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Revista mexicana de ciencias geológicas

versión On-line ISSN 2007-2902versión impresa ISSN 1026-8774

Rev. mex. cienc. geol vol.35 no.3 México dic. 2018

http://dx.doi.org/10.22201/cgeo.20072902e.2018.3.1022 

Articles

Estimation of natural groundwater recharge in the Aguascalientes semiarid valley, Mexico

Estimación de la recarga natural de agua subterránea en el valle semiárido de Aguascalientes, México

Lilia Guerrero-Martínez1 

Martín Hernández-Marín2  * 

Thomas J. Burbey3 

1 Posgrado en Ciencias de los Ámbitos Antrópicos, Universidad Autónoma de Aguascalientes, Aguascalientes, Ags. 20131, Mexico.

2 Departamento de Geotecnia e Hidráulica, Universidad Autónoma de Aguascalientes, Aguascalientes, Ags. 20131, Mexico.

3 Department of Geosciences, Virginia Tech, 4044 Derring Hall, Blacksburg, VA 24061, USA.

Abstract:

Groundwater recharge (GWR) is analyzed and evaluated within the Aguascalientes Valley by means of a modified linearized Boussinesq equation and the Water Table Fluctuations (WTF) technique. These techniques use the specific yield, water table variations and the subsurface drainage of groundwater. The methodology is applied to the semiarid Aguascalientes valley, which contains a thick vadose zone. The combination of the analytical solution based on the Boussinesq equation and the WTF technique, allows the method to be applied in areas with deep groundwater levels, such as the Aguascalientes valley, without the need for high temporal resolution data. The data for the application of the method were provided by various government agencies and includes information on 145 wells positioned within the valley during the period 1985-2015. The specific yield and the transmissivity were integrated from the results of two previous investigations. Results indicate that the variation of recharge ranges from 0.86 to 525.69 mm/year in the analyzed period, with the highest recharge rates occurring in the north and center parts of the valley and is likely attributed to high specific yield and vertical hydraulic conductivity due to the presence of coarse permeable soils present in the area. Conversely, the lowest recharge rates were found to occur near the north and south borders of the valley.

Key words: groundwater recharge; Aguascalientes valley; Water Table Fluctuation; Boussinesq equation; groundwater drainage

Resumen:

En la presente investigación, la recarga de agua subterránea (GWR) se analiza y evalúa dentro del Valle de Aguascalientes mediante el ajuste a la ecuación linealizada de Boussinesq y la técnica Water Table Fluctuation (WTF), que involucra el rendimiento específico, la variación del nivel freático y el drenaje subsuperficial de aguas subterráneas. La metodología se aplica al semiárido valle de Aguascalientes que contiene una zona vadosa espesa. La combinación de la solución analítica basada en la ecuación de Boussinesq y la técnica WTF permite que el método se aplique en áreas con niveles profundos de aguas subterráneas, como el valle de Aguascalientes, sin la necesidad de datos de alta resolución temporal. Los datos para la aplicación del método fueron provistos por varias agencias gubernamentales a través de la información de 145 pozos ubicados a lo largo del valle durante el período 1985-2015. El rendimiento específico se integró a partir de los resultados de dos trabajos anteriores, así como la transmisividad. Como resultado, la variación de la altura de recarga se obtuvo de 0.86 a 525.69 mm/año en el período analizado, las tasas de recarga más altas se presentan al norte y al centro del valle, probablemente atribuidas a un alto rendimiento específico y conductividad hidráulica debido a la presencia de suelos permeables gruesos presentes en el área, por otro lado, las fronteras norte y sur del valle tienen las tasas de recarga más bajas.

