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 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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Rizwan Niaz [verfasserIn] Muhammad Ahmad Raza [verfasserIn] Mohammed M. A. Almazah [verfasserIn] Ijaz Hussain [verfasserIn] A.Y. Al-Rezami [verfasserIn] Mohammed M. Ali Al-Shamiri [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence

Übergeordnetes Werk:	In: Geomatics, Natural Hazards & Risk - Taylor & Francis Group, 2016, 13(2022), 1, Seite 1614-1639
Übergeordnetes Werk:	volume:13 ; year:2022 ; number:1 ; pages:1614-1639

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1080/19475705.2022.2095934

Katalog-ID:	DOAJ025111698

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520			\|a 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.
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allfields	10.1080/19475705.2022.2095934 doi (DE-627)DOAJ025111698 (DE-599)DOAJ161e36f520164e7caf95074781016341 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Rizwan Niaz verfasserin aut Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Muhammad Ahmad Raza verfasserin aut Mohammed M. A. Almazah verfasserin aut Ijaz Hussain verfasserin aut A.Y. Al-Rezami verfasserin aut Mohammed M. Ali Al-Shamiri verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 13(2022), 1, Seite 1614-1639 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:13 year:2022 number:1 pages:1614-1639 https://doi.org/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/article/161e36f520164e7caf95074781016341 kostenfrei https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022 1 1614-1639
spelling	10.1080/19475705.2022.2095934 doi (DE-627)DOAJ025111698 (DE-599)DOAJ161e36f520164e7caf95074781016341 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Rizwan Niaz verfasserin aut Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Muhammad Ahmad Raza verfasserin aut Mohammed M. A. Almazah verfasserin aut Ijaz Hussain verfasserin aut A.Y. Al-Rezami verfasserin aut Mohammed M. Ali Al-Shamiri verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 13(2022), 1, Seite 1614-1639 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:13 year:2022 number:1 pages:1614-1639 https://doi.org/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/article/161e36f520164e7caf95074781016341 kostenfrei https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022 1 1614-1639
allfields_unstemmed	10.1080/19475705.2022.2095934 doi (DE-627)DOAJ025111698 (DE-599)DOAJ161e36f520164e7caf95074781016341 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Rizwan Niaz verfasserin aut Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Muhammad Ahmad Raza verfasserin aut Mohammed M. A. Almazah verfasserin aut Ijaz Hussain verfasserin aut A.Y. Al-Rezami verfasserin aut Mohammed M. Ali Al-Shamiri verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 13(2022), 1, Seite 1614-1639 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:13 year:2022 number:1 pages:1614-1639 https://doi.org/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/article/161e36f520164e7caf95074781016341 kostenfrei https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022 1 1614-1639
allfieldsGer	10.1080/19475705.2022.2095934 doi (DE-627)DOAJ025111698 (DE-599)DOAJ161e36f520164e7caf95074781016341 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Rizwan Niaz verfasserin aut Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Muhammad Ahmad Raza verfasserin aut Mohammed M. A. Almazah verfasserin aut Ijaz Hussain verfasserin aut A.Y. Al-Rezami verfasserin aut Mohammed M. Ali Al-Shamiri verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 13(2022), 1, Seite 1614-1639 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:13 year:2022 number:1 pages:1614-1639 https://doi.org/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/article/161e36f520164e7caf95074781016341 kostenfrei https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022 1 1614-1639
allfieldsSound	10.1080/19475705.2022.2095934 doi (DE-627)DOAJ025111698 (DE-599)DOAJ161e36f520164e7caf95074781016341 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Rizwan Niaz verfasserin aut Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Muhammad Ahmad Raza verfasserin aut Mohammed M. A. Almazah verfasserin aut Ijaz Hussain verfasserin aut A.Y. Al-Rezami verfasserin aut Mohammed M. Ali Al-Shamiri verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 13(2022), 1, Seite 1614-1639 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:13 year:2022 number:1 pages:1614-1639 https://doi.org/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/article/161e36f520164e7caf95074781016341 kostenfrei https://www.tandfonline.com/doi/10.1080/19475705.2022.2095934 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022 1 1614-1639
language	English
source	In Geomatics, Natural Hazards & Risk 13(2022), 1, Seite 1614-1639 volume:13 year:2022 number:1 pages:1614-1639
sourceStr	In Geomatics, Natural Hazards & Risk 13(2022), 1, Seite 1614-1639 volume:13 year:2022 number:1 pages:1614-1639
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61
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container_title	Geomatics, Natural Hazards & Risk
authorswithroles_txt_mv	Rizwan Niaz @@aut@@ Muhammad Ahmad Raza @@aut@@ Mohammed M. A. Almazah @@aut@@ Ijaz Hussain @@aut@@ A.Y. Al-Rezami @@aut@@ Mohammed M. Ali Al-Shamiri @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	626457491
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callnumber-first	T - Technology
author	Rizwan Niaz
spellingShingle	Rizwan Niaz misc TD1-1066 misc GE1-350 misc Standardized Precipitation Index (SPI) misc proportional odds model misc spatial misc interseasonal propagation misc drought frequency misc drought persistence misc Environmental technology. Sanitary engineering misc Environmental sciences misc Risk in industry. Risk management misc HD61 Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
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topic_title	TD1-1066 GE1-350 Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought Standardized Precipitation Index (SPI) proportional odds model spatial interseasonal propagation drought frequency drought persistence
topic	misc TD1-1066 misc GE1-350 misc Standardized Precipitation Index (SPI) misc proportional odds model misc spatial misc interseasonal propagation misc drought frequency misc drought persistence misc Environmental technology. Sanitary engineering misc Environmental sciences misc Risk in industry. Risk management misc HD61
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title	Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
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title_full	Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
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author_browse	Rizwan Niaz Muhammad Ahmad Raza Mohammed M. A. Almazah Ijaz Hussain A.Y. Al-Rezami Mohammed M. Ali Al-Shamiri
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title_sort	proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
callnumber	TD1-1066
title_auth	Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought

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