On the more generalized non‐parametric framework for the propagation of uncertainty in drought monitoring,Meteorological Applications

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On the more generalized non‐parametric framework for the propagation of uncertainty in drought monitoring
Meteorological Applications ( IF 2.3 ) Pub Date : 2020-06-08 , DOI: 10.1002/met.1914
Zulfiqar Ali ₁ , Ijaz Hussain ₂ , Muhammad Faisal ₃ , Marco Grzegorczyk ₄ , Sadia Qamar ₅ , Alaa Mohamd Shoukry _{6,

7} , Mohammed A. W. Sharkawy ₇ , Showkat Gani ₈

Affiliation

Drought has a complex climatic and spatio‐temporal feature. Therefore, its accurate monitoring is a great challenge for hydrological research. Recently, the use of standardized drought indices (SDIs) for drought monitoring is common in practice. However, because of the subjective choices of probability distribution, the uncertainty related to extreme events always exists in SDIs‐based drought‐monitoring tools. The present research extends the generalized non‐parametric framework for drought monitoring. The application of the proposed framework is based on seven meteorological stations in Pakistan. The preliminary analysis considered the standardized precipitation temperature index (SPTI) at different time scales. The significance of the proposed framework is to address extreme values with more accuracy under a non‐parametric framework. It is concluded that the suitable choice of probability‐plotting‐position formulas allows greater accuracy when capturing the probability of extreme drought events.

中文翻译：

关于用于干旱监测不确定性传播的更通用的非参数框架

干旱具有复杂的气候和时空特征。因此，其精确的监测是水文研究的巨大挑战。最近，在实践中通常使用标准化干旱指数（SDI）进行干旱监测。但是，由于概率分布的主观选择，基于SDI的干旱监测工具中始终存在与极端事件相关的不确定性。本研究扩展了干旱监测的广义非参数框架。拟议框架的应用基于巴基斯坦的七个气象站。初步分析考虑了不同时间尺度上的标准化降水温度指数（SPTI）。拟议框架的意义在于在非参数框架下更准确地解决极端价值。

更新日期：2020-06-08

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