**2. Water source differentiation and quantification using natural tracers**

Inner-basin geological differences, in combination with climatic variables and sediment contact time through the basin, provide an ionic and isotope differential composition of natural waters [9–12].

Consequently, this chapter will focus in showing a combination of stable water isotopes and ionic tracer analysis, allowing the readers to identify surface water that originates in different sources like water released from ice bodies, groundwater, rain storms, or snow catchments.

#### **2.1. Ionic tracing**

From the universe of water compounds, in this section, we will focus on major ions, which are usually analyzed. Total salinity, measured by electrical conductivity, will also be discussed.

> Principal and calcium and magnesium bicarbonated for those of the Cordillera Frontal geological province can be seen. Precordillera presents bicarbonated sodium waters mostly. The influence of the petrographic characteristics from the Cordillera Principal, dominating with the presence of gypsum and marking the composition of the Mendoza River waters (mix), which is formed by all the tributaries along the whole studied basin can also be

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37

**Figure 2.** Upper Mendoza River basin (32° 50' S; 62° 45' W) geological map (Source: personal elaboration).

Isotopes are atoms of the same element that possess different neutron numbers in its nucleus, presenting equal atomic number but different mass numbers. The differences in mass generate a different behavior in physically reactions. The mass difference between the atomic nuclei is expressed in different reaction rates, because the isotopically heavier molecules have less mobility, resulting in a lower diffusion rate and a lower frequency of collision with other molecules. This derives in a lower possibility of physical reactions, a situation where light molecules react more frequently. This partitioning of isotopes between two substances or two phases of the same substance with different isotopic contents is known as isotopic fraction-

observed.

ation [13].

**2.2. Isotopical tracing**

In **Figure 2**, an example from an arid mountain basin (the upper Mendoza River basin) can be observed. The geological map of the area is composed from different geological provinces represented in different mountain ranges, named as Cordillera Principal, Cordillera Frontal, and Precordillera, from west–east direction, respectively. As usually occurs in mountain areas, because of the geological differences from each mountain range, water-draining these geologically different basin areas is expected to present different compositions of minerals and ionic chemistry (**Figures 3** and **4**).

In this case, the samples were taken at different sites in the basin, in 500 cc sterile plastic bottles. For these samples, electrical conductivity and the following major ions, bicarbonate (HCO3 − ), sulfate (SO4 −2), chloride (Cl<sup>−</sup> ), calcium (Ca+2), magnesium (Mg+2), sodium (Na+ ), and potassium (K+ ), were analyzed.

As can be observed in **Figure 3**, the geological differences expressed different ionic quantities in the rivers draining the different areas, and the total salinity is like a summary of this process.

For the ionic composition, in a more graphical representation with a Piper diagram (**Figure 4**), a sulfated calcium and magnesium composition for the samples extracted in the Cordillera Hydro-Geochemical Water Inputs Identification in Glacierized Basin Hydrology http://dx.doi.org/10.5772/intechopen.75390 37

**Figure 2.** Upper Mendoza River basin (32° 50' S; 62° 45' W) geological map (Source: personal elaboration).

Principal and calcium and magnesium bicarbonated for those of the Cordillera Frontal geological province can be seen. Precordillera presents bicarbonated sodium waters mostly. The influence of the petrographic characteristics from the Cordillera Principal, dominating with the presence of gypsum and marking the composition of the Mendoza River waters (mix), which is formed by all the tributaries along the whole studied basin can also be observed.

#### **2.2. Isotopical tracing**

contribution from each water source and the opportunity to deliver it in space and time using water natural tracers. These are water stable elements with different proportions in each different water source, without significantly changing their properties over time. This property can be analyzed and performs traceability during its journey in the hydrological cycle. In this chapter we will focus on the interpretation and use of two major types of natural water trac-

This could represent an important tool for policy-makers and the basin's sustainable develop-

Inner-basin geological differences, in combination with climatic variables and sediment contact time through the basin, provide an ionic and isotope differential composition of natural

Consequently, this chapter will focus in showing a combination of stable water isotopes and ionic tracer analysis, allowing the readers to identify surface water that originates in different sources like water released from ice bodies, groundwater, rain storms, or snow catchments.

