Nitrate, phosphate and boron content in wastewater for crop irrigation in Mezquital Valley, Hidalgo
Abstract
Introduction

Mexico City generates an approximate volume of wastewater of 57 m3 s-1, the wastewater is conduct by the drainage network: main channel-west interceptor-central emitter, and conducted to Hidalgo State, during it course, an important volume is poured into irrigation channels and is used for crop irrigation in the Mezquital Valley.

Method

In this study, nitrate (NO3-), phosphate (PO4-3) boron (B3+) and chloride (Cl-) content in 188 wastewater samples was determined. The objective was to assessment the risk of toxicity by specific ions (B3+ and Cl-) and the nutrients content (N, P, K, Ca y Mg) in wastewater used for crop irrigation.

Results

The nitrate (NO3-) concentration was very heterogeneous (CV=59.83 %) and this was attributed to the lixiviation of nitrogen fertilizers. The maximum phosphate (PO4-3) value was 65.7 mg L-1, and its concentration was attributed to the discharge of household wastewater. The boron concentration (B3+) was less than 1.88 mg L-1. The risk of toxicity due to the use of wastewater in irrigation may cause a decrease the yield of sensitive crops, such as beans.

Conclusion

Untreated wastewater used in irrigation in Mezquital Valley, may cause toxicity problems in some crops; the nitrate and phosphate concentrations in wastewater of the Mexico City-Mezquital Valley drainage network were high, and these were attributed to the discharges of domestic and industrial wastewaters and to agricultural drainage, high concentrations of nitrate and phosphate represent a risk for aquatic organisms due to pollution and the possible eutrophication of water bodies. The risk of toxicity by B3+ and Cl- can have a negative effect on the germination and yield of bean crops.

Resumen
Introducción

La Ciudad de México genera un volumen de agua de origen residual de 57 m3 s-1, esta agua se conduce por la red de drenaje: gran canal-interceptor poniente-emisor central, hacia el Estado de Hidalgo, y durante su curso, un volumen importante de esta agua se vierte en canales de riego y se utiliza en la irrigación de cultivos en Valle del Mezquital.

Método

En este estudio se determinó la concentración de nitrato (NO3-), fosfato (PO43-), boro (B3+), cloruro (Cl-), calcio (Ca2+), magnesio (Mg2+) y potasio (K+) en 188 muestras de agua. El objetivo fue evaluar el riesgo de toxicidad por iones específicos (B3+ y Cl-) y el contenido de nutrientes (N, P, K, Ca y Mg) del agua residual utilizada en el riego de cultivos agrícolas.

Resultados

la concentración de nitrato (NO3-) fue muy heterogénea (CV=59.83 %) y se atribuyó a la lixiviación de fertilizantes nitrogenados. El fosfato (PO43-) tuvo un valor máximo de 65.7 mg L-1, y su concentración se atribuyó a la descarga de agua residual de origen doméstico. La concentración de boro (B3+) fue menor de 1.88 mg L-1. El riesgo de toxicidad debido al uso de esta agua en la irrigación puede ocasionar la disminución en el rendimiento de cultivos sensibles como el frijol.

Conclusión

el agua de origen residual sin tratamiento, utilizada en la irrigación en Valle del Mezquital, puede ocasionar problemas de toxicidad en algunos cultivos; la concentración de nitrato y fosfato en el agua residual de la red de drenaje Ciudad de México-Valle del Mezquital fue elevada, lo cual, representa riesgo para los organismos acuáticos por la contaminación y posible eutrofización de los cuerpos de agua. El riesgo de toxicidad por B3+ y Cl- puede ocasionar efectos negativos en la germinación y rendimiento del cultivo de frijol.

Palabras clave:
    • calidad del agua de riego;
    • irrigación;
    • reúso del agua residual;
    • toxicidad por boro.
Keywords:
    • agricultural water quality;
    • boron toxicity;
    • irrigation;
    • wastewater reuse.

Introduction

Mexico City has an estimated population of 8 985 339 inhabitants (INEGI, 2017), which makes it a challenge to satisfy the population’s growing needs regarding the allocation of drinking water, drainage and sanitation. Most rivers in Mexico City have been enclosed in pipes, and their surface waters have been classified as polluted. The rivers under these conditions are: Churubusco, de las Avenidas, de los Remedios, San Juan, de la Compañía, San Buenaventura and Tlamaco dam; therefore these rivers can be considered a part of the drainage system (Perló-Cohen & Zamora-Saenz, 2017). It is estimated that 70 % of the drinking water source in Mexico City is groundwater, and over 26 % is imported from the Lerma and Cutzamala systems; 77 % of the population consumes less than 150 L of water per day, and 96 % of the population has drainage coverage (Guerrero et al., 2009; Ortega-Font, 2011). Considering these reports, it is estimated that population in Mexico City generates an approximate volume of wastewater of 57 m3 s-1, (CONAGUA, 2012); this wastewater goes through the drainage network: grand channel-west interceptor- central emitter (Aguilar-Garduño et al., 2007), and conducted to Hidalgo state. During its course, an important volume is poured into irrigation channels and is used for crop irrigation in the Mezquital Valley (CONAGUA, 2012). In Hidalgo State an agricultural area of approximately 456 855.69 hectares is sown, 80 % of which is rainfed and 20 % undergoes irrigation systems; the greatest surface is used for maize, bean, and oats forage crops (SIAP, 2017).

