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<p>This study evaluates the trends and variations in annual, seasonal and monthly rainfall over the Narmada River basin during 1981–2020 and examines its relationship with geographical and climatic factors. The time-series data on different parameters (rainfall, temperature, sea surface temperature (SST), dipole mode index (DMI), and oceanic niño index (ONI)) have been obtained from the secondary sources and analysed using different statistical measures (average, percentage, standard deviation (SD), coefficient of variation (CV), and correlation coefficient) and trend tests (parametric and non-parametric). The results have revealed large interannual variations in the occurrence of rainfall, varying from 667.90&#xa0;mm in 2000 to 1583.98&#xa0;mm in 2013, with a mean value of 1063.67&#xa0;mm (CV = 19.78 percent and SD = 203.42&#xa0;mm). At a seasonal scale, the highest rainfall has been observed in the monsoon season (973.53&#xa0;mm), followed by the post-monsoon (41.41&#xa0;mm), winter (26.61&#xa0;mm), and pre-monsoon (22.57&#xa0;mm), indicating that rainfall distribution is primarily controlled by southwest monsoon over the basin. Likewise, monthly distribution shows that more than 90 percent of annual rainfall pours only in four months (June–September). Further, trend analysis has revealed a non-significant increase in annual (1.97&#xa0;mm), monsoon (2.54&#xa0;mm), and pre-monsoon (0.17&#xa0;mm) rainfall, whereas post-monsoon (-0.27&#xa0;mm) and winter (−0.16&#xa0;mm) seasons have demonstrated decreasing tendencies. The majority of the rainfall excess (deficit) years have occurred with positive (negative) Indian Ocean dipole (IOD) and negative (positive) ONI years. Notably, rainfall has been found positively correlated with latitude, longitude, elevation, SST, and DMI, whereas air temperature and ONI have affected it negatively. Finally, the findings of the present study may help the planners, water resource administrators, and risk-reduction managers in formulating policies related to the management and sustainable use of regional water resources, designing hydraulic structures, forecasting floods and droughts, and resolving the issues associated with these extreme events.</p>

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Spatio-temporal Variability, Trends and Key Drivers of Rainfall over Narmada River Basin, India

  • 期刊论文

  • 发表日期：

    2025年6月5日

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  • Jyoti Sharma,
  • Omvir Singh

摘要

This study evaluates the trends and variations in annual, seasonal and monthly rainfall over the Narmada River basin during 1981–2020 and examines its relationship with geographical and climatic factors. The time-series data on different parameters (rainfall, temperature, sea surface temperature (SST), dipole mode index (DMI), and oceanic niño index (ONI)) have been obtained from the secondary sources and analysed using different statistical measures (average, percentage, standard deviation (SD), coefficient of variation (CV), and correlation coefficient) and trend tests (parametric and non-parametric). The results have revealed large interannual variations in the occurrence of rainfall, varying from 667.90 mm in 2000 to 1583.98 mm in 2013, with a mean value of 1063.67 mm (CV = 19.78 percent and SD = 203.42 mm). At a seasonal scale, the highest rainfall has been observed in the monsoon season (973.53 mm), followed by the post-monsoon (41.41 mm), winter (26.61 mm), and pre-monsoon (22.57 mm), indicating that rainfall distribution is primarily controlled by southwest monsoon over the basin. Likewise, monthly distribution shows that more than 90 percent of annual rainfall pours only in four months (June–September). Further, trend analysis has revealed a non-significant increase in annual (1.97 mm), monsoon (2.54 mm), and pre-monsoon (0.17 mm) rainfall, whereas post-monsoon (-0.27 mm) and winter (−0.16 mm) seasons have demonstrated decreasing tendencies. The majority of the rainfall excess (deficit) years have occurred with positive (negative) Indian Ocean dipole (IOD) and negative (positive) ONI years. Notably, rainfall has been found positively correlated with latitude, longitude, elevation, SST, and DMI, whereas air temperature and ONI have affected it negatively. Finally, the findings of the present study may help the planners, water resource administrators, and risk-reduction managers in formulating policies related to the management and sustainable use of regional water resources, designing hydraulic structures, forecasting floods and droughts, and resolving the issues associated with these extreme events.