Monitoring and prediction of soil moisture spatial–temporal variations from a hydropedological perspective: a review
Qing Zhu A D , Kaihua Liao A , Yan Xu B , Guishan Yang A , Shaohua Wu C and Shenglu Zhou C
+ Author Affiliations
- Author Affiliations
A State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
B Department of Municipal Engineering, School of Civil Engineering, Southeast University, Nanjing 210096, China.
C School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China.
D Corresponding author. Email: qzhu@niglas.ac.cn
Soil Research 50(8) 625-637 https://doi.org/10.1071/SR12228
Submitted: 16 August 2012 Accepted: 30 December 2012 Published: 5 February 2013
Abstract
Accurate prediction of soil moisture spatial–temporal variations remains critical in agronomic, hydrological, pedological, and environmental studies. Traditional approaches of soil moisture monitoring and prediction have limitations of being time-consuming, labour-intensive, and costly for direct field observation; and having low spatial resolution for remote sensing, and inconsistent accuracy and reliability for landscape feature (e.g. topography, land use, vegetation) modelling. Innovative and effective approaches for accurate soil moisture simulation are needed. Pedological properties, including soil structure, particle size distribution, porosity, horizon, redox feature, and organic matter content, have been accepted as important factors controlling soil moisture and can be potentially used in soil moisture prediction. However, pedological properties mostly lack quantification (e.g. redox feature, horizon, soil structure), and soil sampling and analysis are time-consuming and costly, especially at large spatial scale. These limitations have restricted the utilisation of pedological information to predict soil moisture spatial–temporal variations at different spatial scales. To overcome these difficulties, new tools including geophysical tools and computed tomography, and new methods including mining soil survey information and integrating pedological information with landscape features and modelling, are proposed in this paper.
Additional keywords: geophysics, hydropedology, soil hydrology, soil water content.
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