Many authors agree that wastewater is an important source of organic matter (Fuentes-Rivas et al., 2017) and nutrients such as nitrogen (N) and phosphorus (P) [Belaid et al., 2012], and applying this water to agricultural irrigation will provide a considerable amount of nutrients for crop nutrition (Romero-Álvarez, 1997; Rascón-Alvarado et al., 2008; Zamora et al., 2008). However, the nitrate and phosphate concentration found in wastewater may be due to the excessive application of fertilizers in agriculture (Hem, 1985; Chávez-Alcántar et al., 2011; Guangwei Huang, 2013), and its excess concentration can be lixiviated and cause pollution of groundwater, which may cause damages to the health of people who consume water from contaminated wells, as well as the progressive eutrophication of water bodies (Figueruelo-Alejano & Marino-Dávila, 2004); the importance of high nitrate concentrations in drinking water (10 mg L-1 N = 44 mg L-1 NO3-) lies in health problems for children, who are prone to catching hemoglobinemia (Hem, 1985; OMS, 1998).

Other earlier studies have proven that wastewater contains elements that are potentially toxic for aquatic organisms (Robledo-Zacarías et al., 2017) and heavy metals, added to the soil by irrigation, accumulate on the arable layer of agricultural soils (Siebe, 1994; Prieto-García et al., 2007; Flores-Magdaleno et al., 2011) and can be absorbed and accumulated in plants (Vázquez-Alarcón et al., 2001); furthermore, contact with wastewater affects the health of the overall population (Cifuentes et al., 1994; Cifuentes et al., 2000). On the other hand, wastewater poured into receiving bodies is a high risk for human health and the environment, since medications and narcotics have been found in wastewaters, and can potentially cause toxic effects (even in low concentrations) in aquatic organisms and soil microorganisms (Robledo-Zacarías et al., 2017).

On the other hand, wastewater used in the agricultural area known as the Mezquital Valley had a predominant composition of bicarbonate and sodium (Cuellar-Carrasco et al., 2015; López-García et al., 2016), therefore the use of wastewater in agriculture can have negative effects on the soil and crops regarding salinity and sodicity (Fuentes-Rivas et al., 2017). Toxicity problems in crops arise when some ions are absorbed and accumulated in their tissues in concentrations high enough to cause damage and reduce yields (Ayers & Westcot, 1985). This toxicity depends on the tolerance of a particular crop at extreme levels of ionic concentration (Sánchez-Bernal et al., 2013; Can-Chulim et al., 2017). The most important ions related to toxicity are: B3+, Cl- and Na+; once these ions are absorbed, they are transported to different parts of the plant and during transpiration they accumulate on the leaves.

Nitrogen is a nutrient for plants, however, nitrate concentration between 5 and 30 mg L-1 in irrigation water may affect sensitive crops (Ayers & Westcot, 1985), and regarding boron, toxicity presents itself in some crops when there is a concentration between 1 and 2 mg L-1 (Maas, 1990). The most frequent toxicity is caused by the content of Cl- in irrigation water, since this ion is easily absorbed by the root and carried to different parts of the plant (Ayers & Westcot, 1985).

Considering the above, the objective of this investigation was to determine the concentration of nitrate, phosphate and boron in wastewaters and to estimate its content of nutrients, as well as the estimation of the risk of toxicity by specific ions (B3+ and Cl-) that can affect normal crop development in a negative way. The focus of this investigation is quantitative and has a descriptive scope; given that in the area under study the largest area planted is dedicated to maize, bean and oat, these ions may affect each crop in a different way.

Methods

Sampling, water analysis and statistical analysis

To carry out this investigation, during September 2015 and April 2016, 188 wastewater, rivers and dam water samples were collected and analyzed from 135 sampling stations distributed in the Mexico City-Mezquital Valley drainage system (Fig. 1). Samples were collected according to NMX-AA-003-SCFI-1980, and considering the accessibility of the sites (SCFI, 1980).

Location of the study area. Source: Author’s own elaboration.

All the sampling stations (Table 1) were registered with a Geographic Positioning System (GPS Garmin® Etrex Venture HC). In each sampling station, 2 liters of water were collected and distributed into 1 L polypropylene containers previously washed with an HCl solution at 10 % concentration, then rinsed with distilled water. In all the sampling stations the channels flow in the open, the water was taken from the central part of the drainage channels at an approximate depth of 30 cm using a plastic 10 L bucket. Later, the containers were washed three times with the same collected water (Sánchez-Bernal et al., 2014).

