The BEST (Beerkan Estimation of Soil Transfer parameters) procedure is attractive for simple soil hydrauliccharacterization but there is the need to test the reliability of the predictions. In this investigation, theBEST procedure to predict water retention of 199 Sicilian soils was evaluated. The BEST water retentionmodel performed well (relative error, Er≤0.05) for approximately 80% of the soil samples. Low errorswere obtained in soils with a high clay, cl, content (≥44%), whereas both high and low Er values wereobtained in soils with a lower cl content. The BEST particle size distribution (PSD) model was accurate for50% of the samples and the fitting accuracy increased with cl, with Er≤0.05 for cl≥45.2%. Alternative models,allowing an improved description of the PSD data, were also characterized by a fitting accuracy that increasedwith cl. Differences among alternative estimates of the particle-size shape index, PM, decreased as the cl contentof the soil increased. The laboratory determined water retention shape index, pm, did not coincide withthat estimated according to BEST (mean factor of discrepancy=1.33, maximum=4.6), and absolute discrepancieswere particularly noticeable in soils with clb10%. Better results (mean and maximum discrepancy by afactor of 1.29 and 2.3, respectively) were obtained with the indirect procedure by Minasny and McBratney(2007), using the soil's clay and sand percentages. In conclusion, the BEST water retention model can be consideredappropriate for most soils. Checking the soil textural characteristics before conducting the BEST experimentis suggested to establish if the expected performance of the water retention model is good orthere is the possibility of a poor description of the data. Using a reduced information on soil textural characteristicsdoes not compromise prediction of water retention characteristics in Sicily. Testing the results of thisinvestigation with other databases including a larger number of clay soils is desirable.
|Numero di pagine||10|
|Stato di pubblicazione||Published - 2012|
All Science Journal Classification (ASJC) codes
- Soil Science