Palabras clave: recarga de agua subterránea; valle de Aguascalientes; Water Table Fluctuation; ecuación de Bussinesq; drenaje subterráneo

INTRODUCTION

Historically, humanity has faced the complication of obtaining water because it is a necessary and indispensable resource in our daily activities. In many locations, surface water for human consumption has diminished over the last several decades leading to a necessary increase in groundwater extraction, particularly in many arid and semi-arid regions. For this reason, many semiarid regions have experienced a considerable reduction of groundwater storage as pumping has greatly exceeded natural recharge. Subsequently, researchers in these critical regions are focusing on studies aimed at understanding recharge processes and determining effective ways in which recharge can be enhanced naturally (Carrillo-Rivera, 2000, Carrera- Hernández et al., 2016, Manna et al., 2017, Müller et al., 2016; Scanlon, et al., 2010; Sharda, et al., 2006). Groundwater recharge (GWR) refers to the entry of meteoric water across the water table after first entering the soil zone. Recharge crossing the water table potentially enhances aquifer storage. GWR can occur in two ways, by a downward movement due to the gravity forces in the form of runoff and infiltration or by horizontal movement, which generally occurs as lateral contributions of groundwater flow from adjacent aquifers. Factors such as rate and direction of GWR depend on the hydraulic parameters of the geologic layers that make up the soil profile and aquifer systems in question (Balek, 1988). Groundwater recharge is one of the most important parameters in quantifying sustainability of aquifer systems. Several different methods have been employed to evaluate the quantity of recharge entering aquifer systems. These include physical and hydrogeochemical methods and numerical models (Scanlon et al. 2006, Simmers 1998, Scanlon et al. 2002). Other study factors such as: slope, depth to groundwater, infiltration rate, are used to determine the areas most suitable for groundwater recharge (Ghayoumian et al. 2007) or in the application of geographic information systems (SIG) and numerical modeling (Chenini et al. 2010). These factors are also used in the study of the temporal and spatial variation of recharge, along with the application of natural or artificial tracers (Hernández-Marín et al. 2018, Allison et al. 1994, Sophocleous 1991, Wang et al. 2008, Qin et al. 2011). It is worth mentioning that some techniques do not attempt to quantify an actual GWR rate, but rather estimate potential GWR, a term that refers to the water that infiltrates but does not instantaneously contribute to the aquifer storage, but rather where subsurface drainage actively participates so that the net storage change is not easily quantifiable. For example, in areas with a thick unsaturated zone, the direct influence of the rainfall on the water table and then on GWR varies both temporally and spatially depending on the hydrogeological conditions of the subsoil, precipitation pattern (e.g. intensity and duration) and evapotranspiration, as well as the geomorphological characteristics of the surface (Rushton, 1988, Scanlon et al., 2002). Taking these aspects into consideration, it becomes important to quantify the drainage in a rigorous manner to minimize the error in the quantification of an actual recharge rate that affects overall aquifer storage (Cuthbert, 2010).

In recent years, analytical techniques have been proposed for the evaluation of GWR. Many of these approaches assume that temporary changes in the groundwater level are controlled by two main factors: the balance of recharge and net drainage of groundwater (Crosbie, et al., 2005; Cuthbert, 2010; Jie, et al., 2011). These two factors can be applied to GWR when the aquifer systems are separated from the surface by a thick vadose zone. In this way, the potential recharge of aquifers under known climatic conditions depends mainly on the infiltration from surface water bodies and the lateral contributions.

The aim of this research is to evaluate the potential GWR by applying an analytical adjustment of the Water Table Fluctuation (WTF) technique, in combination with the Boussinesq equation for the quantification of drainage. This methodology is applied to the aquifer of the Aguascalientes Valley, where the territory is classified as semi-arid (POEA, 2013) and 94% of water use originates from underground sources (CONAGUA and SEMARNAT, 2016). The WTF method is based on two intrinsic factors of the aquifer: (1) variations of the static water levels and (2) specific yield. The Boussinesq equation is related to hydraulic conductivity and aquifer thickness (or transmissivity). A further goal is to create a recharge map containing isovalues over the study area and the variations in the recharge isovalues will be discussed in the context of the overall hydrogeology of the region. This analysis will raise awareness about the sustainable management of the local aquifer, as well as to help in decision-making of actions such as the establishment of waste disposal areas, or the delimiting of areas vulnerable to groundwater pollution and to better understand their possible occurrence.

CHARACTERISTICS OF THE STUDY AREA

The study area corresponds to the valley of Aguascalientes in the state with the same name, occupying a strip having a North-South orientation and extending a length of approximately 80 km and a width of 25 km as shown in Figure 1. This zone is in a tectonic graben as described by Aranda-Gómez (1989).

Figure 1 Location of the study area. The main urban centers of the zone are highlighted in yellow. 