Sampling stations in México City-Mezquital Valley hydrographic network.
ID Coordinates Altitude Sampling station Reference State
N W m
1 19.8313333 -99.1186944 2293 Irrigation channel Zumpango-Tequisquiac Mexico State
2 19.7851667 -99.09475 2278 Channel la laminadora Nextlalpan-Zumpango Mexico State
3 19.6843611 -99.0446389 2246 Channel Tonanitla I Sta. María Tonanitla Mexico State
4 19.7343056 -99.0678611 2245 Channel Nextlalpan Nextlalpan Mexico State
5 19.7271944 -99.0835556 2244 Channel Sn. Francisco Nextlalpan Mexico State
6 19.6715333 -99.0404833 2240 Channel Tonanitla II Sta. María Tonanitla Mexico State
7 19.6256167 -99.04575 2239 Pemex bridge channel Los Héroes de Tecámac Mexico State
8 19.7855556 -99.1666389 2239 Grand channel Zumpango Mexico State
9 19.7855556 -99.1666389 2239 Irrigation channel Zumpango Mexico State
10 19.8029167 -99.1136111 2238 Zumpango lagoon Zumpango Mexico State
11 19.7009444 -99.0829167 2235 East emitter tunnel vent 11 Tultepec Mexico State
12 19.808 -99.1106944 2233 Ávila Camacho drain Zumpango Mexico State
13 19.9021111 -99.1226389 2228 Tunnel Tequixquiac Tequixquiac Mexico State
14 19.4670883 -99.0100833 2225 Peñon-Texcoco road channel Texcoco Mexico State
15 19.9135 -99.1437778 2213 Tequixquiac stream Tequixquiac Mexico State
16 19.9039722 -99.1460556 2204 Tunnel Tequixquiac Tequixquiac Mexico State
17 19.9649167 -99.1756944 2180 Tula River Apaxco de Ocampo Mexico State
18 19.9649167 -99.1756944 2180 Apaxco drainage Apaxco de Ocampo Mexico State
19 20.0285556 -99.2033056 2145 Irrigation channel Texas Atotonilco de Tula Hidalgo State
20 20.2482222 -99.4245 2118 Chapatongo River José María Pino Suarez Hidalgo State
21 20.1166667 -99.2042778 2111 Irrigation channel Teltipan Teltipan de Juárez Hidalgo State
22 20.1220833 -99.2525278 2105 Channel Tlahuelilpan Tlahuelilpan Hidalgo State
23 20.0582778 -99.26875 2103 Channel Pemex II Atitalaquia-Cardonal-Tula Hidalgo State
24 20.0565833 -99.2196944 2098 Irrigation channel Atitalaquia Atitalaquia Hidalgo State
25 20.0536944 -99.3130278 2094 Channel Pemex IV El llano-Tula de Allende Hidalgo State
26 20.02075 -99.2135556 2093 Tula River Atotonilco de Tula Hidalgo State
27 20.2139444 -99.1340833 2091 Irrigation channel Morelos III Mixquiahuala Hidalgo State
28 20.1449167 -99.2347222 2091 Irrigation channel Tlahuelilpan Tlahuelilpan Hidalgo State
29 20.0591389 -99.2270833 2089 Irrigation channel la Quina Atitalaquia Hidalgo State
30 20.0591389 -99.2270833 2089 Waterfall la Quina Atitalaquia Hidalgo State
31 20.0593889 -99.2392222 2087 Channel Pemex I Atitalaquia-Cardonal Hidalgo State
32 20.0742778 -99.3162778 2085 Channel Endho El llano-Tula de Allende Hidalgo State
33 20.2214167 -99.1373333 2079 Irrigation channel Morelos II Mixquiahuala Hidalgo State
34 20.05525 -99.3046389 2077 Channel Pemex III Atitalaquia-El llano Hidalgo State
35 20.0984167 -99.3417778 2076 Channel Villagran I Tula-Sta. Ana Ahuehuepan Hidalgo State
36 20.0745833 -99.3337222 2064 Channel Canadiense Tula -Sta. Ana Ahuehuepan Hidalgo State
37 20.1279722 -99.2423611 2050 Channel Tlahuelilpan Tlahuelilpan Hidalgo State
38 20.1557222 -99.2303333 2049 Channel Requena Tlahuelilpan Hidalgo State
39 20.1588056 -99.2304444 2047 Irrigation channel el Tinaco Tlahuelilpan Hidalgo State
40 20.1286667 -99.3500556 2047 Channel Villagrán II Sta. Ana Ahuehuepan Hidalgo State
41 20.0662222 -99.3295556 2040 Green bridge channel Tula de Allende Hidalgo State
42 20.1971389 -99.2241944 2024 Irrigation channel Tezontepec II Tezontepec-Mixquiahuala Hidalgo State
43 20.1451667 -99.3579722 2022 Endhó dam Endhó Hidalgo State
44 20.1451667 -99.3579722 2022 Endhó dam (drain) Endhó Hidalgo State
45 20.1638611 -99.3673611 2017 Irrigation channel Endhó Hidalgo State
46 20.2298056 -99.1363056 2016 Irrigation channel Morelos I Mixquiahuala Hidalgo State
47 20.1971389 -99.2241944 2014 Irrigation channel Tezontepec I Tezontepec-Mixquiahuala Hidalgo State
48 20.0531111 -99.3357222 2002 Tula River Tula de Allende Hidalgo State
49 20.2453333 -99.17875 2000 Irrigation channel el Progreso Progreso Hidalgo State
50 20.3163611 -99.1985278 1994 Irrigation channel la Mora Xochitlán Hidalgo State
51 20.2908333 -99.1878611 1994 Irrigation channel Xoxitlan Xochitlán Hidalgo State
52 20.3436389 -99.3477222 1989 Dolores dam Cerro Azul-Oxtotipan Hidalgo State
53 20.1908611 -99.2547778 1984 Irrigation channel Tezontepec IV Tezontepec Hidalgo State
54 20.3606667 -99.3273056 1984 Channel Rojo Gómez Cerro Azul-Xamajé Hidalgo State
55 20.4243889 -99.3511944 1978 Irrigation channel Vicente Aguirre Alfajayucan Hidalgo State
56 20.2664167 -98.9554444 1977 Wastewater channel Actopan Hidalgo State
57 20.2641944 -98.9601667 1975 Irrigation channel Actopan Actopan Hidalgo State
58 20.2681111 -99.0028333 1973 Irrigation channel Sn. Salvador Poxindejé Hidalgo State
59 20.1910278 -99.2791667 1973 Water spring Tezontepec Tezontepec Hidalgo State
60 20.1881389 -99.2420278 1972 Irrigation channel Tezontepec III Tezontepec Hidalgo State
61 20.2595 -98.9707778 1970 Drain Boxthá Actopan Hidalgo State
62 20.3584722 -99.3228056 1970 Rojo Gómez dam Cerro Azul Hidalgo State
63 20.1943889 -99.2796111 1964 Tula River Tezontepec Hidalgo State
64 20.2808056 -99.0116111 1949 Water well Sn. Salvador Sn. Salvador Hidalgo State
65 20.3753056 -99.33225 1946 Irrigation channel Xamajé Xamajé Hidalgo State
66 20.3139722 -99.0073333 1936 Irrigation channel caxuxi Bominthza Hidalgo State
67 20.3431667 -99.2069167 1928 Irrigation channel Tlacotlapilco Tlacotlapilco Hidalgo State
68 20.3984167 -99.1915278 1927 Irrigation channel Ecoalberto Tlacotlapilco Hidalgo State
