Storms Properties at Bouregreg and Chaouia Region in Morocco

INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 01, JANUARY 2020 ISSN 2277-8616

Storms Properties At Bouregreg And Chaouia Region In Morocco

Khalid Barkouki, Ilias Kacimi, Najat Serhir, Abdelaziz Zerouali, Mohammed Abdellah Ezzaouini

Abstract: In the present research, an analysis of the properties of instantaneous rainfall was carried out on the basis of storms analysis. Based on several values of the minimum inter-event time (MIET), the analysis of storms characteristics concerned durations and depths of storms as well as the classification of storms according to their quartiles. A comparison of the obtained results with the spatial distribution of the rain gauges was also carried out. The database used contains mainly the instantaneous rainfall available at 25 automatic rain gauges covering the period 2009-2016. The analysis presented in this article constitutes the first research of its kind in the analysis of instantaneous rainfall in the Moroccan context; it shows the impact of the MIET on the temporal and spatial characteristics of the selected storms.

Index Terms: Instant rainfall, storm, storm duration, storm depth, quartiles, minimum iner-event time (MIET), Morroco’s data. ——————————  ——————————

1 INTRODUCTION 2.1 Study area Flood protection or stormwater drainage projects rely on The research concerns the area monitored by the Hydraulic rainfall as the main input to estimate runoff. Some estimating Basin Agency of Bouregreg and Chaouia (HBABC), located in methods or models require rainfall data with short time steps. the center-west of Morocco. The area covers 20,470 km², The lack of this data is sometimes bypassed by using "design constituting 3% of the country's territory. The area monitored storm" [1]. The statistical characteristics analysis of the by the HBABC includes the two administrative and economic observed hyetographs allow an understanding of temporal capitals of Morocco. It is an area with a big urban dynamic and distribution of rainfall [2] and subsequently the development of concentrates most of the economic activities. The average "design storm" that can be used by designers in our study annual rainfall varies from 300 mm in the southern borders of area. The objective of this work is to understand the the Plateau zone (Settat-Ben Ahmed), to 450 mm / year at characteristics of instant rainfall in the study area. It is the first Rabat, and reaches nearly 750 mm / year in the high altitude of its kind in the Moroccan context, taking into account the zone at the East (Oulmes). approach followed, the analysis performed, the size of the instantaneous data used and the results obtained. Thus, an 2.2 Used data effort was dedicated to the data collection and the data quality The rainfall data used were collected from the HBABC. They control, in order to ensure a good basis of the treatments are composed mainly of instantaneous rainfall of 27 automatic carried out. The data processing was automated through the rain gauges, which were recorded from 2009 to 2016 (see development of scripts under the Rstudio to facilitate the table 1 and figure 3). The time step for the recordings is 5 iterative work. Indeed, Rstudio is a widely used platform for the minutes. These rain gauges are distributed throughout the analysis, the statistical processing and big data visualization. study area. Available rains range from 2 years to 7 years with an average duration of 6 years. At certain stations, there is also daily rainfall for rain gauges installed since 1968. This

