Advertisement

Applying grey water footprint assessment to achieve environmental sustainability within a nation under intensive agriculture: a high-resolution assessment for common agrochemicals and crops

  • Fatemeh KarandishEmail author
Original Article
  • 93 Downloads

Abstract

Achieving safer environment under intensive agriculture highly depends on input resource management. This research is the first grey water footprint (WF) assessment in which the field-scale heterogeneities in input data are considered to provide new insights for achieving sustainable environment under dense farming. For a 10-year period over 2005–2015, grey WF accounting and impact assessment was carried out, together with sensitivity and uncertainty analysis, for a wide range of agrochemicals commonly applied to the agricultural soils in Iran. Given results were then applied to provide new applicable solutions for reducing the overall pollutant loaded to freshwater bodies from diffuse sources. The 10-year average of the given results showed that with an overall load of 77.1 thousand t year−1, N was the most critical substance among various agrochemicals, especially within the irrigated lands, where are the origin of 83.1% of loaded N to freshwater bodies. Cereals, both irrigated and rainfed, always had the largest contribution in the overall pollutants loaded to water bodies. At the national sale, 48.2 billion m3 year−1 water is annually required to take up the N pollution loads, which is 26.8% less than actual runoff within the country. While the national-scale water pollutant level (WPL) was 0.7, the high-resolution assessment indicated the existence of local polluted area with WPL > 1 in 42.8% of the country, 96% of which located within the arid and semi-arid regions. In these areas, the river’s waste assimilation capacity has been overused by the factors of 1–32.8. Based on the quantitative impact assessment, the overall N-related grey WFs may be reduced by 47% if grey WFs are lowered down to the benchmark levels set at the 25th percentile of crop production, by 9.1% if crops’ yield is improved by 10%, and by 27.8% if N-application rates are reduced to the optimal rate. In addition, regional prioritizing of cropping pattern based on their grey WFs may result in an expressive reduction in WPL due to the large diversity in grey WFs among crops and regions. Based on the results, it could be concluded that, with a 10–16.1% uncertainties, a high-resolution local-scale grey WF assessment is a promising way to achieve safer agricultural environment in a dense-farming country.

Keywords

Agricultural sustainability Agrochemicals Grey WF accounting Impact assessment Uncertainty analysis 

Notes

Acknowledgements

Fatemeh Karandish would like to appreciate the support of University of Zabol for carrying out this research under the grant number “UOZ_GR_9618_4”.

Compliance with ethical standards

Conflict of interest

The author declares that they have no conflict of interest.

