Next Article in Journal
Improving Log Loading Efficiency for Improved Sustainable Transport within the Irish Forest and Biomass Sectors
Next Article in Special Issue
Ranking Water Transparency of Dutch Stock-Listed Companies
Previous Article in Journal
The Framework for KM Implementation in Product and Service Oriented SMEs: Evidence from Field Studies in Taiwan
Previous Article in Special Issue
Sustainability, Efficiency and Equitability of Water Consumption and Pollution in Latin America and the Caribbean
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Green and Blue Water Footprint Accounting for Dry Beans (Phaseolus vulgaris) in Primary Region of Mexico

Lucia Irene Flores Lopez
* and
Carlos Bautista-Capetillo
Engineering Sciences Program, Authonomus University of Zacatecas, Av. Ramón López Velarde 801, Centro, Zacatecas 98000, Mexico
Author to whom correspondence should be addressed.
Sustainability 2015, 7(3), 3001-3016;
Submission received: 16 October 2014 / Revised: 6 March 2015 / Accepted: 6 March 2015 / Published: 12 March 2015
(This article belongs to the Special Issue Water Footprints and Sustainable Water Allocation)


Water shortages are a key obstacle to the sustainable supply of food to the world population, since agriculture has the largest consumptive water use. The Water Footprint (WF) has been developed as a useful tool to assess the contribution of goods and activities to water scarcity. This concept is being used around the world to improve agricultural water management. This paper analyzes climate data in order to estimate green and blue WFs for dry beans in the dry beans primary region of Mexico under both irrigation and dryland conditions. The quantification of green WF is very important in this area, since 95% of the crop is obtained in dryland conditions. Standard methodology was used to assess the crop WF. Five different sowing dates were considered: two for irrigation (15 April and 15 May) and three for dryland (1 and 15 July and 1 August). It was found that the optimum sowing date for dryland conditions is 1 August, with a WF of 1839 m3·Mg−1 (1 Mg equal to 1000 kg) in the sutheastern part of the region; nevertheless, results show that the largest green water availability occurs around the first days of July. Under irrigated conditions the best sowing date is 15 May, with a decrease in crop evapotranspiration of 10.1% in relation to 15 April; which means a reduction of 36.1% of blue water use in the northwestern region mainly.