From the universe of water compounds, in this section, we will focus on major ions, which are usually analyzed. Total salinity, measured by electrical conductivity, will also be

In **Figure 2**, an example from an arid mountain basin (the upper Mendoza River basin) can be observed. The geological map of the area is composed from different geological provinces represented in different mountain ranges, named as Cordillera Principal, Cordillera Frontal, and Precordillera, from west–east direction, respectively. As usually occurs in mountain areas, because of the geological differences from each mountain range, water-draining these geologically different basin areas is expected to present different compositions of minerals

In this case, the samples were taken at different sites in the basin, in 500 cc sterile plastic bottles. For these samples, electrical conductivity and the following major ions, bicarbonate

As can be observed in **Figure 3**, the geological differences expressed different ionic quantities in the rivers draining the different areas, and the total salinity is like a summary of this

For the ionic composition, in a more graphical representation with a Piper diagram (**Figure 4**), a sulfated calcium and magnesium composition for the samples extracted in the Cordillera

), calcium (Ca+2), magnesium (Mg+2), sodium (Na+

), and

ment in the present and future sociopolitical and climate scenarios.

**2. Water source differentiation and quantification using natural** 

ers: water stable isotopes and major ions.

36 Achievements and Challenges of Integrated River Basin Management

**tracers**

waters [9–12].

**2.1. Ionic tracing**

and ionic chemistry (**Figures 3** and **4**).

), were analyzed.

−2), chloride (Cl<sup>−</sup>

), sulfate (SO4

discussed.

(HCO3 −

process.

potassium (K+

Isotopes are atoms of the same element that possess different neutron numbers in its nucleus, presenting equal atomic number but different mass numbers. The differences in mass generate a different behavior in physically reactions. The mass difference between the atomic nuclei is expressed in different reaction rates, because the isotopically heavier molecules have less mobility, resulting in a lower diffusion rate and a lower frequency of collision with other molecules. This derives in a lower possibility of physical reactions, a situation where light molecules react more frequently. This partitioning of isotopes between two substances or two phases of the same substance with different isotopic contents is known as isotopic fractionation [13].

In order to express the contents of these less abundant isotopes, working standards are used for the measurement of the called δ values. Also, to facilitate interlaboratory comparisons, δ values are scaled to internationally accepted standards. Because water is composed by hydrogen and oxygen, and both present heavy stable isotopes, we will focus on these ones. The hydrogen heavy stable isotopes are deuterium and tritium. Oxygen presents two stable isotopes: 18O and 17O. This chapter

Hydro-Geochemical Water Inputs Identification in Glacierized Basin Hydrology

*RVSMOW*

In this way, when ocean water (which is considered to have an average δVSMOW value equal to zero) evaporates, it will generate a heavy isotope depletion (which evaporates proportionally less). When moisture is then transported by winds into the continent, water will be discharged as precipitation fractionating preferentially heavy isotopes along its path; therefore, the water vapor will become increasingly depleted on the heavy isotopes. This will leave a characteristic composition in different water sources, depending on the effects that modify this fractionation (continental effect, latitude, altitude, temperature, etc.). The resulting isotopic composition can then be analyzed and its origin and evolution traced [12, 13, 15], as can

composition of the different water sources arises from this explained isotopic partitioning.

H and the 18O [14]. The differential

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39

H is the VSMOW (Vienna Standard

H ‰, according to Eq. (1):

∗ 1000 (1)

will be focused in the more abundant and used: the deuterium 2

The standard commonly used to report the values of δ<sup>18</sup>O and δ<sup>2</sup>

Mean Ocean Water). Then, the values are expressed in δ<sup>18</sup>O y δ<sup>2</sup>

**Figure 5.** Water δ18O evolution content in the hydrological cycle (Source: personal elaboration).

<sup>δ</sup>*VSMOW* <sup>=</sup> *Rsample* <sup>−</sup> *<sup>R</sup>* \_\_\_\_\_\_\_\_\_\_\_ *VSMOW*

be observed in **Figure 5**.

