Spatio-temporal analysis of trends and variability in precipitation across Morocco: Comparative analysis of recent and old non-parametric methods

Abstract

In the essence of climate change, a better understanding of the variation in precipitation patterns provides in-depth knowledge of water resource management and mitigation of floods and droughts, particularly in Morocco where rainfed agriculture is predominant. This paper investigates the precipitation variability over the whole country of Morocco. To that end, a monthly precipitation dataset of 78 rain gauges with more than 40 years of observation was used to investigate the spatial-temporal variability of precipitation. Moreover, the spatio-temporal trends variation was also assessed through a comparative analysis of the various trend detection methods (both old and new tests). The new methods were used also to identify non-monotonic sub-trends. The results highlighted that (1) Morocco has experienced considerably larger variations regarding the temporal variability of precipitations and their spatial distribution during the last few decades; (2) the greatest variability of precipitation was observed moving latitudinally from humid to arid regions; (3) the annual precipitation exhibited positive and negative trends where there was no clear evidence of upward or downward trends. The significant trends are identified for 5(6,41%), 6 (7,69%), 3 (3,84%), and 65 (83%) stations from the results of the MK test, SR test, Onyutha's method, and ITA method, respectively. (4) the MK, SR, and Onyutha methods exhibited similar trends which indicate that are in perfect concordance. The ITA method showed also some resemblance with the results of other methods even though it proved to be over-sensitive in determining trend significance; and (5) the highlands with a Mediterranean climate are prone to flooding whereas the regions with desertic and semi-arid climates are prone to drought. Overall, our findings allow policy-makers to properly design adaptation strategies for changing precipitation patterns as well as increasing extreme events (floods and droughts).