Predicted and measured soil retention curve parameters in Lombardy region north of Italy

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• 作者：Fatma Wassar^a ; ^c ; ^{fatmawassar@yahoo.fr" class="auth_mail" title="E-mail the corresponding author} ; Claudio Gandolfi^b ; Michele Rienzner^b ; Enrico Antonio Chiaradia^b ; Ettore Bernardoni^b
• 关键词：Comparison ; Laboratory water retention ; Field measurements ; Curve measurements ; Pedo-transfert functions
• 刊名：International Soil and Water Conservation Research
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：4
• 期：3
• 页码：207-214
• 全文大小：1513 K

文摘

Water retention characteristics are fundamental input parameters in any modeling study on water flow and solute transport. These properties are difficult to measure and for that reason, we usually need to use direct and indirect methods to determine them. An extensive comparison between measured and estimated results is needed to determine their applicability for a range of different soils. However this study attempts to make a contribution specifically in this connection. These properties were determined in two representative sites located in Landriano field, in Lombardy region, northern Italy. In the laboratory we used the pressure plate apparatus and the tensiometric box. Field soil water retention was determined including measurements of soil water content with SENTEK probes and matric potential with tensiometers. The soil waer retention curves (SWRC) were also settled on with some recently developed pedo-transfert functions (PTFs). Field retention curves were compared against those obtained from PTFs estimations and laboratory measurements. The comparison showed that laboratory measurements were the most accurate. They had the highest ranking for the validation indices (RMSE ranging between 2.4% and 7.7% and bias between 0.1% and 6.4%). The second best technique was the PTF Rosetta (Schaap et al. 2001). They perform only slightly poorer than the laboratory measurements (RMSE ranging between 2.7% and 10% and bias between 0.3% and 7.7%). The lowest prediction accuracy is observed for the Rawls and Brakensiek (1985) PTF (RMSE ranging between 6.3% and 17% and bias between 5% and 10%) which is in contradiction with previous finding (Calzolari et al., 2001), showing that this function is well representing the retention characteristics of the area. Due to time and cost investments of laboratory and field measurements, we conclude that the Rosetta PTF developed by Schaap et al. (2001) appears to be the best to predict the soil moisture retention curve from easily available soil properties in the Lombardy area and further field investigations would be useful to support this finding.