Improve the prediction of soil bulk density by cokriging with predicted soil water content as auxiliary variable

PurposeSoil bulk density (SBD) is a key soil physical property affecting the transport of water and solutes, which is essential to estimating soil carbon and nutrient reserves. However, it is considered to be time consuming, labor intensive, and expensive to obtain in situ SBD data. Therefore, it is important to estimate SBD at an acceptable level of accuracy using auxiliary variables with limited field-measured data.Materials and methodsThe Heqing Dam agriculture area in Yunnan Province, Southwest China, was selected as the study area. Sampling points of 114 were obtained based on a uniform 1 km × 1 km grid methodology, which were broken into training data and test data using ArcGIS software. The training data (91 soil samples) were used for prediction and the test data (23 soil samples) were used for validation. Predicted soil water content (SWC) was estimated using kriging with high accuracy. The predicted SWC was used as auxiliary data to improve the prediction of SBD by cokriging. The correlation coefficient (r) between field-measured and predicted values, mean error (MAE), and root mean square error (RMSE) were used to validate the performance of the geostatistics.Results and discussionThe SBD was highly correlated with measured (r = −0.73, p < 0.01) and predicted SWC (r = −0.73, p < 0.01). The two parameters MAE and RMSE showed an improvement after introducing the predicted SWC. The MAE and RMSE decreased from 0.111 and 0.032 g cm−3 by kriging to 0.070 and 0.018 g cm−3 by cokriging with predicted SWC, respectively. The r value increased from 0.449 by kriging to 0.852 by cokriging. Compared with kriging, the application of cokriging with predicted SWC resulted in a relative improvement of 45.5 %.ConclusionsThis study demonstrates that predicted SWC used as auxiliary data can improve the prediction of SBD. Therefore, when the predicted data have been demonstrated to be of high accuracy and are highly correlated with the dependent variable, they have the potential to be a good source of auxiliary data for cokriging.

[1]  A. Warrick,et al.  Estimating Soil Water Content Using Cokriging1 , 1987 .

[2]  Shao Ming’an,et al.  Effect of Bulk Density on Soil Saturated Water Movement Parameters , 2006 .

[3]  S. Yates,et al.  Estimates of soil nitrate distributions using cokriging with pseudo-crossvariograms , 1999 .

[4]  A. Mouazen,et al.  Development of a methodology for in situ assessment of topsoil dry bulk density , 2013 .

[5]  C. Cantero‐Martínez,et al.  Root Growth of Barley as Affected by Tillage Systems and Nitrogen Fertilization in a Semiarid Mediterranean Agroecosystem , 2011 .

[6]  Z. Shi,et al.  Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods , 2007 .

[7]  A. Konopka,et al.  FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS , 1994 .

[8]  Elaine Cristina Cardoso Fidalgo,et al.  PEDOTRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY FROM EXISTING SOIL SURVEY REPORTS IN BRAZIL , 2007 .

[9]  Spatial prediction of soil water content in karst area using prime terrain variables as auxiliary cokriging variable , 2014, Environmental Earth Sciences.

[10]  Sacha J. Mooney,et al.  Exploring the interacting effect of soil texture and bulk density on root system development in tomato (Solanum lycopersicum L.) , 2013 .

[11]  S. Archer,et al.  When bulk density methods matter: Implications for estimating soil organic carbon pools in rocky soils , 2012 .

[12]  C. Ritz,et al.  Soil bulk density pedotransfer functions of the humus horizon in arable soils , 2011 .

[13]  N. Maxted,et al.  Population genetic structure in Lens taxa revealed by isozyme and RAPD analysis , 1998, Genetic Resources and Crop Evolution.

[14]  Jeffrey G. White,et al.  Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implications for site-specific management , 2007 .

[15]  A. J. Koolen,et al.  FUTURE RESEARCH NEEDS IN SOIL COMPACTION , 1992 .

[16]  Rainer Duttmann,et al.  Prediction of soil property distribution in paddy soil landscapes using terrain data and satellite information as indicators , 2008 .

[17]  R. Weil,et al.  Root growth and yield of maize as affected by soil compaction and cover crops , 2011 .

[18]  Chuanrong Zhang,et al.  Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging , 2013 .

[19]  S. DeGloria,et al.  Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data , 2009 .

[20]  Jürgen Schmidt,et al.  The effect of soil bulk density on rill erosion - results of experimental studies , 2013 .

[21]  Tammo S. Steenhuis,et al.  Evaluation of spatial interpolation methods for groundwater level in an arid inland oasis, northwest China , 2014, Environmental Earth Sciences.

[22]  M. Shao,et al.  Soil shrinkage and hydrostructural characteristics of three swelling soils in Shaanxi, China , 2011 .

[23]  P. Lammers,et al.  Evaluating model-based relationship of cone index, soil water content and bulk density using dual-sensor penetrometer data , 2014 .

[24]  Robert J. Wright,et al.  Soil spatial variability relationships in a steeply sloping acid soil environment , 1996 .

[25]  Hongsong Chen,et al.  Spatial Variability of Surface Soil Moisture in a Depression Area of Karst Region , 2011 .

[26]  M. Meirvenne,et al.  Predictive Quality of Pedotransfer Functions for Estimating Bulk Density of Forest Soils , 2005 .

[27]  A. Castrignanò,et al.  ESTIMATING SOIL WATER CONTENT USING COKRIGING , 1990 .

[28]  S. Vieira,et al.  Geostatistical analysis of heavy metals in a one-hectare plot under natural vegetation in a serpentine area , 2001 .

[29]  Nidal Abu-Hamdeh,et al.  Compaction and subsoiling effects on corn growth and soil bulk density , 2003 .

[30]  B. Jenkins,et al.  Development, Construction, and Field Evaluation of a Soil Compaction Profile Sensor , 2007 .

[31]  Horng-Yuh Guo,et al.  Geostatistical Analysis of Soil Properties of Mid-West Taiwan Soils , 1997 .

[32]  Yun-qiang Wang,et al.  Prediction of Bulk Density of Soils in the Loess Plateau Region of China , 2014, Surveys in Geophysics.

[33]  A. W. Warrick,et al.  13 – Spatial Variability of Soil Physical Properties in the Field , 1980 .

[34]  J. Hummel,et al.  Spatial Analysis of Soil Fertility for Site-Specific Crop Management , 1994 .

[35]  Abdul Mounem Mouazen,et al.  Development of on-line measurement system of bulk density based on on-line measured draught, depth and soil moisture content , 2006 .

[36]  Daniel Hillel,et al.  Applications of soil physics , 1980 .

[37]  M. Bernoux,et al.  Pedotransfer functions to estimate soil bulk density for Northern Africa: Tunisia case , 2012 .

[38]  T. Kosaki,et al.  Spatial variability of nitrous oxide emissions and their soil-related determining factors in an agricultural field. , 2003, Journal of environmental quality.