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HYDROLOGICAL DROUGHT IN TAFNA BASIN-NORTHWEST OF ALGERIA

MEDDI MOHAMED, Toumi Samir and Madjid MEHAIGUENE

École Nationale Supérieure d’Hydraulique de Blida, route de Soumaa Blida, Algérie LGEE mmeddi@yahoo.fr

ABSTRACT Algeria and in particular the western part has experienced several periods of drought during this century. The last one was characterized by its intensity and its significant impact on water resources and crop yields. The decrease in rainfall associated with the significant increase in temperature over the past two decades has affected cereal yields in general and durum wheat in particular. Studies of drought are many and varied; several authors have studied the rainfall deficit and its impact on water resources. Analysis of the recurrence and persistence of this phenomenon by scientific methods seeks to make an estimation of the probabilities, which could contribute to the planning of water resource management and mobilization strategies. This work focused on the meteorological drought defined by the Standardized Precipitation Index (SPI) for 4 rainfall stations, and the hydrological drought defined by the streamflow drought index (SDI) for overlapping periods of 3, 6, 9 and 12 months at 2 hydrometric stations in the northwest of Algeria over the period 1941-2010. It has been shown that rainfall totals have decreased by more than 20 % in the studied stations. The largest decrease was observed in the south of the basin with 30%. This decrease appeared around 1975 for all stations. September is considered the beginning of the hydrological year in Algeria. The periods in the hydrological year chosen for this work are: September to November, September to February, September to May and from September to August. This choice was also made in Greece by Nalbantis in similar work. Based on the skewness coefficient with critical values of 0.986 and 0.662 for a significance level of 0.02 and 0.10 respectively, we opted for the series with a logarithmic transformation. On the other hand, for the Chouly station, the first two periods require a logarithmic transformation while the last two are considered in the raw state. The results of the hydrological drought analysis based on the SDI showed that almost all the stations suffered from droughts during the study period and especially after 1975. Additionally, extreme droughts occurred most frequently after 1975 where the number of dry years exceeded 62% for the two basins. When studying the prediction by Markov chains, we noticed a high probability to have a dry period (regardless of its duration) after a dry one in the eastern part of the basin represented by the Chouly basin where it exceeds 75%. Key words: rainfall, SPI, hydrological drought, SDI, Markov Chain, Tafna basin, Algeria

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1. INTRODUCTION Algeria and in particular the western part has experienced several periods of drought during this century, during the 40s and 50s to the present day (Meddi et al., 2003; Talia A., 2003).. The last one was characterized by its intensity and significant impact on water resources and crop yields. Studies of drought are many and varied; several authors have studied the rainfall deficit and its impact on water resources. Other works have focused on the study of drought and its impact on crops through water stress. The hydrological drought is defined as the significant decrease in the availability of water in all its forms in the land phase of the hydrological cycle. There are many indices to characterize the hydrological drought, including: the Palmer Hydrological Drought Index (PHDI), Surface Water Supply Index (SWSI) and the Streamflow Drought Index (SDI) proposed by Nalbantis and Taskris (2008). This index has the same advantages of simplicity of that of the Standardised Precipitation Index (SPI) (McKee et al., 1993). The exclusive use of flow is the key variable for the assessment of hydrological droughts. This index uses the stream flow as a basic element to assess hydrological drought. The cumulative flow is used for periods of 3, 6, 9 and 12 months within each hydrological year. This index has been widely used around the world, in Greece (Nalbantis , 2008), Iran (Tabari et al., 2012), Kenya (Kimosop, 2010) and China (Li et al., 2012). In this work, we will focus on the hydrological drought in Tafna drainage basin which is located in the west of Algeria. In this region, the work that we have conducted shows that rainfall reduction began in the second half of the seventies. The decrease is about 20% on an annual basis which leads to a significant reduction in stream flows. Two hydrometric stations (Beni and Bahdel Chouly) having measurements from 1941 to 2009 were selected. 2. MATERIAL AND METHODE 2.1. PRESENTATION OF THE STUDY AREA The Tafna watershed, located in the extreme west of Algeria, consists of 8 sub-basins, two of which are upstream in the Moroccan territory. Reaching the height of 1843, in the djebel Tenouchfi, the basin is bounded by the main relief (Tlemcen Mountains) between the Mediterranean and the high plains of Oran and relayed to the west by the Moroccan Middle Atlas and to the East by the Daia Mountains (Saida). The basin consists mainly of mountains in the south (800- 1400 m of altitude), largely dominant in north, the regions of plains of Maghnia, Hannaya and Sidi Abdelli. This orographic structure, dominated in north by the Taras Mountains (1081 m) of narrow width, causes an effective barrier for precipitation; this explains the aridity of the Maghnia plains. The hydrographical network of the Tafna basin consists mainly by two river arteries: the Oued Tafna in West and the Oued Isser in the East that has its source in the Tlemcen Mountains (fig.1). The climate of the Tafna basin is similar to that of the whole Mediterranean region of Northern Africa, it is mild and humid. The two hottest months are July and August, and have an average temperature of 26°C. The general regime of rainfall is that of the semiarid Mediterranean zones of Northern Algeria. It is characterized by winter precipitation with maxima in December, January and February, and a long period of drought, nearly without rain from June to September. The evaporation in free groundwater reaches the average annual value 1200 mm. Winds are moderate in the north and north-west. 2.2. DATA A lot of rainfall and hydrometric stations were selected to provide an annual rainfall data base. the selected stations have criteria of the information duration and data quantity. The choice of stations is also made to enable a good coverage of the study area. By meeting these criteria, four rainfall stations have been selected with a duration of 69 years (1941-2010). Regarding hydrometric data, the streams that are not disturbed by