The San Pedro River represents the main hydrographic feature of the Valley and flows from north to south almost through the center of the valley. The main land uses in the study region include agriculture with intensive irrigation and livestock (63%), natural pasture (16%), shrubs (15%), oak forest (3.9%), mesquites (0.2%), with the remaining 1.9% corresponding to urban areas, where more than 85% of the population of the state resides (CONABIO et al., 2008, INEGI, 2018). It is important to mention that of the 50 thousand hectares dedicated to the agricultural activities within the valley, almost the entire area is irrigated with groundwater, although there is an important potential for the reuse of groundwater from irrigation, (CONAGUA, 2005; Pacheco-Martínez et al., 2013). In terms of climate, 68% of the territory of Aguascalientes is semi-arid with an average maximum temperature of 25 °C, and an annual average rainfall of 526 mm and annual average potential evaporation of 2,200 mm. The rainy season occurs mainly during summer, with only occasional rainfall during the other seasons of the year (INEGI, 1993).

Geomorphologically, the study area is relatively flat with small hills distributed within the area and increasing slopes toward the mountains. The valley is located between the Tepezalá mountains of to the east and the Sierra Fría mountains in the west. The average altitude of the Aguascalientes Valley is 1,900 m. The valley includes two important physiographic provinces. The Mesa Central is in the east, while the Sierra Madre Occidental is to the west and consists of valleys and elongated mountain ranges oriented mainly NW-SE and NE-SW (CONAGUA, 2018). According to UNAM-UAQ (unpublished data, 2002) a predominance of alluvial and fluvial deposits occurs within the valley with the topmost sedimentary sequence composed primarily of detrital rocks derived from unconsolidated alluvial materials and classified as clays, silts, sands and gravels according to their grain size. The general stratigraphic sequence was determined through vertical electric soundings (SEVs) that were performed throughout the study area (Zermeño-Villalobos, 2016). Beneath the detrital rocks it was determined that the unconsolidated deposits exhibit a variable thickness from a few meters in the periphery of the valley, to up to 380 meters in the center (Hernández-Marín et al. 2018). Approximately 200-300 meters of compacted lithified sediments (conglomerates and sandstones) and fractured igneous rocks (rhyolites and ignimbrites) occur below the fluvio-alluvial refill that occupies the center of the valley. The compacted conglomerates outcrop mostly in the west, while igneous rocks can be observed in the east, conforming to the orientation of the mountain ranges. An analysis of the lithology of the unconsolidated central sediments was evaluated based on the SEV results and the lithological records of deep well logs, which suggests a stratigraphic configuration of coarse sediments such as gravel and sand, with smaller portions of clay and silt. Groundwater is determined to flow from north to south according to water level observations from measured wells. The chief aquifer of the Aguascalientes valley is considered unconfined (DOF, 2012), but with a thick vadose zone. As expressed by some local drilling engineers (Fuentes-López, expert in geophysics and geology, personal communication, 2018), currently no uprising of water levels in wells occurs during drilling, despite the presence of a thick vadose zone. Therefore, the local aquifer is considered as free or unconfined because this type of aquifers is defined by its response to groundwater pressure, regardless of the thickness of the vadose zone.

METHODOLOGY

Conceptualization and analysis of the WTF technique and the quantification of drainage

According to Vélez-Otálvaro (2004) the methods to determine the GWR can be classified into five categories: direct measurements, water balance, chemical tracers, Darcy-Law approximations, and empirical methods. This author also states that some of the most reliable methods for estimating the recharge of semi-arid zones such as the Aguascalientes valley are chemical tracers, direct measurements and water balance. In this research the water balance method is used to quantify recharge and specifically invokes the method of variations of groundwater, defined as Water Table Fluctuation or WTF. This method has been used in several research investigations. Healy and Cook (2002), for example, presented an excellent review of theory and its applications. Cuthbert (2010) performed an analysis that includes underground drainage to minimize the error in the recharge estimate by developing an expression for the drainage component, which is a function of the hydraulic gradient and transmissivity and therefore hydraulic conductivity and saturated thickness. In general, the WTF technique is applicable to several hydrologic scenarios, including ones in which the water table is deep and / or where groundwater levels can vary smoothly, if the hydrogeological properties of the aquifer are relatively well known.

