U.S. Geological Survey, Wisconsin Water Science Center, Middleton, WI 53562, USA.
Ground Water. 2009 Nov-Dec;47(6):835-44. doi: 10.1111/j.1745-6584.2009.00579.x. Epub 2009 Apr 21.
Ground water model calibration has made great advances in recent years with practical tools such as PEST being instrumental for making the latest techniques available to practitioners. As models and calibration tools get more sophisticated, however, the power of these tools can be misapplied, resulting in poor parameter estimates and/or nonoptimally calibrated models that do not suit their intended purpose. Here, we focus on an increasingly common technique for calibrating highly parameterized numerical models-pilot point parameterization with Tikhonov regularization. Pilot points are a popular method for spatially parameterizing complex hydrogeologic systems; however, additional flexibility offered by pilot points can become problematic if not constrained by Tikhonov regularization. The objective of this work is to explain and illustrate the specific roles played by control variables in the PEST software for Tikhonov regularization applied to pilot points. A recent study encountered difficulties implementing this approach, but through examination of that analysis, insight into underlying sources of potential misapplication can be gained and some guidelines for overcoming them developed.
近年来,地下水模型校准取得了重大进展,实用工具如 PEST 为向从业人员提供最新技术发挥了重要作用。然而,随着模型和校准工具变得更加复杂,这些工具的威力可能被错误地应用,导致参数估计不佳和/或校准不适合其预期目的的模型。在这里,我们专注于校准高度参数化数值模型的一种越来越常见的技术——带有 Tikhonov 正则化的试点参数化。试点是空间参数化复杂水文地质系统的一种流行方法;但是,如果不通过 Tikhonov 正则化来约束,试点提供的额外灵活性可能会成为问题。这项工作的目的是解释和说明在 PEST 软件中用于 pilot points 的 Tikhonov regularization 的控制变量所扮演的特定角色。最近的一项研究在实施这种方法时遇到了困难,但通过对该分析的检查,可以深入了解潜在误用的潜在来源,并制定一些克服这些问题的指南。