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dams were selected; in this case the stations of Beni Bahdel and Chouly. The observation period is similar to that of precipitation (1941 to 2010), Fig. 1.

Figure 1 Study area location

2.3. METHODS The annual rainfall totals were calculated by adding the monthly rainfall averages from October to September. This data were then analyzed in four steps. The first step was the analysis of the interannual variability of precipitation using linear regression methods to test the stationarity of rainfall series. In the absence of stationarity (rupture in the arithmetic mean), we have applied the nonparametric Pettitt test (Pettitt, 1979) and the Bayesian procedure proposed by Lee and Heghinaian (Ouarda et al., 1999) to determine the period of the average rupture in the analyzed rainfall series. We have also, through the SPI (Standardized Precipitation Index) developed by McKee et al., (McKee et al. 1993 ; McKee et al. 1995 ), quantified the precipitation deficits at different temporal scales. These reflect the impact of drought on the availability of the various water resources. The positive values of the SPI reflect wet conditions and the negative values indicate a meteorological drought (McKee et al. 1993; Wilhite et al., 2000). The SPI takes into account the rainfall variable in a given region and for defined periods, considered in terms of deficits or surpluses. The SPI is calculated by the fitting of rainfall series collected on long periods to a probability law. The different values of this index SPI indicate the number of years during which the standard deviation of the achieved rainfall observation was far from the average made over a long duration. In general, a continuous series of more than 30 years of observations is required to calculate this index (Anctil F. et al., 2002). One of the major advantages of the SPI is its simplicity in calculation; it is based solely on precipitation. It has also a big flexibility as it can be estimated at any time (Hayes et al., 1999). In the second step, we have used an index characterizing the hydrological drought. In the methodology proposed for the calculation of Streamflow Drought Index, as proposed by Nalbantis (2008), the seasonal cutting is treated as follows, unlike the beginning of the

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hydrological year: (1) September is considered as the beginning of the hydrological year in Algeria ; (2) every three months (30 November, 28 February, 30 Mai, 31 August), an assessment of drought is made as regards the time interval since the beginning of the hydrological year up to that moment, so time intervals of three, six, nine and twelve are used, (3) forecasts will be made based on the time intervals mentioned earlier. The periods of time used in each hydrological year are presented as reference periods. It is about the periods of September-November, September-February, September-Mai and August to September (a complete hydrological year). We assume that a series of monthly streamflow volumes Qi,j is available, where i denotes the hydrological year and j the month within this hydrological year (j = 1 for September et j = 12 for August). On the basis of this series, we obtain: 𝑉𝑖,𝑘=∑ 𝑄𝑖,𝑗

3𝑘𝑗=1

i=1,2,…….J=1,2,……,12 k=1,2,3,4 (1)

Where Vi, k is the monthly streamflow volumes for the i-st hydrological year and the k-ist reference period, k = 1for September-November, k = 2 for September-February, k = 3 for September-Mai, et k = 4 for September-August. On the basis of Vi, k monthly streamflow volumes, the Streamflow Drought Index (SDI) is defined for each k reference period of the i-st hydrological year as follows:

𝑆𝐷𝐼𝑖,𝑘 =𝑉𝑖,𝑘−�̅�𝑘

𝑆𝑘 i=1,2,…, k=1,2,3,4 (2)

Where �̅�𝑘and sk are respectively the mean and standard deviation of the Streamflow Drought Index for the k reference periods estimated for a long period. In general, in Algeria, rates follow a log-normal distribution. The distribution is transformed into normal taking the simple logarithm. The SDI index is defined as follows:

𝑆𝐷𝐼𝑖,𝑘 =𝑌𝑖,𝑘−�̅�𝑘

𝑆𝑌,𝑘 i=1,2,…, k=1,2,3,4 (3)

Où 𝑌𝑖,𝑘 = ln(𝑉𝑖,𝑘) i=1,2,…, k=1,2,3,4 (4)

Are the logarithms of cumulative streamflow with yk representing the mean and standard deviation sy, k. these statistics are estimated over a long observation period. Five hydrological drought conditions are considered, similar to those used in the definition of the meteorological drought indices SPI, (Nalbantis, 2008) Tab. 1.

Table 1 Definition of states of hydrological drought using the SDI (Nalbantis, 2008)

State Description Criterion Probability (%)

0 1 2 3 4

Non-drought Mild drought Moderate drought Severe drought Extreme drought

SD≥0.0 -1.0≤SDI<0.0 -1.5≤SDI<-1.0 -2.0≤SDI<-1.5 SDI<-2

50.0 34.1 09.2 04.4 02.3

In the third step, we will make the revision using Markov chains of order I. The methodology of Markov chains allows us to determine or predict the probability of getting a dry year after a dry one. This process expresses conditional probabilities of transition from the waking situation (previous state) to the state of the current situation. Markov chains (Thirriot , 1986) take into account the connection between successive states. This model will be of first order if streamflow of the k state depends only on the previous state that is to say on the closest past to the state. For Markov process of order 1, four situations are possible [14]: namely: D-D (two successive dry states), DND (a dry state followed by a non-dry state), ND-D (a non-dry state followed by a dry state), and ND-ND (two successive non dry states). 3. RESULTS AND DISCUSSIONS

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In Algeria, climate changes in the recent decades have had a negative impact on water resources (groundwater recharge and dam filling) and crop yield. These changes have made the decision makers review the types of crops that can adapt to the new climate of some regions of the country and especially in western Algeria. In fact, precipitation know fluctuations which result in the existence of dry and wet years, dry or very wet sequences. The consequences of such variability are marked in the annual abundance, the seasonal hydrological years and the extreme forms of flow (floods and low flow). The analysis of the temporal variability of annual precipitation by linear regression reveals a continuing decrease of rainfall totals in the stations of the basin. The comparison of the slopes of the regression lines shows that the rainfall deficit was significant in the south of the basin. The application of the Pettitt test and Bayesian procedure confirmed this significant decrease in rainfall. Moreover, according to these two tests, this decrease occurred around 1975 for all stations. The analysis of the succession of dry and wet periods confirms these dates (fig.2). In fact, it has been observed that there is a surplus of rain before the 70s and a rainfall deficit after that. In addition, table 2 shows that rainfall totals have decreased by more than 20% in the studied stations. The largest decrease was observed in the Khemis Ouled Moussa station south of the basin.

Table 2 Comparison between annual precipitation before and after the change point of the mean

Stations 1941-2010 mean (mm)

Before the shift

After the shift

Range (%)

Khemis Ouled Moussa ** 485 571 396 -31 Beni Bahdel dam ** 466 533 396 -26 Lalla Setti ** 614 702 523 -26 Beni Ouassine** 301 348 253 -27

** = shift occurred after 1975; - = decrease Table 3 Evolution of dry years after and before 1975 for the two basins

Stations State Total

(1941-2010)

Before The shift (1975)

After the shift

(1975)

Beni Bahdel Dam

Non-drought 30 (43,5%) 25 (71,4%) 5 (14,7%)

Mild drought 26 (37,7%) 10 (28,6 %) 16 (47,1%)

Moderate drought 13 (18,8%) 0 13 (38,2%)

Severe drought 0 0 0

Extreme drought 0 0 0

Chouly

Non-drought 30 (43,5%) 22 (62,9%) 8 (23,5%)