1. Introduction

Increasing world population brings about environmental problems, such as resource scarcity, pollution, erosion, and deforestation. In the particular case of water resources, a struggle has been triggered among farmers, industries and households: these sectors require more and more water in order to satisfy increasing demands. Agriculture stands as the largest consumptive water user worldwide: it needs massive amounts of water to produce agricultural products. When it comes to producing crops under water stress conditions, detailed analyses are required to characterize water requirements (evapotranspiration losses and water use efficiency) and water availability. Such analyses have been reported to lead to improvements in agricultural water management policies [1] by implementing strategies to reduce effects that on environmental resources could provoke people, organizations and products since it is critical for sustainability [2]. In this sense, standard indicators have been developed to evaluate human demand on natural resources. Hoekstra et al. [3], based on the studies of virtual water (VW) performed by Allan [4], laid out the concept of water footprint (WF). This term can be defined as the total volume of freshwater used during the production and consumption of goods and services, measured at the place where the product was actually produced [5,6].
For any well-defined group of consumers or producers, WF can be calculated as the sum of the water used along the full production chain. WF was established as a multi-dimensional indicator, allowing the geographical and temporal water consumption evaluation by source [3,7]. Water consumptive use is measured in terms of the water volume consumed (evaporated) and/or polluted per unit of time; as a consequence, WF has been split into three components (green, blue, and grey water). Green water (the portion of rainfall that is stored as moisture in the soil [8]) and blue water (surface and groundwater) refer to consumption/evapotranspiration during the production of a good; grey water quantifies the volume of freshwater that is required to assimilate the load of pollutants based on local environmental water quality standards [9]. Regarding crop production, an accurate knowledge of crop water requirements (CWR) during all phenological stages is called for in order to reach optimal yields. For a specific crop, CWR mainly depend on the climatic conditions [10] of the zone where the crop is established. CWR are usually computed from crop evapotranspiration (ETc) [11], and account for the net water depletion produced by the crop. Once crop evapotranspiration is calculated, it is possible to estimate the green and blue water components contribution to crop growing. Recognizing rainfall as the only source of water for dryland conditions, it is critical to identify the optimum growing period for the crop: when the expected water deficit is minimized. Following this view, WF expresses the water needed to produce a crop, but also the optimum period of the year to grow it.
To understand the water use impacts of crops grown all through the world, agricultural products, such as cotton, wheat, tomato, coffee and rice, have been assessed following the WF methodology. Aldaya and Hoekstra [7] determined WF for wheat, tomato and mozzarella cheese production, as the main ingredients to make pasta and pizza, two of the most important dishes for the Italian diet. Concerning water use in Italy, the authors concluded that: (a) agriculture uses about 72% of the WF in terms of green and blue water; (b) the average production of tomato and wheat are about 7.4 and 6.8 million Mg·year−1, using 30% of the total water resources; and (c) per capita consumption of these crops is 150 and 62 kg·year−1, respectively, as well as 77% of households consume mozzarella cheese (58% of them consume it at least once a week). The average world production of tomatoes (between 2000 and 2010), about 130 million Mg·year−1 [1], was used to estimate its WF. Chapagain and Orr [12] stated that just in Spain the annual water consumption to cultivate 4 million Mg·year−1 of this vegetable is 297 Mm3, from which 18%, 81%, and 1% correspond to green, blue, and grey water, respectively. Besides, these authors reported that this country exports 957 million Mg·year−1 of tomatoes to other countries of the European Union, equivalent to 78 Mm3·year−1 of consumed water. Bulsink et al. [13] assessed water use for agricultural products, such as rice, coconut, corn, and coffee. These authors reported that Indonesia used 335 Gm3·year−1 in these crops, from which 80% of the water requirement was satisfied by rainfall (green water), and 15% by blue water allocations. Only 5% of the water was used to cover the grey water. In Mexico, Farrel et al. [2] assessed wheat WF; they found that the grey water component represented the largest share (10,311 m3·Mg−1), while blue and green water only represented 1140 and 72 m3·Mg−1, respectively. In the same country, wheat WF was evaluated by other researchers [9,14], with estimates some eleven times smaller than those of Farrel et al. [2]. These studies did not consider the global irrigation efficiency of 36% in the Mexican irrigation districts where wheat is typically grown.
The diet of the low-income Mexican population is based on three staple crops: corn, chili and dry beans. Beans combine high protein content and the relatively easy access when compared to alternative protein sources. Relevant surface and groundwater water resources are allocated to irrigated agriculture in Mexico. However, this water is used to irrigate cash crops. Consequently, dry beans are commonly grown under rainfed conditions, a fact that causes a large temporal and spatial variability on crop yield, as these parameters depend mostly on the precipitation received during the crop season [15]. Since dry beans have been established as a mostly rainfed crop, by obtaining the WF it would be possible to apply policies to improve water resources management. WF varies depending on the sowing date, as climatic conditions change with time and space. If WF of dry beans can be obtained for different sowing dates, a major certainty can be provided in terms of crop yield [2]. The global production of dry beans is about 15 million Mg·year−1. This means about 1% of the global crop production WF [16]. Regarding the production of this crop in Mexico, it amounts to 1.05 million Mg·year−1. The Mexican Government considers dry beans as a traditional and strategic product to develop the countryside, since Mexicans are one of the six most important world consumers [15]. Furthermore, the per capita bean consumption is around 13 kg·year−1, which requires a production of 14,300 Mg·year−1 [17]. Consequently, this legume is the third largest crop for Mexico, just after corn and sorghum, and represents 7.17% of total farm production. Moreover, dry beans represent 15.3% of the national production if compared with basic grains (corn, rice, and wheat). Another important fact is that 36% of the total production is for self-consumption. This means that dry beans is both a basic product for Mexican diet and an economic activity supporting the development of the country.
In Mexico, this crop is mainly produced under dryland conditions. The primary region of Mexico (DBM) produces about 95% of dry beans production; this fact leads farmers to look for best conditions that rainfall could provide. The geographical location of this zone provokes that potential evapotranspiration is higher than precipitation. Therefore, crop yield is almost always lower than potential. It is important for farmers to identify the sowing time assuring the highest WF for the regional climate.
This article sets out to characterize the WF of dry beans produced in the Primary Region of Mexico (DBM, see Section 2), as a tool to assess the crop freshwater use. Four objectives were pursued: (a) to analyze local climate using data from weather stations monitored by the Mexican government; (b) to determine crop evapotranspiration and effective precipitation; (c) to estimate the green and blue water fooprints of dry beans; and (d) to define the optimum sowing date in dryland conditions.

2. Materials and Methods

Between 20 and 23 Mha are anually farmed in Mexico, from which 16.4 to 18.9 Mha are rainfed land, while irrigation is applied on 3.6 to 4.1 Mha [18]. Dry beans are cultivated in 12% of the total of agricultural land. Most of this area is rainfed (1.6 Mha), while only 0.3 Mha is irrigated. The current yields are 0.53 Mg·ha−1 and 1.53 Mg·ha−1 for rainfed and irrigation conditions, respectively [19]. Factors such as crop genetics, soil physics, fertilizer use, and water stress affect crop production [20]. Tyagi et al. [21] noticed that in irrigated agriculture, corn and berseem yields and quality were affected by poor water supply and by unsuited, anarchical irrigation schedules. Therefore, understanding the evolution of ETc through the crop season in order to calculate crop water requirements can help to improve irrigation management. Dry beans are grown all over the country during spring-summer season (1.45 Mha cultivated); the main producers are the states of Zacatecas, Durango, and San Luis Potosi (DBM). In Fall-Winter season (0.27 Mha cultivated), the main producers are Chiapas, Nayarit, Veracruz and Sinaloa.

