandevaluatingthe stable soil water reserve, regional water characteristics and eco-hydrological processes in the Loess Plateau of China.

Key words： wateractivelayer      soil water content      redundancy analysis      pedotransfer function      artificial neural network      Loess Plateau     
Received: 11 December 2017      Published: 10 April 2019
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Chunlei ZHAO
Ming'an SHAO
Xiaoxu JIA
Laiming HUANG
Yuanjun ZHU
Cite this article:

Chunlei ZHAO, Ming'an SHAO, Xiaoxu JIA, Laiming HUANG, Yuanjun ZHU. Spatial distribution of water-activesoil layer along the south-north transect in the Loess Plateau of China. Journal of Arid Land, 2019, 11(2): 228-240.

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http://jal.xjegi.com/10.1007/s40333-019-0051-4     OR     http://jal.xjegi.com/Y2019/V11/I2/228

[1] Biswas A, Si B C.2011. Application of continuous wavelet transform in examining soil spatial variation: A review. Mathematical Geosciences, 43(3): 379-396.
[2] Brocca L, Melone F, Moramarco T, et al.2010. Spatial-temporal variability of soil moisture and its estimation across scales. Water Resources Research, 46(2): W02516.
[3] Chen H, Shao MA, Li Y Y.2008. Soil desiccation in the Loess Plateau of China. Geoderma, 143(1-2): 91-100.
[4] Choi M, Jacobs J M.2007. Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints. Advances in Water Resources, 30(4): 883-896.
[5] Crave A, Gascuel-Odoux C.1997. The influence of topography on time and space distribution of soil surface water content. Hydrological Processes, 11(2): 203-210.
[6] Gao L, Shao M A, Peng X H, et al.2015. Spatio-temporal variability and temporal stability of water contents distributed within soil profiles at a hillslope scale. CATENA, 132: 29-36.
[7] Gasch C K, Brown D J, Campbell C S, et al.2017. A field-sensor network data set for monitoring and modeling the spatial and temporal variation of soil water content in a dryland agricultural field. Water Resources Research, 53(12): 10878-10887.
[8] He X B, Li Z B, Hao M D, et al.2003. Down-scale analysis for water scarcity in response to soil-water conservation on Loess Plateau of China. Agriculture, Ecosystems & Environment, 94(3): 355-361.
[9] Heathman G C, Larose M, Cosh M H, et al.2009. Surface and profile soil moisture spatio-temporal analysis during an excessive rainfall period in the Southern Great Plains, USA. CATENA, 78(2): 159-169.
[10] Hu W, Shao M, Han F P, et al.2010. Watershed scale temporal stability of soil water content. Geoderma, 158(3-4): 181-198.
[11] Hu W, Tallon L K, Si B C.2012. Evaluation of time stability indices for soil water storage upscaling. Journal of Hydrology, 475: 229-241.
[12] Hupet F, Vanclooster M.2002. Intraseasonal dynamics of soil moisture variability within a small agricultural maize cropped field. Journal of Hydrology, 261(1-4): 86-101.
[13] Jia X X, Shao M A, Wei X R, et al.2013. Hillslope scale temporal stability of soil water storage in diverse soil layers. Journal of Hydrology, 498: 254-264.
[14] Jia X X, Shao M A, Zhang C, et al.2015. Regional temporal persistence of dried soil layer along south-north transect of the Loess Plateau, China. Journal of Hydrology, 528: 152-160.
[15] Jia X X, Shao M A, Zhu Y J, et al.2017. Soil moisture decline due to afforestation across the Loess Plateau, China. Journal of Hydrology, 546: 113-122.
[16] Jia X X, Shao M A, Yu D X, et al.2019. Spatial variations in soil-water carrying capacity of three typical revegetation species on the Loess Plateau, China. Agriculture, Ecosystems & Environment, 273: 25-35.