2 STUDY AREA AND DESCRIPTION OF USED data have been confronted with instant rainfall to check the DATA quality of the instant rainfall. Recordings of instantaneous rainfall at two rain gauges were discarded due to a large ———————————————— difference with the daily rainfall observed. To verify certain dubious recordings of instantaneous rainfall, the Intensity- • Khalid BARKOUKI is a civil Engineer. Currently, he is a Ph.D Duration-Frequency (IDF) curves available in the cities of student at the Laboratory of Geosciences, Water and Environment of the Water Center, Natural Resources, Environment and Rabat, Casablanca and Nouacer (south of Casablanca) were Sustainable Development, Faculty of Sciences, Mohammed V also used. These IDF curves were developed on the basis of University, Morocco. E-mail: [email protected] instant rainfall by the Directorate of National Meteorology in • Ilias KACIMI is a Hydrologist and Hydrogeologist, Professor and Morocco and cover the periods 1960-2006, 1960-2013 and Head of the Department of Geology, Coordinator of the Laboratory 1970-2013, respectively. of Geosciences, Water and Environment of the Water Center, Natural Resources, Environment and Sustainable Development of th e Faculty of Sciences at the University Mohammed V, Morocco. E -mail: [email protected] • Najat SERHIR is a professor of hydrology and researcher at the laboratory of Civil Engineering, Hydraulic, Environment and Climate of the Hassania School of Public Works, Morocco. E-mail: [email protected] • Mr Abdelaziz ZEROUALI is a hydrogeologist Engineer, he is also an expert in water resources management. Actually, he is the Director of Hydraulic Basin Agency of Bouregreg and Chaoui in Ben Slimane, , Morocco. E-mail: [email protected] • Mr Mohammed Abdellah EZZAOUINI is a Meteorologist Engineer. Currently, he is a Ph.D student at the Laboratory of Geosciences, Water and Environment of the Water Center, Natural Resources, Environment and Sustainable Development, Faculty of Sciences, Mohammed V University, Morocco. E-mail: [email protected] • Morocco. E-mail: [email protected] 2018 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 01, JANUARY 2020 ISSN 2277-8616

TABLE 1

RAINFALL DATA USED

1. The threshold of the rainfall depth: The analysis of the 3 MATERIALS AND METHODS IDF curves available in the study area shows that the centennial rain of 60 min and 240 min are 12.6 mm and 3.1 Data quality control 20.6 mm respectively. Thus, the threshold of 12.7 mm, Before using the available data, it is recommended to check generally used in similar studies at other countries, can their reliability [3]. Indeed, the data control performed consists be adopted. of: 2. In addition, and taking into account that the series of 1. A comparison of instantaneous rainfall and daily rainfall instantaneous rainfall available are not very long, we [4] available at the same rain gauges : This is a adopt the same threshold for the different groups of comparison between the cumulative instantaneous durations defined below. rainfalls and the cumulative daily rainfalls. If there is a 3. The dry period (no rain) or the minimum inter-event significant difference, the percentage of missing data is time (MIET): To give more flexibility to the use of the analyzed in the instantaneous rainfall or the detected results obtained, we analyze the characteristics of deviations are checked by zooming in concerned storms for several values of minimum inter-event time. period. The MIET adopted are 0.5 h, 1 h, 2 h, 6 h, 12 h and 24 2. A comparison of the instantaneous rainfall with the high h. intensities calculated from the IDF curves available in 4. The classification of storms according to groups of the zone [5]: Any recording exceeding a given threshold duration: in the Moroccan context, the temporal was verified (10 mm as centennial rainfall in 5min). This synthetic distributions of the precipitations used are approach has been very useful at the rain gauges generally 4 h and 24 h. In order to analyze the which only the instantaneous rainfall is available. characteristics of the instantaneous rainfall for several Doubtful values were rejected. intervals of duration, the storms selected were divided into groups of 0 h to 4 h, 4 h to 6 h, 6 h to 12 h, 12 h to 3.2 Storms classification 24 h and more than 24h. For the extraction of storms, the following criteria have been 5. The classification of storms by quartile groups: Storms used [6] : were ranked according to quartiles. Groups adopted 2019 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 01, JANUARY 2020 ISSN 2277-8616

are 0 to 25% (Q = 1), 25 to 50% (Q = 2), 50 to 75% (Q From the results summarized in table 2, we remarque that: = 3), 75 at 100% (Q = 4). 1. The MIET has a large impact on the distribution of the observed storms by groups of durations as shown in To facilitate the treatment of instantaneous rainfall, the the results summarized in table 2. Indeed, for the group classification of storms and the analysis of the results of 0-4h, the percentage of storms is inversely obtained, scripts have been developed under the Rstudio proportional to the MIET. By increasing MIET, the allowing to reduce working time (see figure 1). percentage of storms decreases exponentially. On the other hand, for storms lasting more than 24 hours, the increase of MIET causes an increase in the percentage of storms retained ; 2. For the storms of the group 4h-6h, 6h-12h and 12h- 24h, the maximum percentage of the storms corresponds to MIET of 1 h, 2 h and 6 h respectively ; 3. The total of retained storms increases according to the MIET following a logarithmic trend as shown in the figure 2.