**Figure 3.** Different mountain ranges' major ions, pH, and electrical conductivity water composition. (1) Ppal, refers to the Cordillera Principal geological province; (2) Ftal, to the Cordillera Frontal, and (3) Ppal-Ftal, to the Mendoza River where the waters incoming from Cordillera Principal and Frontal are mixed (Source: [12]).

**Figure 4.** Different geomorphological units within the Mendoza River basin and water ionic composition Piper diagram (Source: [12]).

In order to express the contents of these less abundant isotopes, working standards are used for the measurement of the called δ values. Also, to facilitate interlaboratory comparisons, δ values are scaled to internationally accepted standards. Because water is composed by hydrogen and oxygen, and both present heavy stable isotopes, we will focus on these ones. The hydrogen heavy stable isotopes are deuterium and tritium. Oxygen presents two stable isotopes: 18O and 17O. This chapter will be focused in the more abundant and used: the deuterium 2 H and the 18O [14]. The differential composition of the different water sources arises from this explained isotopic partitioning.

The standard commonly used to report the values of δ<sup>18</sup>O and δ<sup>2</sup> H is the VSMOW (Vienna Standard Mean Ocean Water). Then, the values are expressed in δ<sup>18</sup>O y δ<sup>2</sup> H ‰, according to Eq. (1):

$$\left. \Theta\_{\text{VSMCM}} \right| = \frac{R\_{\text{sample}} - R\_{\text{VSMCM}}}{R\_{\text{VSMCM}}} \ast 1000 \tag{1}$$

In this way, when ocean water (which is considered to have an average δVSMOW value equal to zero) evaporates, it will generate a heavy isotope depletion (which evaporates proportionally less). When moisture is then transported by winds into the continent, water will be discharged as precipitation fractionating preferentially heavy isotopes along its path; therefore, the water vapor will become increasingly depleted on the heavy isotopes. This will leave a characteristic composition in different water sources, depending on the effects that modify this fractionation (continental effect, latitude, altitude, temperature, etc.). The resulting isotopic composition can then be analyzed and its origin and evolution traced [12, 13, 15], as can be observed in **Figure 5**.

**Figure 3.** Different mountain ranges' major ions, pH, and electrical conductivity water composition. (1) Ppal, refers to the Cordillera Principal geological province; (2) Ftal, to the Cordillera Frontal, and (3) Ppal-Ftal, to the Mendoza River

**Figure 4.** Different geomorphological units within the Mendoza River basin and water ionic composition Piper diagram

(Source: [12]).

where the waters incoming from Cordillera Principal and Frontal are mixed (Source: [12]).

38 Achievements and Challenges of Integrated River Basin Management

**Figure 5.** Water δ18O evolution content in the hydrological cycle (Source: personal elaboration).

In the basis that environmental factors (such as geological and topographical settings, climate, isotope fractionation processes during cloud formation and precipitation) will imprint the stable water isotope composition, researchers have been using this isotopic finger print to identify the water source draining processes to rivers around the world.

Summarizing, isotopic compositions from the different water sources are affected by soilatmosphere exchange processes, such as precipitation, melting, evaporation, and sublimation [15], which will change according to the altitude, temperature, isotopic composition of the moisture source, and surface characteristics that affect the energy balance of the evaporation processes.

In the case of surface water sampled from the different geomorphological units in a mountain basin (in this case, Cordillera Principal, Cordillera Frontal, and Precordillera mountain ranges), when the co-isotope (δ<sup>2</sup> H and δ<sup>18</sup>O) composition is plotted (**Figure 6**), a significant increase in heavy isotope concentrations as altitude decreases (going east, from the Cordillera Principal to the Precordillera) is clearly observed. Isotopic composition differences between different water sources (glaciers, rock glaciers, groundwater, snow, or rivers) are also observed.

