Sensitivity Analysis and Validation for Numerical Simulation of Water Infiltration into Unsaturated Soil.

International Scholarly Research Notices Pub Date : 2015-09-28 eCollection Date: 2015-01-01 DOI:10.1155/2015/824721
Eng Giap Goh, Kosuke Noborio
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引用次数: 8

Abstract

A FORTRAN code for liquid water flow in unsaturated soil under the isothermal condition was developed to simulate water infiltration into Yolo light clay. The governing equation, that is, Richards' equation, was approximated by the finite-difference method. A normalized sensitivity coefficient was used in the sensitivity analysis of Richards' equation. Normalized sensitivity coefficient was calculated using one-at-a-time (OAT) method and elementary effects (EE) method based on hydraulic functions for matric suction and hydraulic conductivity. Results from EE method provided additional insight into model input parameters, such as input parameter linearity and oscillating sign effect. Boundary volumetric water content (θ L (upper bound)) and saturated volumetric water content (θ s ) were consistently found to be the most sensitive parameters corresponding to positive and negative relations, as given by the hydraulic functions. In addition, although initial volumetric water content (θ L (initial cond)) and time-step size (Δt), respectively, possessed a great amount of sensitivity coefficient and uncertainty value, they did not exhibit significant influence on model output as demonstrated by spatial discretization size (Δz). The input multiplication of parameters sensitivity coefficient and uncertainty value was found to affect the outcome of model simulation, in which parameter with the highest value was found to be Δz.

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非饱和土壤入渗数值模拟敏感性分析与验证。
开发了等温条件下非饱和土中液态水流动的FORTRAN程序,以模拟水渗入Yolo轻黏土。控制方程即理查兹方程,用有限差分法逼近。理查兹方程的灵敏度分析采用归一化灵敏度系数。基于基质吸力和水力导率的水力函数,采用单次法(one-at-a-time, OAT)和基本效应法(elementary effects, EE)计算归一化敏感性系数。EE方法的结果提供了对模型输入参数的进一步了解,如输入参数线性和振荡符号效应。边界体积含水量(θ L(上界))和饱和体积含水量(θ s)是最敏感的参数,对应于水力函数给出的正负关系。此外,虽然初始体积含水量(θ L(初始秒))和时间步长(Δt)分别具有很大的敏感性系数和不确定性值,但从空间离散化大小(Δz)可以看出,它们对模型输出的影响并不显著。发现参数敏感性系数和不确定性值的输入相乘会影响模型仿真的结果,其中值最大的参数为Δz。
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