The Beerkan Estimation of Soil Transfer parameters (BEST) procedure is an attractive, easy, robust, and inexpensive way for a complete soil hydraulic characterization but testing the ability of this procedure to estimate the water retention curve is necessary as relatively little information is available in the literature. In this investigation the soil water retention curve was predicted for four differently textured soils by applying three existing BEST algorithms (i.e., slope, intercept and steady) and the results compared with those measured by the standard Wind evaporation method. A sensitivity analysis of the infiltration constants, beta and gamma, was also carried out and their impact on the estimated retention curve scale parameter, h(g), was evaluated. BEST-slope underestimated the soil water retention for three of the four soils under consideration, providing relatively low root mean squared differences between estimated and measured data (0.0261 cm(3)cm(-3) <= RMSD <= 0.0483 cm(3)cm(-3)). For one site (PAL, sandy-loam soil), BEST-steady provided the lowest RMSD value (0.0893 cm(3)cm(-3)) among the considered algorithms, but the water retention was systematically overestimated as a consequence of a relatively higher difference between field and lab saturated soil water contents. A specific calibration performed for beta and gamma highlighted that: i) the water retention estimations by BEST-slope were more sensitive to beta than those obtained by BEST-intercept and BEST-steady; ii) with the exception of PAL soil, the lowest RMSD values were obtained with BEST-slope. Estimation of the soil water retention curve was not significantly worse when reference values of infiltration constants (beta = 0.6 and gamma = 0.75) were used as detected by negligible differences in RMSDs as compared to calibrated beta and gamma. Therefore, it was concluded that the BEST slope algorithm yielded predictions of water retention closer to the laboratory estimated ones than the alternative BEST algorithms (i.e. BEST-intercept and-steady). For these algorithms, the less accurate estimates of the water retention data were attributed to h(g) overestimations due to the independence of the retention curve scale parameter from gamma.
|Numero di pagine||13|
|Stato di pubblicazione||Published - 2018|
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