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A total of 290 rainfall samples were collected from a network covering 16 stations, mainly distributed in western Syria (Fig. 1b). Table 1 summarizes the number (n) of RW samples collected from each site, the geographical coordinates of the sampling stations (LE, LN, H and DFC), and the average air T, P-amount, and RH values measured at each station during the period 1989-2006. Rainfall sampling was made on a monthly basis (monthly composite), with systematic collection of RW samples twice a day (8 AM and 8 PM), by using suitable plastic containers with catch-diameters of 30-80 cm, according to the P-amount falling over the considered station. The daily collected water from each station was then moved into a tightly-sealed container, large enough to store the cumulated amounts of monthly P. After returning back from the field to the laboratory, all collected samples were instantly stored in a refrigerated room (T below 5°C) until the time of analysis. More details on the sampling procedures were given by Kattan (2019).

At the end of each month in the rainy season (Nov-May) two rinsed bottles (polyethylene or glass) were filled for conducting the isotopic determinations. A first small bottle of 50 mL was filled for the determination of δ¹⁸O and δ²H, while the second bottle (one liter size) was filled for tritium (³H) determination. The subsequent analyses of δ¹⁸O and δ²H in the RW samples were performed by using a Finnigan Mat (Delta E or Delta Plus) mass spectrometer. Measurement accuracy for δ²H and δ¹⁸O are better than ±0.1‰ and ±1.0‰, respectively. The subsequent analyses of tritium in the RW samples were performed, after electrolytic enrichment of the water samples, either by using a Packard-3253 liquid scintillation counter or by an ultra low level liquid scintillation counter (Quantulus 1220). Detection limit for ³H measurements in both instruments is lower than 1 TU (1 TU=1 ³H atom per 10¹⁸¹H atoms). More details on the analytical procedures of these isotopes in water samples were given by Kattan (2006 and 2019).

Analytical results of the stable isotope values are commonly expressed in δ notation in terms per mil (‰), defined as:

where R is the isotopic ratio (²H/¹H or ¹⁸O/¹⁶O), and the indices sam and std denote the sample and the standard, respectively.

The international standard largely used for the calibration of ²H and ¹⁸O isotopes in RW samples is called “Vienna Standard Mean Ocean Water (VSMOW)”, precisely prepared and adopted by the IAEA for this purpose (Coplen, 1996; Gonfiantini, 1978). Specific requirements and quality assurance procedures according to the ISO/IEC 17025 standard are strictly applied in all the labs of the Atomic Energy Commission of Syria (AECS) in order to achieve the production of competent analysis results. Verification of the isotopic analysis results are periodically insured through the participation in the different analysis comparison programs organized either by the IAEA or by other regional laboratories.

Descriptive statistics (average and standard deviation) for the entire dataset, together with those for the RW samples collected from each station were calculated by using the softwares Excel 2007 and Statview 5. The amount-weighted mean value (C_w), that takes into consideration the effect of rainfall intensity during any monitoring period, was calculated by using the following formula (Yurtsever and Gat, 1981):

where P_i is the monthly P-amount and C_i is the isotopic composition of RW sample for the month i.

The deuterium excess value (d-excess or d) in each RW sample was calculated by using the formula, defined by Dansgaard (1964) as:

As the accurate modeling of the spatial distribution of P isotopes requires at least a gridded network of about 10′×10′ unit scale (Lykoudis and Argiriou, 2007), the map sheet of Syria and some parts of the neighboring countries was divided into 4590 grid-units. The software Arc-GIS-9 was first used to generate the values of the geographical coordinates (LE, LN and H) for each of the grid-units, and then to produce the simulated maps for the spatial distributions of P stable isotopes (δ¹⁸O and δ²H), tritium and d-excess values across Syria.

Table 1 illustrates the average stable isotope (δ¹⁸O and δ²H) ratios and d-excess values, compared to the amount-weighted mean values calculated for the RW samples collected at all the stations. The stable isotope ratios in the RW samples were in the range from -14.6‰ to +7.4‰ and from -101‰ to +35‰, with average values of -6 ±3‰ and -32±20‰ for δ¹⁸O and δ²H, respectively (Kattan, 2019). The d-excess value for these dataset varied from ≤0‰ in the highly evaporated samples to +30‰ in the RW samples collected from southern Syria. The amount-weighted mean δ¹⁸O and δ²H values were always lower than the average values at all the stations, likely as heavy stable isotopes are almost more concentrated in the evaporated RW samples (P-amounts<5 mm). The stable isotope ratios in the RW samples at the Arneh and Bloudan stations (H>1500 m a.s.l) were markedly the most depleted (δ¹⁸O<-6.5‰ and δ²H<-35‰), while those at the Tartous, Homs and Palmyra stations (H<400 m a.s.l) were distinctly higher (δ¹⁸O>-5.7‰ and δ²H>-32‰), mostly because of the evaporation of raindrops during their falling on the earth surface (Managave et al., 2016).