Fig. 1. Data processing process [8]

Fig. 2. Number of storms selected according to MIET

4 RESULT AND DISCUSSION To facilitate rainfall classification analysis by rain gauge, taking During data processing, special attention was paid to the into account their spatial distributions, the results were minimum inter-event time. The following results will show its presented in map format (figure 3 to figure 8). By presenting impact on the characteristics of the selected storms. Taking the percentage of the groups of durations at each rain gauge into account the large number of tables, graphs and maps for the same MIET, we notice the same tendency of the developed from the analyzed data, the following paragraphs statistics at the various rain gauges. For example, for a MIET present only the necessary elements summarizing the results of 24 h, storms retained in the majority of rain gauges have obtained and some examples of prepared graphs. duration greater than 24 hours. The same remark can be done

for a MIET of 2h, the storms selected are divided between 4.1 Storms durations durations of 6 h-12 h and 12 h-24 h. The analysis of the spatial Based on a cumulative rainfall of instantaneous data, distribution of the storms groups of durations shows a regional threshold of 12.7 mm and a variable MIET, the following table trend with the exception of the Tighza rain gauge. Indeed, the summarizes the number of storms selected by groups of average percentage of the instantaneous data available at the durations. said point is 13% for 2 years. Thus, the statistics at this rain

gauge are not representative. TABLE 2

DISTRIBUTION OF THE STORMS SELECTED BY GROUPS OF DURATIONS ACCORDING TO THE DIFFERENT MIET

. Classification of the storms selected according to their durations at each rain gauge - MIET=24h Fig. 3

Fig. 4. Classification of the storms selected according to their durations at each rain gauge - MIET=12h

Fig. 5. Classification of the storms selected according to their durations at each rain gauge - MIET=6h

Fig. 6. Classification of the storms selected according to their durations at each rain gauge - MIET= 2 h

Fig. 7. Classification of the storms selected according to their durations at each rain gauge - MIET=1h

Fig. 8. Classification of the storms selected according to their durations at each rain gauge - MIET=0.5h

4.2 Storms depths The analysis of storms depths was made for the different

values of the MIET and the groups of durations adopted. Table lower and upper edges of the box represent the quartiles of 3 summarizes the results obtained. By varying the MIET, the 25% and 75% at each rain gauge. The horizontal line inside variation of the average of storm depth in the same duration the box represents the median. While the upper and lower group remains low. For the same MIET, the mean storms horizontal lines outside the box represent respectively 25% depths usually increase with the increase of the storms minus 1.5 IQR and the quartile 75% plus 1.5 IQR. IQR is the duration. This increase becomes important at the group of interquartile range corresponding to the quartile at 75% minus durations longer than 24 hours. For the values (1) to (5) (Table the quartile at 25% [7]. The width of the boxes is proportional 3), the average values obtained are indicative taking into to the square root of the number of observations per group. account the limited number of storms selected (see Table 2). The analysis of the storms depths, at each rain gauge, shows a regional tendency. Indeed, for a MIET of 24h for example (Fig. 9), the median values of storms depths vary between 19 TABLE 3 mm and 33 mm with an average of 25 mm. Storms depths have an asymmetrical distribution with respect to the median. AVERAGE STORMS DEPTHS BY GROUPS OF DURATIONS ACCORDING TO DIFFERENT MIET In fact, the storms depths above the median are distributed over a wider range than the storms depths below the median. The analysis of the results corresponding to a 2-hour MIET (Fig. 11) confirms the same conclusions of 24-hour MIET.

