CHARACTERISATION OF RECENT AND FUTURE CLIMATIC TRENDS IN THE REGION OF GUELMIM (MOROCCO)

. According to the Intergovernmental Panel on Climate Change (IPCC), climate change is manifested by the increase in average surface atmospheric temperatures and a decrease in rainfall. The impacts are multiple, complex and differentiated from one region to another in the world. In the Guelmim region (southern Morocco), climate change is manifested by severe droughts and/or recurrent floods. The objective of this study is to characterize the recent and future climate variability in the Guelmim region based on time series of precipitation , the study period goes from 1985 to 2017, and from 2020 to 2099 using Standardized Precipitation Index (SPI).Results of SPI analysis indicate that the most notable droughts for their varying intensity, duration and frequency occurred during the 1992-94 and 1997-2000 periods. Future analysis indicates the study area will face several extended periods of drought and wet during 2020 to 2099. The results of this study show also the link between North Atlantic Oscillation and winter precipitation in Guelmim, which are associated with the negative phase of NAO. The purpose of the study is to have a good management of crops and water resources in Guelmim region and either to insure a sustainable management of environment.


Introduction
Some unexpectd impacts of climate change are beginning to become apparent at the regional level everywhere in the world. For example, over the past two centuries, the number of devastating floods is growing faster than other disasters [1]. The fast urbanism development has increased the risk of flooding. The Lack of adequate drainage systems, the construction encroaching on waterways, the reduction of green spaces and an inadequate planning have made many cities vulnerable to flash floods [2].
Morocco is not immune to these considerations. Indeed, recurrent droughts have prevailed for several years, from time to time by sudden and destructive thunderstorms causing devastating floods, which led to an early awareness of the danger posed by climate disturbances. Morocco recorded no less than 35 episodes floods between 1951 and 2015. Flash floods are capable of turning the dry beds of the "Oueds" into violent and destructive torrents [3]. For example, over the past 45 years, the major floods in the Guelmim's region have occurred in 1968, 1985, 2010 and 2014; These floods caused considerable damage [4].
The aim of this study is to characterize the variability of the climate of Guelmim , region which is located in southern Morocco ; and to study the evolution of recent and future climate through precipitation; as well as quantifying aridity by measuring the Standardized Precipitation Index (SPI). The interconnection between this index and the North Atlantic Oscillation (NAO) is also studied to understand its relation with winter precipitation.

Geographic location
Guelmim region is located at 200 km in the South of Agadir. The study area is the hydrological unit of Guelmim with a global area of about 10.000 Km 2 , it superimposed with the province of Guelmim.  Guelmim station is located at (29°1'N; 10°3' W) with an altitude of 300m. The climate of Guelmim region is tempered by oceanic influences. Annual rainfall is 135mm and the rainy season is limited to a few days where three-quarters of annual precipitation is recorded. The rainy season start from November to March but the dry season is observed for the remainder of the year.

The climate hydrology and urbanization of the study area
The most watered months are, November (38mm), December (16mm), January (14mm), February (20mm) and March (17mm), and the driest months start from April to October. The rainfall regime is characterized by a frequent dry periods with some few wet periods. The way the rains are distributed make the difference between the years. The average maximums relative humidity measured at the Guelmim station ranges between 70 and 93%; this is equivalent to dry air or moderately moist air. The average minimum relative humidity measured ranges from 21 to 57%.
The main Oued in the Hydrological Unit of Guelmim are: 1-The Oued Seyyad: it originates at 1200 m of altitude on the slopes of the Anti-Atlas, and its flow is in the East-West direction for 152 km and receives many affluents, especially on the right bank, this Oued delimits the Seyyad sub-basin; 2-Oued Bouissafene: it is 82 km long and its watershed totals 1964 km2. The river beds are few, this Oued delimits the Bouissaffene sub-basin; 3-Oued Aouiroera, 56 km in length, drains the sub-basin occupying the North West of the study area and covering an area of 1036 km2.  The hydrological unit of Guelmim belongs to the geological domain of the anti-Atlas. We encounter the phenomenon of water erosion, linked to the dynamics of water in different facies. The wind erosion is also encountered. We encounter also the phenomenon of desertification which is one of the problems that slow down the development of the region. The sanding phenomenon can also be caused by wind erosion, i.e. due to high winds combined with periods of severe drought.    In Guelmim rural exodus and population growth have led to a dynamic of urbanization which has led to a change in land occupation, and causes risky events, uncontrolled and unplanned growth, thus contributes to the outbreaks of floods, since the developed massifs makes the passages more narrow, as well as it decreases the capacity of the catchment area. This change in land use with weather and hydrological events contributed to the floods.

Dataset
Observations data of precipitation used in this study are derived from Global Historical Climatological Network (GHCN) [5] for the period from 1985 to 2017. For the analysis of precipitation variability, standardized precipitation index is studied rather than precipitation sums to overcome problems of statistical analysis arising from the strong spatial heterogeneity of rainfall sums. The station used have minimum availability of missing data. This data set has been extensively quality controlled.