The relationship δ²H-δ¹⁸O for the entire RW samples (Fig. 2a) clearly shows that most of the sample points are scattered between the Global Meteoric Water Line (GMWL), defined by Craig (1961) as: δ²H=8 δ¹⁸O+10, and the Mediterranean Meteoric Water Line (MM WL), given by Nir (1967), as: δ²H=8 δ¹⁸O+22. However, a few sample points, with depleted stable isotope ratios, are regrouped close to the MMWL. The second part of the samples, with enriched isotopic ratios (δ¹⁸O>-4‰ and δ²H>-20‰), are located very close to the GMWL. The equation of the least squares regression line fitting all the sample points is given as:

Fig. 2. 
Relationships between monthly δ²H and δ¹⁸O values for all the RW samples collected in Syria (a) and between amount-weighted mean δ²H and δ¹⁸O values for all the stations (b). Black dark circles denote RW samples or station points with their error-bars. Black lines are the linear fittings for the RW samples or the station points. Red, olive and blue lines are arbitrary lines, with a slope of 8 and different Y-intercept values (17‰, 20‰ and 23‰, respectively), schematically plotted for approximate matching with the different station points.

Projection of the amount-weighted mean δ²H and δ¹⁸O values of all the stations in the diagram δ²H-δ¹⁸O permits to classify the monitoring stations in three different groups (Fig. 2b): (1) a group of stations (Bloudan, Arneh, Bab-Janeh, Al-Suwieda, Izraa and Al-Kounietra) fitting a line, with δ²H=8 δ¹⁸O+23; (2) a group of stations (Qatana, Aleppo, Damascus, Homs, Al-Raqqa and Tartous) matching a line, with δ²H=8 δ¹⁸O+20; and (3) a group of stations (Al-Nabk, Idleb, Jarblous and Palmyra) fitting a line, with δ²H=8 δ¹⁸O+17.

This distribution reflects not only the impacts of the T effect (Kattan, 2019; Rozanski et al., 1993) and secondary evaporation during the rain falling on the land surface (Managave et al., 2016; Froehlich et al., 2005; Araguás-Araguás et al., 2000), but also the exchange with the enriched moisture (d>22‰) produced by evaporation from the MS (Gat et al., 2003).

The concentrations of ³H in the RW samples during the period 1989-1993 were in the range of 4-14 TU, while during the period 2004-2006 they were in the range of 3-10 TU. This change, which means that the concentration of ³H is annually decreasing by ≈5-6%, clearly suggests a return back toward the natural cosmogenic production levels in the upper atmosphere before starting the nuclear weapons testing (Michel et al., 2015). Also, it can be observed that the amount-weighted mean ³H values in the RW samples at all the stations were lower than the average ³H values, with a difference of 0.2-1 TU (Table 1). The concentrations of ³H in the RW samples at the coastal station (Tartous) and Al-Kounietra and Qatana stations, located nearly close to the MS, were remarkably <5 TU, while at the Palmyra station, located at a farther distance from the MS coast, were higher than 9 TU. The amount-weighted mean ³H values in the RW samples at the Al-Suwieda and Izraa stations were relatively higher than 5 TU, most probably because of the short monitoring period (1989-1993). The measured ³H concentrations in the RW samples at both stations during that period (8-9 TU) were clearly very close to those reported for the Damascus and Aleppo stations that have nearly a similar DFC value (Kattan, 1997b).

The temporal variation of average monthly ³H concentrations in the RW samples during the rainy season (Fig. 3), clearly shows a progressive increase from ≈3 TU in November up to ≈12 TU during April to May. This trend, which indicates that more than 2/3 of the total ³H load was occurred during the spring season, clearly reflects the tropospheric injection, or the so-called “Spring Leak” phenomenon (Harms et al., 2016; Rozanski et al., 1991).

Fig. 3. 
Temporal variation of average monthly ³H value in the RW samples during the rainy season extended between November and May.

Variations of the stable isotope ratios in meteoric water are known to be highly influenced by the ambient local weather conditions, specifically the common meteorological (T, P-amount and RH) parameters (Araguás-Araguás et al., 1998; Rozanski et al., 1993; Dansgaard, 1964). Pressure of the water vapor in the atmosphere, air depressions, weather cold fronts and backward trajectory tracks of humid air masses are also decisive factors that play certain roles in the formulation of the isotopic signature of meteoric water (Li et al., 2015; Muller et al., 2015; Baldini et al., 2010; IAEA, 2005).