References

  1. Aldaya MM, Hoekstra AY (2010) The water needed for Italians to eat pasta and pizza. Agric Syst 103:351–360CrossRefGoogle Scholar
  2. Alexandratos N, Bruinsma J (2012) World agriculture towards 2030/2050: the 2012 revision. ESA Working paper No. 12-03. Rome, FAOGoogle Scholar
  3. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration guide Lines for computing crop water requirements. Irrigation and drainage paper 56, Rome, Italy. p. 300Google Scholar
  4. Anderson D, Glibert P, Burkholder J (2005) Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries 25, 704–726CrossRefGoogle Scholar
  5. Araujo J, Delgado FI, Paumgartten FJR (2016) Glyphosate and adverse pregnancy outcomes, a systematic review of observational studies. BMC Public Health 16:472CrossRefGoogle Scholar
  6. Burow KR, Nolan BT, Rupert MG, Dubrovsky NM (2010) Nitrate in groundwater of the United States, 1991–2003. Environ Sci Technol 44:4988–4997CrossRefGoogle Scholar
  7. Cao X, Wu M, Shu R, Zhuo L, Chen D, Shao G, Guo X, Wang W, Tang S (2018) Water footprint assessment for crop production based on field measurements: A case study of irrigated paddy rice in East China. Sci Total Environ 609(2017):587–597Google Scholar
  8. Carson R (1962) Silent Spring. Fawcett Crest, GreenwichGoogle Scholar
  9. Carter C, Zhong F, Zhu J (2012) Advances in Chinese agriculture and its global implications. Appl Econ Perspect Policy 34:1–36CrossRefGoogle Scholar
  10. Carvalho FP (2017) Pesticides, environment, and food safety. Food Energy Secur 6(2):48–60CrossRefGoogle Scholar
  11. Carvalho FP, Gonzalez-Farias F, Villeneuve J-P, Cattini C, Hernandez-Garza M, Mee LD et al (2002) Distribution, fate and effects of pesticide residues in tropical coastal lagoons of the northwest of Mexico. Environ Technol 23:1257–1270CrossRefGoogle Scholar
  12. Carvalho FP, Montenegro-Guillén S, Villeneuve J-P, Cattini C, Tolosa I, Bartocci J et al (2003) Toxaphene residues from cotton fields in soils and in the coastal environment of Nicaragua. Chemosphere 53:627–636CrossRefGoogle Scholar
  13. CCME (2013) Canadian water quality guidelines for the protection of aquatic life. Canadian Council of Ministers of the Environment, WinnipegGoogle Scholar
  14. Chukalla AD, Krol MS, Hoekstra AY (2017) Marginal cost curves for water footprint reduction in irrigated agriculture: Guiding a cost-effective reduction of crop water consumption to a permit or benchmark level. Hydrol Earth Syst Sci 21:3507–3524CrossRefGoogle Scholar
  15. Chukalla AD, Krol AS, Hoekstra AY (2018) Trade-off between blue and grey water footprint of crop production at different nitrogen application rates under various field management practices. Sci Total Environ 626:962–970CrossRefGoogle Scholar
  16. Dahan O, Babad A, Lazarovitch N, Russak EE, Kurtzman D (2014) Nitrate leaching from intensive organic farms to groundwater. Hydrol Earth Syst Sci 18:333–341CrossRefGoogle Scholar
  17. Denis DM, Kumar M, Srivastava S, Suryavanshi S, Denis AF, Singh R, Yadav A, Mishra M (2016) A high resolution assessment of water footprint of wheat to understand yield and water use heterogeneities. Water Resour Manag 30:2641–2649CrossRefGoogle Scholar
  18. Dudley LM, Ben-Gal A, Lazarovitch N (2008) Drainage water reuse: biological, physical, and technological considerations for system management. J Environ Qual 37:25–35CrossRefGoogle Scholar
  19. EC: European Commission (1998) Council Directive 98/83/EC of 3 November 1998: on the quality of water intended for human consumption. EC: European Commission, BrusselsGoogle Scholar
  20. ECA (2017) European chemicals agency. https://echa.europa.eu/regulations/reach/legislation. Accessed 10 Jan 2017
  21. EEC (1975) Quality required of surface water intended for the abstraction of drinking water in the Member States, Council Directive 75/440/EEC. European Economic Community, BrusselsGoogle Scholar