Standardized Precipitation Index (SPI)
In general, droughts characterization can be done based on their duration, severity and spatiotemporal variability [6], drought can be characterized in multiple ways [7,8]. Drought indices are primary tools for defining different drought parameters, which include intensity, duration, severity and spatial extent. Several drought indices are developed in recent decades to quantify the drought for different time scales [9]. The Standardized Precipitation Index (SPI) [10,11] is employed due to its advantages over other drought indexes, which includes: -It is derived using rainfall records alone, so drought quantification is possible even if other hydrometeorological measurements are not available, -Due to its flexibility over various timescales, it is possible to describe a range of meteorological, hydrological and agricultural applications, -Due to its standardization, SPI ensures that drought quantification at any location and on any time scale are consistent.
The universal meteorological drought index, Standardized Precipitation Index (SPI), is recommended by the WMO and developed by McKee and all [10], is less complicated and used to quantify the precipitation deficit for multiple time scales , reflecting the impact of precipitation deficiency on the availability of various water supplies.
A criteria defined for classifying droughts based on SPI values as shown in The choice of the SPI Index is related to its advantages in terms of statistical coherence and the ability to describe and quantify the precipitation at multiple time scales, it also analyzes wet periods as well as dry periods which leads to the possibility of ensuring an early alert of drought and analyzing wet periods as well as periods Dry. In this study, the characteristics of precipitation variability in the Guelmim region are determined in by the use of the SPI. Monthly precipitation is used over 33 years . The temporal variability of precipitation is studied mainly by SPI applied to the different time series (1, 3, 6, 9 and 12 months).

Analysis of observed SPI index for the Guelmim station (1985-2017):
The monthly SPI_1mois (Figure 8) reflects short-term conditions; it is the meteorological drought; the years were the flooding occur in the region (1985 and 2014) has a maximum of SPI (3.0). For the rest of the years the SPI is located between -1 and 1.We note that the variation of drought for SPI_1month is uniform during the 40 years of the study, and has a period of one to two years during the period 1985-2008 and of two to three years during the period 2008-2017.
The quarterly SPI (Figure 8) reflects the weather drought and we have a quarter period where the value of the SPI exceeds 2 (extremely wet). Similarly, we have dries periods where the value of the SPI is less than -1.5. We note that the variation in drought for a period of three months have a periodicity of 8 to nine years, and reaches the maximum at 2010 (SPI =-2.44).
The variation in wet quarters have ten-year periodicity and reaches the maximum (SPI=-2.5). The semi-annual SPI (Figure 8 November 2014 (Flood Month) and a drought during the year 1992 (SPI= -2.9).
The annual SPI (Figure 8) (Figure 9) . In particular, the North Atlantic Oscillation (ONA) exerts some influence on Moroccan winter precipitation( Figure  9), which is negatively correlated to it, notably the western part of the Atlas Mountains [15].
In order to quantify the relationship between precipitation at Guelmim and NAO variability, a calculation of linear correlation coefficients between the SPI series (for the Guelmim station) and the NAO index over the period available (1985-2017) for different seasons and year has been established. The results of these correlations are illustrated in Figure 10 and 11: This curve in Figure 10 shows a fluctuation of NAO between the positive and the negative with NAO + 's dominance. Monthly trends in the SPI for Guelmim ( Figure 11) during the period 1985-2017 showed that we have 5 dries months which correspond to 80% in the NAO, this explain the rainfall deficits during these periods. SPI_3month ( Figure 11) showed 17 dries months, which correspond to 69.5% in the positive phase of NAO, this explain the rainfall deficits during these periods. The semi-annual SPI during the period 1985-2017 ( Figure  11) showed 15 dries months that correspond to 75% of the positive phase of NAO. The nine-month trends in the SPI index in Guelmim during the period 1985-2017 showed that we have 12 dries months that correspond to 50% of the positive phase of NAO which helps to explain the much of the rainfall deficits during these periods.
The annual SPI index in Guelmim during the period 1985-2017 ( Figure 11) showed that we have 10 hydrologically dries months in this station, which correspond to 46% of the positive NAO phase, that helps explain much of the rainfall deficits. Generally, the times series of SPI for different time scales shows an alternation of dry and wet periods for the region of Guelmim during the period from 2020 to 2099.
For the future SPI (1 month 2020-2099: Figure 13), we note six peaks of wet periods with a maximum in the year 2076 and 9 peaks of dry periods. For the future SPI (9 months 2020-2099: Figure 13), we note 15 peaks of wet with a maximum in the year 2042; and 14 peaks of drought with a maximum in the year 2056.
For the future SPI (12 months 2020-2099: Figure 13), we note 12 peaks of humidity with a maximum in the year 2042 and 13 peaks of drought with a maximum in the year 2025.

Conclusion
In this study, we have analyzed the variability of precipitation in Guelmim's region, which shows a strong irregular aspect with an overall trend of decreasing. The climate in Guelmim between 1985 entre 2017 showed a significant change in the annual and seasonal distribution. In this work, we have shown the link between North Atlantic Oscillation and precipitation in Guelmim. We can notice that the highly quantities of precipitations recorded during winter are associated with the negative phase of NAO.
The standardized precipitation index remains a very interesting tool for characterizing wet and dry periods. Through the analysis of this SPI index, we have detected a trend of increasing droughts in the future, we have also defined the driest periods in the recent as well as in the future. The Future SPI identifies a multitude and long periods of extreme droughts between the years 2020 and 2099.