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

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 SDIsbased 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 nonparametric framework. It is concluded that the suitable choice of probabilityplotting-position formulas allows greater accuracy when capturing the probability of extreme drought events.