Another useful tool derived from isotopical tracing is the "deuterium excess." Under different conditions than 100% atmospheric humidity, the fractionation rate of hydrogen is higher than oxygen heavy isotopes. This difference in fractionation rates is expressed as the "deuterium excess" and is calculated according to Eq. (2):

$$\mathbf{d} = \delta^2 \mathbf{H} \mathbf{-} \mathbf{8} \* \delta^{18} \mathbf{O} \tag{2}$$

Since 18O/16O variations in precipitation were observed [16], Craig [17] described the Global Meteoric Water Line, and Dansgaard [18] introduced the deuterium excess concept, many decades have passed and the stable water isotope applications have developed rather fast. Currently, stable isotopes are widely used by scientists from many different fields to provide

**Figure 7.** Different water source deuterium excess values in Las Docas beach area, Central Chile (33° 8' S; 71°42' W). QLR stream refers to a seasonal stream inside Las Docas region. Lagoon stream refers to the tributary stream feeding the

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41

This value is very important to determine different evaporation processes, such as by water stagnation and evaporation. In **Figure 7** an example of water sources (in this case in Las Docas region, Central Chile) is presented. Deuterium excess values (d‰) from different streams, rain, and ocean, which fed the estuarine lagoon, show evident differences. The lower deuterium excess values of the lagoon are explained by evaporation processes. The hydrogen isotopes are more affected by the evaporation process than the oxygen heavy isotopes, by the

ionic determination. In this case, the differential signature can be detected using the deuterium excess value. In **Figure 8**, a graphic example is presented where it was possible to significantly differentiate uncovered glaciers (nr. 1) with snow basins (nrs. 7 and 9) through the differential evaporation condition expressed in the deuterium excess value for each source.

Using the chemical and stable water isotope characterization previously presented, a statistical analysis could be carried out to investigate if any significant differences can be identified and thus to strengthen the information that can be provided in order to identify different water sources. As it was observed for the Mendoza River basin (**Figures 4**, **6**, and **8**), the different tracer composition allows the contribution identification from different geographic origins in space and time, considering the characteristic composition of each type of water source in each subbasin and, from there, estimates the proportion and moment of water delivery in

H, δ18O, or

information about the origin and geochemical history of water.

estuarine lagoon (Lagoon) (Source: personal elaboration).

explained mass difference resulting in different fractionation inertias.

**2.3. Combined ionic and isotopic composition analysis**

a basin [12].

Sometimes, two or more water sources cannot be distinguished significantly via δ<sup>2</sup>

**Figure 6.** Dispersion of the stable isotope values of water samples analyzed in the Mendoza River basin. The blue line represents the Local Meteoric Water Line (LMWL), following the equation: δ<sup>2</sup> H = 8.29 δ18O + 13.13; R2 = 0.99. The red line represents the Global Meteoric Water Line, (GMWL) (15) (Source: [12]).

**Figure 7.** Different water source deuterium excess values in Las Docas beach area, Central Chile (33° 8' S; 71°42' W). QLR stream refers to a seasonal stream inside Las Docas region. Lagoon stream refers to the tributary stream feeding the estuarine lagoon (Lagoon) (Source: personal elaboration).

Since 18O/16O variations in precipitation were observed [16], Craig [17] described the Global Meteoric Water Line, and Dansgaard [18] introduced the deuterium excess concept, many decades have passed and the stable water isotope applications have developed rather fast. Currently, stable isotopes are widely used by scientists from many different fields to provide information about the origin and geochemical history of water.

This value is very important to determine different evaporation processes, such as by water stagnation and evaporation. In **Figure 7** an example of water sources (in this case in Las Docas region, Central Chile) is presented. Deuterium excess values (d‰) from different streams, rain, and ocean, which fed the estuarine lagoon, show evident differences. The lower deuterium excess values of the lagoon are explained by evaporation processes. The hydrogen isotopes are more affected by the evaporation process than the oxygen heavy isotopes, by the explained mass difference resulting in different fractionation inertias.

Sometimes, two or more water sources cannot be distinguished significantly via δ<sup>2</sup> H, δ18O, or ionic determination. In this case, the differential signature can be detected using the deuterium excess value. In **Figure 8**, a graphic example is presented where it was possible to significantly differentiate uncovered glaciers (nr. 1) with snow basins (nrs. 7 and 9) through the differential evaporation condition expressed in the deuterium excess value for each source.

