沙漠研究 19-1, 331- 334 (2009 )Journal of Arid Land Studies“Desert Technology IX ”
Refereed Paper

Drought Impact on the Olive-Trees in the Tunisian Jeffara
Hanen DHAOU1, Dalel OUERCHEFANI1, Houcine TAAMALLAH1,Gabriels DONALD2, Mohamed OUESSAR1
Abstract: In spite of its high adaptation capacities and also its aptitude to grow in the arid
areas, the olive-tree did not escape to the negative effects of the drought resulting usually in afall of the production, the accentuation of the alternation production cycle and in some ultimate
cases by the withering of the olive-tree. This work concerned the study of drought impact onolive-growing plantations in the Tunisian Jeffara (province of Médenine). It aim at
characterizing the rainfall deficit observed in the study zone during the period 1999-2002, andto identify the meteorological drought intensity differences in the same region. The rainfall
data from two gauging stations: Médenine (1903-2002) and Zarzis (1908-2002), were analyzed
using several indices. It was found that drought is a recurring phenomenon in the study zone.
The occurrence of successive dry years is less frequent in the costal zones than in the otherlocalities. The year 2000-2001 is founded the most exceptional dry period which affected
negatively the development and the growth of the olive trees resulting in partial or complete
loss of a large number of olive-trees.
Keywords: Arid areas, Drought indices, Olive trees

1. Introduction
Historically, drought is known to affect periodically and withvarying intensities the Mediterranean basin regions, Africa, Asia,
Australia and America. In fact, their geographical positions make thatcertain areas receive more rainfall than others (Trabelsi, 1992). Tunisia,
for example, due to its position between the polar and Saharan weather
systems, is often threatened by climatic disturbances resulting generally
in the emergence of drought conditions (Trabelsi, 1992; Benzarti et al.,2001) which can prevail for one month, one season, one year and caneven persist for two or three consecutive years. In this case, the water
shortage and the yearly and the seasonally variability of rainfall generate
hardships especially for agriculture related activities. In addition, its
effect on the arboriculture plantations is variable from one site to another. Fig. 1. Geographical location of thestudy area.
Some groves resisted the water deficit but others were subject to partial
or total parching though this inheritance is made mainly of olive-tree,
known by its high capacity of adaptation to different bio-climate from the country and also its aptitude to beplanted in arid areas (Alouini et al., 1999). It is in this framework that this study was devoted to the analysis of
the rainfall deficit during the last two decades and particularly the last drought (1999/2000-2001/2002) which
affected the Tunisian Jeffara (province of Médenine) (Fig. 1) in terms of frequency, duration, intensity difference
in order to explain the damages caused to the olive tree groves.
2. Materials and Methods
2.1. Assessment of the drought impact on the olive trees
In order to assess the drought impacts on the olive trees groves in the region, the regional department of
the Ministry of Agriculture (CRDA) in Médenine, made a census of the state of the olive trees during the threeconsecutive dry years (1999/2000-2001/2002).
2.2. Rainfall data collectedThe Rainfall data were obtained from the records available at the water resources division of the CRDA ofMédenine. The selection of stations was based on the geographical position to the coast and the observation
12

Institut des Régions Arides, 4119 El Fjè Médenine, Tunisia
Department of Soil Management and Soil Care, Faculty of Bio-engineering, Coupure Links 653, 9000 Race, Belgium

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periods. Then, two rainfall gauging stations were chosen: Médenine sud, having 96 years of records,representing the inland zone, and Zarzis which represents the costal zone and it detains 94 years of records.
2.3. Characterization of the climatic drought
To characterize and estimate the drought intensity in the study area, several methods and indices were used.
2.3.1. Percentage departure of rainfall (PDR)
Considering the normal rainfall, as a standard of comparison the estimation of actual rainfall can be doneby calculating the percentage departure of rainfall. The PDR is calculated as:

PDR(%) = [( Pi − Pm) Pm]× 100

Where: Pi: actual rainfall (mm); Pm: normal rainfall (mm). The variation is positive for the wet years andnegative for the dry years (Benzarti, 1992).
2.3.2. Frequency analysis
Annual rainfall records are classified in an ascending order according to their probability with not going
beyond (F) whose formula is as follows:

