Litcius/Paper detail

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

Zulfiqar Ali, Ijaz Hussain, Muhammad Faisal, Marco Grzegorczyk, Sadia Qamar, Alaa Mohamd Shoukry, Mohammed Abdel Wahab Sharkawy, Showkat Gani

2020Meteorological Applications12 citationsDOIOpen Access PDF

Abstract

Abstract 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.

Topics & Concepts

Parametric statisticsEnvironmental scienceComputer sciencePropagation of uncertaintyPrecipitationExtreme value theoryParametric modelProbability distributionIndex (typography)ClimatologyStatisticsMeteorologyMathematicsGeographyGeologyAlgorithmWorld Wide WebHydrology and Drought AnalysisClimate variability and modelsHydrology and Watershed Management Studies