69 20.3448056 -99.0295833 1926 Irrigation channel boxani Lagunilla Hidalgo State
70 20.3526667 -99.03675 1924 Irrigation channel Lagunillas II Lagunilla Hidalgo State
71 20.2860278 -99.0091944 1921 Agricultural drainage Sn. Salvador-El Bondhó Hidalgo State
72 20.3869167 -99.0679444 1920 Irrigation channel Yolotepec II Yolotepec Hidalgo State
73 20.36125 -99.0375 1920 Irrigation channel Lagunillas II Lagunilla-Patria Nueva Hidalgo State
74 20.3921944 -99.0794167 1917 Irrigation channel Yolotepec I Yolotepec Hidalgo State
75 20.3767778 -99.0536667 1917 Irrigation channel Yolotepec III Yolotepec-Patria Nueva Hidalgo State
76 20.3928056 -99.0868333 1913 Irrigation channel Yolotepec-Julián Villagrán Hidalgo State
77 20.4871111 -99.0813611 1887 Irrigation channel debodhé-florida Pozuelos Hidalgo State
78 20.2513017 -99.19595 1887 Tula River Progreso Hidalgo State
79 20.2513017 -99.19595 1887 Infiltration water Progreso Hidalgo State
80 20.4347222 -99.3625556 1872 Vicente Aguirre dam Antonio Corrales Hidalgo State
81 20.4838889 -99.1206389 1862 Debodhé dam Debodhé Hidalgo State
82 20.4590556 -99.3411667 1850 Irrigation channel Xigüi Vía Huichapan-Ixmiquilpan Hidalgo State
83 20.4559167 -99.3693056 1846 Irrigation channel Sn. Francisco Alfajayucan-Yonthé Grande Hidalgo State
84 20.4142778 -99.3487778 1845 Alfajayucan River Alfajayucan Hidalgo State
85 20.326 -99.2226389 1837 Tula River Chilcuautla Hidalgo State
86 20.326 -99.2226389 1837 Infiltration water for nopal irrigation Chilcuautla Hidalgo State
87 20.326 -99.2226389 1837 Infiltration water for nopal irrigation Chilcuautla Hidalgo State
88 20.4733611 -99.3290833 1837 Irrigation channel el Portezuelo Portezuelo Hidalgo State
89 20.5050278 -99.3119167 1803 Irrigation channel Portezuelo 2 Portezuelo Hidalgo State
90 20.4785 -99.3635278 1803 Irrigation channel el Bermejo Yonthé Grande Hidalgo State
91 20.4092222 -99.2058333 1800 Irrigation channel El Alberto Tlacotlapilco-Ixmiquilpan Hidalgo State
92 20.43525 -99.1568333 1793 Main channel alto Ixmiquilpan Taxadhó Hidalgo State
93 20.4851667 -99.3663056 1791 Reservoir el Bermejo Yonthé Grande Hidalgo State
94 20.5001389 -99.1571389 1790 Irrigation channel Arenalito El Nith-Debodhé Hidalgo State
95 20.4748333 -99.3655 1790 Irrigation channel Yonthe Grande Yonthé Grande Hidalgo State
96 20.4950278 -99.1635556 1789 Irrigation channel la estación El Nith-Debodhé Hidalgo State
97 20.4961667 -99.1568889 1789 Irrigation channel bangandhó El Nith-Debodhé Hidalgo State
98 20.4234167 -99.1696389 1789 Irrigation channel Maguey Blanco Parque acuático Maguey Blanco Hidalgo State
99 20.5055556 -99.1357222 1788 Irrigation channel EST-57 Debodhé Hidalgo State
100 20.4905833 -99.1123333 1787 Debodhé dam (drain) Debodhé Hidalgo State
101 20.4829444 -99.2718611 1784 Irrigation channel dexthó Ixmiquilpan-Portezuelo Hidalgo State
102 20.3741944 -99.2236389 1784 Tula River Tlacotlapilco Hidalgo State
103 20.4924722 -99.1148056 1775 Irrigation channel Debodhé Debodhé Hidalgo State
104 20.5072778 -99.1392222 1772 Irrigation channel capula Debodhé Hidalgo State
105 20.4268889 -99.2270556 1769 Tula River in Ecoalberto Tlacotlapilco-Ixmiquilpan Hidalgo State
106 20.4268889 -99.2270556 1769 Irrigation channel Tlacotlapilco-Ixmiquilpan Hidalgo State
107 20.5047222 -99.1435278 1766 Agricultural drainage bangandhó El Nith-Debodhé Hidalgo State
108 20.4902222 -99.1944167 1761 Irrigation channel El Nith-Debodhé Hidalgo State
109 20.4426389 -99.1741111 1759 Wastewater channel El Tephé Hidalgo State
110 20.4819167 -99.38775 1758 Infiltration water Sn. Fco. Sacachichilco Hidalgo State
111 20.4756944 -99.3901389 1758 Sn. Francisco River Sn. Fco. Sacachichilco Hidalgo State
112 20.4432222 -99.1718333 1755 Wastewater channel el Tephé El Tephé Hidalgo State
113 20.4933056 -99.1760833 1754 Agricultural drainage El Nith-Debodhé Hidalgo State
114 20.5170278 -99.15475 1752 Chicabasco River Capula-El Rosario Hidalgo State
115 20.5170278 -99.15475 1752 Irrigation channel Chicabasco Capula-El Rosario Hidalgo State
116 20.48825 -99.2731667 1752 Drenaje agrícola Dexthó Ixmiquilpan-Portezuelo Hidalgo State
117 20.4493611 -99.1791111 1750 Irrigation channel Siqueiros El Tepe Hidalgo State
118 20.4841667 -99.3843333 1747 Channel Xigatza Sn. Fco. Sacachichilco Hidalgo State
119 20.4923333 -99.1822778 1746 Irrigation channel La joya El Nith-Debodhé Hidalgo State
120 20.4969722 -99.2736667 1746 Irrigation channel Dexthó 2 Ixmiquilpan-Portezuelo Hidalgo State
121 20.5029167 -99.38725 1746 Madho Corrales dam Sn. Fco. Sacachichilco Hidalgo State
122 20.4795278 -99.2492222 1745 Irrigation channel el mexicano Ixmiquilpan-Portezuelo Hidalgo State
123 20.4810278 -99.2553333 1742 Irrigation channel el mexicano 2 Ixmiquilpan-Portezuelo Hidalgo State
124 20.5248889 -99.3238056 1720 Irrigation channel Tasquillo Tasquillo Hidalgo State
125 20.5270833 -99.321 1709 Irrigation channel Tasquillo Tasquillo Hidalgo State
126 20.4863056 -99.2108056 1706 Irrigation channel Ixmiquilpan Hidalgo State
127 20.0605 -99.2221111 1694 Salt River Atitalaquia Atitalaquia Hidalgo State
128 20.4806667 -99.2210833 1693 Tula River Ixmiquilpan Hidalgo State
129 20.4821389 -99.2151944 1693 Wastewater channel Ixmiquilpan Hidalgo State
130 20.5499722 -99.2916389 1645 Tula River Juchitlán Hidalgo State
131 20.5499722 -99.2916389 1645 Water spring Juchitlán Hidalgo State
132 20.5499722 -99.2916389 1645 Baths Tzindejéh Juchitlán Hidalgo State
133 20.66125 -99.48775 1596 Zimapán Dam Saucillo Hidalgo State
134 20.576 -99.3463611 1590 Tula River Tasquillo Hidalgo State
135 20.8645 -99.4455 935 Moctezuma River La Mora Queretaro State

