Geographic location

The Calera aquifer is located in the central zone of the state of Zacatecas, Mexico. Its central-southern zone is made up of the municipalities of Enrique Estrada, Calera and Morelos, with an area of 766,447 km², representing 33.97 % of the total area of the aquifer. It is bordered to the north by the municipality of Fresnillo, to the east by Pánuco and Vetagrande, to the south by Zacatecas and to the west by Jerez (Figure 1). The zone has a predominantly semi-dry temperate climate with average annual temperatures of 14.6 to 16.6 °C (^{IGH, 2010}), average annual precipitation of 425 mm and evapotranspiration of 2 263 mm per year (^{CONAGUA, 2015}).

Figure 1 Location of the central-southern zone of the Calera aquifer. Source: Author-made. 

Study crops in the central-southern zone of the Calera aquifer

The study was carried out on irrigated crops for the 2007-2017 period. The crops were determined considering their relative importance in terms of their percentage contribution to the planted area and gross production value of the agricultural census of the municipalities of Enrique Estrada, Calera and Morelos (^{Sistema de Información Agroalimentaria y Pesquera [SIAP], 2018}) (Table 1); for this, the drip and gravity irrigation systems reported by ^{Vélez et al. (2013)} were considered.

Agricultural water productivity

Agricultural water productivity was calculated using Equation 1 (^{Molden, Murray-Rust, Sakthivadivel, & Makin, 2003}) and expressed in physical and economic terms (^{Bessembinder, Leffelaar, Dhindwal, & Ponsioen, 2005}).

Where WP is the agricultural water productivity (kg·m^-3 or $·m^-3), R is the production volume (kg) or production value ($), and V is the volume of water used for irrigation (m³).

Physical water productivity

The variables analyzed were planted area (ha) and production volume (t), for the period, crops and municipalities mentioned above. The values were obtained from the SIAP database (2018). The reported values for each variable were added to obtain the totals for the study area and each crop per year.

Irrigation volume was calculated with Equation 2, for which the information presented in Table 2 was used.

Where V _ji is the total irrigation volume (hm³) of crop j (garlic, alfalfa, onion, green pepper, dry bean or corn for grain) and of year i of the period 2007 to 2017, ST is the total planted area (ha), Lr is the irrigation depth (cm) and 10 000 is a conversion factor to hm³. The production volume R of the alfalfa crop was considered to be dry product at 20 % moisture.

Economic water productivity

Gross and net economic water productivity levels were calculated. The first was determined because no information on production costs was found for the years 2007 to 2016 and it was desired to know their behavior in the period studied. On the other hand, net economic productivity was calculated only for 2017 for all crops, for which production costs with a 9-CU rate subsidy and those without a 9 rate subsidy were considered. This was done in order to have a result closer to reality and to know the impact that this stimulus has on the aquifer.

The variable average rural price (ARP) (in pesos per ton) was analyzed for the period and the municipalities studied. The values were obtained from ^{SIAP (2018)} and averaged for each municipality by crop and year.

The gross production value was obtained by multiplying the ARP by annual physical production. The valuation of gross and net economic productivity, subsidized and unsubsidized, was performed with the June 2012 base period = 100 using the National Producer Price Index reported by ^{INEGI (2019)}. Results were expressed in constant Mexican pesos (MXN).

Production costs with and without subsidy

Before describing production costs, it is important to note that the cost of “irrigation” was considered as the cost of electricity consumed by pumping water for irrigation and labor for its application; this is because no water fees are paid for agricultural use. Emphasis is placed on this concept because it involves the object of study and the subsidy that impacts the aquifer.

For production costs with a 9-CU rate subsidy, those provided by ^{SAGARPA (2018b)} (Table 3) were taken into account.

Production costs without subsidy were estimated based on the costs reported by ^{SAGARPA (2018b)}, for which the cost of irrigation was replaced by the one calculated with the costs of the 9 rate (^{CFE, 2018}) and the following characteristics of an average well located in the study area were considered: flow rate of 37 L·s^-1, pumping depth of 150 m, average equipment efficiency of 60 % (indicated in NOM-006-ENER-2015 as the minimum for 126 to 350 HP submersible pump motors [^{DOF, 2015}]) and a 25-m water column to contemplate total losses in suction and discharge, as well as delivery pressure at discharge.

Electricity consumption was calculated using the following equation:

where:

Csmo EE _j is the electricity consumption per unit area of crop j (kWh·ha^-1), VU _j is the irrigation volume per unit area of crop j (m³·ha^-1), HP is the horsepower, Q is the pumped flow rate (37 L·s^-1), γ is the specific weight of water (1 000 kg·m^-3), CDT is the total dynamic load (m), η _mB is the efficiency of the engine and pump (dimensionless), 76 is the conversion factor of kW units to HP that contemplates water temperature correction, 0.746 is the conversion factor of HP units to kW, h _s is the suction height (m), Hf are the total load losses that the liquid undergoes in the suction and discharge piping (m), h _d is the discharge load height (static load) (m) and v22g is the discharge velocity load (m), where v is the discharge velocity (m·s^-1) and g is the gravitational acceleration (9.81 m·s^-2).

Once the electricity consumption was calculated, its cost (CEE) in pesos per hectare was determined with Equation 6, for which an average rate 9 price of $9.377·kWh^-1 for the months May-September 2017 (^{CFE, 2018}) was considered.

Physical water productivity

Onion was the most efficient and productive crop in terms of water use. On average, this crop had a productivity 3.6 times higher than that of garlic, which was the second most efficient crop, and 18 times higher than that of dry bean, which was the least efficient crop (Table 4 and Figure 2).

