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On the more generalized non‐parametric framework for the propagation of uncertainty in drought monitoring
Zulfiqar Ali (Minhaj University Lahore), Ijaz Hussain (Quaid-i-Azam University), Muhammad Faisal (University of Bradford, Bradford Institute for Health Research), Marco Andreas Grzegorczyk (University of Groningen), Sadia Qamar (University of Sargodha), Alaa Mohamd Shoukry (Cairo University, King Saud University), Mohammed Abdel Wahab Sharkawy (Cairo University), Showkat Hussain Gani (King Saud University)
Résumé : 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.