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DOI10.3390/hydrology11020027
Long-Term Spatiotemporal Investigation of Various Rainfall Intensities over Central India Using EO Datasets
Awasthi, Nitesh; Tripathi, Jayant Nath; Petropoulos, George P.; Kumar, Pradeep; Singh, Abhay Kumar; Dakhore, Kailas Kamaji; Ghosh, Kripan; Gupta, Dileep Kumar; Srivastava, Prashant K.; Kalogeropoulos, Kleomenis; Singh, Sartajvir; Singh, Dhiraj Kumar
发表日期2024
EISSN2306-5338
起始页码11
结束页码2
卷号11期号:2
英文摘要This study involved an investigation of the long-term seasonal rainfall patterns in central India at the district level during the period from 1991 to 2020, including various aspects such as the spatiotemporal seasonal trend of rainfall patterns, rainfall variability, trends of rainy days with different intensities, decadal percentage deviation in long-term rainfall patterns, and decadal percentage deviation in rainfall events along with their respective intensities. The central region of India was meticulously divided into distinct subparts, namely, Gujarat, Daman and Diu, Maharashtra, Goa, Dadra and Nagar Haveli, Madhya Pradesh, Chhattisgarh, and Odisha. The experimental outcomes represented the disparities in rainfall distribution across different districts of central India with the spatial distribution of mean rainfall ranges during winter (2.08 mm over Dadra and Nagar Haveli with an average of 24.19 mm over Odisha), premonsoon (6.65 mm over Gujarat to 132.89 mm over Odisha), monsoon (845.46 mm over Gujarat to 3188.21 mm over Goa), and post-monsoon (30.35 mm over Gujarat to 213.87 mm over Goa), respectively. Almost all the districts of central India displayed an uneven pattern in the percentage deviation of seasonal rainfall in all three decades for all seasons, which indicates the seasonal rainfall variability over the last 30 years. A noticeable variation in the percentage deviation of seasonal rainfall patterns has been observed in the following districts: Rewa, Puri, Anuppur, Ahmadabad, Navsari, Chhindwara, Devbhumi Dwarka, Amreli, Panch Mahals, Kolhapur, Kandhamal, Ratnagiri, Porbandar, Bametara, and Sabar Kantha. In addition, a larger number of rainy days of various categories occurred in the monsoon season in comparison to other seasons. A higher contribution of trace rainfall events was found in the winter season. The highest contributions of very light, light rainfall, moderate, rather high, and high events were found in the monsoon season in central India. The percentage of various categories of rainfall events has decreased over the last two decades (2001-2020) in comparison to the third decade (1991-2000), according to the mean number of rainfall events in the last 30 years. This spatiotemporal analysis provides valuable insights into the rainfall trends in central India, which represent regional disparities and the potential challenges impacted by climate patterns. This study contributes to our understanding of the changing rainfall dynamics and offers crucial information for effective water resource management in the region.
英文关键词rainfall; trend analysis; rain days; spatiotemporal; climate
语种英语
WOS研究方向Water Resources
WOS类目Water Resources
WOS记录号WOS:001172224500001
来源期刊HYDROLOGY
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/305955
作者单位University of Allahabad; Harokopio University Athens; Kamla Nehru Institute of Technology Sultanpur; Banaras Hindu University (BHU); Ministry of Earth Sciences (MoES) - India; India Meteorological Department (IMD); Banaras Hindu University (BHU); University of West Attica; Chandigarh University; Chandigarh University
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GB/T 7714
Awasthi, Nitesh,Tripathi, Jayant Nath,Petropoulos, George P.,et al. Long-Term Spatiotemporal Investigation of Various Rainfall Intensities over Central India Using EO Datasets[J],2024,11(2).
APA Awasthi, Nitesh.,Tripathi, Jayant Nath.,Petropoulos, George P..,Kumar, Pradeep.,Singh, Abhay Kumar.,...&Singh, Dhiraj Kumar.(2024).Long-Term Spatiotemporal Investigation of Various Rainfall Intensities over Central India Using EO Datasets.HYDROLOGY,11(2).
MLA Awasthi, Nitesh,et al."Long-Term Spatiotemporal Investigation of Various Rainfall Intensities over Central India Using EO Datasets".HYDROLOGY 11.2(2024).
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