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A new comprehensive approach for regional drought monitoring
The Standardized Precipitation Index (SPI) is a vital component of meteorological drought. Several researchers have been using SPI in their studies to develop new methodologies for drought assessment, monitoring, and forecasting. However, it is challenging for SPI to provide quick and comprehensive...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9074876/ https://www.ncbi.nlm.nih.gov/pubmed/35529496 http://dx.doi.org/10.7717/peerj.13377 |
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author | Niaz, Rizwan Almazah, Mohammed M. A. Hussain, Ijaz Faisal, Muhammad Al-Rezami, A. Y. Naser, Mohammed A. |
author_facet | Niaz, Rizwan Almazah, Mohammed M. A. Hussain, Ijaz Faisal, Muhammad Al-Rezami, A. Y. Naser, Mohammed A. |
author_sort | Niaz, Rizwan |
collection | PubMed |
description | The Standardized Precipitation Index (SPI) is a vital component of meteorological drought. Several researchers have been using SPI in their studies to develop new methodologies for drought assessment, monitoring, and forecasting. However, it is challenging for SPI to provide quick and comprehensive information about precipitation deficits and drought probability in a homogenous environment. This study proposes a Regional Intensive Continuous Drought Probability Monitoring System (RICDPMS) for obtaining quick and comprehensive information regarding the drought probability and the temporal evolution of the droughts at the regional level. The RICDPMS is based on Monte Carlo Feature Selection (MCFS), steady-state probabilities, and copulas functions. The MCFS is used for selecting more important stations for the analysis. The main purpose of employing MCFS in certain stations is to minimize the time and resources. The use of MCSF makes RICDPMS efficient for drought monitoring in the selected region. Further, the steady-state probabilities are used to calculate regional precipitation thresholds for selected drought intensities, and bivariate copulas are used for modeling complicated dependence structures as persisting between precipitation at varying time intervals. The RICDPMS is validated on the data collected from six meteorological locations (stations) of the northern area of Pakistan. It is observed that the RICDPMS can monitor the regional drought and provide a better quantitative way to analyze deficits with varying drought intensities in the region. Further, the RICDPMS may be used for drought monitoring and mitigation policies. |
format | Online Article Text |
id | pubmed-9074876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90748762022-05-07 A new comprehensive approach for regional drought monitoring Niaz, Rizwan Almazah, Mohammed M. A. Hussain, Ijaz Faisal, Muhammad Al-Rezami, A. Y. Naser, Mohammed A. PeerJ Statistics The Standardized Precipitation Index (SPI) is a vital component of meteorological drought. Several researchers have been using SPI in their studies to develop new methodologies for drought assessment, monitoring, and forecasting. However, it is challenging for SPI to provide quick and comprehensive information about precipitation deficits and drought probability in a homogenous environment. This study proposes a Regional Intensive Continuous Drought Probability Monitoring System (RICDPMS) for obtaining quick and comprehensive information regarding the drought probability and the temporal evolution of the droughts at the regional level. The RICDPMS is based on Monte Carlo Feature Selection (MCFS), steady-state probabilities, and copulas functions. The MCFS is used for selecting more important stations for the analysis. The main purpose of employing MCFS in certain stations is to minimize the time and resources. The use of MCSF makes RICDPMS efficient for drought monitoring in the selected region. Further, the steady-state probabilities are used to calculate regional precipitation thresholds for selected drought intensities, and bivariate copulas are used for modeling complicated dependence structures as persisting between precipitation at varying time intervals. The RICDPMS is validated on the data collected from six meteorological locations (stations) of the northern area of Pakistan. It is observed that the RICDPMS can monitor the regional drought and provide a better quantitative way to analyze deficits with varying drought intensities in the region. Further, the RICDPMS may be used for drought monitoring and mitigation policies. PeerJ Inc. 2022-05-03 /pmc/articles/PMC9074876/ /pubmed/35529496 http://dx.doi.org/10.7717/peerj.13377 Text en © 2022 Niaz 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 | Statistics Niaz, Rizwan Almazah, Mohammed M. A. Hussain, Ijaz Faisal, Muhammad Al-Rezami, A. Y. Naser, Mohammed A. A new comprehensive approach for regional drought monitoring |
title | A new comprehensive approach for regional drought monitoring |
title_full | A new comprehensive approach for regional drought monitoring |
title_fullStr | A new comprehensive approach for regional drought monitoring |
title_full_unstemmed | A new comprehensive approach for regional drought monitoring |
title_short | A new comprehensive approach for regional drought monitoring |
title_sort | new comprehensive approach for regional drought monitoring |
topic | Statistics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9074876/ https://www.ncbi.nlm.nih.gov/pubmed/35529496 http://dx.doi.org/10.7717/peerj.13377 |
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