The stationarity paradigm revisited: Hypothesis testing using diagnostics, summary metrics, and DREAM(ABC)
The stationarity paradigm revisited: Hypothesis testing using diagnostics, summary metrics, and DREAM(ABC)
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重新审视平稳性范式：使用诊断、汇总指标和 DREAM(ABC) 进行假设检验
DOI：
10.1002/2014wr016805
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发表时间：
2015
影响因子：
5.4
通讯作者：
E. Volpi
中科院分区：
文献类型：
--
作者：
M. Sadegh;J. Vrugt;Chonggang Xu;E. Volpi
水文研究界使用的许多流域模型假设（默认）稳定条件，即控制水流的关键流域特性被认为是时不变的。这个假设是相当方便和实用的，并开辟了广泛的（多变量）统计和非线性优化方法的推断（时间固定）模型参数。水文文献的几个贡献带来了问题的持续有用性，这种固定的水文模型。本文建立在Vrugt和Sadegh（）的无似然诊断方法的基础上，并使用一组不同的水文汇总指标来检验平稳假设，并检测流域对水文气候强迫的响应变化。具有固定参数值的模型不能充分模拟观测到的集水数据的汇总统计中的时间变化，因此，DREAM（ABC）算法不能找到充分荣誉观测到的度量的解决方案。我们证明，所提出的方法是能够成功地区分流域被归类为固定和那些经历了显着的变化，土地利用，城市化，和/或水文气候条件，因此被认为是非固定的。
Many watershed models used within the hydrologic research community assume (by default) stationary conditions, that is, the key watershed properties that control water flow are considered to be time invariant. This assumption is rather convenient and pragmatic and opens up the wide arsenal of (multivariate) statistical and nonlinear optimization methods for inference of the (temporally fixed) model parameters. Several contributions to the hydrologic literature have brought into question the continued usefulness of this stationary paradigm for hydrologic modeling. This paper builds on the likelihood‐free diagnostics approach of Vrugt and Sadegh ( ) and uses a diverse set of hydrologic summary metrics to test the stationary hypothesis and detect changes in the watersheds response to hydroclimatic forcing. Models with fixed parameter values cannot simulate adequately temporal variations in the summary statistics of the observed catchment data, and consequently, the DREAM(ABC) algorithm cannot find solutions that sufficiently honor the observed metrics. We demonstrate that the presented methodology is able to differentiate successfully between watersheds that are classified as stationary and those that have undergone significant changes in land use, urbanization, and/or hydroclimatic conditions, and thus are deemed nonstationary.
影响因子：
10.7
作者：
Pritchard, JK;Seielstad, MT;Feldman, MW
通讯作者：
Feldman, MW