#### **2.3. Combined ionic and isotopic composition analysis**

In the basis that environmental factors (such as geological and topographical settings, climate, isotope fractionation processes during cloud formation and precipitation) will imprint the stable water isotope composition, researchers have been using this isotopic finger print to

Summarizing, isotopic compositions from the different water sources are affected by soilatmosphere exchange processes, such as precipitation, melting, evaporation, and sublimation [15], which will change according to the altitude, temperature, isotopic composition of the moisture source, and surface characteristics that affect the energy balance of the evaporation

In the case of surface water sampled from the different geomorphological units in a mountain basin (in this case, Cordillera Principal, Cordillera Frontal, and Precordillera mountain ranges),

heavy isotope concentrations as altitude decreases (going east, from the Cordillera Principal to the Precordillera) is clearly observed. Isotopic composition differences between different water sources (glaciers, rock glaciers, groundwater, snow, or rivers) are also observed.

Another useful tool derived from isotopical tracing is the "deuterium excess." Under different conditions than 100% atmospheric humidity, the fractionation rate of hydrogen is higher than oxygen heavy isotopes. This difference in fractionation rates is expressed as the "deuterium

d = δ<sup>2</sup> H–8 ∗ δ<sup>18</sup> O (2)

**Figure 6.** Dispersion of the stable isotope values of water samples analyzed in the Mendoza River basin. The blue line

H = 8.29 δ18O + 13.13; R2 = 0.99. The red line

represents the Local Meteoric Water Line (LMWL), following the equation: δ<sup>2</sup>

represents the Global Meteoric Water Line, (GMWL) (15) (Source: [12]).

H and δ<sup>18</sup>O) composition is plotted (**Figure 6**), a significant increase in

identify the water source draining processes to rivers around the world.

40 Achievements and Challenges of Integrated River Basin Management

processes.

when the co-isotope (δ<sup>2</sup>

excess" and is calculated according to Eq. (2):

Using the chemical and stable water isotope characterization previously presented, a statistical analysis could be carried out to investigate if any significant differences can be identified and thus to strengthen the information that can be provided in order to identify different water sources. As it was observed for the Mendoza River basin (**Figures 4**, **6**, and **8**), the different tracer composition allows the contribution identification from different geographic origins in space and time, considering the characteristic composition of each type of water source in each subbasin and, from there, estimates the proportion and moment of water delivery in a basin [12].

concentration is observed in autumn, indicating the contribution of water with greater contact with sediments (groundwater). The observed changes from autumn to spring are observed in the ion dilution dimension and then again become a predominantly snow contribution in early summer. In this case, it was a temporal lagoon detected (purple circle in **Figure 9**). The water source that had been feeding the lagoon was unknown, because it could be a snowmelt or a groundwater water source origin. As can be observed (**Figure 9**), after the PCA analysis, the snowmelt provenance of the water filling this temporal small lagoon was inferred [12].

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43

In order to quantitatively estimate the relative contributions from each type of water source to a river flow, an end-member mixing analysis (EMMA) [19] could be performed based on the

In this way, the equation for proportions *(f)* of river inputs composed by three components (*C:* snow or rock glacier, glacier, and groundwater) requires the use of two tracers (ions and isotopes), and the ratio of each source is calculated according to the following set of equations

> <sup>1</sup> + *f* <sup>2</sup> + *f*

where f is the discharge fraction and C is the component concentration. The subscripts refer

<sup>1</sup> = 1 − *f*

tive, or there may be contributions from other sources not characterized (**Figure 10**).