The concentration of NO3-, PO43- and B3+ was determined by spectrophotometry (JENWAY® 7305 Spectrophotometer), with different dependent wavelengths based on the Beer-Lambert law, which indicates that by knowing the absorbance at a given wavelength it can be used to estimate the concentration (Rodger, 2013):

A = ε C l

Where: A is light absorption, ε is the coefficient of extinction or dependent wavelength (nm), C is the concentration (mol L-1) and l is the length of the sample through which light passes (cm). NO3- was determined using the salicylic acid nitration method (Robarge et al., 1983); PO43-, with the ascorbic acid method (Eaton et al., 1998), and to find the concentration of B3+, the H-Azomethine method was used (Rodier, 1978). In all three cases, solutions of known concentrations were used to establish the calibration lines. The regression equations used were the following:

N O 3 - = 119.81 × A + 1.3416 ;   R 2 = 0.986

P O 4 3 - = 8.9707 × A ;   R 2 = 0.994

B 3 + = 6.6675 × A + 0.0609 ;   R 2 = 0.995

The ions Ca2+, Mg2+ were determined by volumetric titration with disodic EDTA (0.01 N), and the volumetric titration of Cl- was carried out with silver nitrate (0.05 N). The concentration of K+ was determined with a flame spectrometer (Instrumentation Laboratory® AutoCal Flame Photometer 643), the detection limit was 5 meq L-1 of K+ [Eaton et al., 1998; Richards et al., 1982]. The procedure to verify the correct analysis of water samples was the anion-cation balance criterion established in standard methods for the examination of water and wastewater (Eaton et al., 1998).

Once all the results were obtained from the chemical analysis of water, a statistical analysis was carried out on each one of the variable, which consisted in determining: normality test using the Kolmogorov-Smirnov method, skewness, kurtosis, minimum, maximum, mean, median, standard deviation, range, coefficient of variation (CV), quartiles, and extreme values (Montgomery & Runger, 2015). The software used was SAS® version 9.0 and the graphs were created in SigmaPlot® version 10.0.

To establish the risk of toxicity by specific ions, the concentrations of B3+, and Cl- were considered according to the criteria established in different investigations (Ayers & Westcot, 1985; Maas, 1990; Richards et al., 1982). The estimation of the nutrient content was carried out based on the results obtained from the concentrations of NO3-, PO43, B3+, Ca2+, Mg2+ and K+ using the dimensional analysis technique and considering 1 m irrigation sheet, which is normally applied on crops in the Mezquital Valley.