Figure 2 Physical water productivity during the 2007-2017 period in the central-southern zone of the Calera aquifer, Zacatecas, Mexico. Source: Author-made based on data from the Comisión Nacional del Agua (^{CONAGUA, 2018}) and the Sistema de Información Agroalimentaria y Pesquera (^{SIAP, 2018}).  

Subsidized and unsubsidized production costs

The garlic crop had the highest production cost (Table 5) due to the cultural work carried out, as well as the amount of fertilizers, insecticides and fungicides it demands. On the contrary, dry bean turned out to be the crop with the lowest cost per hectare, which may be partly why it is the crop with the largest area in the study zone, in addition to custom, as indicated by ^{Vélez et al. (2013)}.

Based on data provided by ^{SAGARPA (2018b)}, it was observed that, on average, 15 % of production costs were allocated to the electricity used in pumping water for irrigation; however, if the 9-CU rate subsidy did not exist, an average of 63.5 % of total costs would be allocated to the payment of electricity. In this way, alfalfa, garlic and onion would allocate up to 85, 37 and 48 % of the total costs for this item, respectively.

Institutions such as the Organization for Economic Cooperation and Development (OECD), the World Bank, the United Nations Educational, Scientific and Cultural Organization (UNESCO) and SAGARPA agree that subsidizing electricity for pumping water for agricultural irrigation is a program that has negative effects, since it promotes incentives for inefficient production and damages the environment (^{Moreno-Vázquez et al., 2010}), making it a determining factor in the depletation of aquifers (^{Secretaria de Medio Ambiente y Recursos Naturales [SEMARNAT], 2012}).

This study estimated a total subsidy, approximate to the cost of electricity of 338.6 million pesos in 2017 (Table 6), which grows exponentially compared to the linear growth of the 9-CU and 9-N rates (Figure 3).

Figure 3 Behavior of electricity rates. Source: Author-made based on data from the Comisión Federal de Electricidad (^{CFE, 2018}). 

Green pepper and alfalfa were the crops that received the greatest benefit, the first due to the area it occupied, and the second due to the amount of irrigation required. According to ^{SEMARNAT (2012)}, the subsidy for agricultural pumping is inequitable at the national level, since while 10 % of the largest users receive 409 thousand pesos per year, 20 % of the smallest irrigation units receive 113 pesos per year. In other words, this subsidy benefits the richest farmers, and it is to be assumed that something similar happens in the study area, since green pepper was the most benefited crop, and at the same time the one with the greatest investment per total occupied area, which indicates that the producers of this crop have greater economic resources and are favored more with the subsidy.

Economic water productivity

Gross economic productivity showed growth across all crops (Figure 4).

Figure 4 Gross economic productivity of the 2007-2017 period. Source: Author-made based on data from the Sistema de Información Agroalimentaria y Pesquera (^{SIAP, 2018}). 

Without considering production costs, economic productivity was high in 2017 (Table 7), compared to the values obtained with energy subsidies (Table 8). The vegetable group had higher gross and net economic productivity, with and without electricity subsidies. This group had positive unsubsidized productivity, while alfalfa, corn and dry bean had negative productivity (Table 9).

^{IGH (2011b)}, when evaluating the Calera aquifer with production cost values of the 2005-2006 cycle, found that the economic productivity of the garlic, green pepper and corn crops was 3.35, 3.28 and 0.35 MXN·m^-3, respectively, while ^{Pedroza-Sandoval et al. (2014)}, in the Lagunera region, obtained for alfalfa an economic productivity level of 0.90 MXN·m^-3. On the other hand, ^{Ríos-Flores et al. (2017b)} reported productivity of 3.27 MXN·m^-3 in dry bean in the municipality of Calera, Zacatecas, and of 10.84 MXN·m^-3 in onion in Delicias, Chihuahua (^{Ríos-Flores et al., 2017a}), both 2015 crops. These values differ, for the most part, from the results obtained in this work (Table 8), which was to be expected because there are external factors that can directly influence the economic productivity of water, such as market access, market prices, change in the cost of inputs (fertilizers, insecticides and seed, among others), product demand and supply, and positioning in the international market (such as the vegetable group), among others. For this reason, the values most similar to those determined for 2017 belong to more recent studies, such as the case of dry bean and onion.

Production values were analyzed per hectare because many small producers do not seek to maximize profits, as is the case with business-type producers, but rather consider the total value entered at the end of the cycle. Alfalfa and dry bean are a good example of such a situation, since per hectare alfalfa had a higher yield than dry bean; however, in the latter, more profits were obtained per unit of water used (Table 9). If water were paid for, the real cost would mean that alfalfa would have a lower value in the cost-benefit ratio indicator (which would be -0.6) compared to other crops, and a lower profit per unit of water used.

Without the electricity subsidy, economic productivity was reduced in all crops, even becoming negative for alfalfa, dry bean and corn (Figure 5). The first was the least sustainable, since it was neither economically viable nor environmentally supportable, while corn and dry bean were less economically favored compared to the vegetable group.

Figure 5 Gross and net economic water productivity, with and without electricity subsidies, in 2017. Source: Author-made based on data from the Comisión Federal de Electricidad (^{CFE, 2018}), the Comisión Nacional del Agua (^{CONAGUA, 2018}), the Sistema de Información Agroalimentaria y Pesquera (^{SIAP, 2018}) and the Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación (^{SAGARPA, 2018b}).