RT - Journal Article T1 - Evaluation of Hydraulic Conductivity at Inflection Point of Soil Moisture Characteristic Curve as a Matching Point for some Soil Unsaturated Hydraulic Conductivity Models JF - JSTNAR YR - 2012 JO - JSTNAR VO - 16 IS - 59 UR - http://jstnar.iut.ac.ir/article-1-2206-en.html SP - 169 EP - 182 K1 - Unsaturated hydraulic conductivity K1 - Soil moisture characteristic curve K1 - Inflection point of characteristic curve K1 - Water diffusivity AB - Direct measurement of soil unsaturated hydraulic conductivity (K(h) or K(θ)) is difficult and time-consuming, and often in many applied models, predicting hydraulic conductivity is carried out according to measurements of soil retention curve and saturated hydraulic conductivity (Ks). However, using KS as a matching point in many procedures may result in over-estimation of unsaturated hydraulic conductivity in dry regions. Therefore, the unsaturated hydraulic conductivity at inflection point of retention curve (Ki) and Ks was used as a matching point to predict K(h). For measurement of K(h), 30 soil samples were collected based on variety of soil texture (8 texture classes from sandy to clay) and other chemical and physical properties. In addition to Ks, K(θ) values of undisturbed samples were measured using multi-step outflow method at matric suctions of 0.1, 0.2, 0.3, 0.5 0.7, 1 bar and inflection point of retention curve by using hanging water column and pressure plate. Then, the measured K(h), and water diffusivity (D(θ)) values were compared to the predicted values of van Genuchten and Brooks and Corey models (with Mualem and Burdine constraint). The results showed that for 80% of the samples, the van Genuchten–Mualem model with Ki was the best model for predicting K(h) (i.e. using Ki as a matching point in the van Genuchten–Mualem model resulted in best fitting to measured data). Also, in 6.7 % of samples (two sandy clay samples), Brooks and Corey-Mualem model with Ki and in 13.3 % soil samples (2 silty clay and 2 silty clay loam samples), van Genouchten–Mualem model had a best fitting to K(h) measured data. Furthermore, in 20 % samples (4 clay loam, and 2 silt loam textures), the accuracy and efficiency of van Genuchten–Mualem with Ki and van Genuchten–Mualem models in predicting K(h) were almost similar. According to t-Student test, the mean of RMSE and GSDER of van Genuchten–Mualem model with Ki was significantly less than van Genuchten–Mualem model at P < 0.01. In 90 percent of samples, van Genuchten-Mualem and Brooks and Corey-Burdine theory had the best fitting to the measured data of water diffusivity, but in some cases van Genuchten-Burdine model with Ki was the best model for predicting D(θ). LA eng UL http://jstnar.iut.ac.ir/article-1-2206-en.html M3 ER -