Moisture characteristics and their point pedotransfer functions for coarse‐textured tropical soils differing in structural degradation status

Abstract

The effect of soil structure on hydraulic pedotransfer functions (PTFs) in tropical soils with similar mineralogy and texture has not been well documented. Structurally contrasting soils from representative locations in southeastern Nigeria were analyzed for moisture retention at 0, 6, 10, 33, 100, 300 and 1500 kPa among other properties. They were grouped by depth (topsoils or subsoils) and also by their structural degradation status into low‐ and high‐stability soils, corresponding to organic matter (OM):[silt + clay] of <7.5 and >7.5%, respectively. Soil depth and structural stability influenced the soil moisture characteristic curves. The data were fitted to three tropical point PTFs, but none of them proved appropriate for predicting moisture retention in the soils. We therefore derived new ones using multiple linear stepwise regressions before and after the dataset grouping and compared their performances by means of cross‐validation. Moisture retention in the soils (sand content, 73.2–93.8%) could not be calibrated from texture and OM concentration alone, until when bulk density, total porosity and microporosity were included among the regressors. Microporosity's role was particularly outstanding at all matric potentials but the 1500 kPa. The ensuing PTFs represent a good fit for the soil moisture retention data. The two grouping strategies resulted in lower SE of the estimates in some cases, but this did not enhance the performances of the concerned PTFs. At the 1500 kPa, however, the PTF incorporating all datasets performed better than separate PTFs for topsoils/subsoils but worse than the one for high‐stability soils. Information on soil structure can therefore benefit PTF derivation for kaolinite‐dominated, coarse‐textured tropical soils at all the matric potentials considered. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluation and Development of Pedotransfer Functions for Estimating Soil Water Holding Capacity in the Tropics: The Case Of Sokoine University of Agriculture Farm in Morogoro, Tanzania

“…Soil water holding capacity is one of the key parameters important in soil and water management practices for sustainable and improved agricultural production (Obalum and Obi, 2012). The parameter is important for both modeling the hydrology of segments of the landscape and for evaluating field soil water regimes in relation to the potential of soil for various uses (Wösten, et al, 2013).…”

“…Direct measurements of soil water retention capacity are expensive, time consuming and labour intensive (Obalum & Obi, 2012;Wösten, et al, 2013). However, the parameters can alternatively be estimated using available soil data such as particle size distribution, organic matter content, bulk density and soil porosity (Schaap et al, 1999;Young et al, 1999).…”

Pedotransfer functions to predict water retention for soils of the humid tropics: a review

“…Chakraborty et al (2011) developed PTFs from a wide textural range of Indian soils for four points of the SWRC, namely -33, -100, -500, and -1500 kPa. Recently, Obalum & Obi (2012) proposed point-based PTFs for kaolinitic and coarse-textured tropical soils from southeastern Nigeria. Santos et al (2013) generated and validated PTFs to predict gravimetric water content at -33 and -1500 kPa for different soil classes from the central-south portion of the State of Rio Grande do Sul in Brazil.…”

“…equivalent (Tomasella et al, 2003), micro-porosity, and total porosity (Obalum & Obi, 2012) are rarely found in tropical soil databases and, therefore, have been rarely used as predictors in the development of tropical PTFs. Other predictors related to soil structure (Pachepsky et al, 2006) and topography (Sharma et al, 2006) have been suggested to improve the predictive ability of PTFs, but they have not yet been used for tropical PTFs.…”

Prediction of Soil Moisture-Holding Capacity with Support Vector Machines in Dry Subhumid Tropics

“…Utility of PTFs necessitates validation or development of new PTFs for improved modelling outputs [9,12]. Studies to this end for tropical soils in sub-Saharan Africa include Wosten et al [7], Botula et al [11], Young et al [15], Mdemu and Mulengera [16], Mugabe [17], Obalum and Obi [18], and Mdemu [19]. All these studies have drawbacks including evaluation on small soil datasets or compiled soil databases or frequent application of the multiple linear regression method.…”