The expression used in the method assumes that temporal water-level changes of an aquifer are controlled by the recharge balance R (mm/year) and the net drainage of groundwater D (mm/year) at a given observation point for a certain period of time, t. The recharge can be calculated as:

R=Syhδt+D (1)

Where S y represents the specific yield, ∂h/∂t is the temporal variation of the water table in the study area, and D is the drainage.

The WTF method frequently ignores factors such as trapped air or barometric fluctuations that may affect the water level (Healy and Cook, 2002). In addition, the water that infiltrates and moves through the unsaturated zone can vary significantly in time and quantity, depending on certain conditions such as evapotranspiration, porosity, hydraulic conductivity, specific yield, and depth. The main limitations of the WTF technique are the difficulties of defining and estimating the specific yield as well as the quantification of drainage in areas with thick unsaturated zones, since in shallow water tables, the error in drainage may be minimal because the water level may increase significantly during a rainfall period. Therefore, in areas with a considerably deep water table, it is important to rigorously estimate the drainage to minimize the error in the quantification of the recharge, as suggested by Cuthbert, (2010). This author also establishes the equation for the drainage calculation considering the case of an ideal homogeneous horizontal aquifer limited at one end with x = 0, conceptually representing a boundary without flow (e.g. the mountains along the basin perimeter), and at the other end with x = L where a river exists and exhibits a constant head boundary condition, as shown in Figure 2. This idealized scenario is a typical conceptual representation of many aquifer systems.

The calculation of the drainage is based on the one-dimensional Boussinesq equation of the groundwater flow for an aquifer that receives homogeneous recharge and that follows a sinusoidal pattern. The applicable equation is the following:

D=2h¯tL2x2 (2)

Figure 2 Idealized conceptual section of an aquifer that receives recharge with sinusoidal variation of the water level h (x, t) (Cuthbert, 2010). 

Where T is the transmissivity (m²/d) and h¯ is the hydraulic gradient. Recalling that the transmissivity is the product of the aquifer thickness b (m) and the average value of the hydraulic conductivity k (m/d) (Freeze and Cherry, 1979).

By combining equations 1 and 2, the recharge and drainage can be calculated for a period of time as:

R=Syht+2h¯TL2x2 (3)

Specific Yield (S y ) estimation

The specific yield S y is a fundamental parameter in the WTF method and can be defined as the volume of water released per unit area of the unconfined aquifer when the water table decreases by one unit of height. However, this definition is only valid under conditions of equilibrium and small-scale experiments. Currently, there are several methods to measure S y , such as laboratory, fieldwork, empirical, etc. However, they all have a degree of associated uncertainty. Commonly, S y is assumed to be a constant value (Healy and Cook, 2002, Tritscher et al., 2000), although this parameter varies depending on the different intrinsic conditions of the aquifer such as the local water flow, the depth of the phreatic level and the heterogeneity of the soil (Fetter, 2001). Thus, its variability depends on the factors that are considered for its calculation and the means in which they are obtained (Childs, 1960). The specific yield is inherently treated as a storage term independent of time in the WTF method, which in theory explains the instantaneous release of stored water.

APPLICATION OF THE METHOD

Estimation and distribution of specific yield S y

The distribution of the specific yield throughout the study zone was mapped based on the results of two previous investigations, (UNAM-UAQ unpublished data, 2002; CONAGUA 2015).

In the first report, a numerical groundwater model was developed using the Visual-Modflow package program, in which a map of the variation of S y was developed through model calibration, which yielded a S y isocurve map for year 1996. The researchers used a total of 160 wells during their modeling analysis. In the second report, the results of 13 pumping tests ranging from hours to days were performed in the north and center of the Aguascalientes Valley. Time-drawdown curves were developed from the pumping tests and compared with the theoretical curves developed by Boulton (1963), Neuman and Witherspoon (1972) and Moench (1996) for the calculation of the specific yield at each pumping test location. Linear interpolation was then used to create a map of the variations of S y in the area where the pumping tests were performed. The S y maps from both investigations were combined algebraically using the multilevel B-spline interpolation method to create a new map of the variation of the specific yield in the study area. The new map is shown in Figure 3.