F = [r ( N + 1)]× 100

With: r: range of the year according to an increasing classification of the rain quantities; N: number of years ofobservation. Then, years are classified according to their probability of occurrence into five classes (Alouini etal., 2001). The humid part of the frequency value is split into “very wet” (F ≥ 85%) and “wet” conditions (65%≤ F < 85%. The normal conditions are indicated by 35% ≤ F < 65%. A drought event starts when the frequency
values indicates “dry” conditions (15% ≤ F < 35%) and “Very dry” conditions (F < 15%).
2.3.3. Persistence of drought
The drought severity is more felt as far as the dry year follows or precedes one or several dry years. A
sequence of dry years is more severe than an isolated drought (Benzarti, 1992). Drought as defined by thefrequency analysis can happen on one or several years (two, three or even more consecutive years). Whereas an
isolated drought, even very severe, preceded or followed by wet years has less effects.
2.3.4. Standard deviation index (SDI)
The drought severity was calculated also by using the comparison criterion to the average and to theaverage minus a standard deviation. This index is calculated by the comparison of the annual average rainfall(Pm) with a number of standard variations (σ) whose formula is the following (Beran and Rodier, 1987):

σ = [1 (N − 1)]∑ (Pi − Pm )12

When Pi is lower than Pm - σ, the drought is severe and it becomes very severe when Pi is lower than Pm - 2 σ.
The moderate drought are indicated by Pm – σ < Pi < Pm.
3. Results and discussion
3.1. Assessment of the drought impact on the olive trees
It was noticed that the groves close to the coast were less affected than those in the other areas where it
resulted in a significant fall of production and even by the deterioration of the olive-tree with various degrees(Fig. 2) leading to the pulling up for the production of wood coal (Fig. 3). Indeed, more than 98% of olive trees
were affected in the region of Médenine while this ratio did not exceed 24% in Zarzis region.
3.2. Characterization of the climatic drought
3.2.1. Percentage departure of rainfall (PDR)As shown by the Figure 4, the application of this index to the study gauging stations revealed thealternation of sequences of years with dry trends and others with humid trends. During the observation period,
the percentage deficit years is higher than that of the surplus years. In fact, the percentage of deficit years rangesis 57% in Zarzis and 60% in Médenine. The PRD has detected 83% of the years, in Médenine, have a sequenceof more than one dry year, whereas it is 80% in Zarzis. The longest dry sequences are 8 consecutive years from1961-1962 to 1968-1969 in Zarzis and only 7 consecutive years from 1960-1961 to 1966-1967 in Médenine. At
the level of the two stations, the overall tendency during the period 1908-1969 is marked by dry conditions
interrupted with very short wet periods. However, from 1969/1970 to 1995/1996, this tendency was reversed to333

Fig. 2. Partial and total drying of the olivetrees (year 2000)

Fig. 3. Pulling up and coal production fromolive-tree wood (year 2001)

200

200
PDR ( %)B 300

PDR (%)

A 300

100
0100
0-100
-200

1903
19 04
13
19 14
23-2
19 4
33
19 34
43
19 44
53
19 54
63-6
19 4
73
19 74
83-8
19 4
93-9
4

1908
19 09
18
19 19
28
19 -2 938
19 -3 948
19 -4958
19 -5968
19 69
78
19 -7988
19 -8998-99-100

Ye arsYe arsFig. 4. Percentage of rainfall departure in Médenine (A) and Zarzis (B)Pi15%
65%

500
300
200
100Pi
15%
65%

B 800
Pi (mm)Pi (mm)400

Pm
35%85%

600

Pm
35%
85%

400
200
01903
19 -0413
19 -1423
19 24
33
19 -3443
19 -4453
19 -5463
19 -6473
19 -7483
19 -84
93-9
40