2.1. Study Area Delimitation

This research was conducted in the dry beans primary region of Mexico (Figure 1), which is located in the Northern region of the country between extreme geographical coordinates 21°30′30.7″N latitude and 100°25′22.5″W longitude, and 21°30′32.6″N latitude and 100°25′23.5″W longitude. The climate is semiarid, with minimum and maximum mean monthly temperatures of 6.5 °C (December and January), and 29.6 °C (May), respectively. Average annual precipitation is approximately 350 mm, of which 80% occurs from June through September.
Dryland crop area in the region is as follows: in the northwestern region, 153,857 ha; in the central region 273,251 ha; and in the southeastern region 59,736 ha. The irrigated crop area is 3131 ha in Durango; 8311 ha in Zacatecas; and 6225 ha in San Luis Potosi [22]. Producers choose a specific sowing date according to regional customs; farmers who irrigate tend to sow as early as possible to take advantage of the market (high prices for early producers). Sowing dates range from 15 April to 15 May. Farmers who do not irrigate wait for the best opportunity that precipitation can provide, choosing the sowing date empirically after the first significant rainfall. The sowing period oscillates between 1 July and 1 August. WF was estimated taking into account the entire crop area (for each one of the considered sowing dates), not considering the natural time variability among specific farms. Average yields for DBM are: Durango, 0.64 Mg·ha−1; Zacatecas has 0.59 Mg·ha−1 and San Luis Potosi 0.42 Mg·ha−1 for dryland conditions. As for irrigation the values are 1.50 Mg·ha−1, 1.72 Mg·ha−1 and 2.11 Mg·ha−1 in the same order [17].
Figure 1. Area of dry beans primary region of Mexico. Source INEGI 1997 [23].
Figure 1. Area of dry beans primary region of Mexico. Source INEGI 1997 [23].
Sustainability 07 03001 g001

2.2. Blue and Green Water Footprints

This study evaluates the volume of green and blue water utilized in dry beans production following the methodology proposed by Hoekstra et al. [3]. The fraction of WF corresponding to green and blue water components of a certain crop can be obtained from Equation (1). The research skips the calculation of grey water, since most dryland Mexican producers of DBM do not use fertilizer to improve yields (mainly for economic reasons). Consequently, local soils do not need leaching to eliminate the pollution originated by these agrochemicals [24].
WF = W F green + W F blue
where WFgreen and WFblue (m3·Mg−1) are the green and blue water footprints during the crop season, respectively. These values are computed as the ratio between crop water use (CWU, m3·ha−1) and average crop yield (Y, Mg·ha−1). The Mexican Goverment has implemented a statistical program for monitoring qualitative and quantitative annual agricultural indicators. This program is called Agricultural, Food and Fisheries Information Service (SIAP) [19]. SIAP data for the period 2006–2009 were used to estimate WF. In irrigated conditions, it is possible to satisfy the entire CWR with both PEF (green water) and irrigation water (blue water). In this sense, CWR is entirely covered, so that, for this case it can be assumed that CWU is equal to ETc and the planted area. In this case both footprints, blue and green, are present, since the fraction of water that is not satisfied by rainfall is taken from a surface or groundwater source. In dryland conditions, CWU is typically lower than ETc, as the only water source is green water, which usually is not enough to satisfy crop water requirements.
In arid and semiarid regions, where rainfall is not enough to satisfy crop evapotranspiration, the missing water volume is fulfilled with blue water component if available. This amount of water is the net irrigation water requirements (NIWR, m3·ha−1), determined as the difference between CWU and effective precipitation (PEF, m3·ha−1). Effective precipitation is the portion of total precipitation that is retained by the soil so that it is available for crop production [1]. Hoekstra et al. (2011) [3] indicate that green water evapotranspiration (ETgreen) can be equated to the minimum of ETc and PEF (Equation (2)), while blue water evapotranspiration (ETblue) is the result of ETc minus PEF in the analyzed period, but it will take a zero value if PEF is larger than crop evapotranspiration (Equation (3)).
E T green = min ( E T c , PEF )
E T blue = max ( 0 , E T c PEF )

2.3. Dry Beans Evapotranspiration (ETc) and Crop Coefficients (Kc)

ETc is calculated as the product of reference evapotranspiration (ET0) and a crop coefficient (Kc) [11]. Kc varies along the crop phenological development, i.e., Kc can be plotted as a function of time during the crop season. Different methodologies have been proposed to determine Kc curves. The Food and Agriculture Organization of the United Nations (FAO) proposed defining four phenological stages (initial, development, mid-season, and late or final stages), estimating three Kc values (at the initial, Kcini; mid-season, Kcmid; and late-season, Kcend), and connecting straight line segments through each of the four growth stages [11]; horizontal lines are drawn through Kc in the initial and mid-season stages, while diagonal lines are drawn from Kcini to Kcmid within the course of the development stage and from Kcmid to Kcend within the course of the late-season stage. The Kc curves and length of stages recommended by FAO [11] for dry beans were used in this work to estimate the Kc values. The Kc values used for initial season, mid-season and late season were Kcini = 0.40, Kcmid = 1.15, and Kcend = 0.35, respectively, with lengths of 40 days for initial stage, 25 days for development stage, 25 days for mid-season stage, and 30 days for late stage.

