Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana
Highlights 1. Temperature and precipitation time series data from 1950 to 2020 were analyzed for the states of Haryana and Punjab. 2. SARIMA models provided the most accurate temperature predictions for both states, though precipitation predictions in July were sometimes overestimated. 3. SARIMA pro...
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| Format: | Article |
| Language: | English |
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Springer
2024-11-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-024-06380-5 |
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| author | Pankaj Dahiya Mohit Kumar Shilpa Manhas Ankit Saini Sunil Kumar Yadav Sanjeev Sirohi Mohit Kamboj Madan Lal Khichar Ekta Pathak Mishra Vipasha Sharma Vijender Kour Mohammad Reza Fayezizadeh |
| author_facet | Pankaj Dahiya Mohit Kumar Shilpa Manhas Ankit Saini Sunil Kumar Yadav Sanjeev Sirohi Mohit Kamboj Madan Lal Khichar Ekta Pathak Mishra Vipasha Sharma Vijender Kour Mohammad Reza Fayezizadeh |
| author_sort | Pankaj Dahiya |
| collection | DOAJ |
| description | Highlights 1. Temperature and precipitation time series data from 1950 to 2020 were analyzed for the states of Haryana and Punjab. 2. SARIMA models provided the most accurate temperature predictions for both states, though precipitation predictions in July were sometimes overestimated. 3. SARIMA provided better results than machine learning-based models, with lower RMSE, AIC, and BIC values. 4. Model forecasts can improve flood prediction, urban planning, and water resource management, benefiting scientists and decision-makers. |
| format | Article |
| id | doaj-art-b0cd63e3f07e4c3ead0edbee5704cd5f |
| institution | DOAJ |
| issn | 3004-9261 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-b0cd63e3f07e4c3ead0edbee5704cd5f2025-08-20T02:49:09ZengSpringerDiscover Applied Sciences3004-92612024-11-0161211610.1007/s42452-024-06380-5Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and HaryanaPankaj Dahiya0Mohit Kumar1Shilpa Manhas2Ankit Saini3Sunil Kumar Yadav4Sanjeev Sirohi5Mohit Kamboj6Madan Lal Khichar7Ekta Pathak Mishra8Vipasha Sharma9Vijender Kour10Mohammad Reza Fayezizadeh11Department of Agronomy, Lovely Professional UniversityDivision of Computer Applications, ICAR IASRIDepartment of Agronomy, Lovely Professional UniversityDepartment of Agronomy, Eternal University, Himachal PradeshICAR-KVK-PanchmahalDepartment of FEES, Statistics, CCSHAUDepartment of Agricultural Meteorology, CCSHAUDepartment of Agricultural Meteorology, CCSHAUGrow IndigoDepartment of Geography, Lovely Professional UniversityDepartment of Geography, Lovely Professional UniversityDepartment of Horticultural Science, Faculty of Agriculture, Shahid Chamran University of AhvazHighlights 1. Temperature and precipitation time series data from 1950 to 2020 were analyzed for the states of Haryana and Punjab. 2. SARIMA models provided the most accurate temperature predictions for both states, though precipitation predictions in July were sometimes overestimated. 3. SARIMA provided better results than machine learning-based models, with lower RMSE, AIC, and BIC values. 4. Model forecasts can improve flood prediction, urban planning, and water resource management, benefiting scientists and decision-makers.https://doi.org/10.1007/s42452-024-06380-5TemperaturePrecipitationForecastingARIMASARIMA |
| spellingShingle | Pankaj Dahiya Mohit Kumar Shilpa Manhas Ankit Saini Sunil Kumar Yadav Sanjeev Sirohi Mohit Kamboj Madan Lal Khichar Ekta Pathak Mishra Vipasha Sharma Vijender Kour Mohammad Reza Fayezizadeh Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana Discover Applied Sciences Temperature Precipitation Forecasting ARIMA SARIMA |
| title | Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana |
| title_full | Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana |
| title_fullStr | Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana |
| title_full_unstemmed | Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana |
| title_short | Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana |
| title_sort | time series study of climate variables utilising a seasonal arima technique for the indian states of punjab and haryana |
| topic | Temperature Precipitation Forecasting ARIMA SARIMA |
| url | https://doi.org/10.1007/s42452-024-06380-5 |
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