Figure 3 Distribution of the specific yield in the study area. This map combines the results from UNAM-UAQ (unpublished data, 2002) and CONAGUA (2015) using the interpolation Multilevel B-Splines method. 

Evaluation of groundwater levels

Groundwater levels were obtained by analyzing data provided by government agencies such as PROACTIVA medio Ambiente CAASA, which is the company commissioned for the distribution of water in the municipality of Aguascalientes, and the CONAGUA. Both agencies provided the static water levels of wells measured throughout the Valley during the period 1968-2015. This investigation focuses only on the period between 1985 and 2015. Figure 4 shows a map with the location of the wells with the provided data, the measurements in the wells are mostly annual and sometimes monthly.

Figure 4 Location of wells used in this study and provided by CONAGUA and PROACTIVA Medio Ambiente CAASA. 

Unfortunately, as in many cases, not all the wells have complete data that could be used for direct application of the method, thus, a classification of the wells was performed in order to discard those without sufficient information. To determine which and how many wells would be included in the study, we first considered those active during 2015, recalling that this is the most recent year of the analysis period. The availability of regular measurement records was also considered. In some cases, the missing data was completed by applying one of four statistical methods according to the amount of missing data and the location of the well in the valley. The methods applied were linear regression, neighborhood averages, average ratios and the correlation method. As a final analysis, 145 wells were used for the application of the WTF technique.

Estimation of underground drainage

To estimate the underground drainage, the methodology described by Cuthbert (2010) was considered. As mentioned earlier, this author proposed a conceptual model with the section of a free aquifer of length x = L. In the study area, this model is represented by a section of the basin of the Aguascalientes valley, where the San Pedro River would form a constant hydraulic head boundary, while the model periphery represents a no-flow condition at x = 0 as shown in Figure 5 (see also Figure 2 and Eq. 3).

Figure 5 All sections (represented as horizontal lines) on the Aguascalientes valley were used to estimate the drainage, with x = 0 representing the no-flow boundary, and x = L representing a constant-head boundary, which coincides with the location of the San Pedro River through the center of the valley. 

The values of transmissivity were taken from reports of various agencies of both public and private sectors (Table 1). Similarly, as was done for creating a map of S y , the B-Spline Multilevel technique was used as an interpolation method to obtain the distribution of the transmissivity distribution in the study area as shown in Figure 6.

Table 1 Transmissivity values taken from various agencies of the public and private sectors (CONAGUA, 2015). Coordinates in WGS 84 / UTM Zone 13Q North. 

Well
ID
UTM Coordinate T
(m2/day)
Well
ID
UTM Coordinate T
(m2/day)
Well
ID
UTM Coordinate T
(m2/day)
Well
ID
UTM Coordinate T
(m2/day)
X Y X Y X Y X Y
68-22 775938 2416730 846.72 42-79 778242 2441802 648 27 788605 2425861 13.0464 III 785023 2418770 409.536
51-50 782121 2434346 388.8 42-33 780569 2444860 864 34 783284 2422929 655.776 X 790796 2452293 607.392
33-43 780214 2452735 1123.2 33-52 784818 2455822 138.24 41 782917 2422196 402.624 VIII 794399 2449891 9.504
23-4 777303 2461804 518.4 43-4 798648 2445439 250.56 44 782137 2422104 538.272 VII 799734 2448679 72.4896
24-57 786328 2461753 544.32 23-3 775953 2462251 181.44 53 783513 2421050 384.48 VI 772512 2461130 55.0368
3-10 777821 2484558 362.88 24-6 781780 2470351 475.2 56 782871 2419905 686.016 IV 778544 2465290 1161.993
78-6 780934 2406973 95.04 15-2 780668 2480729 250.56 58 784385 2420180 113.184 V 783632 2465257 209.952
68-16 774098 2417086 146.88 41 787028 2475627 19.872 64 781765 2416606 26.0928 88 779641 2476307 11.7504
79-1 799641 2412077 1468.8 1 779000 2485523 551.23 66 785165 2419492 13.1328 7A 786555 2474032 55.1232
60-26 779474 2425622 129.6 19 778799 2482188 436.32 69 786770 2418943 12.8736 90 779302 2468233 13.824
50-64 775976 2433108 26.784 3 781994 2430787 51.235 98 789155 2415186 2.68704 68 777563 2447623 58.4928
51-87 790663 2435136 23.328 9 785164 2429507 8.0697 I 783485 2418911 1099.958 172 772481 2431870 7.56
PAB-4 790683 2438531 49.248 21 782129 2424253 328.32 II 784144 2417735 244.512 178 780264 2399489 5.14944

