Soil Water Surplus in Salado River Basin and Its Variability during the Last Forty Years (Buenos Aires Province, Argentina)

Soil water surplus and deficit occur frequently in Buenos Aires province in Argentina. This paper analyses the soil water surplus in a sub-area, the Salado River basin, in the period 1968–2008. This basin is divided in seven drainage areas, delimitated according to the National Water Resources. The series of soil water surplus data were adjusted by means of the theoretical normal cubic-root probability distribution, and the mean areal soil water surplus value of 300 mm was considered as a threshold above which floods can cause severe damage. An increase in the frequency of extreme events and in their tendency exists during the recent years, coherent with the increase of precipitation recorded in the region. The statistical significance of the results was assessed using the Mann Kendall and MAKESENS tests. The results showed a relevant temporal variability, but did not show significant tendencies.


Introduction
The Salado River is located in the Buenos Aires (hereafter, BA) province, in eastern Argentina, and flows eastwards to the Atlantic Ocean.Its basin is an almost flat region with a mean gradient of 0.25‰ from west to east, and covers a wide region known as the Pampas Plain or Pampean flatlands.The basin is roughly rectangular, and its coordinate margins are: 34°30'S and 38°10'S for the latitude, and 63°23'W and 56°41'W for the longitude.In recent decades, there were several episodes of soil water surplus (sws, hereafter), caused mainly by intense rainfall [1][2][3].
The goal of this paper is to analyze the evolution of annual sws in the period 1968-2008, considering seven drainage areas corresponding to the Salado River basin (BA province, Argentina), in order to determine the areas with the highest frequencies of occurrence.
The BA province is a large plain with an elevation of less than 300 m.The Tandilia and Ventania hills, located in the southern part of the region, reach 520 m and 1240 m, respectively.The Salado River basin covers 91,505 km 2 , and the homonymous river-more than 700 km long-is the most important.Its main affluents are the Las Flores and Vallimanca streams.The drainage system consists of meandering rivers partially connected to permanent and seasonal lagoons.The low regional terrain slope favors the retention and storage of rainwater for long periods, mainly in the soil, over the floodplain and in shallow lagoons.
Historically, this region was characterized by long periods of water deficit, persistent droughts and high temperatures, interspersed with periods of heavy rainfall that cause severe floods.Since grain production in the Salado River basin accounts for 30% of the national production, that of meat for 25% and the agro-industrial products of vegetal origin exceeds 60%, it is evident that these natural phenomena can have a relevant impact on the national economy.
The climate of the area is temperate and humid, with warm summers and cool winters.Mean annual temperatures oscillate between 13 °C and 16 °C .The temperature of the warmest month (January) ranges between 20 °C and 23 °C, while that of the coldest month (July) between 7 °C and 9 °C.Annual precipitation varies from 1000 mm in the north-eastern part of the region to 700 mm in the south-west.The largest precipitation events are usually generated by the contrast between the warm and humid air mass originating from the semi-permanent anticyclone over the Atlantic Ocean and the cold air mass flowing from the south-west.
The sws is the quantity of rainwater that remains over the soil surface when the water infiltration is null because the soil storage capacity is achieved.This water often cannot infiltrate because the water table is too close to the surface, and there are many depressed areas in the Pampean flatlands.Thus, vertical rainfall and evapotranspiration fluxes are more important than horizontal water movements or surface and subsurface flows in flat regions like the study area.The level of the water table is high during periods of sws, eventually rising to the surface, thereby increasing the flood potential as well as the extension of lakes, ponds and surface impoundments.Nowadays, such a situation occurs more frequently over the Pampean flatlands as a result of the increased precipitation, as the studies performed during the last decades [4][5][6].
According to Barros et al. [7] subtropical Argentina, Paraguay and southern Brazil recorded more precipitation during summer in the last decades of the XX century, and the interannual variability also increased.During this season, a low-level convergence area, a high-level divergence area and an intense convection develop in the northern part of this macro-area, forming the South Atlantic Convergence Zone (SACZ), which has a relationship with the interannual precipitation variability in the same area.
Kruse et al. [8] described the relationship between precipitation, evapotranspiration, soil water storage, sws, the water table, subsurface and surface runoff under different scenarios in the north-western BA province, finding a good temporal relationship between water table levels and sws.
Events of sws occur almost every year, regardless of the ENSO phase, but are particularly intense during the El Niño phase [9].The differences between the rainfalls in the two ENSO phases appear most evident in the northern BA province, where they reach values of 100 mm, suggesting that the El Niño phase seems to control the magnitude and spatial extent of the sws.In particular, the north-eastern BA reveals high risks of saturated soils and floods in general during the autumn, and in particular during the years characterized by the El Niño phase.

Materials and Methods
This section is divided in several parts related to the different sources of information and methodologies utilized in the elaborations.
Figure 1 represents the geographical location of the BA province, and reports also the reticular composition of the basin.

