Monthly drought prediction based on ensemble models

Muhammad Haroon Shaukat,Muhammad Ismail,Showkat Gani,Elsayed Elsherbini Elashkar,Ahmad Al-Dousari,Ijaz Hussain,Alaa Mohamd Shoukry,Muhammad Faisal

doi:10.7717/peerj.9853

Abstract

Drought is a natural hazard, which is a result of a prolonged shortage of precipitation, high temperature and change in the weather pattern. Drought harms society, the economy and the natural environment, but it is difficult to identify and characterize. Many areas of Pakistan have suffered severe droughts during the last three decades due to changes in the weather pattern. A drought analysis with the incorporation of climate information has not yet been undertaken in this study region. Here, we propose an ensemble approach for monthly drought prediction and to define and examine wet/dry events. Initially, the drought events were identified by the short term Standardized Precipitation Index (SPI-3). Drought is predicted based on three ensemble models i.e., Equal Ensemble Drought Prediction (EEDP), Weighted Ensemble Drought Prediction (WEDP) and the Conditional Ensemble Drought Prediction (CEDP) model. Besides, two weighting procedures are used for distributing weights in the WEDP model, such as Traditional Weighting (TW) and the Weighted Bootstrap Resampling (WBR) procedure. Four copula families (i.e., Frank, Clayton, Gumbel and Joe) are used to explain the dependency relation between climate indices and precipitation in the CEDP model. Among all four copula families, the Joe copula has been found suitable for most of the times. The CEDP model provides better results in terms of accuracy and uncertainty as compared to other ensemble models for all meteorological stations. The performance of the CEDP model indicates that the climate indices are correlated with a weather pattern of four meteorological stations. Moreover, the percentage occurrence of extreme drought events that have appeared in the Multan, Bahawalpur, Barkhan and Khanpur are 1.44%, 0.57%, 2.59% and 1.71%, respectively, whereas the percentage occurrence of extremely wet events are 2.3%, 1.72%, 0.86% and 2.86%, respectively. The understanding of drought pattern by including climate information can contribute to the knowledge of future agriculture and water resource management.

Highlights

In the last few decades, global warming has become an undeniable fact which causes climate irregularities i.e., extreme weather events and droughts (Bai et al, 2020; Horton et al, 2016; Mishra & Singh, 2010)
The present analysis consists of four meteorological stations i.e., Multan, Bahawalpur, Barkhan and Khanpur
The high percentage of extremely wet events were found in Khanpur

Summary

Introduction

In the last few decades, global warming has become an undeniable fact which causes climate irregularities i.e., extreme weather events and droughts (Bai et al, 2020; Horton et al, 2016; Mishra & Singh, 2010). Sharafati & Pezeshki (2020) proposed a robust approach to assess climate change impact variability on future extreme events over Dehbar catchment in Iran. They used the Lars-WG6 model to generate future climate weather variables such as temperature and rainfall depth using five coupled models with several emission scenarios. They concluded that trends in extreme rainfall depth and river discharge is increasing due to climate and inferred that the future extreme rainfall depth at more than 500-year return periods has more variability

Objectives

Methods

Discussion

Conclusion