  22. Ercin AE, Aldaya MM, Hoekstra AY (2011) Corporate water footprint accounting and impact assessment: the case of the water footprint of a sugar-containing carbonated beverage. Water Resour Manag 25:721–741CrossRefGoogle Scholar
  23. FAO (2013) FAOSTAT. Food and Agriculture Organization of the United Nations, Rome, Italy. http://www.fao.org/faostat/en/
  24. FAO (2017) FAOSTAT. Food and Agriculture Organization of the United Nations, Rome, Italy. http://www.fao.org/faostat/en/
  25. Franke N, Mathews R (2012) C&A’s water footprint strategy: cotton clothing supply chain. Water Footprint Network, EnschedeGoogle Scholar
  26. Franke N, Mathews R (2013) Grey water footprint indicator of water pollution in the production of organic vs. conventional cotton in India. Water Footprint Network, EnschedeGoogle Scholar
  27. Franke NA, Boyacioglu H, Hoekstra AY (2013) Grey Water Footprint Assessment: Tier 1—supporting guidelines. Water Footprint Network, EnschedeGoogle Scholar
  28. Garbarino JR, Snyder-Conn E, Leiker TJ, Hoffman GL (2002) Contaminants in arctic snow collected over northwest Alaskan sea ice. Water Air Soil Pollut 139:183–214CrossRefGoogle Scholar
  29. Gil R, Bojacá CR, Schrevens E (2017) Uncertainty of the agricultural grey water footprint based on high resolution primary data. Water Resour Manag.  https://doi.org/10.1007/s11269-017-1674-x CrossRefGoogle Scholar
  30. Hoekstra AY (2017) Water footprint assessment: evolvement of a new research field. Water Resour Manag 31:3061–3081CrossRefGoogle Scholar
  31. Hoekstra AY, Chapagain AK (2008) Globalization of water: sharing the planet’s freshwater resources. Blackwell, OxfordGoogle Scholar
  32. Hoekstra AY, Mekonnen MM (2012) The water footprint of humanity. Proc Natl Acad Sci 109(9):3232–3237CrossRefGoogle Scholar
  33. Hoekstra AY, Chapagain AK, Aldaya MM, Mekonnen MM (2011) The Water Footprint Assessment Manual: Setting the Global Standard. Earthscan, LondonGoogle Scholar
  34. IMAJ (2017) Iran’s Ministry of Agriculture Jihad, Tehran, Iran. http://www.maj.ir
  35. Kale S, Murthy NBK, Raghu K, Sherkane PD, Carvalho FP (1999) Studies on degradation of 14C-DDT in the marine environment. Chemosphere 39:959–968CrossRefGoogle Scholar
  36. Karandish F, Hoekstra AY (2017) Informing national food and water security policy through water footprint assessment: the case of Iran. Water.  https://doi.org/10.3390/w9110831 CrossRefGoogle Scholar
  37. Karandish F, Šimůnek J (2017) Two-dimensional modeling of nitrogen and water dynamics for various N-managed water-saving irrigation strategies using HYDRUS. Agric Water Manag 193:174–190CrossRefGoogle Scholar
  38. Karandish F, Salari S, Darzi-Naftchali (2015) Application of virtual water trade to evaluate cropping pattern in arid regions. Water Resour Manag 29(11):4061–4074CrossRefGoogle Scholar
  39. Karandish F, Mousavi SS (2016) Climate change uncertainty and risk assessment in Iran during twenty-first century: evapotranspiration and green water deficit analysis. Theoret Appl Climatol 131(1–2):777–791Google Scholar
  40. Karandish F, Mousavi SS, Tabari H (2016) Climate change impact on precipitation and cardinal temperatures in different climatic zones in Iran: analyzing the probable effects on cereal water-use efficiency. Stoch Environ Res Risk Assess 31(8):2121–2146CrossRefGoogle Scholar
  41. Karandish F, Darzi-Naftchali A, Asgari A (2017) Application of machine-learning models for diagnosing health hazard of nitrate toxicity in shallow aquifers. Paddy Water Environ 15:201–215CrossRefGoogle Scholar
  42. Klocke NL, Schneekloth JP, Melvin SR, Clark RT, Payero JO (2004) Field scale limited irrigation scenarios for water policy strategies. Appl Eng Agric 20(5):623–631CrossRefGoogle Scholar
  43. Landsberg JH (2002) The effects of harmful algal blooms on aquatic organisms. Rev Fish Sci 10:113–390CrossRefGoogle Scholar
  44. Leach AM, Galloway JN, Bleeker A, Erisman JW, Kohn R, Kitzes J (2012) A nitrogen footprint model to help consumers understand their role in nitrogen losses to the environment. Environ Dev 1:40–66CrossRefGoogle Scholar