Mild drought 25 (36,2%) 13 (37,1%) 12 (35,3%)

Moderate drought 14 (20,3%) 0 14 (41,2%)

Severe drought 0 0 0

Extreme drought 0 0 0

The analysis of winter and spring rains is responsible of the decrease in annual rainfall. The application of the tests mentioned above showed that the rains of December saw a reduction of between 5% and 63%, the rains of January has recorded very significant deficits varying between 33% and 53%. The variations of March vary between 37% and 69%. For the month of April, the deficits have exceeded 67%. This rainfall of these months is responsible of the rate of runoff and flow at the annual scale, this decrease gives a preliminary idea on the evolution of the hydrological regime. Based on the SDI, we found that before 1975 more than 62% of years are considered non-drought for the two basins, while after this date, more than 76% of years are dry. So we notice that the impact of rainfall reduction has had a direct impact o the surface flow, showing an extreme reduction after 1975 (Tab. 3). The reduction of stream flow is 62 and 64% after 1975 for the basins of Beni Bahdel and Choul respectively.

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Based on the skewness coefficient with critical values of 0.986 and 0.662 for a significance level of 0.02 and 0.10 respectively, we opted for the series with a logarithmic transformation. On the other hand, for the Chouly station, the first two periods require a logarithmic transformation while the last two are considered in the raw state (Table 4).

Figure 2 SPI and 5 years moving average over the period 1941–2010

The hydrological regime changes in the eastern part of the basin are similar to those of the western part. We have noticed a decrease in flow rate for the different periods chosen since the beginning of the eighties. The fall season at beni Bahdel basin was characterized by surpluses (Fig. 3) compared to other months and regarding to the eastern part (Fig. 4).

Station : Khemis Ouled Moussa

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Table 4 Skewness coefficient of cumulative streamflow and of its natural logarithm

Basin Calculation basis Sept-Nov Sept-Feb Sept - Mai Year

Beni Bahdel

Initial data 0.852 1.179 1.173 1.145

Logarithms -0.614 -0.387 -0.381 -0.357

Final data -0.614 -0.37 -0.381 -0.357

Chouly

Initial data 1.337 1.115 0.800 0.735

Logarithms -0.995 -0.968 -1.079 -1.076

Final data -0.995 -0.968 0.800 0.735

Statistically significant values (at the 0.10 probability) are in bold

Figure 3 SDI series for the Beni Bahdel dam basin and the reference periods September-November,

September-February, September- May and September- August

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Figure 4 SDI series for the Chouly basin and the reference periods september-November, September-

February, September- May and September- August

We used Markov chains of order 1 for the prediction. There is a high probability to have a dry period (regardless of its duration) after a dry one in the eastern part of the basin represented by the Chouly basin where it exceeds 75%. To have a dry period (regardless of its duration) after a wet period, the probability is lower in the eastern part of the basin than in the western part (Tables 5 and 6).

Table 5 Frequency of state transition as estimated from data of the Beni Bahdel dam basin.

DD DND NDD NDND

Sept - Nov 62,50 37,50 17,78 80,00

Sept – Feb 64,52 32,26 26,32 73,68

Sept - May 72,00 28,00 15,91 81,82

Sept - Aug 73,08 26,92 16,28 81,40

Table 6 Frequency of state transition as estimated from data of the Beni Bahdel dam basin. DD DND NDD NDND

Sept - Nov 75,00 20,00 10,20 89,80

Sept - Feb 76,19 19,05 10,42 89,58

Sept - May 75,00 21,43 17,07 82,93

Sept - Aug 78,57 17,86 14,63 85,37

4. CONCLUSION Generally, precipitation determines the variability, or rather the inter-seasonal and interannual irregularity of surface runoff. It represents the essential part of river recharge. After 1975 rainfall has experienced a decrease of 26% in the Tafna basin. This reduction a remarkable lowering of runoff of about 62%. The number of dry years after 1975 is significant with more than 62%. The application of Marcov chains for prediction showed a high probability to have a dry period (regardless of its duration) after a dry one in the eastern part of the basin represented by the Chouly basin where it exceeds 75%. REFERENCES Anctil, F., Larouche, W., Viau, A.A., Parent, L.E. (2002) Interpretation of the standardized precipitation indictor using regional statistical analysis. CJSS, 82(1), 115-125 (2002), [in French].

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