Assessment by statistical approach of climate change impact on water resources: application to the Gharb perimeter (Morocco)
In order to evaluate the climate change impact on water resources, we carry out in this work, a spatio-temporal statistical analysis of some water balance variables. In order to understand past climate variations, a statistical analysis must be made for representative time series both temporally and spatially. These data sets, however, often have irregularities and gaps in the measurements which hinder their direct use. For this reason, the statistical analysis used in this study was based on three steps: i) filling gaps of missing data using two imputation methods, namely multiple imputation by chained equations (MICE) and the k-nearest neighbour method (k-NN); ii) the detection within time series of significant changes that occurred in the past. Dates of these changes are characterized by breaks at the level of the mean of the studied climate variables. These breaks were confirmed by three statistical tests (Pettitt, Buishand, and Normal Homogeneity SNH); iii) the investigation of potential climate data trends by using statistical tests (Sen and Mann-Kendall) as well as with a projection technique for the future. As an application, we processed climate data from five weather stations in the Gharb perimeter, located in northern Morocco, for the periods 1974-2016 and 2021-2050. The results obtained showed that MICE imputation is the most efficient for all stations. For trends, while the series of temperatures, potential evapotranspiration, and water deficit showed significant upward trends over all time steps, the trends were non-significant for the precipitation series. The projections for 2021-2050 showed that we could witness a slight shift in the wettest season of the year and that the effect of warming would be greater from west to east in the Gharb perimeter due to the effect of continentality.