Figure 6 Distribution of transmissivity. Map resulting from the Multilevel B-Splines interpolation and the data of Table 1

RESULTS

The GWR was calculated for each of the 145 wells using Eq. 3 along with the isocurves from Figures 3 and 6. The calculated GWR and the parameters used in the computation are compiled in Table 2 (which only shows the results of 30 wells for brevity). This table also includes some of the annual data over the span of the 30-year analysis.

Table 2 Representative sample of results of the application of the WTF method (Δh*) and the analytical solution of the Boussinesq equation (D*) for the estimation of GWR (R*). The differences in the value of the column of Sy and T are determined by the location of the well on the maps of specific yield and transmissivity, respectively. h¯* corresponds to the hydraulic gradient of the wells analyzed to the San Pedro River, x* is the distance from the boundary of the basin to the location of the well, L* is the total distance from the boundary of the basin to the San Pedro River, passing through the analyzed well; T indicates the transmissivity, D* is the drainage calculated with equation 2; Sy indicates the specific yield, Δh* is the variation hydraulic head between the first and last years of analysis (from 1985 to 2015); and R* indicates the annual recharge obtained through the proposed methodology. Coordinates in WGS 84 / UTM Zone 13Q North. 

Well
ID
UTM Coordinates h¯ *
(m)
x*
(m)
L*
(m)
T*
(m2/d)
D*
(mm/d)
S y * Δh*
(mm)
R*
(mm/year)
X Y
1 778394.6 2484628 0.020 4108.600 9267.440 423.360 0.087 0.004 36926.781 5.134
4 781311.2 2480026 0.015 4108.600 9267.440 259.200 0.042 0.004 53880.000 7.406
6 780709.7 2476737 0.010 4108.600 9267.440 86.400 0.010 0.004 57869.300 7.918
7 783861.7 2477367 0.004 4108.600 9267.440 181.440 0.008 0.004 85882.023 11.745
10 778877.9 2471298 0.004 5647.180 14086.210 293.760 0.005 0.080 57729.936 153.951
11 786033.2 2470462 0.004 12846.190 14411.690 259.200 0.018 0.004 51989.000 7.124
12 781580.1 2470578 0.004 8457.590 13485.980 432.000 0.012 0.004 60167.400 8.235
13 788169.5 2473568 0.021 5373.620 7070.390 98.323 0.070 0.004 64326.668 8.862
14 785940.1 2470072 0.037 12696.830 14518.230 267.494 0.145 0.004 6655.400 1.054
15 778958.6 2476200 0.011 2176.640 9161.830 42.336 0.004 0.004 46484.005 6.357
17 778468.7 2465203 0.001 5791.200 14414.310 1140.480 0.007 0.100 49921.400 166.411
18 781394.1 2463445 0.002 7230.370 12755.150 437.184 0.006 0.200 55283.600 368.563
19 784890.3 2467963 0.009 12411.420 14881.270 3162.240 0.321 0.004 52230.800 7.460
20 779191.5 2460838 0.002 5933.510 13432.770 451.872 0.006 0.100 52855.500 176.191
21 785664.4 2461996 0.007 11204.060 12330.950 535.680 0.096 0.082 56919.500 155.676
22 784988.9 2462107 0.006 10587.270 12199.260 453.600 0.056 0.200 48847.704 325.707
23 780607.9 2461276 0.004 6786.290 12907.140 449.280 0.010 0.082 65161.700 178.119
25 777425.6 2457806 0.000 4378.570 13380.330 419.040 0.000 0.082 44765.546 122.359
27 777473.5 2442462 0.006 7211.950 13387.010 599.616 0.019 0.082 44147.392 120.689
28 780722.9 2458545 0.004 8737.350 14505.950 428.544 0.008 0.100 65455.900 218.195
30 783625.3 2452290 0.001 13941.470 16109.780 518.400 0.004 0.082 58538.500 160.009

GWR shown in Table 2 was converted into a digital map for further analysis. The results reveal the regions with the highest and lowest estimated GWR within the study area. The greatest recharge is located mainly in the northern and central parts of the valley, where a maximum recharge of 525.67 mm/year is estimated. Conversely, at the north and south boundaries of the study site, as well as in the metropolitan area of the city of Aguascalientes, the lowest values of GWR are estimated to be on the order of 0.086 mm/year. Figure 7 shows the calculated distribution of the recharge for the study area.

