A novel spatially weighted accumulative procedure for regional drought monitoring. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Niaz, Rizwan; Hussain, Ijaz; Ali, Zulfiqar; Faisal, Muhammad; Elashkar, Elsayed Elsherbini; Shoukry, Alaa Mohamd; Gani, Showkat; Al-Deek, Fares Fawzi
• Is Part Of: Tellus. Volume 72:Issue 1(2020)
• Page Start: 1
• Page End: 13
• Publication Date: 2020-01-01
• Subjects: meteorological stations -- Standardized Drought Indices (SDI) -- Markov chain -- steady-state probabilities; Dynamic meteorology -- Periodicals; Oceanography -- Periodicals; 551.5
• DOI: 10.1080/16000870.2020.1838194
• Languages: English
• ISSNs: 0280-6495

Abstract

Abstract: A variety of drought monitoring tools are being used for early warning systems and formulating drought mitigation policies. Standardized Drought Indices (SDI) are the most commonly used. However, the use of SDI at multiple stations located in a homogenous climatic region with internally similar characteristics and contagious in space arises several problems due to spatial and temporal behaviour in data preliminaries. Therefore, a comprehensive procedure is required to accumulate information coming from multiple stations. In this paper, we proposed a new procedure for regional drought monitoring: the Spatially Weighted Accumulated Drought Index (SWADI). The potential of the proposed procedure is based on steady-state probabilities, which were used as a weighting scheme for the prospective of accumulating information from different stations. We employed the proposed procedure on six meteorological stations of the Northern areas of Pakistan. The performance of the proposed procedure is observed based on three commonly used drought indices at a one-month time scale. This research provides a basis for the development and enhancement of drought hazards' characterization, motivates researchers and policymakers to use the accurate and more representative temporal characterization of drought hazard in a specific homogenous climatic region.