For three components and two tracer models, as it was the example, the mixing spaces are defined by the two tracers (e.g., isotopic composition and electrical conductivity). If they are graphed, the three components must form the vertices of a triangle, and all the samples of the river must be framed by the triangle. If this standard is not met, the tracers are not conserva-

In this example, the relative contribution from each water source for the Cuevas River in

) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ (*<sup>C</sup>*<sup>1</sup>

(*C*<sup>1</sup> <sup>1</sup> − *C*<sup>3</sup> 1 ) \_\_\_\_\_\_ (*C*<sup>2</sup> <sup>1</sup> − *C*<sup>3</sup> 1 )) *f*

<sup>1</sup> − *f*

1 *f* <sup>1</sup> + *C*<sup>2</sup> 1 *f* <sup>2</sup> + *C*<sup>3</sup> 1 *f* <sup>3</sup> = *Ct*

2 *f* <sup>1</sup> + *C*<sup>2</sup> 2 *f* <sup>2</sup> + *C*<sup>3</sup> 2 *f* <sup>3</sup> = *Ct*

<sup>1</sup> − *C*<sup>3</sup> 1 )(*C*<sup>2</sup> <sup>2</sup> − *C*<sup>3</sup> 2 ) − (*C*<sup>2</sup> <sup>1</sup> − *C*<sup>3</sup> 1 )(*Ct* <sup>2</sup> − *C*<sup>3</sup> 2

<sup>1</sup> − *C*<sup>3</sup> 1 )(*C*<sup>2</sup> <sup>2</sup> − *C*<sup>3</sup> 2 ) − (*C*<sup>2</sup> <sup>1</sup> − *C*<sup>3</sup> 1 )(*C*<sup>1</sup> <sup>2</sup> − *C*<sup>3</sup> 2

<sup>1</sup> <sup>=</sup> (*Ct*

<sup>2</sup> <sup>=</sup> ( (*Ct* <sup>1</sup> − *C*<sup>3</sup> 1 ) \_\_\_\_\_\_ (*C*<sup>2</sup> <sup>1</sup> − *C*<sup>3</sup> 1 )) <sup>−</sup> ( <sup>2</sup> (3)

<sup>1</sup> (4)

<sup>2</sup> (5)

) (6)

<sup>1</sup> (7)

<sup>2</sup> (8)

**2.4. Water source input quantification**

(Eqs. 3 to 8):

And, finally

chemical determinations previously explained.

1 = *f*

to the components and superscripts to the tracers.

*C*<sup>1</sup>

*C*<sup>1</sup>

*f*

*f*

*f*

February 2014 is presented in **Table 1**.

**Figure 8.** Different water sources (in numbers) deuterium excess values (D‰) in the Cordillera Principal mountain range area, upper Mendoza River basin. (1) glacier, (2) debris-covered glacier, (3) debris-covered glacier and rock glacier, (4) total precipitation, (5) rock glacier, (6) rivers and streams, (7) "Valle Azul" stream in winter and spring, (8) snow, (9) "Los Puquios" stream in winter and spring, (10) groundwater (Source: [4]).

A combination of both, ionic and isotopic compositions, can reveal river behaviors along a year. In this case, a simplification thought a principal components analysis (PCA) can be a useful way. As can be seen in **Figure 9**, the first dimension of a principal component analysis (PCA), related to ion chemistry, separates groundwater from snow and ice bodies. The second dimension, related to stable isotopes, separates the snow and the different types of ice bodies (snow and rock glacier from uncovered or debris-covered glaciers). The temporal evolution of the different rivers along the main dimensions of the PCA shows a movement along the stable isotope axis, which is considerable in summer compared to autumn in several rivers. Saline

**Figure 9.** Stable isotopes and salts of water samples from the Mendoza River basin principal components analysis (PCA) plot. The behavior (marked by the dominance of the contribution of glaciers, groundwater, or snow) of the different subbasins that contribute to the Mendoza River (marked by the different rivers with the lines in different colors), throughout the seasons of the year. The number 1 corresponds to summer, 2 autumn, 3 winter, 4 spring, and 5 to the summer of the following year. In the upper left margin is the resulting characteristic of rock glaciers (brown stars) and snow precipitation (green and black circles). In the upper right of the groundwater (yellow rectangles and triangles) and, in the lower left, the characteristic features of glaciers (blue stars) (Source: [12]).

concentration is observed in autumn, indicating the contribution of water with greater contact with sediments (groundwater). The observed changes from autumn to spring are observed in the ion dilution dimension and then again become a predominantly snow contribution in early summer. In this case, it was a temporal lagoon detected (purple circle in **Figure 9**). The water source that had been feeding the lagoon was unknown, because it could be a snowmelt or a groundwater water source origin. As can be observed (**Figure 9**), after the PCA analysis, the snowmelt provenance of the water filling this temporal small lagoon was inferred [12].