Figure 7 General map of GWR rate. 

DISCUSSION

The results from Figure 7 clearly show that the center and north portions of the valley have the largest rates of GWR. These areas of high recharge can be attributed in part to the dominant type of soil, which corresponds to course-grained alluvial deposits with relatively high values of specific yield and hydraulic conductivity (0.010 to 0.30 and 0.2 to 20 m/d respectively). Furthermore, as a consequence of the predominance of this type of soil, the estimated drainage increases in the vicinity of the San Pedro River, which is likely enhanced by extensive agricultural practices in this area due to the high return volume of irrigation water to the subsoil. Conversely, the regions with the lowest estimated rates of GWR, located at the north and south boundaries of the valley, as well as in the metropolitan area of the city of Aguascalientes, is attributed to the large discharge of groundwater that lowers water levels and consequently thickens the vadose zone and results in reduced levels of estimated recharge. Also, possibly contributing to the reduced estimates of recharge is, the presence of sandstones and conglomerates exhibiting a low specific yield and small hydraulic head variations. Interestingly, these low recharge areas are where the highest calculated contributions by drainage occur. Clearly, the high drainage does not appear to make a significant difference in the general estimation of recharge.

When comparing the recharge estimated in this study with that estimated by UNAM- UAQ (unpublished data, 2002) using natural tracers (O-18 and Deuterium) the zones with the largest potential for recharge coincide with the results estimated in this investigation. Furthermore, they also determine that the zone with the lowest potential for recharge is within the city of Aguascalientes, which also coincides with the results presented here.

On the other hand, an estimation of natural recharge reported by CONAGUA (2018) takes into account a water balance with four factors: underground horizontal flow input based on the static level and Darcy's law (83.1×106 m³), horizontal flow outputs with an estimated volume of 2.4×106 m³, pumping of 427.4×106 m³ and storage change, taking into account the configuration of the evolution of the static level registered during the period 2000-2014, with an annual average of -180.2×106 m³, the natural recharge estimated by CONAGUA is 249.6×106 m³, but if only the vertical recharge is taken into account CONAGUA recharge is 166.5×106 m³, which is 0.9% less than the total recharge estimated in this investigation (168×106 m³). It should be noted that in the technique described here, does not consider the horizontal recharge. Despite the different methods used in the calculation of the vertical recharge, the results are almost equal, these comparisons indicate that the technique proposed in this work is applicable to the Aguascalientes valley, although it may be necessary to apply new methodologies or to include new factors in the future to reduce uncertainly in estimated recharge. Some of the factors to consider may be water bodies, effects of anisotropy, and climate data for long-term periods.

CONCLUSIONS

This investigation presents a methodology for the estimation of groundwater recharge (GWR) by employing an analytical solution of Boussinesq for unconfined flow into the Water Table Fluctuation (WTF) method. The study area encompasses the semi-arid valley of Aguascalientes, in central Mexico. This rectangular north-south trending valley represents a tectonic graben that is about 80 km in length and 25 km in width. The estimated GWR is variable throughout the valley with an estimated maximum annual value of 526.26 mm and a minimum annual rate of 0.86 mm. The areas with the greatest estimated recharge are located at the northern and central parts of the valley and is attributed to agricultural practices and coarser-grained soils in these areas. Conversely, the lowest estimated recharge occurs along the north and south boundaries of the study area and within the city of Aguascalientes. These low values are attributed to heavy pumping, which lowers the water level and increases the thickness of the vadose zone as well as to lithologies having a low specific yield. The results present similarity in volume and space, with previous studies.

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Recibido: 25 de Julio de 2018; Revisado: 20 de Agosto de 2018; Aprobado: 24 de Agosto de 2018

* Corresponding author: Martín Hernández-Marín, e-mail: mhernandez@correo.uaa.mx

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