1   m m = 1   L m 2   y   1000   m m = 10,000,000   L 10,000   m 2 1   m i r r i g a t i o n   s h e e t = 10,000,000   L h a

m g L ÷ 1,000,000 = k g L ; k g L 10,000,000   L h a = k g h a

Results and discussion

Nitrate, phosphate and boron content in wastewater

The concentrations of nitrate, phosphate, and boron in wastewater in the Mexico City-Mezquital Valley drainage network (Table 2) were determined. For the three ions, the coefficient of variation was found to be high, indicating the heterogeneity in the concentration of these ions in the wastewater.

Nitrate, phosphate and boron content.
NO3- PO43- B3+
-------------------------------------- mg L-1 --------------------------------------
Skewness 0.726 0.986 0.268
Kurtosis 0.350 2.842 0.283
K-S 0.01 0.01 0.01
Minimum 1.440 0.00 0.00
Maximum 177.342 65.776 1.881
Mean 60.656 14.319 0.822
Median 57.185 15.490 0.777
Std. Dev. 36.294 10.804 0.318
Range 175.902 65.776 1.881
CV 59.836 75.451 38.782
Q1 34.866 3.754 0.621
Q3 73.467 22.293 1.028
95 % 134.570 29.145 1.381
K-S: Kolmogorov-Smirnov normality test (p-Value), (=0.05; n=188

Source: Author’s own elaboration.

Wastewater contains nitrogen, phosphorous, potassium, copper, iron and zinc and its use can reduce the need for fertilizers (Duncan & Cairncross, 1990). However, in this study, the concentration of nitrate was attributed precisely to the use of fertilizers; the wastewater, in its course across the agricultural area known as the Mezquital Valley, becomes enriched with these ions that are lixiviate from agricultural soils and transported in drainage water. The continuous use of wastewater may cause problems in the natural fertility soil, and in the protection of water resources due to the high concentration of sodium, nitrate and phosphate salts (Belaid et al., 2012).

The main drainage channel for Mexico City, through the 14-Peñón-Texcoco highway, had a nitrate concentration of 3.908 mg L-1, and the 16-Tequisquiac tunnel, 2.180 mg L-1 of nitrate. The highest concentration of this ion was found in the Tula River water in 17-Apaxco and 26-Atotonilco (153.380 mg L-1 and 154.578 mg L-1 respectively), in 112-agricultural drainage water (177.342 mg L-1 of NO3-) and filtration water in 30-Atitalaquia (146.431 mg L-1 of NO3-), indicating that wastewater coming from Mexico City, in its course through the State of Hidalgo is used in agriculture, and the excess of nitrogenated fertilizers is leached and evacuated by agricultural drainage, as well as the wastewater that is poured into the Tula River, so this River receives urban and industrial wastewater and agricultural drainage, which explains it nitrate concentration.

The data are asymmetrical (p-value < (); the third quartile (Q3) had a value of 73.467 mg L-1 of NO3-, and the median was of 57.185 mg L-1 of NO3-. These data indicated that wastewater contain excess of nitrate (> 30 mg L-1), 19 % of the water samples had between 5 mg L-1 and 30 mg L-1 of NO3-, and only six water samples contained lees than 5 mg L-1 of NO3-.

The excess nitrate is due to the discharging of agricultural drainage into this hydrographic network, this occurs by the altitudinal gradient (from 2293 masl to 935 masl); finally, the flow of water is evacuated by the Moctezuma River. Use of the wastewater for agricultural irrigation may decrease the yield and quality of sensitive crops; their sensitivity to high ion concentration varies during the crop’s phenological stages, so as the crop’s needs decrease, high ionic concentration may be harmful (Ayers & Westcot, 1987). Figure 2 illustrates the data distribution on the nitrate concentration found in the Mexico City-Mezquital Valley drainage network.

Distribution of the concentration of nitrate in the Mexico City-Mezquital Valley drainage network. Source: Author’s own elaboration.

On the other hand, water runoff and infiltration with high nitrate content due to fertilization practices, creates an important problem of widespread pollution in water resources, and if the nitrate reaches groundwater bodies, it can cause serious health problems for people, who consume this water (Aruzo et al., 2006).

In Mexico, the highest nitrate concentration permitted in sources of drinking water is (10 mg L-1 N = 44.26 mg L-1 NO3-) (Secretaría de Salud, 2000). This investigation did not analyze the quality of groundwater, but it is possible that the Mezquital Valley aquifer has infiltrations of wastewater, since more than 80% of the main channels are not revetted (Lesser-Carrillo et al., 2011). In this sense, there is a possibility that a part of this excess concentration of NO3- can lixiviate into the aquifer (Belaid et al., 2012), since irrigation sheet of over 1 m are applied in the crops irrigation, indicating that there is a leaching fraction greater than 0.45, it helps to keep low salinity levels (Hoffman, 1990), but it increases the risk of ions lixiviation such as NO3- outside the root zone of the crops.

The concentration of nitrogen is obtained using the following equations:

N O 3 -   ( m g   L - 1 ) 4.42688 = N m g   L - 1

N m g   L - 1 1,000,000 = N k g   L - 1 ; N k g   L - 1 × 10,000,000   L   h a - 1 = k g   h a - 1   o f   N

Estimated nitrogen content was 137.01 kg ha-1, for a 1 m irrigation sheet. The excessive concentration of salts and nutrients such as N are a risk for long-term agricultural production, although this conclusion must be verified for diverse types of crops and soils irrigated with wastewater (Belaid et al., 2012).

