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Water quality implications of raising crop water productivity

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  • Nangia, V.
  • de Fraiture, C.
  • Turral, H.

Abstract

Because of a growing and more affluent population, demand for agricultural products will increase rapidly over the coming decades, with serious implications for agricultural water demand. Symptoms of water scarcity are increasingly apparent, threatening ecosystem services and the sustainability of food production. Improved water productivity will reduce the additional water requirements in agriculture. However, there is a tradeoff between the quantity of water used in agriculture and the quality of return flow. Where yields are low due to limited nitrogen (N) and water supply, water productivity can be enhanced through higher fertilizer applications and improved water management. This limits the amount of additional water needed for increased food demand, thus leaving more water for environmental requirements. But it also increases the amount of nitrate (NO3-N) leaching, thus adversely affecting the water quality of return flows. This paper quantifies the tradeoff between enhanced water productivity and NO3-N leaching and shows the importance of the right management of water and N applications. Using the Decision Support System for Agro-technology Transfer (DSSAT) crop model, several scenarios combining different water and N application regimes are examined for maize (Zea mays L.) in Gainesville, FL, USA. Without adequate water, nitrogen use efficiency (NUE) remains low, resulting in substantial NO3-N leaching. Too much water leads to excessive NO3-N leaching and lower water productivity. The lack of N is a cause of low water productivity but too much of it leads to lower NUE and higher losses. The paper concludes that increased NO3-N leaching is an inevitable by-product of increased water productivity, but its adverse impacts can greatly be reduced by better management of water and N application. The paper briefly shows that leaching can be reduced and water productivity increased by split application of N-fertilizer. This implies that improved water and nutrient management at field- and scheme-level is a prerequisite to limit adverse impacts of agriculture on ecosystems, now and especially in the future.

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  • Nangia, V. & de Fraiture, C. & Turral, H., 2008. "Water quality implications of raising crop water productivity," Agricultural Water Management, Elsevier, vol. 95(7), pages 825-835, July.
  • Handle: RePEc:eee:agiwat:v:95:y:2008:i:7:p:825-835
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    References listed on IDEAS

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    1. de Fraiture, Charlotte & Wichelns, D. & Rockstrom, J. & Kemp-Benedict, E. & Eriyagama, Nishadi & Gordon, L. J. & Hanjra, M. A. & Hoogeveen, J. & Huber-Lee, A. & Karlberg, L., 2007. "Looking ahead to 2050: scenarios of alternative investment approaches," Book Chapters,, International Water Management Institute.
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    5. Molden, David & Frenken, K. & Barker, R. & de Fraiture, Charlotte & Mati, Bancy & Svendsen, M. & Sadoff, Claudia W. & Finlayson, Max & Atapattu, Sithara & Giordano, Mark & Inocencio, Arlene & Lannerst, 2007. "Trends in water and agricultural development," IWMI Books, Reports H040195, International Water Management Institute.
    6. Zwart, Sander J. & Bastiaanssen, Wim G. M., 2004. "Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize," Agricultural Water Management, Elsevier, vol. 69(2), pages 115-133, September.
    7. Molden, David, 2007. "Water for food, water for life: a comprehensive assessment of water management in agriculture," IWMI Books, Reports H040193, International Water Management Institute.
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    Cited by:

    1. Jeong, Hanseok & Jang, Taeil & Seong, Chounghyun & Park, Seungwoo, 2014. "Assessing nitrogen fertilizer rates and split applications using the DSSAT model for rice irrigated with urban wastewater," Agricultural Water Management, Elsevier, vol. 141(C), pages 1-9.
    2. Huang, Feng & Li, Baoguo, 2010. "Assessing grain crop water productivity of China using a hydro-model-coupled-statistics approach. Part II: Application in breadbasket basins of China," Agricultural Water Management, Elsevier, vol. 97(9), pages 1259-1268, September.
    3. Sharma, Bharat & Molden, D. & Cook, Simon, 2015. "Water use efficiency in agriculture: measurement, current situation and trends," Book Chapters,, International Water Management Institute.
    4. Zhang, Xiaodong & Huang, Guo H. & Nie, Xianghui, 2009. "Optimal decision schemes for agricultural water quality management planning with imprecise objective," Agricultural Water Management, Elsevier, vol. 96(12), pages 1723-1731, December.
    5. Muriu-Ng’ang’a, F.W. & Mucheru-Muna, M. & Waswa, F. & Mairura, F.S, 2017. "Socio-economic factors influencing utilisation of rain water harvesting and saving technologies in Tharaka South, Eastern Kenya," Agricultural Water Management, Elsevier, vol. 194(C), pages 150-159.
    6. Liu, M. & Huang, G.H. & Liao, R.F. & Li, Y.P. & Xie, Y.L., 2013. "Fuzzy two-stage non-point source pollution management model for agricultural systems—A case study for the Lake Tai Basin, China," Agricultural Water Management, Elsevier, vol. 121(C), pages 27-41.
    7. Zwart, Sander J. & Bastiaanssen, Wim G.M. & de Fraiture, Charlotte & Molden, David J., 2010. "A global benchmark map of water productivity for rainfed and irrigated wheat," Agricultural Water Management, Elsevier, vol. 97(10), pages 1617-1627, October.
    8. Thakur, Amod K. & Mohanty, Rajeeb K. & Singh, Rajbir & Patil, Dhiraj U., 2015. "Enhancing water and cropping productivity through Integrated System of Rice Intensification (ISRI) with aquaculture and horticulture under rainfed conditions," Agricultural Water Management, Elsevier, vol. 161(C), pages 65-76.
    9. Sharma, Bharat & Molden, D. & Cook, Simon, 2015. "Water use efficiency in agriculture: measurement, current situation and trends," IWMI Books, Reports H046807, International Water Management Institute.

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