Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
Drought is probably the most multifaceted environmental disaster that results from a precipitation deficiency. It perhaps has directly and indirectly potential effects on people's lives, the economy, and other environmental resources worldwide. However, for reducing the potential negative impac...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 |
| _version_ | 1811296990016831488 |
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| author | Rizwan Niaz Muhammad Ahmad Raza Mohammed M. A. Almazah Ijaz Hussain A.Y. Al-Rezami Mohammed M. Ali Al-Shamiri |
| author_facet | Rizwan Niaz Muhammad Ahmad Raza Mohammed M. A. Almazah Ijaz Hussain A.Y. Al-Rezami Mohammed M. Ali Al-Shamiri |
| author_sort | Rizwan Niaz |
| collection | DOAJ |
| description | Drought is probably the most multifaceted environmental disaster that results from a precipitation deficiency. It perhaps has directly and indirectly potential effects on people's lives, the economy, and other environmental resources worldwide. However, for reducing the potential negative impacts of drought, the understanding and information about seasonal drought frequency and persistence are crucial for drought early warning and mitigations policies. Therefore, the current research examines the selected stations' seasonal meteorological drought frequency and persistence. For this purpose, ordinal outcomes of the current research are modelled under the set of cumulative Logit Models (CLM). The estimation of the CLM is made from the logit link function. Further, the Brant Test (BT) is used to check the parallel line assumptions. The BT substantiates that the odds ratios are the same across the several drought classes. Thereby the POM is a ubiquitous choice for the current analysis. Therefore, the Proportional Odds Model (POM) is utilized to compute the odds and Probability of Drought Persistence (PDP) in varying seasons (March, April, May (Spring); June, July, August (Summer); September, October, November (Autumn); December, January, February (Winter). Further, Standardized Precipitation Index (SPI) for a certain time scale (i.e. three-month time scale SPI-3) is mainly utilized in POM. Amid SPI and various seasons, the relationship is found significant at a 5% significance level in various stations, including Murree, Rawalpindi, Sialkot, Sargodha, Faisalabad, Bahawalnagar, Bahawalpur, Mianwali, Jhelum Multan, Khanpur, and Lahore. The potential of the current research is substantiated by twelve meteorological stations in a certain province of Punjab, Pakistan. The current research outcomes provide the direction to dynamically identify the spatial interseasonal propagation of meteorological drought. Moreover, the obtained results can be helpful in making useful policies for the early warning system, drought risk assessment, and management, and formulating the drought-reducing plans. |
| first_indexed | 2024-04-13T05:56:30Z |
| format | Article |
| id | doaj.art-161e36f520164e7caf95074781016341 |
| institution | Directory Open Access Journal |
| issn | 1947-5705 1947-5713 |
| language | English |
| last_indexed | 2024-04-13T05:56:30Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj.art-161e36f520164e7caf950747810163412022-12-22T02:59:36ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132022-12-011311614163910.1080/19475705.2022.2095934Proportional odds model for identifying spatial inter-seasonal propagation of meteorological droughtRizwan Niaz0Muhammad Ahmad Raza1Mohammed M. A. Almazah2Ijaz Hussain3A.Y. Al-Rezami4Mohammed M. Ali Al-Shamiri5Department of Statistics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Mathematics, College of Sciences and Arts (Muhyil), King Khalid University, Muhyil, Saudi ArabiaDepartment of Statistics, Quaid-i-Azam University, Islamabad, PakistanMathematics Department, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi ArabiaDepartment of Mathematics, College of Sciences and Arts (Muhyil), King Khalid University, Muhyil, Saudi ArabiaDrought is probably the most multifaceted environmental disaster that results from a precipitation deficiency. It perhaps has directly and indirectly potential effects on people's lives, the economy, and other environmental resources worldwide. However, for reducing the potential negative impacts of drought, the understanding and information about seasonal drought frequency and persistence are crucial for drought early warning and mitigations policies. Therefore, the current research examines the selected stations' seasonal meteorological drought frequency and persistence. For this purpose, ordinal outcomes of the current research are modelled under the set of cumulative Logit Models (CLM). The estimation of the CLM is made from the logit link function. Further, the Brant Test (BT) is used to check the parallel line assumptions. The BT substantiates that the odds ratios are the same across the several drought classes. Thereby the POM is a ubiquitous choice for the current analysis. Therefore, the Proportional Odds Model (POM) is utilized to compute the odds and Probability of Drought Persistence (PDP) in varying seasons (March, April, May (Spring); June, July, August (Summer); September, October, November (Autumn); December, January, February (Winter). Further, Standardized Precipitation Index (SPI) for a certain time scale (i.e. three-month time scale SPI-3) is mainly utilized in POM. Amid SPI and various seasons, the relationship is found significant at a 5% significance level in various stations, including Murree, Rawalpindi, Sialkot, Sargodha, Faisalabad, Bahawalnagar, Bahawalpur, Mianwali, Jhelum Multan, Khanpur, and Lahore. The potential of the current research is substantiated by twelve meteorological stations in a certain province of Punjab, Pakistan. The current research outcomes provide the direction to dynamically identify the spatial interseasonal propagation of meteorological drought. Moreover, the obtained results can be helpful in making useful policies for the early warning system, drought risk assessment, and management, and formulating the drought-reducing plans.https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934Standardized Precipitation Index (SPI)proportional odds modelspatialinterseasonal propagationdrought frequencydrought persistence |
| spellingShingle | Rizwan Niaz Muhammad Ahmad Raza Mohammed M. A. Almazah Ijaz Hussain A.Y. Al-Rezami Mohammed M. Ali Al-Shamiri Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought Geomatics, Natural Hazards & Risk Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence |
| title | Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought |
| title_full | Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought |
| title_fullStr | Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought |
| title_full_unstemmed | Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought |
| title_short | Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought |
| title_sort | proportional odds model for identifying spatial inter seasonal propagation of meteorological drought |
| topic | Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 |
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