[17] Jia Y H, Shao M A.2014. Dynamics of deep soil moisture in response to vegetational restoration on the Loess Plateau of China. Journal of Hydrology, 519: 523-531.
[18] Li Y S.1983. The properties of water cycle in soil and their effect on water cycle for land in the Loess Plateau. Acta Ecologica Sinica, 3: 91-101. (in Chinese)
[19] Minasny B, Mcbratney A B.2002. Uncertainty analysis for pedotransfer functions. European Journal of Soil Science, 53(3): 417-429.
[20] Mohanty B P, Famiglietti J S, Skaggs T H.2000. Evolution of soil moisture spatial structure in a mixed vegetation pixel during the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Water Resources Research, 36(12): 3675-3686.
[21] Motaghian H R, Mohammadi J.2011. Spatial estimation of saturated hydraulic conductivity from terrain attributes using regression, kriging, and artificial neural networks. Pedosphere, 21(2): 170-177.
[22] Nyberg L.1996. Spatial variability of soil water content in the covered catchment at Gårdsjön, Sweden. Hydrological Processes, 10(1): 89-103.
[23] Patil N G, Chaturvedi A.2012. Estimation of bulk density of waterlogged soils from basic properties. Archives of Agronomy and Soil Science, 58(5): 499-509.
[24] Starr G C.2005. Assessing temporal stability and spatial variability of soil water patterns with implications for precision water management. Agricultural Water Management, 72(3): 223-243.
[25] Wang J, Ge Y, Heuvelink G B M, et al.2015. Upscaling in situ soil moisture observations to pixel averages with spatio-temporal geostatistics. Remote Sensing, 7(9): 11372-11388.
[26] Wang S, Fu B J, Piao S L, et al.2016. Reduced sediment transport in the Yellow River due to anthropogenic changes. Nature Geoscience, 9: 38-41.
[27] Wang X C, Li J, Tahir M N, et al.2012. Validation of the EPIC model and its utilization to research the sustainable recovery of soil desiccation after alfalfa (Medicago sativa L.) by grain crop rotation system in the semi-humid region of the Loess Plateau. Agriculture, Ecosystems & Environment, 161: 152-160.
[28] Wang Y Q, Shao M A, Zhu Y J, et al.2011. Impacts of land use and plant characteristics on dried soil layers in different climatic regions on the Loess Plateau of China. Agricultural and Forest Meteorology, 151(4): 437-448.
[29] Wang Y Q, Shao M A, Liu Z P.2012. Pedotransfer functions for predicting soil hydraulic properties of the Chinese Loess Plateau. Soil Science, 177(7): 424-432.
[30] Wang Y Q, Shao M A, Liu Z P, et al.2014. Prediction of bulk density of soils in the Loess Plateau region of China. Surveys in Geophysics, 35(2): 395-413.
[31] Xiong W, Li J, Chen Y Y, et al.2016. Determinants of community structure of zooplankton in heavily polluted river ecosystems. Scientific Reports, 6: 22043.
[32] Xiong Y W, Wallach R, Furman A.2011. Modeling multidimensional fiow in wettable and water-repellent soils using artificial neural networks. Journal of Hydrology, 410(1-2): 92-104.
[33] Yang Q Y, Zhang B P, Zheng D.1988. On the boundary of the Loess Plateau. Journal of Natural Resources, 3(1): 9-15. (in Chinese)
[34] Zhao C L, Shao M A, Jia X X, et al.2016. Particle size distribution of soils (0-500 cm) in the Loess Plateau, China. Geoderma Regional, 7(3): 251-258.
[35] Zhao C L, Jia X X, Zhu Y J, et al.2017a. Long-term temporal variations of soil water content under different vegetation types in the Loess Plateau, China. CATENA, 158: 55-62.
[36] Zhao C L, Shao M A, Jia X X, et al.2017b. Estimation of spatial variability of soil water storage along the south-north transect on China's Loess Plateau using the state-space approach. Journal of Soils and Sediments, 17(4): 1009-1020.
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