Assessment of spatiotemporal variability of rainfall and surface wind speed over the eastern coastal agro-ecological zones of India using advanced trend detection approaches

Paramaguru, P.; Panda, Kanhu Charan; Suna, Truptimayee; Rajput, Jitendra

doi:10.1007/s00704-023-04556-4

Theor Appl Climatol

2023

DOI: 10.1007/s00704-023-04556-4

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Assessment of spatiotemporal variability of rainfall and surface wind speed over the eastern coastal agro-ecological zones of India using advanced trend detection approaches

P. Paramaguru¹,

Kanhu Charan Panda

Truptimayee Suna

et al.

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Cited by 2 publications

References 104 publications

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Advanced CMD predictor screening approach coupled with cellular automata-artificial neural network algorithm for efficient land use-land cover change prediction

Panda,

Singh,

Singh

2024

Journal of Cleaner Production

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Advanced CMD predictor screening approach coupled with cellular automata-artificial neural network algorithm for efficient land use-land cover change prediction

Panda,

Singh,

Singh

2024

Journal of Cleaner Production

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Trend detection and change point analysis of inflows in Karuppanadhi and Gundar dams of Chittar River Basin, Tamil Nadu, India

Anusty J,

Singh,

Khanna

et al. 2023

Water Practice &Amp; Technology

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Gaining insights into the patterns of hydroclimatic elements such as inflows to dams is essential to adeptly strategize and oversee water resource planning. For this investigation, we focused on Karuppanadhi and Gundar dams within the Chittar River Basin in Tamil Nadu. We employed various time series trend assessment methods – Mann–Kendall (MK), modified Mann–Kendall (MMK), Sen slope estimator, and innovative trend analysis (ITA). Furthermore, we conducted change point detection analysis using homogeneity tests, namely Pettitt's test, standard normal homogeneity test (SNHT), and Buishand test. The analysis was carried out across three-time scales: monthly, seasonal, and annual for 30 years (1991–2020) span. Results revealed declining trends significantly across all three timescales for the Karuppanadhi dam. Whereas for the Gundar dam, notable trends included increased patterns in January, March, December, and the winter season, while other months/seasons showed statistically decreasing trends. ITA exhibited greater sensitivity in identifying trends at monthly and seasonal scales, indicating its superior trend detection over MK and MMK methods. Change point analysis of trends identified a rising trend in August post-2017 for both dams. Other change points indicated decreasing inflow trends thereafter. Analysing trends and change points in dam inflows aid decisions on water resources management.

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Assessment of spatiotemporal variability of rainfall and surface wind speed over the eastern coastal agro-ecological zones of India using advanced trend detection approaches

Cited by 2 publications

References 104 publications

Advanced CMD predictor screening approach coupled with cellular automata-artificial neural network algorithm for efficient land use-land cover change prediction

Advanced CMD predictor screening approach coupled with cellular automata-artificial neural network algorithm for efficient land use-land cover change prediction

Trend detection and change point analysis of inflows in Karuppanadhi and Gundar dams of Chittar River Basin, Tamil Nadu, India

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