Submitted to: Bridging Scales in Soil Physics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 10, 2002
Publication Date: March 2, 2003
Citation: Timlin, D.J., Pachepsky, Y.A., Walthall, C.L. 2003. A mix of scales: topographic information, point samples and yield maps. Bridging Scales in Soil Physics. p. 227-241. Interpretive Summary: Knowledge of soil water holding capacity provides agricultural managers important information on the potential productivity of their soil and irrigation requirements. Soil water holding capacity can be expensive and time consuming to measure so usually only a small number of samples are taken with large distances between samples. Larger numbers of closer spaced samples can provide important information on the spatial variability of water holding capacity which is useful in precision agriculture applications. Topographic information such as elevation, slope and soil surface curvature are easy to measure and are often strongly related to soil water holding capacity. The goal of this study was to investigate the optimum spacing for elevation measurements in order to use topographic information to interpolate and map a small number of water holding capacity measurements. We tested spatial autoregression as a statistical method to do the interpolation. The 25- by 25-m measurement distances for elevation gave the best results in terms of matching measured and interpolated values of water holding capacity. At closer measurement distances, there was too much noise and at further measurement distances there was too much smoothing of the topographic variables.
Technical Abstract: Data on soil water holding capacity and its distribution in the landscape are necessary for agricultural land management, especially precision agriculture. Because soil water holding capacities have generally been sampled manually they are often discontinuous and represent localized sites and small scales. Large scale landscape features such as slope and curvature are often good predictors of soil texture and related soil hydraulic properties and can be used to tie together small scale, discontinuous measures of soil water holding capacity. The purpose of this study was to investigate the effect of scale on the relationships between soil topographic variables slope and curvature, and water holding capacity. The experimental site was a 6 ha corn field located on the USDA Agricultural Research Service Beltsville Agricultural Research Center in Beltsville, Maryland. We laid out 30-meter long transects at four landscape positions, each plot was the same size as a yield monitor cell. We also collected duplicate soil cores for water retention and soil texture from each plot. Elevation slope, profile curvature and tangential curvature were calculated from elevations obtained from a topographic survey of the site. Spatial auto-regression was used to develop regression equations that predicted soil water holding capacity as a function of topographic parameters. Slope and tangential curvature were found to be significant predictors of water holding capacity in the upper 10 cm of soil. Spatial autocorrelation explained 60 to 70% of the variance in the relationship between landscape parameters and WHC. The 25- by 25-m scale of landscape parameters gave the best fit. At finer scales, there was too much noise and at more coarse scales too much smoothing of the terrain attributes.