Pedo-transfer function for saturated hydraulic conductivity of lowland paddy soils |
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| Authors: | W Aimrun M S M Amin |
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| Institution: | (1) Smart Farming Technology Laboratory, Institute of Advanced Technology, 43400 Serdang, Selangor, Malaysia;(2) Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia |
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| Abstract: | In paddy field, soil saturated hydraulic conductivity (K
s) plays as an important component in the calculation of irrigation requirement of the water balance equation and also for
irrigation efficiency. Several laboratory and field methods can be used to determine K
s. Laboratory and field determinations are usually time consuming, expensive and labour intensive. Pedo-transfer functions
(PTF) serve to translate the basic information found in the soil survey into a form useful for broader applications through
empirical regression of functional relationships, such as simulation modelling. Since PTFs have not been applied to paddy
soils in the study area, a lot of field measurements will require high labour input to determine K
s hence high cost. This study attempts to seek a simplified method for determining K
s values based on common existing soil properties through PTF technique. Soil samples (n = 408 samples) were collected randomly depending on the soil series within the 2,300 ha Sawah Sempadan rice cultivation area.
Both field work and laboratory work were carried out. The samples were then analysed for the following properties: dry bulk
density (D
b), soil particle percentage (Sand-S, Silt-Si and Clay-C), organic matter (OM) and geometric mean diameter (GMD). The measured
K
s values were obtained by using the falling head method. The parameters were then used as inputs for developing a K
s model by regression analysis using Statistical Analysis System (SAS) package. Stepwise regression analysis was applied to
determine the best fit model based on R
2 and significant level. The results of the study showed that there is a high spatial variability of the saturated hydraulic
conductivity in the paddy area. The best regression model for estimating K
s was based on C, D
b, OM and GMD with the dependent variable (K
s) in a form of natural logarithm. The model inputs introduced by stepwise regression are commonly available therefore, this
model is useful to replace the conventional method. |
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| Keywords: | Falling head method Water balance equation Irrigation requirement Spatial variability Stepwise regression analysis |
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