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Pedotransfer Functions for Predicting Soil Hydraulic Properties of the Chinese Loess Plateau

Wang, Yunqiang1,2; Shao, Ming’an1; Liu, Zhipeng2,3

doi: 10.1097/SS.0b013e318255a449
Technical Article

Abstract: Soil hydraulic properties play an important role in modelingwater and solute movement within the vadose zone of soils. Direct measurement of hydraulic parameters at a wide range of scales involves considerable time, labor, and money. Pedotransfer functions (PTF) may provide an alternative way of estimating these parameters indirectly from easy-to-measure soil properties. The Loess Plateau of China lacks large databases of hydraulic parameters and also the PTF that could determine them accurately enough for scientists and policy makers to address many of the region’s related problems, such as severe soil erosion. In this study, new PTF for saturated hydraulic conductivity (Ks), field capacity, and saturated soil-water content were developed. Multiple linear regression was used to analyze 252 data sets of the hydraulic and basic soil properties, as well as altitude, to derive the PTF. A further 130 data sets were used for validation. The predictive capabilities of the PTF were the best for saturated soil-water content (Radj2 = 0.78) and least for log Ks (Radj2 = 0.36). Bulk density, soil organic carbon, and soil particle composition were identified as significant input variables for the PTF. The inclusion of a topographic factor (altitude) significantly improved the predictive capability of the PTF for log Ks. Compared with established PTF, the PTF developed in this study predicted the hydraulic parameters more accurately as indicated by higher R2 and lower RMSE values when predicted, and measured parameter values were compared, and the greatest improvement was obtained for log Ks. The new PTF are the first set of PTF based on data from the Loess Plateau. Their better performance makes them applicable for a variety of purposes in the Plateau region and possibly in other loess regions around the world.

1Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.

2State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences & Ministry of Water Resources, Yangling, China.

3Graduate University of Chinese Academy of Sciences, Beijing, China.

Address for correspondence: Dr. Ming’an Shao, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. E-mail: shaoma@igsnrr.ac.cn

Financial Disclosures/Conflicts of Interest: This research was supported by the National Natural Science Foundation of China (no. 41071156 and no. 41101204), the Innovation Team Program of Chinese Academy of Sciences, China Postdoctoral Science Foundation Funded Project, and State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau (no. 10501-278).

Received September 21, 2011.

Accepted for publication March 6, 2012.

© 2012 Lippincott Williams & Wilkins, Inc.