  45. Lewitus AJ, Horner RA, Caron DA, Garcia-Mendoza E, Hickey BM, Hunter M, Huppert DD, Kudela RM, Langlois GW, Largier JL et al (2012) Harmful algal blooms along the north american west coast region: history, trends, causes, and impacts. Harmful Algae 19:133–159CrossRefGoogle Scholar
  46. Li R, Jin J (2013) Modeling of temporal patterns and sources of atmospherically transported and deposited pesticides in ecosystems of concern: a case study of toxaphene in the Great Lakes. J Geophys Res Atmos 118:11863–11874CrossRefGoogle Scholar
  47. Liu C, Kroeze C, Hoekstra AY, Gerbens-Leenes W (2012) Past and future trends in grey water footprints of anthropogenic nitrogen and phosphorus inputs to major world rivers. Ecol Ind 18(0):42–49.  https://doi.org/10.1016/j.ecolind.2011.10.005 CrossRefGoogle Scholar
  48. Lovarelli D, Bacenetti J, Fiala M (2016) Water footprint of crop productions: a review. Sci Total Environ 548–549:236–251CrossRefGoogle Scholar
  49. McCuen R (1974) A sensitivity and error analysis CF procedures used for estimating evaporation. J Am Water Resour Assoc 10(3):486–497CrossRefGoogle Scholar
  50. McKnight US, Rasmussen JJ, Kronvang B, Binning PJ, Bjerg PL (2015) Sources, occurrence and predicted aquatic impact of legacy and contemporary pesticides in streams. Environ Pollut 200:64–76.  https://doi.org/10.1016/j.envpol.2015.02.015 CrossRefGoogle Scholar
  51. Mekonnen MM, Hoekstra AY (2014) Water footprint benchmarks for crop production: a first global assessment. Ecol Indic 46:214–223CrossRefGoogle Scholar
  52. Mekonnen MM, Hoekstra AY (2015) Global gray water footprint and water pollution levels related to anthropogenic nitrogen loads to fresh water. Environ Sci Technol 49(21):12860–12868CrossRefGoogle Scholar
  53. Mekonnen MM, Hoekstra AY (2017) Global anthropogenic phosphorous loads to fresh water and associated grey water footprints and water pollution levels: a high-resolution global study. Water Resour Res.  https://doi.org/10.1002/2017WR020448 CrossRefGoogle Scholar
  54. Mekonnen MM, Lutter S, Martinez A (2016) Anthropogenic nitrogen and phosphorous emissions and related grey water footprint caused by EU-27’s crop production and consumption. Water.  https://doi.org/10.3390/w8010030 CrossRefGoogle Scholar
  55. Melo A, Pinto E, Aguiar A, Mansilha C, Pinho O, Ferreira I (2012) Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides. Environ Monit Assess 184:4539–4551CrossRefGoogle Scholar
  56. Miglietta PP, Toma P, Fanizzi FP, Donno AD, Coluccia B, Migoni D, Bagordo F, Serio F (2017) A grey water footprint assessment of groundwater chemical pollution: case study in Salento. Sustainability.  https://doi.org/10.3390/su9050799 CrossRefGoogle Scholar
  57. Montesinos P, Camacho E, Campos B, Rodríguez-Díaz JA (2011) Analysis of virtual irrigation water: application to water resources management in a Mediterranean river basin. Water Resour Manag 25:1635–1651CrossRefGoogle Scholar
  58. Moreno-Gonzalez R, Leon VM (2017) Presence and distribution of current-use pesticides in surface marine sediments from a Mediterranean coastal lagoon (SE Spain). Environ Sci Pollut Res Int 24:8033–8048.  https://doi.org/10.1007/s11356-017-8456-0 CrossRefGoogle Scholar
  59. Naylor R, Steinfeld H, Falcon W, Galloway J, Smil V, Bradford E, Alder J, Mooney H (2005) Losing the links between livestock and land. Science 310:1621–1622CrossRefGoogle Scholar
  60. O’Bannon C, Carr J, Seekell DA, D’Odorico P (2014) Globalization of agricultural pollution due to international trade. Hydrol Earth Syst Sci 18:503–510CrossRefGoogle Scholar
  61. Pahlow M, Van Oel PR, Mekonnen MM, Hoekstra AY (2015) Increasing pressure on freshwater resources due to terrestrial feed ingredients for aquaculture production. Sci Total Environ 536:847–857CrossRefGoogle Scholar