2.4. Reference Evapotranspiration (ET0)

Several methodologies can be found in the literature to estimate ET0. However, the most widely accepted one is the proposal by Allen et al. [11], which is based on the application of the Penman-Monteith equation (Equation (4)), which involves factors, such as net radiation, soil heat flux, vapor pressure deficit of the air, mean air density at constant pressure, specific heat of the air, slope of the saturation vapor pressure temperature relationship, psychrometric constant, surface, and aerodynamic resistances.
E T 0 = 0.408 D ( R n G ) + g 900 T + 273 u 2 ( e s e a ) D + g ( 1 + 0.34 u 2 )
where ET0 is reference evapotranspiration (mm·day−1); Rn is net radiation (MJ·m−2·day−1); G is soil heat flux (MJ·m−2·day−1); T is average air temperature at a height of 2 m (°C); u2 is air speed at a height of 2 m (m·s−1); es – ea is vapor pressure deficit of the air (kPa); D is the slope of the curve of the saturation vapor pressure temperature relationship (kPa·°C−1); and g is psychrometric constant (kPa·°C−1). The National Research Institute for Forestry, Agriculture and Livestock of Mexico (INIFAP) monitors the variables mentioned previously and processes these data in order to obtain the corresponding ETc.
A network composed of 35 automated weather stations (Figure 2) located within the area of study was used to measure daily rainfall, daily average wind speed at 2 m above ground, daily average relative humidity, daily minimum and maximum air temperature, and daily total solar radiation. The weather stations are monitored by the Experimental Fields of INIFAP: Zacatecas [25], Durango [26] and San Luis Potosí [27]; the weather information corresponds to a period from 2006 to 2011. These data were used to estimate ET0 by the FAO Penman-Monteith method [11].
Figure 2. Weather stations of dry beans primary region of Mexico. Source INIFAP 2011 [25,26,27].
Figure 2. Weather stations of dry beans primary region of Mexico. Source INIFAP 2011 [25,26,27].
Sustainability 07 03001 g002

2.5. Irrigation Net Dry Beans Water Requirements

The net irrigation water requirements for dry beans were determined from Equation (3). Daily values were used for the variables above in this research. ETc and PEF were estimated as follows:
E T c = i = t T s K c i E T 0 _ i
where ET0_i (mm) is the reference evapotranspiration for day i; Kci is the crop coefficient for day i; t and Ts are the first and last day of the considered period.
PEF = 0.75 P s     if  P s > 0.2 E T 0 _ s PEF = 0.00     if  P s 0.2 E T 0 _ s
where Ps (mm) and ET0_s (mm) are precipitation and reference evapotranspiration, respectively, for the considered period [28].
In irrigated systems, at least two efficiency parameters must be considered: conveyance efficiency (Ec) and application efficiency (Ea). These parameters permit to assess the potential and/or actual effectiveness of water use by a given system. Ec is defined as the ratio of the volume of water delivered for irrigation to the volume of water placed in the conveyance system [29,30]. Ea can be estimated using the definition by Howell [31]: the ratio between irrigation needed by the crop and water applied to the field. The product of Ec and Ea results in the global efficiency (Eg). The gross irrigation depth (mm) can be calculated as follows:
IGD = E T blue E g
Several investigations have been performed to estimate the global efficiency in different irrigation zones of Mexico. According to the outcomes obtained in the mentioned works, the global efficiency is between 40% and 60% [32].

2.6. Mapping Parameters to Calculate WF

In order to prepare WF maps of ETc, precipitation and total water depth, Cartesian coordinates were assigned to each weather station and climatologic information was concatenated with ArcGis 10.2 software. The ordinary Kriging interpolation technique was used with a spherical semivariogram model. These maps allow characterizing the spatial variability of reference evapotranspiration (ET0), rainfall and total water depth.

