Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation
The phenomenon of drought is common in the world, especially in Pakistan. El Niño-Southern Oscillation (ENSO) influences the spatial and temporal variability of drought and rainfall in Pakistan. Therefore, the objectives of this study are to identify homogeneous rainfall regions and their trend regi...
| Main Authors: | , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Springer
2022
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| Online Access: | https://hdl.handle.net/10568/119704 |
| _version_ | 1855525901374062592 |
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| author | Oliveira-Junior, J.F. de Shah, M. Abbas, A. Iqbal, Muhammad Shahid Shahzad, R. Gois, G. de Silva, M.V. da Rosa Ferraz Jardim, A.M. da Souza, A. de |
| author_browse | Abbas, A. Gois, G. de Iqbal, Muhammad Shahid Oliveira-Junior, J.F. de Rosa Ferraz Jardim, A.M. da Shah, M. Shahzad, R. Silva, M.V. da Souza, A. de |
| author_facet | Oliveira-Junior, J.F. de Shah, M. Abbas, A. Iqbal, Muhammad Shahid Shahzad, R. Gois, G. de Silva, M.V. da Rosa Ferraz Jardim, A.M. da Souza, A. de |
| author_sort | Oliveira-Junior, J.F. de |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The phenomenon of drought is common in the world, especially in Pakistan. El Niño-Southern Oscillation (ENSO) influences the spatial and temporal variability of drought and rainfall in Pakistan. Therefore, the objectives of this study are to identify homogeneous rainfall regions and their trend regions, as well as the impact of ENSO phases. In this study, monthly rainfall data from 44 weather stations are used during 1980–2019. Moreover, descriptive and exploratory statistics tests (e.g., Pettitt and Mann-Kendall—MK), Sen method, and cluster analysis (CA) are evaluated along with the annual Standardized Precipitation Index (SPI) on spatiotemporal scales. ENSO occurrences were classified based on the Oceanic Nino Index (ONI) for region 3.4. Using the cophenetic correlation coefficient (CCC) and a significance level of 5%, seven methods were applied to the rainfall series, with the complete method (CCC > 0.9082) being the best. According to the CA method, Pakistan has four groups of homogeneous rainfall (G1, G2, G3, and G4). Descriptive and exploratory statistics showed that G1 differs from the other groups in size and spatial distribution. Pettitt’s technique identified the most extreme El Niño years in terms of spatial and temporal drought variability, along with the wettest months (March, August, September, June, and December) in Pakistan. Non-significant increases in Pakistan’s annual precipitation were identified via the MK test, with exceptions in the southern and northern regions, respectively. No significant increase in rainfall in Pakistan was found using the Sen method, especially in regions G2, G3, and G4. The severity of the drought in Pakistan is intensified by El Niño events, which demand attention from public managers in the management of water resources, agriculture, and the country’s economy. |
| format | Journal Article |
| id | CGSpace119704 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1197042025-12-02T10:59:51Z Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation Oliveira-Junior, J.F. de Shah, M. Abbas, A. Iqbal, Muhammad Shahid Shahzad, R. Gois, G. de Silva, M.V. da Rosa Ferraz Jardim, A.M. da Souza, A. de drought rain precipitation time series analysis el nino-southern oscillation trends spatial distribution meteorological stations The phenomenon of drought is common in the world, especially in Pakistan. El Niño-Southern Oscillation (ENSO) influences the spatial and temporal variability of drought and rainfall in Pakistan. Therefore, the objectives of this study are to identify homogeneous rainfall regions and their trend regions, as well as the impact of ENSO phases. In this study, monthly rainfall data from 44 weather stations are used during 1980–2019. Moreover, descriptive and exploratory statistics tests (e.g., Pettitt and Mann-Kendall—MK), Sen method, and cluster analysis (CA) are evaluated along with the annual Standardized Precipitation Index (SPI) on spatiotemporal scales. ENSO occurrences were classified based on the Oceanic Nino Index (ONI) for region 3.4. Using the cophenetic correlation coefficient (CCC) and a significance level of 5%, seven methods were applied to the rainfall series, with the complete method (CCC > 0.9082) being the best. According to the CA method, Pakistan has four groups of homogeneous rainfall (G1, G2, G3, and G4). Descriptive and exploratory statistics showed that G1 differs from the other groups in size and spatial distribution. Pettitt’s technique identified the most extreme El Niño years in terms of spatial and temporal drought variability, along with the wettest months (March, August, September, June, and December) in Pakistan. Non-significant increases in Pakistan’s annual precipitation were identified via the MK test, with exceptions in the southern and northern regions, respectively. No significant increase in rainfall in Pakistan was found using the Sen method, especially in regions G2, G3, and G4. The severity of the drought in Pakistan is intensified by El Niño events, which demand attention from public managers in the management of water resources, agriculture, and the country’s economy. 2022-07 2022-05-31T19:16:36Z 2022-05-31T19:16:36Z Journal Article https://hdl.handle.net/10568/119704 en Limited Access Springer de Oliveira-Junior, J. F.; Shah, M.; Abbas, A.; Iqbal, M. Shahid; Shahzad, R.; de Gois, G.; da Silva, M. V.; da Rosa Ferraz Jardim, A. M.; de Souza, A. 2022. Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-Southern Oscillation. Theoretical and Applied Climatology, 149(1-2):843-862. [doi: https://doi.org/10.1007/s00704-022-04082-9] |
| spellingShingle | drought rain precipitation time series analysis el nino-southern oscillation trends spatial distribution meteorological stations Oliveira-Junior, J.F. de Shah, M. Abbas, A. Iqbal, Muhammad Shahid Shahzad, R. Gois, G. de Silva, M.V. da Rosa Ferraz Jardim, A.M. da Souza, A. de Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title | Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title_full | Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title_fullStr | Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title_full_unstemmed | Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title_short | Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Nino-southern oscillation |
| title_sort | spatiotemporal analysis of drought and rainfall in pakistan via standardized precipitation index homogeneous regions trend wavelet and influence of el nino southern oscillation |
| topic | drought rain precipitation time series analysis el nino-southern oscillation trends spatial distribution meteorological stations |
| url | https://hdl.handle.net/10568/119704 |
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