  62. Paraiba LC, Pazianotto RAA, Luiz AJBL, Maia AHN, Jonsson CM (2014) A mathematical model to estimate the volume of grey water of pesticide mixtures. Spanish J Agric Res 12(2):509–518CrossRefGoogle Scholar
  63. Payero JO, Melvin SR, Irmak S, Tarkalson D (2006) Yield response of corn to deficit irrigation in a semiarid climate. Agric Water Manag 84(1–2):101–112CrossRefGoogle Scholar
  64. Pellicer-Martínez F, Martínez-Paz (2018) Probabilistic evaluation of the water footprint of a river basin: accounting method and case study in the Segura River Basin, Spain. Sci Total Environ 627:28–38CrossRefGoogle Scholar
  65. Popp J, Peto K, Nagy J (2013) Pesticide productivity and food security: a review. Agron Sustain Dev 33:243–255CrossRefGoogle Scholar
  66. Rasmussen JJ, Wiberg-Larsen P, Baattrup-Pedersen A, Cedergreen N, McKnight US, Kreuger J et al (2015) The legacy of pesticide pollution: an overlooked factor in current risk assessments of freshwater systems. Water Res 84:25–32CrossRefGoogle Scholar
  67. Shrestha S, Pandey VP, Chanamai C, Ghosh DK (2013) Green, blue and grey water footprints of primary crops production in Nepal. Water Resour Manag 27:5223–5243Google Scholar
  68. Singh Z, Kaur J, Kaur R, Hundal SS (2016) Toxic effects of organochlorine pesticides: a review. Am J Biosci 4:11–18CrossRefGoogle Scholar
  69. Smith V (2003) Eutrophication of freshwater and coastal marine ecosystems a global problem. Environ Sci Pollut Res 10:126–139CrossRefGoogle Scholar
  70. Smith LED, Siciliano G (2015) A comprehensive review of constraints to improved management of fertilizers in China and mitigation of diffuse water pollution from agriculture. Agric Ecosyst Environ.  https://doi.org/10.1016/j.agee.2015.02.016 CrossRefGoogle Scholar
  71. Spalding RF, Exner ME (1993) Occurrence of nitrate in groundwater—a review. J Environ Qual 22:392–402CrossRefGoogle Scholar
  72. Steen-Olsen K, Weinzettel J, Cranston G, Ercin AE, Hertwich EG (2012) Carbon, land, and water footprint accounts for the european union: consumption, production, and displacements through international trade. Environ Sci Technol 46:10883–10891CrossRefGoogle Scholar
  73. Stone LR (2003) Crop water use requirements and water use efficiencies. In: Proceedings of the 15th annual central plains irrigation conference and exposition, Colby, Kansas, pp 127–133Google Scholar
  74. UN. 2015. United Nations, Department of Economic and Social Affairs, Population Division (2015) World population prospects: the 2015 revision, key findings and advance tables. Working paper no. ESA/P/WP.241. United Nations New York, 2015Google Scholar
  75. Velázquez E, Madrid C, Beltrán MJ (2011) Rethinking the concepts of virtual water and water footprint in relation to the production–consumption binomial and the water–energy nexus. Water Resour Manag 25:743–761CrossRefGoogle Scholar
  76. Wackernagel M, Onisto L, Bello P, Callejas Linares A, Susana López Falfán I, Méndez García J, Isabel Suárez Guerrero A, Guadalupe Suárez Guerrero M (1999) National natural capital accounting with the ecological footprint concept. Ecol Econ 29:375–390CrossRefGoogle Scholar
  77. WHO (2017) Agrochemicals, health and environment: directory of resources. http://www.who.int/heli/risks/toxics/chemicalsdirectory/en/index1.html. Accessed 10 Jan 2017
  78. Zhang C, McBean EA, Huang J (2014) A virtual water assessment Methodology for cropping pattern investigation. Water Resour Manag 28:2331–2349CrossRefGoogle Scholar
  79. Zhang Y, Zhang JH, Tian Q, Liu ZH, Zhang HL (2018) Virtualwater trade of agricultural products: a newperspective to explore the Belt and Road. Sci Total Environ 622–623:988–996CrossRefGoogle Scholar
  80. Zhuo L, Mekonnen MM, Hoekstra AY (2016) Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: a case study for winter wheat in China. Hydrol Earth Syst Sci 20(11):4547–4559CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Water Engineering DepartmentUniversity of ZabolZabolIran

Personalised recommendations