Recently it was shown that the T effect was the major factor that strongly controls the temporal variation of P stable isotopes in Syria (Kattan, 2019). This effect was remarkably reflected by enrichments of ≈0.34‰/°C and ≈1.9‰/°C for δ¹⁸O and δ²H, respectively, accompanied by a decrease of ≈-0.8‰/°C for the d-excess value with T increasing. Fig. 4a shows the relationship between the monthly δ¹⁸O values and the average monthly T values for all the RW samples collected in Syria.

Fig. 4. 
Relationships between monthly δ¹⁸O and T values (a), monthly δ²H and P-amount values (b) and monthly d-excess and RH values (c) for all the RW samples in Syria. Black lines denote the linear fittings and their equations.

The effect of P-amount is also an important factor. This effect, which highly depends on the local weather conditions during the time of rain falling, was reflected by a significant decline in the stable isotope ratios (Fig. 4b), accompanied by a remarkable increase in the d-excess value with the increasing of monthly P-amount. However, it can be observed that the gradient in d-excess value in the case of the mountainous stations located close to the MS was generally small, while it was remarkably much higher in the remaining stations.

The RH effect was reflected by a decrease in the stable isotope ratios, accompanied by a comparative enrichment in the d-excess value with RH increasing. Fig. 4c shows that the low d-excess values were usually associated with low RH values (≈40%), whereas the higher d-excess values were typically coupled with high RH values (>80%).

The common geographical factors that have strong controls on the spatial variability of stable isotopes in meteoric water are the altitude, latitude and longitude coordinates (Wang et al., 2016; Terzer et al., 2013; Lykoudis et al., 2010; Bowen et al., 2005). The DFC factor may also affect the spatial variation of P isotopes, likely the concentration of ³H, that tends to increase with the increasing of the inland distance (Harms et al., 2016; Michel et al., 2015; Kattan, 1997b; Michel, 1989; Gat and Carmi, 1970). Table 2 summarizes the regression parameters of the fitted straight lines and second-order polynomial curves for the different relationships between the amount weighted-mean δ¹⁸O, δ²H, d-excess and ³H values in the RW samples at all the stations in function with the corresponding values of LE, LN, H and DFC parameters. Accordingly, it can be observed that the correlation coefficients for the fitted second-order polynomial curves are almost similar to those of the fitted straight lines. The high correlation coefficients (r>0.73), that were found for the relationships δ¹⁸O-H and δ²H-H, strongly indicate that the so-called “altitude effect” was the most important factor controlling the spatial variability of both stable isotopes. The negative slope values for both relationships also show that this effect was shown up by progressive depletion gradients of -0.002±4E-4‰ and -0.009±0.002‰ for δ¹⁸O and δ²H, respectively (Fig. 5a).

Fig. 5. 
Relationships between amount-weighted mean δ¹⁸O ratios and LN values (a), amount-weighted mean δ²H and H values (b), amount-weighted mean d-excess and LN values (c), and amount-weighted mean ³H and DFC values (d) for all the stations in Syria. Black lines and red curves denote the linear and the second order polynomial fittings and their equations, respectively.

Although the altitude factor was with strong effect on the spatial variation of P stable isotopes, its impact on the spatial variation of the d-excess parameter was rather moderate (r≈0.5-0.52). The correlation coefficients for the relationships between the stable isotope ratios (δ¹⁸O and δ²H) and the geographical coordinates (LE and LN) were found also to be rather moderate (0.3<r<0.6), meaning that these factors have minor controls on the spatial variation of P stable isotopes, most likely because of the small geographical extent of the country (Fig. 5b). Similarly, it was observed that the correlation coefficients for the relationships (δ¹⁸O-DFC and δ²H-DFC) were also low (0.3<r<0.4). The reason is because the MS coast is typically extending in parallel to the global longitudinal lines (LE), and thus the impact of the DFC factor must be rather similar to that of the LE factor. However, it can be observed that the correlation coefficients for the relationship d-excess-LN for the linear and the second-order polynomial functions (Fig. 5c) were remarkably high (0.7<r<0.8 and P-value<0.001). The reason that the correlation coefficients for this relationship were remarkably high, and with a negative slope value (-1.39±0.3), is clearly due to the extensive exchange with the enriched MS moisture (d≈22‰), likely as a high percentage of prevalent winds (>50%) usually coming from the directions of SW and S.

A low correlation coefficient (r≈0.26) was found for the relationship d-excess-DFC, suggesting also a weak impact of the DFC factor on the spatial variability of d-excess value.

In the case of ³H spatial variation, the best correlation coefficient (r>0.63) was found for the relationship ³H-DFC (Fig. 5c). This later coefficient, which was rather close to the coefficient (r>0.59) calculated for the relationship ³H-LE, clearly indicates that both factors have somewhat similar controls on the spatial variability of ³H in Syria. The correlation coefficients for the relationships ³H-LN and ³H-H were both low (r<0.3), indicating thus weak influences of the H and LN factors on the spatial variation of this radio isotope.