Years

1908-0
19 9
18
19 19
28-2
19 93819 39
48-4
19 95819 59
68-6
19 978-7
19 988
19 89
98
-99A

Years

Fig. 5. Variation of the annual rains by comparison with the various classes of frequencies: 15%, 35%, 65%
and 85% of the two stations: Médenine (A) and Zarzis (B)wet but a drought period prevailed from 1996-1997 to 2001-2002.
This simple index indicates the yearly deficit and their sequences. Then, in order to better determine thedrought intensity other indices could be useful such as frequency analysis, standard deviation, etc. (Benzarti,1992).
3.2.2. Frequency analysis
The analysis of the climatic drought by this method brought more details on the normal years compared tosurplus or deficit years, as indicated in Figure 5. This figure shows that noticed that, 14 % of the years are verydry (deficit ranges from 54.78 % to 90.77 %), 21 % are dry (deficit ranges from 25.01 to 54.41 %), 29 % arenormal (24.78% of deficit and 4.28% of surplus) and 21 % o are wet (surplus from 7.51 % to 46.73 %) for Zarzis.
But, it showed that only 15 % of the years are very dry (deficit ranges from 48.2 % to 75.2 %), 20 % are dry(deficit ranges from 21.7 % to 47.5 %), 30 % are normal (20.8 % of deficit and 4.6 % of surplus) and 20 % arewet (surplus from 5.54 % to 34.3 %) for Médenine. Moreover, this index detected the same percentage of very
wet class for the two stations (15%). Then, in contradiction with was revealed by the percentage of rainfall
departure index, only 35 % of the observation years were dry to very dry in the two stations. This index reduces
sharply the occurrence of drought conditions.
3.2.3. Persistence of drought
For our case study, it was noted that the isolated droughts prevail with only 45.45 % in Zarzis for 48.5% in
Médenine. Then, the two consecutive years sequences are less important for the two stations: they represent

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600

Pi
Pm -σ

Pm
Pm -2σ600
Pi (mm)400200

Pm
Pi
Pm -σ

B 800

400
2000

1903
19 04
1319 14
23
19 24
33
19 34
43
19 -44
53
19 54
63
19 64
73
19 74
83
19 84
93-9
40

Year s

1908
19 09
18
19 19
28
19 29
38
19 39
48
19 49
58
19 59
68
19 69
78
19 79
88
19 89
98
-9
9Pi (mm)

AYearsFig. 6. Variation of the annual rainfall (Pi) by comparison with the average (Pm), the average minus one
standard deviation (Pm - σ) and the average minus two standard deviation (Pm – 2σ) of the twostations Médenine (A) and Zarzis (B).

only 24%.
3.2.4. Standard deviation index (SDI)
The application of this index to the two rain gauging stations, as indicated in Figure 6, showed that
79.63 % of the years are represented by moderate drought years in Zarzis against 39.7 % in Médenine.
Moreover, it detected only 20.37 % of severe drought years in Zarzis against 27.6 % in Médenine. For the very
severe drought, 32.8 % of years are detected in Médenine whereas this type did not occur in Zarzis.
4. Conclusions
Drought is a recurring phenomenon in the Tunisian Jeffara (province of Médenine). The analyses of therainfall records of Médenine and Zarzis, representing the study zone, allowed depicting the rainfall deficit
differences at the scale of the same area. In fact, the PRDI revealed that dry years represent 60 % and 55% of
the total observation records in Médenine and Zarzis, respectively. Moreover, the Standard Deviation Index
revealed 32.8 % of very severe drought years in Médenine whereas this type did not occur in Zarzis. Thisdifference of drought severity detected by the Standard Deviation Index shows better the difference of damages
caused to the olive tree groves in the two study area. Therefore, the SDI seems to be the most appropriate for thecharacterisation of drought severity in the same region.
References
Alouini A., Louati M.H. (1999): Guide pratique de gestion de la sécheresse en Tunisie, approche méthodologique.
Alouini A., Bergaoui M. (2001): Caractérisation de la sécheresse météorologique et hydrologique, cas du bassin versant de Siliana enTunisie. Sécheresse, 4(12): 205 -213.
Benzarti Z. (1992): La pluviométrie indice de sécheresse tendances pluriannuelles, in Surveillances permanente évaluation et mesurede contrôle de la sécheresse et de la désertification, rapport préparé par le groupe d’étude CagM-IX chargé de la surveillance, del’évaluation et de la lutte contre la sécheresse et la désertification, OMM/TD–N°505, Genève, Octobre, 1992.
Benzarti Z., Hbaieb H. (2001): Etude de la persistance de la sécheresse en Tunisie par utilisation des chaînes de Markov (1909-1996),
Sécheresse, 4(12): 215-220.
Beran MA., Rodier JA. (1987): Aspects hydrologiques des Sécheresse. Contribution au programme hydrologique international.
Rapport préparé par un comité mixte UNESCO/COM, 172p.
Trabelsi H. (1992): Mécanisme de la sécheresse et sécheresse en Tunisie, in Surveillances permanente évaluation et mesure decontrôle de la sécheresse et de la désertification, rapport préparé par le groupe d’étude CagM-IX chargé de la surveillance, del évaluation et de la lutte contre la sécheresse et la désertification, OMM/TD–N°505, Genève, Octobre, 1992.