Spatiotemporal Analysis of Extreme Precipitation Characteristics for Prairie Region of Canada. Mirza, M. M. Q., Gough, W. A., & Noorisameleh, Z. In Chenchouni, H., Zhang, Z., Bisht, D. S., Gentilucci, M., Chen, M., Chaminé, H. I., Barbieri, M., Jat, M. K., Rodrigo-Comino, J., Panagoulia, D., Kallel, A., Biswas, A., Turan, V., Knight, J., Çiner, A., Candeias, C., & Ergüler, Z. A., editors, Recent Advancements from Aquifers to Skies in Hydrogeology, Geoecology, and Atmospheric Sciences, pages 259–261, Cham, 2024. Springer Nature Switzerland.
doi  abstract   bibtex   
The Canadian Prairies are identified as a potential climate change “hotspot” due to their relatively high latitude and central location on the continent. Agriculture is very vital in the southern part of the region, particularly the Prairie’s ecozone. Droughts are a frequent visitor in this region and so as floods from convective heavy precipitation events. Over a 24-h period, one single extreme precipitation event could deliver more than 25% of the mean annual precipitation. The behavior of extreme precipitation poses many challenges to flood management, adaptation, and coping mechanisms. The goal of this research is to uncover temporal and spatial aspects of 24-h maximum precipitation in the Canadian Prairie region, including change points, trends, long-term persistence, spatial correlation, upper tail properties, and any clustering to facilitate adaptation and coping mechanisms to extreme floods. 24-h precipitation data collected by tipping bucket rain gauges (TBRG) for 26 stations distributed across Alberta, Manitoba, and Saskatchewan provinces were used. We have investigated abrupt changes in the first two moments of the distribution by applying the Pettit test. The lag-1 (r1) serial correlation coefficient was used to calculate the auto- or serial correlation in the extreme rainfall datasets. The pre-whitening scheme was applied where there was statistically significant serial correlation before trend analysis. Nonparametric Mann–Kendall (MK) test and Theil-Sen’s slope estimator were applied for trend detection at 5% significance level. The presence of long-term persistence determined by estimating the Hurst exponent. Statistical modeling was conducted by applying the generalized extreme value (GEV) distribution. The results of the trend analysis suggest that the 24-h extreme precipitation trend is decreasing. Hurst exponent of \textgreater 0.5 was found in 65% of the stations demonstrating long-term persistence, while the remaining 35% showed no long-term persistence. In general, 24-h extreme precipitation in the Prairie region is heavy tailed as found in the GEV analysis. All three GEV parameters demonstrate a pronounced decreasing trend from the north to the south while plotted against latitude. Plotted map of 100-year return period values displays three clusters of high precipitation and flood vulnerable areas. One is in the northwest of Alberta and the other two in the South of Saskatchewan and Manitoba.
@inproceedings{mirza_spatiotemporal_2024,
	address = {Cham},
	title = {Spatiotemporal {Analysis} of {Extreme} {Precipitation} {Characteristics} for {Prairie} {Region} of {Canada}},
	isbn = {978-3-031-47079-0},
	doi = {10.1007/978-3-031-47079-0_58},
	abstract = {The Canadian Prairies are identified as a potential climate change “hotspot” due to their relatively high latitude and central location on the continent. Agriculture is very vital in the southern part of the region, particularly the Prairie’s ecozone. Droughts are a frequent visitor in this region and so as floods from convective heavy precipitation events. Over a 24-h period, one single extreme precipitation event could deliver more than 25\% of the mean annual precipitation. The behavior of extreme precipitation poses many challenges to flood management, adaptation, and coping mechanisms. The goal of this research is to uncover temporal and spatial aspects of 24-h maximum precipitation in the Canadian Prairie region, including change points, trends, long-term persistence, spatial correlation, upper tail properties, and any clustering to facilitate adaptation and coping mechanisms to extreme floods. 24-h precipitation data collected by tipping bucket rain gauges (TBRG) for 26 stations distributed across Alberta, Manitoba, and Saskatchewan provinces were used. We have investigated abrupt changes in the first two moments of the distribution by applying the Pettit test. The lag-1 (r1) serial correlation coefficient was used to calculate the auto- or serial correlation in the extreme rainfall datasets. The pre-whitening scheme was applied where there was statistically significant serial correlation before trend analysis. Nonparametric Mann–Kendall (MK) test and Theil-Sen’s slope estimator were applied for trend detection at 5\% significance level. The presence of long-term persistence determined by estimating the Hurst exponent. Statistical modeling was conducted by applying the generalized extreme value (GEV) distribution. The results of the trend analysis suggest that the 24-h extreme precipitation trend is decreasing. Hurst exponent of {\textgreater} 0.5 was found in 65\% of the stations demonstrating long-term persistence, while the remaining 35\% showed no long-term persistence. In general, 24-h extreme precipitation in the Prairie region is heavy tailed as found in the GEV analysis. All three GEV parameters demonstrate a pronounced decreasing trend from the north to the south while plotted against latitude. Plotted map of 100-year return period values displays three clusters of high precipitation and flood vulnerable areas. One is in the northwest of Alberta and the other two in the South of Saskatchewan and Manitoba.},
	language = {en},
	booktitle = {Recent {Advancements} from {Aquifers} to {Skies} in {Hydrogeology}, {Geoecology}, and {Atmospheric} {Sciences}},
	publisher = {Springer Nature Switzerland},
	author = {Mirza, M. Monirul Qader and Gough, William A. and Noorisameleh, Zahra},
	editor = {Chenchouni, Haroun and Zhang, Zhihua and Bisht, Deepak Singh and Gentilucci, Matteo and Chen, Mingjie and Chaminé, Helder I. and Barbieri, Maurizio and Jat, Mahesh Kumar and Rodrigo-Comino, Jesús and Panagoulia, Dionysia and Kallel, Amjad and Biswas, Arkoprovo and Turan, Veysel and Knight, Jasper and Çiner, Attila and Candeias, Carla and Ergüler, Zeynal Abiddin},
	year = {2024},
	keywords = {Characteristics, Climate change, Extreme precipitation, Frequency and Prairies},
	pages = {259--261},
}
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