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An assessment of the BEST procedure to estimate the soil water retention curve: A comparison with the evaporation method

机译:评估估计土壤水保留曲线的最佳程序:与蒸发方法的比较

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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.
机译:土壤转移参数(最佳)程序的Beerkan估算是一种具有吸引力,容易,坚固,廉价的方式,可用于完整的土壤液压表征,但测试该程序估计水保留曲线的能力,因为相对较少的信息文献。在该研究中,通过使用标准风蒸发方法测量的那些,通过应用三种现有的最佳算法(即,坡度,截止和稳定),预测土壤水保留曲线进行四种不同纹理的土壤。还对渗透常数,β和γ进行敏感性分析,并评估对估计的保留曲线比例H(g)的影响。最好的斜坡低估了在考虑的四个土壤中的三种土壤水保留,提供估计和测量数据(0.0261cm(3)厘米(-3)厘米(-3)厘米(-3)之间的相对较低的根平均平均差异; LT; RMSD& LT; = 0.0483 cm(3)cm(-3))。对于一个网站(PAL,砂土土壤),最稳定的提供最低的RMSD值(0.0893cm(3)厘米(3)厘米(3)厘米(3)厘米(3)),但由于相对的结果,水保留系统地高估了现场与实验室饱和土壤含水量之间的差异更高。对β和伽马进行的特定校准突出显示:i)最佳斜率的水保留估计比通过最佳截距和最稳定获得的β更敏感; ii)除了PAL土壤外,最低的RMSD值用最佳斜率获得。当与校准的β和γ类似于RMSDS的渗透常数(β= 0.6和γ= 0.75)使用时,土壤水保留曲线的估计没有显着差。因此,得出结论是,最佳的斜坡算法产生了比替代最佳算法更接近实验室估计的水保留的预测(即最佳拦截和稳定)。对于这些算法,由于伽马的保留曲线比例参数的独立性,水保持数据的较少准确估计归因于H(g)高度估计。

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