Fig. 9. Box-whisker plot of rain storm depths- MIET=24h

Fig. 10. Box-whisker plot of rain storm depths- MIET=2h

To evaluate the spatial variability of storms depths, an analysis was made by Box-whisker plot . For the Box-whisker plot, the 2024 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 01, JANUARY 2020 ISSN 2277-8616

4.3 Quartiles 4.4 Seasonal distribution of storms Selected storms were ranked according to their quartiles. The Selected storms are divided mainly between three seasons: following figures present two examples (MIET = 24h and MIET spring, autumn and winter. This conclusion is valid for the = 0.5h) of dimensionless storms retained. different MIET values used.

TABLE 5 SEASONAL DISTRIBUTION OF STORMS

For a monthly time step, the majority of storms are recorded between October and April. They constitute 90% of all selected storms. Also, the number of selected storms per season is proportional to the MIET. In other words, decreasing the MIET Fig. 11. Classification of storms according to their quartiles makes the number of retained storms smaller. Indeed, the (MIET=24h) [9] decrease of the MIET generates a division of the storms of long durations in storms of small durations. Thus, some storms become below the threshold of 12.7 mm and are subsequently discarded. The confrontation of table 2 and figure 13 shows that the shortest storms are concentrated in the month of November. On the other hand, the storms of January, February and March are rather long durations.

Fig. 12. Classification of storms according to their quartiles (MIET=0.5h)

The analysis of selected storms shows that the percentage of quartiles is slightly impacted by the variation of MIET. Thus, in average 32%, 25%, 21%, 22% of storms belong to quartiles 1, 2, 3 and 4 respectively. The detailed results corresponding to each MIET are summarized in table 4.

Fig. 13. Monthly storms distribution (number of storms per month) TABLE 4 PERCENTAGE OF QUARTILES ACCORDING TO MIET 4 CONCLUSION The objective of this research is to analyze the characteristics of storms in area monitored by the Hydraulic Basin Agency of Bouregreg and Chaouia (HBABC) in Morocco. Analysis was based on instantaneous rainfall database. It concerns 25 automatic rain gauges covering the period 2009-2016. The series used cover periods ranging from 2 years to 7 years with an average duration of 6 years. Important conclusions allowing an understanding of the instantaneous rain in the study area has been concluded. The results obtained show that:

logarithmic tendancy according to the MIET: an instantanées au niveau de Bouregreg et la Chaouia au equation has been proposed to estimate the number of Maroc’, in 2nd Edition of the Doctoral Seminar of Earth storms according to the MIET used; Sciences, 2018. 2. The decrease in MIET favors the selection of storms of [9] K. Barkouki, I. Kacimi, N. Serhir, and A. Ezzahoum, short durations; ‘Analysis of instant rainfall at bouregreg and chaouia 3. The spatial analysis of storms duration groups shows a region in morocco’, in 16th Plinius Conference on homogeneous tendency at the different rain gauges Mediterranean Risks, 2018, vol. 9. used; 4. By varying the MIET, the variation of the average values of storms depths in the same groups of duration remains low; 5. Regional homogeneity was observed in the storms depths for the different MIET used; 6. The classification of storms according to their quartiles is independent of the MIET used: In average, 57% of the storms selected are 1st and 2nd quartiles. While the remaining 43% is distributed between the 3rd and 4th quartile; 7. 90% of selected storms are occurring between the months of October and April. The shortest storms are concentrated in the month of November. While, storms of January, February and March are rather long durations.

Thus, taking into account the impact of the MIET on certain results obtained, it is concluded that the choice of the MIET must take into account the objectives of use of the selected storms. The extracted data in this research can be used for the preparation of synthetic rainfall distribution adapted to the study area. The development of these distributions must take into consideration the characteristics of the storms extracted especially the impact of the MIET on the results obtained.

5 ACKNOWLEDGMENT We are grateful to Hydraulic Basin Agency of Bouregreg and Chaouia (HBABC) for providing great help in data collect process which is a very important step in this work. Our gratitude goes especially to Abdelaziz ZEROUALI (Director), Mohammed Abdellah EZZAOUINI (Division Manager), Ayoub NAFII (Engineer) and Ilham RADOUANE (Manager).

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