Future Predictions of Precipitation and Discharge Using CMIP5 Models in the Western Ghats Region, India
| Autor: | Shilpa A. Veerabhadrannavar and B. Venkatesh |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Nature Environment and Pollution Technology, Vol 21, Iss 5, Pp 2201-2209 (2022) |
| Druh dokumentu: | article |
| ISSN: | 0972-6268 2395-3454 |
| DOI: | 10.46488/NEPT.2022.v21i05.014 |
| Popis: | Climate change is expected to exacerbate the hydrological cycle globally and have a significant impact on water resources. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report states that observed and projected increases in both temperature and precipitation variability are the main reasons for projected climate change impacts on natural water resources. The examination of meteorological variables of the region, especially when agriculture is rainfall dependent, is very essential to formulate feasible adaptation strategies. As a result, using CORDEX-SA (Coordinated Regional Downscaling Experiment-South Asia) rainfall data (2021 to 2050), trend analysis was used to examine variations in rainfall data in the Kokkarne catchment of the Seetha river basin. Regression analysis was used to identify the season-wise rainfall trend. Annual, Summer, Monsoon, and Winter rainfall have depicted increasing trends with a rate of 2.46, 1.21, 2.77, and 0.009 mm per year respectively. The post-monsoon rainfall has projected a declining trend with a rate of -1.54 mm per year. Hence it is recommended that the designed strategies in the agricultural sector have to take the increasing, decreasing, and erratic nature of the trend of rainfall into consideration. Further considering the use of a Multi-Model Ensemble (MME) is reducing the SD and CV of rainfall data by 862 mm and 48.5% respectively. 87% of annual rainfall is contributed by monsoon season only with a Standard deviation of 424.4 mm and CV of 12%. |
| Databáze: | Directory of Open Access Journals |
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