3. Results and Discussion

The average meteorological conditions from 2006 to 2011 between April and November are presented in Figure 3, covering the 35 weather stations used in this research. Average air temperature was 18.4 °C; minimum and maximum air temperature values were 10.4 °C and 26.7 °C. Vapor pressure deficit (VPD) ranged between 0.38 and 1.98 kPa, with an average value of 1.27 kPa. Average wind speed was 6.7 m·s−1. Monthly ET0 ranged between 113.4 and 198.1 mm·month−1 in the study period. Daily average ET0 was 5.03 mm·day−1. The total average rainfall was 358.3 mm. The minimum and maximum average rainfall were 3.5 mm·month−1 in November and 94.5 mm·month−1 in September. A large share of precipitation occurred from June to September (88.6%). Figure 4 and Figure 5 present the time evolution of average ET0 from April to November (covering the crop season). According to information plotted in Figure 4, the lowest ET0 values were found between the months of September and November (75–120 mm·month−1), representing only 40% of the ET0 computed for the period April to May (200–290 mm·month−1), when the highest ET0 values were recorded. Figure 5 shows the average monthly rainfall in the crop Primary Region of Mexico. The maximum precipitation values were observed in July, August, and September (35–175 mm·month−1), while April, May and November accounted for 11.1% of the maximum monthly precipitation value. Regarding the spatial distribution of ET0, this variable was relatively uniform in the analyzed region for the entire studied period. However, in some months (April, May, September, and November) the northwestern region showed an ET0 increase of 29% in relation to the southeastern region (Figure 4). As for the distribution of precipitation, the values obtained in April, May, October, and November are uniformly spread, reaching 70 mm. From July to September, precipitation was relatively lower in the southeastern region, with 35–140 mm vs. 70–175 mm in the northwestern region.
Figure 3. Weather conditions of dry beans primary region of Mexico. Source INIFAP 2011 [25,26,27].
Figure 3. Weather conditions of dry beans primary region of Mexico. Source INIFAP 2011 [25,26,27].
Sustainability 07 03001 g003
Figure 4. Reference evapotranspiration of dry beans primary region of Mexico.
Figure 4. Reference evapotranspiration of dry beans primary region of Mexico.
Sustainability 07 03001 g004
Figure 5. Rainfall of dry beans primary region of Mexico.
Figure 5. Rainfall of dry beans primary region of Mexico.
Sustainability 07 03001 g005

3.1. Dry Beans Water Requirements

The reported methodology permitted identifying the most common sowing dates for rainfed and irrigated conditions. The sowing dates considered in this research are the product of the experience that farmers as well as expert technicians in dry beans have been managed historically in DBM. Under dryland conditions, it is to take advantage of rainfall; as for irrigation conditions it is to obtain a major possible economical profit. For rainfed cultivation, the common sowing period extends through the month of July; as for irrigated cultivation, the period ranges between middle April to middle May. Net crop water requirements (ETblue, Equation (5)) were estimated for five different sowing dates, three for dryland (DSD) and two for irrigated land (ISD): (a) 1 July, 15 July, and 1 August for DSD1, DSD2, and DSD3, respectively; and (b) 15 April, and 15 May for ISD1, and ISD2, respectively. Figure 6 shows the CWR for each sowing date considered in the study. The Primary Region of Mexico devotes 17,667 ha for dry beans under irrigation, and 486,844 ha under rainfed conditions, allocating an average volume of 3159 m3·ha−1 from surface or groundwater sources to satisfy blue water requirements. This volume represents about 7% of the withdrawals for agricultural use [24].
Table 1 and Table 2 present the corresponding values of ETc, CWU and WF for dryland as well as for irrigated conditions. According to these results, the minimum ETc is found when the season starts on ISD2, with 412 mm in the central region. The northwestern region shows the maximum value, with 512 mm, for ISD1. As for dryland conditions, on the DSD3 the minimum is 338 mm in the central region again; on the other hand, the maximum occurs in the northwestern region with 395 mm if the season starts on DSD1.
Figure 6. Dry beans water use for each sowing date considered: (a) rainfed crop and (b) irrigation crop.
Figure 6. Dry beans water use for each sowing date considered: (a) rainfed crop and (b) irrigation crop.
Sustainability 07 03001 g006
Table 1. ETc, CWU and WF in dryland season.
Table 1. ETc, CWU and WF in dryland season.
StateSowing DateETc (mm)Green Water (mm)CWU (m3·ha−1)WF (m3·Mg−1)
Durango1 July395.0263.126314085
San Luis Potosi365.8114.811482734
Durango15 July388.4220.822083429
San Luis Potosi362.298.09802333
Durango1 August383.3176.917692746
San Luis Potosi363.077.27721839
Crop evapotranspiration, ETc; Crop Water Use, CWU; Water Footprint, WF.
Table 2. ETc, CWU and WF in irrigation season.
Table 2. ETc, CWU and WF in irrigation season.
StateSowing DateETc (mm)Green Water (mm)Blue Water (mm)CWU (m3·ha−1)WF (m3·Mg−1)
Durango15 April512.1152.7359.451213426
San Luis Potosi471.759.4412.247172231
Durango15 May460.4230.8229.646043079
San Luis Potosi426.587.3339.342652018
Crop evapotranspiration, ETc; Crop Water Use, CWU; Water Footprint, WF.
As shown in Table 1, CWU is the only available water source for dryland areas. CWU is typically lower than ETc, because the available water is not enough to satisfy the dry beans water requirements. Under dryland conditions, CWR is hardly achieved, in such a way CWU can be considered equal to green water.
The Mexican Government monitors dry beans yield, both dryland and irrigation, through SAGARPA [17]. This work has taken these data in order to obtain the dry beans yield occurred in DBM from 2006 to 2009 (Table 3). It can be observed that for the irrigation period the average yield is 2.114 Mg·ha−1, meanwhile dryland season performs an average of 0.644 Mg·ha−1. In order to simplify data presentation, since it is not possible to identify which part of harvested land area is used for each sowing date.
Table 3. Yields of dry beans primary region of Mexico.
Table 3. Yields of dry beans primary region of Mexico.
YearSeasonDurango (Mg·ha−1)Zacatecas (Mg·ha−1)San Luis Potosi (Mg·ha−1)
Average 0.6440.5890.420
Average 1.4951.7212.114

