Search

Based on data from 1966 to 2018, the present study analyses precipitation trends in the Zohreh–Jirahi basin in Iran. The homogeneity of data was estimated based on the Kolmogorov–Smirnov method. Missing data were reconstructed using inverse distance weighted (IDW) and ordinary-linear-kriging methods. The results were evaluated by the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). A multidimensional raster was generated containing precipitation values related to the statistical period years, and time-series data were produced in array format per unit area. Based on the period range, 34,267 points underwent the time-series analysis, and the trend change was assessed based on the Mann–Kendall method. The Sen’s slope was evaluated using yearly and monthly scales in these points, followed by producing raster maps. The IDW was selected with an R2 value of 0.95 as the optimal method of missing data reconstruction in this time period based on the model evaluation. The results showed no significant trends on a yearly scale, but on the monthly scale, December–April–November–August–September showed the highest ascending trends, respectively, February–December–March–May exhibited the highest descending trend, respectively, and June–July–September showed no trends. The maximum and minimum mean Sen’s Slope were estimated for December (0.213) and February (–0.68), respectively. Water resources management is inevitable, particularly in the agricultural sector as the main consumer with macro socioeconomic dimensions. Given the notable impact of water supply time to optimise and increase productivity, the current study can contribute to revising the cultivation patterns and time in the region. The recharge of aquifers, the storage process, and the consumption process should be compatible with forthcoming changes. [ABSTRACT FROM AUTHOR]

Understanding local-scale climate change is vital to developing adaptive strategies in the face of the century-old river of global warming posing a threat to humanity. This study focuses on assessing temperature and rainfall trends in Beni City, using monthly and yearly (1990–2020) weather station data. Climate variability was analysed using the standardised variable index, and rainfall concentration patterns were highlighted using the precipitation concentration index (PCI). The climate trends were analysed by using the Mann–Kendall test and Sen's slope estimator. The findings indicated that the Tmin is 18.82±0.62°C, and Tmax is 28.22±0.75°C, resulting in a mean temperature of 23.52±0.57°C. The annual and seasonal temperature trend analysis indicated that a significant warming trend was observed in both Tmin and Tmax. Beni City's precipitation trends also showed a mean annual rainfall of 1988.38±416.59 mm, with significant year-to-year variations. Annual rainfall analysis exhibited a slight upward trend; meanwhile, the seasonal trend analysis revealed an increase in rainfall during Mar–Apr–May (MAM) and Aug–Sep–Oct–Nov (ASON) seasons with roughly no discernible trend during Dec–Jan–Feb (DJF), and Jun–Jul (JJ) seasons. Overall, annual and seasonal analyses of specific temperature and rainfall patterns have shown pronounced warming and increased rainfall in the study area. Research highlights: The study reveals significant trends in temperature and rainfall in Beni city, Democratic Republic of Congo, over a 31-year period (1990–2020). Both minimum and maximum temperatures show significant warming trends, with the most recent decade witnessing substantial increases in maximum temperatures. Rainfall patterns exhibit variations, with a slight upward trend in annual rainfall, although the 1990s experienced a notable decrease in precipitation. Monthly analyses highlight specific temperature and rainfall patterns with some months experiencing pronounced warming and increased rainfall. [ABSTRACT FROM AUTHOR]

This study explores variations and trends in dry/wet days and spells over Banas River basin during 1961–2020. For this, daily rainfall data acquired from Water Resources Department of Rajasthan, India have been utilised. The variations have been identified in relation to number (dry/wet days and spells), mean and maximum length of dry/wet spells. For identifying trends, Mann–Kendall (MK), innovative trend analysis (ITA) and Sen’s slope estimator tests have been executed, whereas change points have been detected with the help of Pettit, Buishand range, standard normal homogeneity and Neumann ratio tests. In Banas River basin, dry days have been found much higher (330 days) as compared to wet (35 days), while the number of dry/wet spells has been found almost identical (18). A decreasing trend in dry days has been detected, whereas wet days have increased. In addition, change point detection tests have detected 1993 as the year of noteworthy change in dry/wet days and spells, whereas most of the stations witnessed such change in 1995 and 2009. These results will be valuable for water resource and risk reduction managers in managing the risks of drought and flood over the Banas River basin. [ABSTRACT FROM AUTHOR]

Mann–Kendall trend test and Sen's slope estimator method were used to find out significant changes in extreme climate indices for daily temperature and precipitation in Cherrapunji over the period from 1979 to 2020. In this study, 21 precipitation and temperature-based extreme climate indices were calculated using RClimDex v 1.9-3, among which six were derived from the number of days above nn mm rainfall (Rnn) according to India Meteorological Department (IMD) convention and the rest 15, in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). It was observed that, among all the indices, consecutive dry days (CDD), summer days (SU25) and very light rainfall (VLR) days increased significantly with 0.54, 1.58 and 0.14 days/yr, respectively, while only consecutive wet days (CWD) decreased significantly with 0.36 days/yr. A slight negative trend was observed in the case of tropical nights (TR20) and among the other precipitation indices as well. Again, the indices associated with daily maximum temperature increased significantly with 0.06–0.07°C/yr. For the indices associated with daily minimum temperature, almost no change or a slight negative change was observed, except a significant positive trend in February and significant negative trend in November for monthly minimum of daily minimum temperature (TNN) only. The analysis revealed that some of the extreme climate indices which explain the climatic conditions of Cherrapunji have shown statistically significant change over the period of 42 years and if this trend continues, then Cherrapunji will be under threat when it comes to climate change. [ABSTRACT FROM AUTHOR]