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Proposing a new framework for analyzing the severity of meteorological drought
Department of Statistics, Quaid-I-Azam University, Islamabad, Pakistan.
Department of Mathematics, College of Sciences and Arts (Muhyil), King Khalid University, Muhyil, Saudi Arabia.
Mathematics Department, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
College of Statistical Sciences, University of the Punjab, Lahore, Pakistan.
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2023 (English)In: Geocarto International, ISSN 1010-6049, E-ISSN 1752-0762, Vol. 38, no 1, article id 2197512Article in journal (Refereed) Published
Abstract [en]

The quantitative description of meteorological drought from various geographical locations and indicators is crucial for early drought warning to avoid its negative impacts. Therefore, the current study proposes a new framework to comprehensively accumulate spatial and temporal information for meteorological drought from various stations and drought indicators (indices). The proposed framework is based on two major components such as the Monthly-based Monte Carlo Feature Selection (MMCFS,) and Monthly-based Joint Index Weights (MJIW). Besides, three commonly used SDI are jointly assessed to quantify drought for selected geographical locations. Moreover, the current study uses the monthly data from six meteorological stations in the northern region for 47 years (1971-2017) for calculating SDI values. The outcomes of the current research explicitly accumulate regional spatiotemporal information for meteorological drought. In addition, results may serve as an early warning to the effective management of water resources to avoid negative drought impacts in Pakistan.

Place, publisher, year, edition, pages
Taylor & Francis, 2023. Vol. 38, no 1, article id 2197512
Keywords [en]
homogeneous region, Monte Carlo feature selection, Spatio-temporal, standardized drought index, steady-state probabilities
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-60318DOI: 10.1080/10106049.2023.2197512ISI: 000974206800001Scopus ID: 2-s2.0-85153088752Local ID: HOA;intsam;878638OAI: oai:DiVA.org:hj-60318DiVA, id: diva2:1755083
Available from: 2023-05-05 Created: 2023-05-05 Last updated: 2023-05-15Bibliographically approved

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Omer, Talha

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