首页> 外文期刊>International journal of applied mechanics >Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits
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Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits

机译:研究多种土壤水保留模型的单峰,双峰,PDI和双峰PDI变体:II。 对直接配合的参数网站传输功能的评估

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A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VG(m) model). In addition, eleven bimodal, Peters-Durner-Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (theta (s)). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VG(m) parametric PTF with an RMSE of 0.034 cm(3) cm(-3) was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm(3) cm(-3) showed the highest performance. The best performance of all models occurred at S6 when theta s was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters.
机译:通过Hyprop系统测量的高分辨率土壤水保留数据集(81种具有7729个观察的土壤样品)来开发和评估回归参数网站传输功能(PTF)的性能。评估了十六种土壤液压模型,包括Brooks和Corey(BC Model),Fredlund和Xing(FX模型),Kosugi(K型号),Van Genuchten有四个免费参数(VG模型)和面包车真正有五个免费参数(VG(M)型号)。此外,还研究了11个双峰,Peters-Durner-Iden(PDI)和原始表达的Bimodal-PDI变体。通过以下输入预测因素的不同组合检查六种建模情景:土壤纹理(砂,淤泥和粘土的百分比),土壤堆积密度,有机物质含量,稳定的聚集体百分比和饱和含水量(θ( s)))。尽管大多数模型参数显示出与基本土壤性质的低相关性,但大多数参数PTF都提供了合理的水含量估计。当考虑所有输入预测器时,具有0.034cm(3)cm(3)cm(3)cm(-3)的Vg(m)参数PTF是最好的PTF。当平均模拟场景时,具有0.045cm(3)厘米(-3)的RMSE的K模型的PDI变体显示出最高的性能。当Theta S被视为额外的输入预测器时,所有模型的最佳性能发生在S6。 16个型号中的11个最佳性能属于S1,具有土壤纹理组件作为唯一的输入。我们的结果不建议使用双峰变体的参数PTFS的开发,因为它们的性能差,归因于他们的空闲参数大量。

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