3.2. WF for Dryland Environments

Dry beans cultivated under rainfed conditions depend only on green water. Such circumstance leads, in the case of the study area, to a water deficit, which affects crop growth. All regions present water deficit independently of the sowing date. Nevertheless, variations are present along the region. In the case of the northwestern region, deficits are 33.4% (DSD1), 43.2% (DSD2) and 53.8% (DSD3), respectively; in the central region, DSD1 has a deficit of 43.87%, DSD2 of 51.2% and DSD3 gets the maximum (60.5%); as for the southeastern region, deficits are 68.6% (DSD1), 72.9% (DSD2) and 78.7% (DSD3), respectively.
In the northwestern region, DSD1 requires an average of 4083 m3·Mg−1 of water during the full season; if the crop season starts on DSD2, WF is 3427 m3·Mg−1; DSD3 has 2745 m3·Mg−1 for WF. The central region shows a similar behavior: (a) if the season begins on DSD1, WF results are 3344 m3·Mg−1; (b) the DSD2 has a WF of 2843 m3·Mg−1; and (c) for the DSD3, it was found a WF of 2268 m3·Mg−1. Conditions in the southeastern region of the region are: for a season that starts on DSD1, WF is 2732 m3·Mg−1; if the season beginning is DSD2, WF is 2332 m3·Mg−1; the DSD3 displays a value of 1839 m3·Mg−1 for WF. Therefore, under these conditions the best sowing date is 1 August (DSD3).
The highest available water is found for DSD1, since the northwestern region has a CWU of 2631 m3 ha. The central region presents a CWU of 1970 m3 ha. Finally, the southeastern region only has a CWU of 1148 m3 ha. According to the obtained results, the best date to establish the dry beans under rainfed conditions at the Primary Region of Mexico is around 1 July. This permits to take advantage from the weather in the entire studied area.

3.3. WF for Irrigation Environments

For ISD1 and ISD2 it is observed that the best conditions according to ETc and PEF, were present when the crop season started on ISD1. During this period the impact on blue water is the smallest. The northwestern region shows that if the season starts on ISD1, the average WF is 3426 m3·Mg−1, with a blue water contribution of 70.2% of the total requirement. Starting on ISD2 results in a blue water requirement of 49.9%, since WF amounts to 3079 m3·Mg−1. The central region presents similar conditions: for a season starting on ISD1, WF is 2631 m3·Mg−1, resulting in 72.5% of blue water. If the season begins on ISD2, WF is 2392 m3·Mg−1, with 56.6% of blue water. As for the southeastern region, starting on ISD1 results in a WF of 2231 m3·Mg−1, with blue water amounting to 87.4% of the total. Starting on ISD2 results in a WF of 2018 m3·Mg−1 (blue water represents 79.5% of the total). Although we found that the best sowing date was 15 May, farmers tend to plant the crop as early as possible in order to maximize opportunities in the market. It must be mentioned that for dry beans, the part of WF corresponding to blue water, increases between 40% and 60% as a result of the conditions in the irrigation systems in Mexico, expressed in terms of global efficiency.
Mekonnen and Hoekstra [16] presented an average global WF for dry beans. The values presented by these authors were 3945 m3·Mg−1, 125 m3·Mg−1, and 983 m3·Mg−1 for green, blue, and grey WF, respectively. Comparing these results with those obtained in this study, it was found some similarity in the green water footprints of Mekonnen and Hoekstra [16] (1.4 times the average value obtained in this study). Nevertheless, blue water shows an opposite behavior, since the study area presents 14 times the global average.

