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Evaluation of wet and dry event’s trend and instability based on the meteorological drought index

A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet b...

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Autores principales: Shaukat, Muhammad Haroon, Al-Dousari, Ahmad, Hussain, Ijaz, Faisal, Muhammad, Ismail, Muhammad, Mohamd Shoukry, Alaa, Elashkar, Elsayed Elsherbini, Gani, Showkat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7451013/
https://www.ncbi.nlm.nih.gov/pubmed/32904207
http://dx.doi.org/10.7717/peerj.9729
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author Shaukat, Muhammad Haroon
Al-Dousari, Ahmad
Hussain, Ijaz
Faisal, Muhammad
Ismail, Muhammad
Mohamd Shoukry, Alaa
Elashkar, Elsayed Elsherbini
Gani, Showkat
author_facet Shaukat, Muhammad Haroon
Al-Dousari, Ahmad
Hussain, Ijaz
Faisal, Muhammad
Ismail, Muhammad
Mohamd Shoukry, Alaa
Elashkar, Elsayed Elsherbini
Gani, Showkat
author_sort Shaukat, Muhammad Haroon
collection PubMed
description A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet been explored in Pakistan. In this study, we have two-fold objectives: (1) evaluate the weather instabilities, and (2) the trend of dry/wet events of selected stations of Pakistan. To observe weather instabilities, we used Mean Marginal Hilbert Spectrum (MMHS) and Continuous Wavelet Power Spectrum (CWPS) as meteorological series are mostly non-linear and non-stationary. We used Ensemble Empirical Mode Decomposition (EEMD) for the analysis of temporal characteristics of dry/wet events. We found that all stations are facing severe weather instabilities during the short period of 5 and 10 months using MMHS method and CWPS has shown the weather instabilities during 4 to 32 months of periodicity for all stations. Ultimately, the achieved short-term weather instabilities indicated by MMHS is consistent with CWPS. In summary, these findings might be useful for water resource management and policymakers.
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spelling pubmed-74510132020-09-04 Evaluation of wet and dry event’s trend and instability based on the meteorological drought index Shaukat, Muhammad Haroon Al-Dousari, Ahmad Hussain, Ijaz Faisal, Muhammad Ismail, Muhammad Mohamd Shoukry, Alaa Elashkar, Elsayed Elsherbini Gani, Showkat PeerJ Agricultural Science A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet been explored in Pakistan. In this study, we have two-fold objectives: (1) evaluate the weather instabilities, and (2) the trend of dry/wet events of selected stations of Pakistan. To observe weather instabilities, we used Mean Marginal Hilbert Spectrum (MMHS) and Continuous Wavelet Power Spectrum (CWPS) as meteorological series are mostly non-linear and non-stationary. We used Ensemble Empirical Mode Decomposition (EEMD) for the analysis of temporal characteristics of dry/wet events. We found that all stations are facing severe weather instabilities during the short period of 5 and 10 months using MMHS method and CWPS has shown the weather instabilities during 4 to 32 months of periodicity for all stations. Ultimately, the achieved short-term weather instabilities indicated by MMHS is consistent with CWPS. In summary, these findings might be useful for water resource management and policymakers. PeerJ Inc. 2020-08-24 /pmc/articles/PMC7451013/ /pubmed/32904207 http://dx.doi.org/10.7717/peerj.9729 Text en ©2020 Shaukat et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Agricultural Science
Shaukat, Muhammad Haroon
Al-Dousari, Ahmad
Hussain, Ijaz
Faisal, Muhammad
Ismail, Muhammad
Mohamd Shoukry, Alaa
Elashkar, Elsayed Elsherbini
Gani, Showkat
Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title_full Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title_fullStr Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title_full_unstemmed Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title_short Evaluation of wet and dry event’s trend and instability based on the meteorological drought index
title_sort evaluation of wet and dry event’s trend and instability based on the meteorological drought index
topic Agricultural Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7451013/
https://www.ncbi.nlm.nih.gov/pubmed/32904207
http://dx.doi.org/10.7717/peerj.9729
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