Soil Science Society of America Journal Soil Sci. Soc. Am. J. doi:10.2136/sssaj2014.05.0218 Received 30 May 2014. *Corresponding author (tsren@cau.edu.cn).. © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. An Empirical Model for Estimating Soil Thermal Conductivity from Texture, Water Content, and Bulk Density Soil Physics Soil thermal conductivity (l) models are needed frequently in studying coupled heat and water transfer in soils. Several models are available, but some are complicated and some produce relatively large errors. In this study, we developed a simple model for estimating l from soil texture, bulk density (r b ), and water content (q). Three parameters, a, b, and l dry , are included in the model, where l dry is determined by r b and a and b are shape factors estimated from soil texture and r b . Empirical relations were developed for a and b by itting the model to heat-pulse (HP) measure- ments of l(q) on seven soils of various textures. The model performance was evaluated with independent l(q) data from independent HP mea- surements and literature values. The results show that the model is able to express the l(q) curves from oven dry to saturation at ixed r b values. When r b is varied, the estimated l data agree well with measured values. The root mean square errors are <0.15 W m −1 K −1 , and the bias is within 0.10 W m −1 K −1 . The new model has the potential for use in studying heat movement in soils of varying texture, bulk density, and water content and can be incorporated into numerical algorithms for describing coupled heat and mass transfer processes. Abbreviations: HP, heat pulse; PSD, particle size distribution; RMSE, root mean square error. S oil thermal conductivity (l), a measure of the ability of a soil to conduct heat, is needed frequently in soil science (Horton and Ochsner, 2011). he magnitude of l depends largely on soil texture, mineral composition, water content (q), and bulk density (r b ) (de Vries, 1963; Campbell, 1985). At similar q and r b values, a sandy soil usually has a higher l value than a clay soil. A soil with higher quartz content (f q ) usually has greater l because quartz has a l value two times that of most other soil minerals (Campbell, 1985). Larger r b , or smaller porosity, leads to greater l, as more solid matter per unit volume results in better contacts between soil particles (Farouki, 1986). he arrangement of soil particles and soil microstructure also inluences l signiicantly (Kohout et al., 2004; Ju et al., 2011). Under ield conditions, soil l is strongly afected by q, which changes dy- namically with time and depth. Several semi-theoretical and empirical models have been developed to estimate l from q or the degree of saturation (S r ). De Vries (1963) presented a physically based model that treated soil as a mixture of ellipsoidal particles in the continuous media of air and water. his model has been used widely for modeling soil l with considerable accuracy (Wierenga et al., 1969; Campbell et al., 1994). Farouki (1986) indicated that the major er- Yili Lu Dep. of Soil and Water Sciences China Agricultural Univ. Beijing 100193 China Sen Lu Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China Robert Horton Dep. of Agronomy Iowa State Univ. Ames, IA 50011 Tusheng Ren* Dep. of Soil and Water Sciences China Agricultural Univ. Beijing 100193 China Published September 29, 2014