Dario Autovino, Vincenzo Bagarello, Massimo Iovino, Laurent Lassabatere, Deniz Yilmaz
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Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T-algorithm) and (ii) the last four data points, yielding a reference value of steady-state infiltration rate (R-algorithm). A third algorithm, similar to the R-algorithm, was applied to previously re-sampled infiltration data at fixed time intervals (RR-algorithm). The intercept, <i>b</i><sub><i>s</i></sub>, of the straight line fitted to the data describing steady-state on the cumulative infiltration plot depended on the applied algorithm more than the slope of this line. Consequently, <i>β</i> varied with the applied algorithm more than <i>γ</i>. The RR-algorithm, yielding 0.62 ≤ β ≤ 1.99 and 0.74 ≤ <i>γ</i> ≤ 0.98, was preferred since it mediated between advantages and disadvantages of T- and R-algorithms. The influence of the choice of proper values for <i>β</i> and <i>γ</i> on the estimates of <i>S</i> and <i>K</i><sub><i>s</i></sub> was evaluated using BEST. Using the default values of <i>β</i> (0.6) and <i>γ</i> (0.75) yielded accurate estimates of <i>S</i> but not of <i>K</i><sub><i>s</i></sub>. Soil dependent <i>β</i> and <i>γ</i> values should be used in this case. A check of the reliability of the estimates of <i>b</i><sub><i>s</i></sub> can be made by a sequential analysis of the cumulative infiltration data. 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Calculating these properties requires choosing the <i>β</i> and <i>γ</i> parameters of the Haverkamp infiltration model. These parameters can be obtained from numerically simulated three-dimensional (3D) infiltration runs reaching steady-state. This investigation tested dependence of the estimated <i>β</i> and <i>γ</i> parameters on the algorithm for steady-state selection using simulated 3D cumulative infiltrations for different soils and initial conditions. Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T-algorithm) and (ii) the last four data points, yielding a reference value of steady-state infiltration rate (R-algorithm). A third algorithm, similar to the R-algorithm, was applied to previously re-sampled infiltration data at fixed time intervals (RR-algorithm). 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引用次数: 0
摘要
土壤水力特征的 BEST(Beerkan Estimation of Soil Transfer parameters)方法被广泛应用于估算吸水率 S 和饱和导水率 Ks。计算这些特性需要选择哈弗坎普渗透模型的 β 和 γ 参数。这些参数可以从达到稳态的三维(3D)渗透数值模拟运行中获得。本研究利用不同土壤和初始条件下的模拟三维累积渗透,测试了估计的 β 和 γ 参数对稳态选择算法的依赖性。两种算法使用原始模拟输出,包括使用 (i) 定义稳态的阈值(T 算法)和 (ii) 最后四个数据点,得出稳态渗透率的参考值(R 算法)。第三种算法与 R 算法类似,适用于先前以固定时间间隔重新采样的渗透数据(RR 算法)。在累积渗透图上,与描述稳态的数据拟合的直线的截距(bs)取决于所应用的算法,而不是该直线的斜率。RR 算法的结果为 0.62 ≤ β ≤ 1.99 和 0.74 ≤ γ ≤ 0.98,由于它兼顾了 T 算法和 R 算法的优缺点,因此更受青睐。利用 BEST 评估了 β 和 γ 适当值的选择对 S 和 Ks 估计值的影响。使用默认的 β 值(0.6)和 γ 值(0.75)可以准确估计 S,但不能准确估计 Ks。在这种情况下,应使用与土壤有关的 β 和 γ 值。可以通过对累积入渗数据进行连续分析来检验 bs 估计值的可靠性。未来的发展包括考虑不同规模的水源,并确定建议的 β 和 γ 值是否普遍适用于现有的 BEST 算法。
Parameterizing Haverkamp Model From the Steady-State of Numerically Generated Infiltration: Influence of Algorithms for Steady-State Selection
BEST (Beerkan Estimation of Soil Transfer parameters) methods of soil hydraulic characterisation are widely applied for estimating sorptivity, S, and saturated hydraulic conductivity, Ks. Calculating these properties requires choosing the β and γ parameters of the Haverkamp infiltration model. These parameters can be obtained from numerically simulated three-dimensional (3D) infiltration runs reaching steady-state. This investigation tested dependence of the estimated β and γ parameters on the algorithm for steady-state selection using simulated 3D cumulative infiltrations for different soils and initial conditions. Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T-algorithm) and (ii) the last four data points, yielding a reference value of steady-state infiltration rate (R-algorithm). A third algorithm, similar to the R-algorithm, was applied to previously re-sampled infiltration data at fixed time intervals (RR-algorithm). The intercept, bs, of the straight line fitted to the data describing steady-state on the cumulative infiltration plot depended on the applied algorithm more than the slope of this line. Consequently, β varied with the applied algorithm more than γ. The RR-algorithm, yielding 0.62 ≤ β ≤ 1.99 and 0.74 ≤ γ ≤ 0.98, was preferred since it mediated between advantages and disadvantages of T- and R-algorithms. The influence of the choice of proper values for β and γ on the estimates of S and Ks was evaluated using BEST. Using the default values of β (0.6) and γ (0.75) yielded accurate estimates of S but not of Ks. Soil dependent β and γ values should be used in this case. A check of the reliability of the estimates of bs can be made by a sequential analysis of the cumulative infiltration data. Future developments include considering sources differing in size and establishing if the suggested β and γ values apply in general to the available BEST algorithms.
期刊介绍:
Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.