Modeling the spatial variation of P isotopes is a smart alternative tool for mapping the approximate isotopic composition of P at any location on the Earth Globe (Bowen et al., 2005). Hence, extensive efforts were made to fit between the P isotopic data with the key geographical parameters (LE, LN and H), either on global scales (Bowen et al., 2005; Bowen and Revenaugh, 2003; Bowen and Wilkinson, 2002), or on regional scales (Lykoudis et al., 2010; Liu et al., 2010; Lykoudis and Argiriou, 2007; Longinelli and Selmo, 2003). However, some other works were focused on the development of certain algorithms and models that can determine, not only the average annual isotopic composition of P at a certain site, but also the seasonal, or even the daily isotopic values (Sturm et al., 2005).

In this study, attempts were made to simulate the spatial variation of P isotopes in Syria by using the amount weighted-mean δ¹⁸O, δ²H, ³H, and d-excess values in the RW samples collected at the different stations in this country, in conjunction with the corresponding key geographical parameter (LE, LN and H) values. The purpose behind such essays was to extract mathematically the appropriate empirical relationships that fit between the measured isotopic values with the corresponding geographical parameters. The final aim was to produce a high-resolution gridded isotopic data that can be used later for covering certain areas lacking similar isotopic data. Such simulated data can also be used to map the spatial distributions of P isotopes in this country, by using the traditional geographical information system (GIS), largely applied in this domain (Johnston et al., 2004).

By excluding the isotopic data of the Al-Nabk station, that has a special weather character strongly different from the other stations (Kattan, 2019), the best models (multi polynomial expressions) that were found to produce the finest gridded isotopic data for the above isotopic parameters in function with the allied geographical factors (LE, LN and H) are the following:

The correlation coefficients for the fitted polynomial models vary between r=0.67 in the case of ³H and r=0.89 in the case of δ¹⁸O. These coefficients are generally good, and thus they can safely be used to generate the isotopic data for the different gridded-units or cells for the selected sheet map of Syria.

Fig. 6 illustrates the relationships that were found between the calculated (simulated) and the observed (measured) amount weighted-mean δ¹⁸O, δ²H, ³H and d-excess values in P at the different Syrian stations. Accordingly, the above mentioned models were all used to generate the appropriate isotopic data for the gridded cells of the Syrian map, by assuming that the cell centre is representative for the simulated isotopic values.

Fig. 6. 
Relationships between modeled and measured δ¹⁸O (a), δ²H (b), d-excess (c), and ³H (d) values for15 stations in Syria.

The modeled spatial distributions for the stable isotopes (δ¹⁸O and δ²H) imply that their values change remarkably in accordance with the topographical features in the country (Figs. 7 and 8). This distribution highly reflects the significant role of the altitude factor on the spatial variability of both isotopes, with clearly depleted isotopic ratios (δ¹⁸O<-7.5‰ and δ²H<-45‰) in the high altitude areas (Mts Hermon, Anti-Lebanon and Al-Arab), and enriched isotopic ratios (δ¹⁸O>-5.5‰ and δ²H>-33‰) in the interior inland areas, most specifically in the low altitude areas in north-eastern Syria. However, it is noteworthy to observe that the produced map for the distribution of d-excess values in P in this country is rather of a particular spatial variation trend (Fig. 9), with a remarkable high d-excess value (d>20‰) in southern and south-western Syria (Mts Al-Arab, Hermon and Anti-Lebanon), and gradually lower d-excess value (d<20‰) in the eastern and north-eastern parts of Syria.

Fig. 7. 
Spatial distribution of simulated P δ¹⁸O values (‰, VSMOW) in Syria.

Fig. 8. 
Spatial distribution of simulated P δ²H values (‰, VSMOW) in Syria.

Fig. 9. 
Spatial distribution of simulated P d-excess values (‰, VSMOW) in Syria.

Although the correlation coefficient for the relationship between predicted and measured amount weighted-mean ³H values in P at the different stations (r=0.67) was lower than those found for the stable isotopes and d-excess parameters (r>0.84), the simulated map for the spatial variability of this radioisotope was also remarkable (Fig. 10). This map permits to observe a progressive build up or ³H enrichment with the increasing distance from the Syrian coast, from a value of about 5 TU along the MS coast to values higher than 9 TU in the farther inland areas in the eastern and north-eastern parts of the country. This distribution clearly explains the continuous mixing between the low tritium of the MS moisture and the higher tritium of the continental moisture (Michel et al., 2015; Mook, 2001).

Fig. 10 
Spatial distribution of simulated P ³H values (TU) in Syria.