Modeling cation exchange capacity and soil water holding capacity from basic soil properties

Abstract

Cation exchange capacity (CEC) is a good indicator of soil productivity and is useful for making recommendations of phosphorus, potassium, and magnesium for soils of different textures. Soil water holding capacity (SWHC) defines the ability of a soil to hold water at a particular time of the season. This research predicted CEC and SWHC of soils using pedotransfer models developed (using Minitab 17 statistical software) from basic soil properties (Sand(S), Clay(C), soil pH, soil organic carbon (SOC)) and verify the model by comparing the relationship between measured and estimated (obtained by PTFs) CEC and SWHC in the Forest Vegetative Zone of Nigeria. For this study, a total of 105 sampling points in 35 different locations were sampled in the study areas. Three sampling points were randomly selected per location and three undisturbed samples were collected at each sampling point. The results showed success in predicting CEC and SWHC from basic soil properties. In this study, five linear regression models for predicting soil CEC and seven linear regression models for predicting SWHC from some soil physical and chemical properties were suggested. Model 5 [CEC =-13.93+2.645 pH +0.0446 C (%)+2.267 SOC (%)] was best for predicting CEC while model 12 [SWHC (%)=36.0-0.215 S (%)+0.113 C (%)+10.36 SOC (%)] is the most acceptable model for predicting SWHC.

Assessment of geotechnical and physico-chemical properties of age-long greywater-contaminated soils in basement complex areas, southwest Nigeria

“…The correlation between % sand and % clay agrees with the results of Coffin and Lauenroth (1992), Kaiser et al (1992), and Pan et al (2012). Negative correlation between % sand and MC is in line with similar results by Senjobi and Ogunkunle (2011) and Olorunfemi et al (2016). The strong negative correlation between % sand and ALs agrees with similar results by Deng et al (2017) and Igwe et al (2013), while correlation between % sand and PI (− 1.000**) is in line with similar result by Roy and Bhalla (2017) who reported that increase in sand content results in decreased PI.…”

“…This buttressed the fact that the higher the fine particles (clay), the higher the MC but lower the DD (Dave et al 2017). However, negative correlation found between CEC and % clay is in contrast with positive correlation between % clay and CEC found earlier by Lambooy (1984) and Olorunfemi et al (2016). This may be due to low MC and high sand content of analysed soil samples.…”

Consecutive 2-year data analysis to assess the soil quality and ecological risk of heavy metals in Tobacco field: a case study in Northern Bangladesh

“…Available sulfur was determined by the turbidimetric method [21]. Exchangeable potassium (K + ) and sodium (Na + ) were determined by flame photometry [22] while exchangeable magnesium (Mg 2+ ) and calcium (Ca 2+ ) were determined by atomic absorption spectrophotometer [23]. Cation exchange capacity (CEC) was measured by ammonium acetate (NH 4 OAc at pH 7.0) method [24].…”

Comparison of Cation Exchange Capacity Estimated from Vis–NIR Spectral Reflectance Data and a Pedotransfer Function

“…The consistency of PTFs is mainly dependent on the number of samples and range of the input parameters (Chirico et al, 2010). Pedotransfer functions for CEC are often developed from a combination of different properties (e.g., clay content, organic C [OC] content, and hygroscopic water content) (Arthur, 2017; Krogh et al, 2000; McBratney et al, 2002; Olorunfemi et al, 2016; Torrent et al, 2015). For instance, Krogh et al (2000) showed that a PTF based on clay and OM contents dominated by illite reliably explained 90% of the variability in CEC for Danish soils.…”