TY - JOUR AU - Buccigrossi, Floriano AU - Caliandro, Angelo AU - Rubino, Pietro AU - Mastro, Mario Alberto PY - 2009/03/31 Y2 - 2024/03/29 TI - TESTING SOME PEDO-TRANSFER FUNCTIONS (PTFS) IN APULIA REGION JF - Journal of Agricultural Engineering JA - J Agric Eng VL - 40 IS - 1 SE - Original Articles DO - 10.4081/jae.2009.1.19 UR - https://www.agroengineering.org/jae/article/view/jae.2009.1.19 SP - 19-31 AB - The knowledge of soil water retention vs. soil water matric potential is used to study irrigation and drainage schedules, soil water storage capacity (plant available water), solute movement, plant growth and water stress. The hydraulic soil properties measuring is expensive, laborious and takes too long time, so, frequently, matemathic models, called pedo-transfer functions (PTFs) are utilized to estimate hydraulic soil properties through soil chimical and phisical characteristics. Six pedo-transfer functions have been evaluated (Gupta & Larson, 1979; Rawls et al., 1982; De Jong et al., 1983; Rawls & Brakensiek, 1985; Saxton et al., 1986; Vereecken et al., 1989) by comparing estimated with measured soil moisture values at soil water matric potential of –33 and –1500 kPa of 361 soil samples collected from 185 pedons of Apulia Region (South Italy), having various combinations of particle-size distribution, soil organic matter content and bulk density. Accuracy of the soil moisture predictions have been evaluated by statistic indexes such as Weighted stantard error (WSEE), Mean Deviation (MD), Root Mean Squared Deviation (RMSD) and the determination coefficient (R2) between estimated and measured water retention values. The Rawls PTF model demostrated to have the lowest values of WSEE, MD and RMSD indexes (0.044, -0.007 and 0.059 m3 H2O m-3 soil, respectively) at –33 Kpa soil water matric potential (Field Capacity), while for estimating soil moisture at the Wilting Point (-1500 kPa) Rawls & Brakensiek model is adequate (WSEE, MD and RMSD of 0.034, -0.016 and 0.046 m3 H2O m-3 soil). De Jong, Saxton and Rawls & Brakensiek models, at –33 kPa soil water matric potential and Gupta & Larson and De Jong models at –1500 kPa soil water matric potential, showed the highest statistic errors. ER -