4. Conclusions

In the dry beans primary region of Mexico farmers are used to sow dry beans between April and May for irrigated land. As for dryland, the sowing dates oscillate between July and August. That is why this paper analyzes five different sowing dates: two for irrigated land (15 April and 15 May), and three for dryland (1 July, 15 July and 1 August). The region is divided in three areas: the northwestern region (Durango), the central region (Zacatecas) and the southeastern region (San Luis Potosi).
For irrigated conditions, the best sowing date is 15 May. In the northwestern region a decrease in ETc was observed of 10.1% and a decrease in blue water consumption of 36.1%, in comparison with 15 April. In the central region the decreases in ETc and blue water consumption were 9.1% and 31%, respectively. In the southeastern region the decreases in ETc and blue water were 9.6% and 17.7%, respectively, comparing with 15 April. The obtained outcomes show that WF values were 3079 m3·Mg−1, 2392 m3·Mg−1 and 2017 m3·Mg−1, in the northwestern, central and southeastern regions, respectively.
Regarding dryland cultivation, in all the dates and locations a deficit in fulfilling crop water requirements was found. In the three parts of the region the best sowing date was 1 July. The later the date, the larger the deficit: in the northwestern region it was 33.4%, in the central region it was 43.9% and in the southeastern region it was 68.6%. The dryland analysis permits concluding that the best planting date is 1 August, with values of 2745 m3·Mg−1 in the northwestern region, 2268 m3·Mg−1 in the central region and 1838 m3·Mg−1 in the southeastern region.
These results are subordinated to crop yield estimates. The average yield for irrigated land was 1.8 Mg·ha−1, while for dryland it was barely 0.5 Mg·ha−1. The main result of this research was the identification of the best sowing date for dry beans, particularly under rainfed conditions. Farmers can take advantage of the most suitable green water conditions around 1 July in the whole Primary Region of Mexico.


Thanks for the scholarship provided by Consejo Nacional de Ciencia y Tecnología (CONACYT), to the Doctorado en Ciencias de la Ingeniería UAZ as well as to Arjen Hoekstra for guidance to useful methods and data.

