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Proposing a new fra...
Proposing a new framework for analyzing the severity of meteorological drought
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- Niaz, R. (författare)
- Department of Statistics, Quaid-I-Azam University, Islamabad, Pakistan
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- Almazah, M. M. A. (författare)
- Department of Mathematics, College of Sciences and Arts (Muhyil), King Khalid University, Muhyil, Saudi Arabia
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- Al-Rezami, A. Y. (författare)
- Mathematics Department, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
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- Ali, Z. (författare)
- College of Statistical Sciences, University of the Punjab, Lahore, Pakistan
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- Hussain, I. (författare)
- Department of Statistics, Quaid-I-Azam University, Islamabad, Pakistan
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- Omer, Talha (författare)
- Jönköping University,IHH, Statistik
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(creator_code:org_t)
- 2023-03-29
- 2023
- Engelska.
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Ingår i: Geocarto International. - : Taylor & Francis. - 1010-6049 .- 1752-0762. ; 38:1
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- homogeneous region
- Monte Carlo feature selection
- Spatio-temporal
- standardized drought index
- steady-state probabilities
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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