GroMoPo Metadata for Zeeland leaky aquifer model

The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley [Vecchia, A.V. & Cooley, R.L., Water Resources Research, 1987, 23(7), 1237-1250] was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km(2) of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters. (C) 1999 Elsevier Science Ltd. All rights reserved.

地下水模型的因变量通常为模型参数的非线性函数，这一事实表明，在精准计算模型参数及参数相关函数（如模型计算得到的因变量数值）的置信区间时，该特性是一项具有潜在重要影响的因素。本文采用Vecchia与Cooley提出的拉格朗日（Lagrangian）方法[Vecchia, A.V. & Cooley, R.L., 《水资源研究》，1987，23(7)，1237-1250]，针对覆盖450平方千米越流含水层的稳态地下水流模型，计算其参数及模拟水头的非线性谢菲（Scheffe）型置信区间。将该非线性置信区间与对应的线性置信区间进行对比。正如该回归模型显著的非线性特征所预示的那样，线性置信区间往往并不精准。学界普遍认为线性置信区间的宽度总是低估了实际（非线性）区间宽度，这一假设并不成立。研究结果表明，非线性效应可导致非线性置信区间呈现不对称性，且其宽度可大于或小于线性近似区间。导水率的先验信息有助于缩小置信区间的范围，其中最显著的影响体现在带有先验信息的参数，以及对应参数分区内的水头数值上。© 1999 爱思唯尔科学有限公司 版权所有。