#### **2.4. Water source input quantification**

In order to quantitatively estimate the relative contributions from each type of water source to a river flow, an end-member mixing analysis (EMMA) [19] could be performed based on the chemical determinations previously explained.

In this way, the equation for proportions *(f)* of river inputs composed by three components (*C:* snow or rock glacier, glacier, and groundwater) requires the use of two tracers (ions and isotopes), and the ratio of each source is calculated according to the following set of equations (Eqs. 3 to 8):

$$\mathbf{1} = f\_1 + f\_2 + f\_2 \tag{3}$$

$$\mathbf{C}\_1^1 f\_1 + \mathbf{C}\_2^1 f\_2 + \mathbf{C}\_3^1 f\_3 = \mathbf{C}\_i^1 \tag{4}$$

$$\mathbf{C}\_1^2 f\_1 + \mathbf{C}\_2^2 f\_2 + \mathbf{C}\_3^2 f\_3 = \mathbf{C}\_r^2 \tag{5}$$

where f is the discharge fraction and C is the component concentration. The subscripts refer to the components and superscripts to the tracers.

And, finally

A combination of both, ionic and isotopic compositions, can reveal river behaviors along a year. In this case, a simplification thought a principal components analysis (PCA) can be a useful way. As can be seen in **Figure 9**, the first dimension of a principal component analysis (PCA), related to ion chemistry, separates groundwater from snow and ice bodies. The second dimension, related to stable isotopes, separates the snow and the different types of ice bodies (snow and rock glacier from uncovered or debris-covered glaciers). The temporal evolution of the different rivers along the main dimensions of the PCA shows a movement along the stable isotope axis, which is considerable in summer compared to autumn in several rivers. Saline

"Los Puquios" stream in winter and spring, (10) groundwater (Source: [4]).

42 Achievements and Challenges of Integrated River Basin Management

**Figure 8.** Different water sources (in numbers) deuterium excess values (D‰) in the Cordillera Principal mountain range area, upper Mendoza River basin. (1) glacier, (2) debris-covered glacier, (3) debris-covered glacier and rock glacier, (4) total precipitation, (5) rock glacier, (6) rivers and streams, (7) "Valle Azul" stream in winter and spring, (8) snow, (9)

**Figure 9.** Stable isotopes and salts of water samples from the Mendoza River basin principal components analysis (PCA) plot. The behavior (marked by the dominance of the contribution of glaciers, groundwater, or snow) of the different subbasins that contribute to the Mendoza River (marked by the different rivers with the lines in different colors), throughout the seasons of the year. The number 1 corresponds to summer, 2 autumn, 3 winter, 4 spring, and 5 to the summer of the following year. In the upper left margin is the resulting characteristic of rock glaciers (brown stars) and snow precipitation (green and black circles). In the upper right of the groundwater (yellow rectangles and triangles) and,

in the lower left, the characteristic features of glaciers (blue stars) (Source: [12]).

And, finally

$$f\_1 = \frac{(\mathbf{C}\_r^1 - \mathbf{C}\_3^1)(\mathbf{C}\_2^2 - \mathbf{C}\_3^2) - (\mathbf{C}\_2^1 - \mathbf{C}\_3^1)(\mathbf{C}\_r^2 - \mathbf{C}\_3^2)}{(\mathbf{C}\_1^1 - \mathbf{C}\_3^1)(\mathbf{C}\_2^2 - \mathbf{C}\_3^2) - (\mathbf{C}\_2^1 - \mathbf{C}\_3^1)(\mathbf{C}\_1^2 - \mathbf{C}\_3^2)}\tag{6}$$