Regarding phosphate (Fig. 3), a high coefficient of variation was found. Maximum PO43- values were found in different irrigation channels: 65.776 mg L-1 (46-irrigation channel 1, Morelos colony, Actopan-Ixmiquilpan road), 60.849 mg L-1 (24-irrigation channel Atitalaquia), 36.899 mg L-1 (23-irrigation channel Pemex, Atitalaquia-Tula road), 36.212 mg L-1 (21-Teltipan-Tlaxcoapan road) and 36.091 mg L-1 (11-Eastern emission channel, Ecatepec). The latter corresponds to the discharge of wastewaters from Mexico City. Infiltration water (in Progreso and Chilcuautla) and the Juchitlán spring, in this agricultural area, presented the lowest concentration values for PO4-3 (<0.083 mg L-1), indicating a sanitation of wastewater through the soil. The mean value for PO43- was 14.319 mg L-1, and the median had a value of 15.490 mg L-1 of PO43-. Q1 had a value of 3.754 mg L-1 of PO43-, and Q3 had a value of 22.293 mg L-1 of PO43-; 95 % of the water samples had a concentration of PO43- lower than 29.145 mg L-1.

Distribution of the concentration of phosphate in the Mexico City-Mezquital Valley drainage network. Source: Author’s own elaboration.

The concentration of phosphorous and phosphate is obtained using the following equations:

P O 4 3 -   ( m g   L - 1 ) 3.06618 = P m g   L - 1

P m g   L - 1 1,000,000 = P k g   L - 1 ; P k g   L - 1 × 10,000,000   L   h a - 1 = k g   h a - 1   o f   P

In this case, the concentration of phosphorus in the water is, on average, of 4.66 mg L-1. This value indicates the hypertrophic condition in which the water is found (Moreno-Franco et al., 2010); domestic and industrial wastewater are the main source of phosphorus, as well as agricultural drainage, and its main characteristic is that it is composed of detergents that derive from anthropogenic activity (Lizárraga-Mendiola et al., 2013; Ongom et al., 2017) and the leaching of phosphated fertilizers. The phosphorus content was estimated in 46.6998 kg ha-1 on average for a 1 m irrigation sheet, which was attributed to the discharge of wastewater and the leaching of phosphated fertilizers. Normal phosphate values in irrigation water are generally below 2 mg L-1 (Ayers & Westcot, 1985); in this case, the excess concentration of phosphate may be due to agricultural, domestic and industrial discharge (Velázquez-Machuca et al., 2010).

Risk of toxicity due to the concentration of boron and chloride

The concentration of boron (B3+) was attributed to borax waste N a 2 B 4 O 7 · 10 H 2 O ), which is widely used as a cleaning agent, and therefore present in domestic and industrial wastewaters (Hem, 1985). This ion is important in agriculture, although amounts lower than 1 mg L-1 are toxic to some crops such as citrus fruits and beans, hence boron is the most likely element to cause toxicity in crops (Page et al., 1990).

Figure 4 shows the distribution of B3+ in wastewater. The highest values were the following: 1.881 mg L-1 (14-grand drainage channel near the Peñón-Texcoco road), 1.568 mg L-1 (113-agricultural drain, Nith-Debodhé road), 1.565 mg L-1 (11-eastern emission tunnel, Tonanitla-Xaltocan road, in Ecatepec), 1.494 mg L-1 (61-Boxtha drain in Actopan) and 1.461 mg L-1 (4-Nextlalpan). The mean and median were 0.822 mg L-1 and 0.777 mg L-1, respectively. Irrigation with this water may cause decrease in the yield of sensitive crops to a concentration of B3+ of over 0.3 mg L-1, whereas tolerant crops do not show symptoms at a concentration of B3+ in the soil solution of 4 mg L-1 (Page et al., 1990). It is recommended that the effects of irrigation water be measured directly on the soil and crops, yet it has been found that crop yields decrease as the concentration of B3+ increases to toxic levels (Pratt & Suarez, 1990):

y = 100 - m x - A

Distribution of the concentration of boron in the Mexico City-Mezquital Valley drainage network. Source: Author’s own elaboration.

Where y is the relative yield of a crop (%); m is the decrease in yield per unit increase B3+ concentration; A is the maximum concentration of B that does not reduce yield (threshold); x is the B3+ concentration in irrigation water.

For one concentration of B3+ in irrigation water, there is a different concentration of B3+ in the root zone, depending on the leaching fraction. In this case, the leaching fraction is estimated in 0.45 and this value helps keep low salinity levels, and as the leaching fraction decreases, the salinity in soil water increases, due to the effect of concentration (Pratt & Suarez, 1990) and this represents a risk of toxicity for crops, mainly for bean, which is considered sensitive to electric conductivity (EC < 1 dS m-1) and B3+ (< 1 mg L-1) (Maas, 1990).

The risk of toxicity by chloride (Cl-) was estimated with the ionic concentration of Cl- in irrigation water, and according to the following values (Ayers & Westcot, 1985): without restriction of use when the concentration of Cl- is < 4 meq L-1, use restriction is moderate between 4 meq L-1 and 10 meq L-1 of Cl- and the use is not recommended when concentrations are over 10 meq L-1 of Cl-. The mean was 5.077 meq L-1 of Cl- and the median was 4.935 meq L-1 of Cl-. The coefficient of variation was 36 % and indicates very heterogeneous Cl- values, Q1 had a value of 3.610 meq L-1 of Cl-, the value in Q3 was 6.215 meq L-1 of Cl-, and 95 % of the water samples had less than 7.960 meq L-1 of Cl-. According to the distribution of these data (Fig. 5), there is a risk of toxicity due to the concentration of Cl- for sensitive crops such as bean (Maas, 1990).