Data and Meteorological Stations
Daily precipitation data for the period 1968-2008 were provided by the National Meteorological Service-SMN (29 stations) and by the National Institute of Agronomic Technology-INTA (five stations).The meteorological stations were selected according to their long record, homogeneity and historical development.
Figure 2 shows the studied area and reports the position of the meteorological stations used in the work, which are listed in Table 1.

Basic Hydrological Concepts
The aim of this work is the evaluation of the soil water budget on a daily basis, considering the daily precipitation as input data.The daily mean potential evapotranspiration, two soil hydrologic values (the field capacity and the permanent wilting point) and the corresponding drought levels, evaluated according to the method used by [10,11], were calculated for each station.
Daily sws data were thus obtained using the method of [12] which, in turn, is based on the method of Thornthwaite and Mather for evaluating the soil water balance (Equation 1) on a daily basis.The input data required are the measured precipitation and the daily mean potential evapotranspiration.The latter was estimated using the Penman-Monteith method [13].

N
The soil water balance equation used in the model is: where PP is the daily precipitation, EP the daily mean potential evapotranspiration, ∆ St the soil water storage variation, Su the sws and Def the soil water deficit.
In the following step, the annual values were evaluated by summing the daily soil water balance, and were aggregated in annual areal values; thus, allowing the evaluation of the annual sws on areal basis.
The annual water balance and the sws were then analyzed in order to find the possible tendencies.As the sws values do not have normal distribution, the annual series were adjusted by using an empiric distribution of frequencies (normal cubic-root probability distribution).This operation allowed analysis of the normal distribution of the sws, calculation of the mean value relative to the studied period, and the probability of occurrence of 50% to be obtained.

The Salado River Basin
The Salado river basin was considered subdivided in seven drainage areas, according to National Water Resources [14], as indicated in Table 2 and displayed in Figure 3.

Map Graphical Representation
Maps showing the sws for every year of the studied period were created using the software SURFER 8.0, which allows isoline maps of the sws to be drawn.

Soil Water Surplus
The obtained maps allowed the spatial distribution of the annual sws to be detailed.The mean areal value was calculated for each of the drainage sub-areas mentioned in Table 2, and the sequence of these annual values of sws was used to study their temporal distribution.An annual mean areal value of 300 mm was considered as a threshold of sws, above which there is a relevant probability that floods can cause severe damage.

Statistical Analysis
The non parametric Mann-Kendall test was applied to the complete series of data.In addition, an Excel template, called MAKESENS and described in [15], was used for detecting and estimating trends in the time series of annual values of sws.This procedure is based on the nonparametric Mann-Kendall test for the trends, and the nonparametric Sen's method for estimating the magnitude of the trend.In detail, in the first step, the Mann-Kendall test allows detection of a monotonic trend in the time series of data without seasonal or other cycles.Subsequently, the Sen's method tries to fit the data with a linear model, reported in Equation 2, where t is the time expressed in years: where Q is the slope and B the offset to be determined.Finally, MAKESENS evaluates the test statistical significance using the α levels 0.001, 0.01, 0.05 and 0.1 [16].The Sen's method gives the following results, depending on the number of years n:  Test Z for the trend assessment: if the number of samples n is greater than 10, the value of the statistic test Z is displayed.The absolute value of Z is compared to the standard normal cumulative distribution for assessing the presence of a trend at the selected significance level α, while a positive (negative) value of Z indicates an upward (downward) trend.
 Statistical significance: α represents the smallest significance level at which the null hypothesis (absence of trends) must be rejected.If n is lower than 10, the test uses the S statistic, while if n is larger or equal to 10, the test uses the Z (normal) statistic.To show the significance levels, the following symbols are used: *** existence of a trend with level of significance α = 0.001; ** existence of a trend with level of significance α = 0.01; * existence of a trend with level of significance α = 0.05; + existence of a trend with level of significance α = 0.1.
 Estimate with the Sen's method of the slope Q in Equation 2: Q represents the annual rate of variation of the areal sws, and is thus expressed in mm/year: Q min 99: estimate of the lower limit of Q with a 99% confidence interval (α = 0.1); Q max 99: estimate of the upper limit of Q with a 99% confidence interval (α = 0.1); Q min 95: estimate of the lower limit of Q with a 95% confidence interval (α = 0.05); Q max 95: estimate of the upper limit of Q with a 95% confidence interval (α = 0.05).
 Estimate with the Sen's method of the constant B in Equation 2: B represents the mean annual areal value at the beginning of the observations, and is expressed in mm: B min 99: estimate of the lower limit of B with a 99% confidence interval (α = 0.1); B max 99: estimate of the upper limit of B with a 99% confidence interval (α = 0.1); B min 95: estimate of the lower limit of B with a 95% confidence interval (α = 0.05); B max 95: estimate of the upper limit of B with a 95% confidence interval (α = 0.05);

