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首页> 外文期刊>Journal of Hydrology >The development of a Nonstationary Standardized Precipitation Index using climate covariates: A case study in the middle and lower reaches of Yangtze River Basin, China
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The development of a Nonstationary Standardized Precipitation Index using climate covariates: A case study in the middle and lower reaches of Yangtze River Basin, China

机译：利用气候协变者制定非间断的标准化降水指数：中国长江盆地中下游的案例研究

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摘要

The widely used probability based drought indices for drought characterization usually underlie the assumption of the considered hydrometeorological variables to be stationary, which is largely challenged under the current global change. Incorporating the parameters of probability distribution with covariates, such as time or climate indices, has become a common way to develop drought index considering nonstationarity. However most previous drought studies emphasized more on the linear relationship between distribution parameters and related covariates, which may neglect the inherent nonlinear relationship and lost useful information for drought assessment. Our study aims to develop a Nonstationary Standardized Precipitation Index (NSPI) with distribution parameters nonlinearly varying with potential influencing climate indices. The middle and lower reaches of the Yangtze River Basin (MLRYRB) of China are selected as the case study area to examine the performance of the NSPI with the performance of the traditional standardized precipitation index (SPI). Results indicate that the NSPI (with climate indices as covariates) is more robust than both the NSPI (with time as the covariate) and the traditional SPI. Furthermore, the nonlinear dependence of distribution parameters on climate indices considered in the nonstationary model can be more suitable for drought assessment than the linear dependence of distribution parameters. Besides, there exists a higher frequency of extreme drought by the NSPI than the SPI in recent decades in most regions of the MLRYRB. Although the NSPI is a lithe computationally expensive with more required inputs of climate variables, it can depict the influence of changing environment on the drought occurrence, thus can be a feasible alternative for drought assessment considering nonstationarity in view of future change and provide valuable support for further studies.
机译：用于干旱特征的广泛使用的概率基于概率的干旱指标通常利于所考虑的水流气象变量是静止的，这在目前的全球变化下主要挑战。将概率分布的参数与协变量（例如时间或气候指数）纳入，这已成为考虑非间抗性的干旱指数的常用方式。然而，最先前的干旱研究更加强调了分布参数和相关协变量之间的线性关系，这可能忽视固有的非线性关系，并损失干旱评估的有用信息。我们的研究旨在开发一个非间断的标准化降水指数（NSPI），其分布参数与影响气候指标的潜在不同。中国长江盆地（MLRYRB）的中下游被选为案例研究区，以研究NSPI的性能，具有传统的标准化降水指数（SPI）。结果表明，NSPI（随着协变量的气候指数）比NSPI（随着协变量）和传统SPI更强大。此外，分布参数对非间平模型中考虑的气候指标的非线性依赖性可以更适合于干旱评估而不是分布参数的线性依赖性。此外，在MLRYRB的大多数区域中，NSPI的NSPI存在较高的极端干旱频率。虽然NSPI是一种计算昂贵的气候变量输入昂贵，但它可以描绘改变环境对干旱发生的影响，因此对于未来的变化，考虑非间抗性的干旱评估可以是一种可行的替代方案深度学习。

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