Distribution of the chloride concentration in the Mexico City-Mezquital Valley drainage network. Source: Author’s own elaboration.

The extreme values for the concentration of Cl-, higher than the upper limit, were found in drainage water: 12.98 meq L-1 (4-Nextlalpan), 11.72 meq L-1 (113-Nith-Debodhé road), 9.52 meq L-1 (97-Bangandhó), 8.54 meq L-1 (56-Actopan) and 8.27 meq L-1 in the 129-Mercado-Ixmiquilpan sampling station.

Content of nutrients and organic matter in wastewater

Regarding the content o N, P, K, Ca, Mg, total solids (TS) and total volatile solids (TVS or total organic matter OM), Table 3 shows the corresponding data. The following sequence was found, from higher to lower concentration: Ca > Mg > K > N > P. This water contains organic matter (276 mg L-1), as well as a considerable amount of total salts (>770 mg L-1), mostly sodium and bicarbonate (Cuellar-Carrasco et al., 2015; López-García et al., 2016), which creates the risk of salinization for soils and crops irrigated with this water.

Content of nitrogen, phosphorous, potassium, calcium, magnesium, total solids and total volatile solids.
Min. Max. Mean Median Std. Dev. Range CV Q1 Q3 95 %
N 0.325 40.060 13.701 12.918 8.198 39.735 59.83 7.876 16.596 30.398
P 0.00 21.452 4.670 5.052 3.523 21.452 75.45 1.224 7.270 9.505
K 6.256 66.473 29.257 26.980 10.509 60.217 35.92 24.047 31.673 51.224
Ca 9.616 76.152 42.290 42.886 12.645 66.533 29.90 34.869 50.100 64.128
Mg 8.266 88.860 40.761 39.497 13.783 80.594 33.81 29.045 50.083 63.211
TS 232 2472 1015.383 1046 340.784 2240 33.56 724 1224 1512
TVS 84 660 271.936 276 96.286 576 35.40 190 342 424
All the variables are expressed in mg L-1 units; TS: total solids; TVS: total volatile solids or total organic matter; n = 188

Source: Author’s own elaboration.

According to the data obtained by Can-Chulim et al. (2017) the increase in the ionic concentration reduces the percentage of germination of Phaseolus Vulgaris and NaHCO3 was the salt that caused the lowest percentage of germination, in this sense, a negative effect on the bean crops irrigated with wastewater in the Mezquital Valley is expected.

Regarding the content of organic matter, the remaining residue after calcination does not provide a precise distinction between organic and inorganic residues, given that the loss by calcination is not limited only to organic matter, but also includes losses produced by the decomposition of some mineral salts. It is recommendable to determine the chemical oxygen demand and biochemical oxygen demand in wastewaters (Eaton et al., 1998). This investigation only provides an approximation to the organic matter content by determining the total volatile solids.

Conclusions

According to the results obtained under the conditions in which this investigation was carried out, we concluded that the concentration of nitrate and phosphate in the wastewater of the Mexico City-Mezquital Valley drainage network was high, and this was attributed to the discharges of domestic and industrial wastewaters and to agricultural drainage.

The high concentration of these ions represents a risk, due to the possible gradual eutrophication of the water bodies. There is also a risk of contamination of the aquifers, since over 80 % of the irrigation channels are not revetted, and this may cause the leaching of NO3-.

Regarding the content of nutrients, the following sequence was found, from higher to lower concentration: Ca > Mg > K > N >P. The value of the median, regarding the organic matter content, was 276 mg L-1, and the median for total solids was 1 046 mg L-1, therefore the total salt concentration was 770 mg L-1.

The risk of toxicity by B3+ and Cl- can have a negative effect on the germination and yield of bean crops (to a lesser extent, maize, oat and alfalfa), since it is sensitive to the concentration of these ions found in wastewaters. The use of this water is still restricted, since this study does not consider the microbiological aspects or the heavy metals that can accumulate in the soil and crops. Likewise, it has been proven that the contact of the general population with this water causes public health problems in the agricultural area known as the Mezquital Valley. It is recommendable to perform the wastewater treatment before it is discharged into receptor bodies. Finally, the concepts presented here must be verified experimentally in the soil and crops irrigated with wastewater in this agricultural area.

Acknowledgements

  • To the National Science and Technology Council of Mexico, for the allocation of economic resources. To the reviewers of this paper.

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History:
  • » Received: 06/05/2018
  • » Accepted: 12/07/2018
  • » Digital publication: 04/2019

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Nova Scientia is a multidisciplinary, electronic publication that publishes biannually in the months of May and November; it is published by the Universidad De La Salle Bajío and aims to distribute unpublished and original papers from the different scientific disciplines written by national and international researchers and academics. It does not publish reviews, bibliographical revisions, or professional applications.

Nova Scientia, year 11, issue 22, May – October 2019, is a biannual journal printed by the Universidad De La Salle Bajío, with its address: Av. Universidad 602, Col. Lomas del Campestre, C. P. 37150, León, Gto. México. Phone: (52) 477 214 3900, http://novascientia.delasalle.edu.mx/. Chief editor: Ph.D. Ramiro Rico Martínez. ISSN 2007 - 0705. Copyright for exclusive use No. 04-2008-092518225500/102, Diffusion rights via computer net 04 - 2008 – 121011584800-203 both granted by the Instituto Nacional del Derecho de Autor.

Editor responsible for updating this issue: Direction of Research Department of the Universidad De La Salle Bajío, last updated on May 28th, 2019.