Results and Discussion
Figure 4 shows the spatial distribution of the mean areal annual sws for two years (2001 and 2002) in which there were relevant values of sws that caused major floods in the Salado River basin.The maximum value refers to the third drainage area (S3) in 1993 (600 mm), and the second maximum to the seventh drainage area in 1980.The former value is in agreement with those found by Scarpati et al. [17,18] and Gonzalez and Fernandez [2], who studied the floods of the Salado river basin.The obtained results can be summarized in this way: 1. 1968 to 1980: the values of sws were generally small; 2. 1980 to 1995: in several years, the threshold of 300 mm was exceeded, including the two cases above mentioned; 3. 1995 to 1999: only the second and fourth drainage areas exceeded 300 mm, in 1997 Figure 6, grouping the decadal values relative to all drainage areas, can exalt the different behavior of the values during the studied period, which can be summarized in the following way:  S1 always shows values lower than 200 mm, and the minimum was observed during the second decade;  S2 always shows values higher than 200 mm, and the maximum was observed during the second decade;  S3 shows a high value during the second decade, but the maximum corresponds to the third;  the maxima of S4 and S5 are recorded during the second decade, and high values are also observed in the third;  S6 and S7 values show the smallest inter-decadal variations among all drainage areas.Table 3. Annual values of soil water surplus lower than 100 mm (yellow boxes), larger than 300 mm (orange boxes) and larger than 500 mm (grey boxes) for the seven drainage areas.The last column reports the number of drainage areas showing sws larger than 300 mm.The last two lines report the number of stations in which annual sws was larger than 300 mm (last row) and lower than 100 mm (second last row).Table 3 summarizes the number of years with low (lower than 100 mm) and high (higher than 300 mm) sws, for each drainage area.The second and sixth areas show the maximum number (12) of high sws, while the minimum value of cases is shown by the first area.Generally, there were a larger number of cases with low values of sws than with high values of sws, but this general distribution was different in the different drainage areas.For instance, the fifth and first areas show a clear prevalence of the years characterized by low sws, while the third area shows a prevalence of years with high sws.

Year
The Mann-Kendall test revealed that the trends observed are statistically significant only for the third drainage area, at the level of 95% (Table 4).As the results of the application of MAKESENS test were similar to those of the Mann-Kendall test, only the details relative to the only statistically significant trend, i.e., that of the third drainage area, are reported (Figure 7 and Table 5).For sake of completeness, the Sen's estimates for the slope of the linear trends relative to the other drainage areas, considered non significant, are: for S1, 100 mm/year; for S2, 200 mm/year; for S4, 150 mm/year; for S5, 120 mm/year; for S6, 200 mm/year; and for S7, 180 mm/year.The trend of S3 area varies from 169 to 222 mm/year.

Conclusions
The soil water surplus relative to the period 1968-2008 was analyzed in seven drainage areas of the Salado River basin.The annual mean areal value of 300 mm for sws was considered as the threshold above which subsequent floods can cause damages.The maximum value present in the series of data was 600 mm.The seven drainage areas in which the Salado River basin has been subdivided show different annual mean sws values, as well as a different number of events, thus the flood or drought risk differs between the different areas.
The decade 1979-1988 showed the highest values in every drainage area, except for S1 and S3.The temporal variability of the sws was evidenced by the choice of five periods related to the cycles visualized through the studied period, and they could be connected to climate change.The behavior of the sws data of drainage area 3 (Salado River mouth) is the only one with statistical significance.
As a general conclusion, an increase of the frequency of sws values above the 300 mm threshold in the period 1968-2008 was identified.The years 1968 and 2008 showed the smallest sws values during the whole analyzed period, and 2008 registered the worst drought in the last 40 years.
The years showing the maximum values of sws were 1983, 1985, 1993, 2001 and 2002.
The third drainage area (Salado River mouth) showed the highest sws value (600 mm), followed by the second area (Central area of the Salado River basin) and the seventh (Channels area south of the Salado River).The sixth area (Western Channels area south of the Salado River) registered the largest frequency of sws values higher than 300 mm (12 events).
Since 1980, the sws values experienced important fluctuations.An increasing tendency during the last years is observed and it is coherent with the increase in precipitation.

Figure 1 .
Figure 1.Buenos Aires province and the Salado river basin.

Figure 2 .
Figure 2. The locations of the meteorological stations.

Figure 4 .Figure 5
Figure 4. Spatial distribution of the mean areal annual sws of the Salado River basin.

Figure 5 .Figure 6 .
Figure 5. Annual distribution of soil water surplus (sws) in the seven drainage areas.

; 4 .
2000 to 2002: almost all drainage areas, except the fifth, showed large values; 5. 2003 to 2008: the sws values never reached the 300 mm threshold, and are very similar to the first cycle.

Table 1 .
Denomination and code of the meteorological stations used in this study.

Table 2 .
Drainage areas studied in the Buenos Aires province.

Table 4 .
Statistical significance of the soil water surplus (sws) trends according to the Mann-Kendall test.

Table 5 .
Drainage area 3 (S3) results for MAKESENS test.Trend statistics of annual soil water surplus (sws) using the Mann-Kendall test and Sen's slope.