Author Contributions

Both authors have collected and processed data, mapped images and written throughout the manuscript equally working to develope this research.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Food and Agriculture Organization (FAO). Available online: (accessed on 15 January 2012).
  2. Farell, C.; Turpin, S.; Suppen, N. Assesment of the water footprint of wheat in Mexico. In Towards Life Cycle Sustainability Management; Springer: Berlin, Germany, 2011. [Google Scholar]
  3. Hoekstra, A.Y.; Chapagain, A.K.; Aldaya, M.M.; Mekonnen, M.M. The Water Footprint Assessment Manual: Setting the Global Standard; Earthscan: London, UK, 2011. [Google Scholar]
  4. Allan, J.A. Virtual water: A strategic resource, global solutions to regional deficits. Groundwater 1998, 36, 545–546. [Google Scholar] [CrossRef]
  5. Chapagain, A.K.; Hoekstra, A.Y. The global component of freshwater demand and supply: An assessment of virtual water flows between nations as a result of trade in agricultural and industrial products. Water Int. 2008, 33, 19–32. [Google Scholar] [CrossRef]
  6. Yu, Y.; Hubacek, K.; Feng, K.; Guan, D. Assessing regional and global water footprints for the UK. Ecol. Econ. 2010, 69, 1140–1147. [Google Scholar] [CrossRef]
  7. Aldaya, M.M.; Hoekstra, A.Y. The water needed for Italians to eat pasta and pizza. Agric. Syst. 2010, 103, 351–360. [Google Scholar] [CrossRef]
  8. Falkenmark, M.; Rockstrom, J. The new blue and green water paradigm: Breaking new ground for water resources planning and management. J. Water Resour. Plan. Manag. 2006, 132, 129–132. [Google Scholar] [CrossRef]
  9. Mekonnen, M.M.; Hoekstra, A.Y. A global and high-resolution assessment of the green, blue and grey water footprint of wheat. Hydrol. Earth Syst. Sci. 2010, 14, 1259–1276. [Google Scholar] [CrossRef] [Green Version]
  10. Arabi, A.; Alizadeh, A.; Rajaee, Y.V.; Jam, K.; Niknia, N. Agricultural water footrint and virtual water budget in Iran related to the consumption of crop products by conserving irrigation efficiency. J. Water Resour. Prot. 2012, 4, 318–324. [Google Scholar] [CrossRef]
  11. Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; Paper 56; Food and Agriculture Oreganization of the United Nations: Rome, Italy, 1998. [Google Scholar]
  12. Chapagain, A.K.; Orr, S. An improved water footprint methodology linking global consumption to local water resources: A case of Spanish tomatoes. J. Environ. Manag. 2009, 90, 1219–1228. [Google Scholar] [CrossRef]
  13. Bulsink, F.; Hoekstra, A.Y.; Booij, M.J. The water footprint of Indonesian provinces related to the consumption of crop products. Hydrol. Earth Syst. Sci. 2010, 14, 119–128. [Google Scholar] [CrossRef]
  14. Hoekstra, A.Y.; Chapagain, A.K. Water footprints of nations: Water use by people as a function of their consumption pattern. Water Resour. Manag. 2005, 21, 35–48. [Google Scholar] [CrossRef]
  15. Reyes Rivas, E.; Padilla Bernal, L.E.; Pérez Veyna, O.; López Jáquez, P. Historia, naturaleza y cualidades alimentarias del fríjol. Rev. Investig. Cient. 2008, 4, 1–21. [Google Scholar]
  16. Mekonnen, M.M.; Hoekstra, A.Y. The green, blue and grey water footprint of crops and derived crop products. Hydrol. Earth Syst. Sci. 2011, 15, 1577–1600. [Google Scholar] [CrossRef]
  17. Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación (SAGARPA). Available online: (accessed on 3 September 2011). (In Spanish)
  18. Comisión Nacional del Agua (CONAGUA). Available online: (accessed on 16 May 2011).
  19. Servicio de Información Agroalimentaria y Pesquera (SIAP). Available online: (accessed on 10 September 2010).
  20. Luna, F.M. (Ed.) El Cultivo de Maíz en Zacatecas; Universidad Autónoma de Zacatecas/Coordinación de Investigación y Posgrados: Zacatecas, México, 2008. (In Spanish)
  21. Tyagi, N.K.; Sharma, D.K.; Luthra, S.K. Determination of evapotranspiration for maize and barseem clover. Irrig. Sci. 2003, 21, 173–181. [Google Scholar]
  22. Instituto Nacional de Estadística, Geografía e Informática (INEGI). Anuario Estadístico de los Estados Unidos Mexicanos 2010; INEGI: Aguascalientes, Mexico, 2010. (In Spanish) [Google Scholar]
  23. Instituto Nacional de Estadística, Geografía e Informática (INEGI). El Frijol en el Estado de Zacatecas 1997; INEGI: Zacatecas, México, 1997. (In Spanish) [Google Scholar]
  24. Mojarro Dávila, F.; de León Mojarro, B.; Júnez Ferreira, H.E.; Bautista Capetillo, C.F. Agua Subterránea en Zacatecas; Universidad Autónoma de Zacatecas: Zacatecas, México, 2013; ISBN 978-607-7678-90-8. (In Spanish) [Google Scholar]
  25. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias de México (INIFAP). Red de monitoreo agroclimático del Estado de Zacatecas. Available online: (accessed on 8 May 2011).
  26. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias de México (INIFAP). Red de monitoreo agroclimático del Estado de Zacatecas. Available online: (accessed on 10 June 2011).
  27. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias de México (INIFAP). Red de monitoreo agroclimático del Estado de San Luis Potosi. Available online: (accessed on 14 July 2011).
  28. Bautista-Capetillo, C.; Zavala, M.; MArtínez-Cob, A. Using Thermal Units for Crop Coefficient Estimation and Irrigation Scheduling Improves Yield and Water Productivity of Corn (Zea mays L.). J. Irrig. Drain. Eng. 2013, 139, 214–220. [Google Scholar] [CrossRef]
  29. Korkmaz, N.; Avci, M.; Unal, H.; Asik, S.; Gunduz, M. Evaluation of the Water Delivery Performance of the Menemen Left Bank Irrigation System Using Variables Measured On-Site. Irrig. Drain. Eng. 2009, 135, 633–642. [Google Scholar] [CrossRef]
  30. Rendón, P.L.; Fuentes, R.C.; Magaña, S.G. Diseño del Riego por Gravedad. In Manual para Diseño de Zonas de Riego Pequeñas; Comisión Nacional del Agua and Instituto Mexicano de Tecnología del Agua: Morelos, México, 2007; pp. 75–86, ISBN 978-968-9513-04-9. (In Spanish) [Google Scholar]
  31. Howell, T.A. Irrigation Efficiency. In Encyclopedia of Soil Science; United States Department of Agriculture (USDA): Bushland, TX, USA, 2003. [Google Scholar]
  32. De Leon Mojarro, B.; Robles Rubio, B. Manual para diseño de zonas de riego pequeñas. In Manual para Diseño de Zonas de Riego Pequeñas; Comisión Nacional del Agua and Instituto Mexicano de Tecnología del Agua: Zacatecas, México, 2011; Volume II. (In Spanish) [Google Scholar]

Share and Cite

MDPI and ACS Style

Lopez, L.I.F.; Bautista-Capetillo, C. Green and Blue Water Footprint Accounting for Dry Beans (Phaseolus vulgaris) in Primary Region of Mexico. Sustainability 2015, 7, 3001-3016.

AMA Style

Lopez LIF, Bautista-Capetillo C. Green and Blue Water Footprint Accounting for Dry Beans (Phaseolus vulgaris) in Primary Region of Mexico. Sustainability. 2015; 7(3):3001-3016.

Chicago/Turabian Style

Lopez, Lucia Irene Flores, and Carlos Bautista-Capetillo. 2015. "Green and Blue Water Footprint Accounting for Dry Beans (Phaseolus vulgaris) in Primary Region of Mexico" Sustainability 7, no. 3: 3001-3016.

Article Metrics

Back to TopTop