$$f^2 = \left(\frac{\left(\mathbf{C}\_1^\mathrm{i} - \mathbf{C}\_3^\mathrm{i}\right)}{\left(\mathbf{C}\_2^\mathrm{i} - \mathbf{C}\_3^\mathrm{i}\right)}\right) - \left(\frac{\left(\mathbf{C}\_1^\mathrm{i} - \mathbf{C}\_3^\mathrm{i}\right)}{\left(\mathbf{C}\_2^\mathrm{i} - \mathbf{C}\_3^\mathrm{i}\right)}\right) f^1\tag{7}$$

$$f\_1 = \ 1 - f\_1 - f\_2 \tag{8}$$

For three components and two tracer models, as it was the example, the mixing spaces are defined by the two tracers (e.g., isotopic composition and electrical conductivity). If they are graphed, the three components must form the vertices of a triangle, and all the samples of the river must be framed by the triangle. If this standard is not met, the tracers are not conservative, or there may be contributions from other sources not characterized (**Figure 10**).

In this example, the relative contribution from each water source for the Cuevas River in February 2014 is presented in **Table 1**.

inhabit the basins in mountain areas. The spatial and temporal distribution data of the water supply's main components is fundamental for the hydrological resource use and distribution planning among the basin's different social actors. These tools could be relevant to water supply projections and water demand regulations when analyzing the water source bail in upper basin areas, as a consequence of precipitation reduction and temperature increase in high elevations, which, for example, has resulted in a generalized retreat of the glaciers along the Central Andes [8, 20–22]. It is estimated that these glaciers' fronts and areas' negative variations are largely due to the rise of the 0°C isotherm in the region [23]. Also, when some corporations deny any specific water source contribution relevance, these tools can provide a

Hydro-Geochemical Water Inputs Identification in Glacierized Basin Hydrology

http://dx.doi.org/10.5772/intechopen.75390

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Recently, between 2010 and 2015, the Andes region between 29° and 35°S experienced the longest drought in the instrumental record [3]. This extraordinary event has occurred in the warmest decade of the last 100 years and apparently has no analogies in the last millennium, according to paleoclimatic reconstructions of this area [3]. The long-term climate projections also do not present an encouraging picture for this region of the Andes, since they indicate a tendency to warming and a greater recurrence of droughts in the coming

In view of the worrying future perspective that is coming for this region (and others) in terms of its reduction of strategic water resources, it is vital to know in detail the behavior of the different water sources associated with climate variability. In this chapter we have shown the different contribution along time and space from different water sources, which can be key information for the development of reservoir infrastructure and water distribution networks, generation of water supply, and distribution models for different uses, in addition to other

The use of ionic and isotopic tools, together with traditional hydrological and climatic data, can allow the creation of new information and early warning systems to reduce the risk of droughts and floods, among other applications that will modernize the way we guide decision-making in complex climate dynamic mountain basins. Besides this, extending these tools to other areas of the landscape, such as the foothills, lowlands, and valleys, will be useful to recognize and quantify changes in isotopic signatures in space and time. The knowledge of this water information can be considered analogous to the knowledge of the circulatory system in living organisms, because it is vital to diagnose the functioning and health of the ecosystems that feed on this resource in different basin zones. This information will favor the different water source feature identification from the feeding areas within the basin to the

In summary, the development of new geographic and temporal information systems using chemical and isotopic tools is of fundamental importance for water distribution, flood, and drought damping infrastructure planning scenarios. Interconnected to other environmental parameters, it will serve as a basis to establish development strategies and provide information for decision-making in areas that depend on mountain hydrology and its complex net-

good exploration analysis to determine their water contribution.

adaptation plans aimed at specific sectors of the population.

areas where it is used by each inhabitant of the territory.

work of water sources that supply the territory.

decades [1, 3, 24].

**Figure 10.** Scatter plot showing the isotopic and average electrical conductivity (EC) compositions for the different water sources that contribute to the Cuevas River in February (Source: [4]).


**Table 1.** Percentage contribution from different water sources to the Cuevas River along February 2014 (source: [4]).
