Implications of Agricultural Intensification and Climate Change on Water Quality-A Global Assessment

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Presentation by Hua Xie at The International Conference on Sustainability in the Water-Energy-Food Nexus, meeting in Bonn, Germany on May 19th and 20th 2014

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Implications of Agricultural Intensification and Climate Change on Water Quality-A Global Assessment

  1. 1. Uniting agriculture and nature for poverty reduction Hua Xie*, Claudia Ringler and Gauthier Pitois Implications of Agricultural Intensification and Climate Change on Water Quality-A Global Assessment Sustainability in the Water-Energy-Food Nexus International Food Policy Research Institute May 19-20, 2014 in Bonn, Germany
  2. 2. Uniting agriculture and nature for poverty reduction Outline Water quantity and water quality- two sides of one coin Global water quality assessment – an emerging research field Non-point source agricultural pollution
  3. 3. Uniting agriculture and nature for poverty reduction Nitrogen and phosphorus in agriculture  Essential elements for life  Excess nitrogen and phosphorus in aquatic environment cause water quality problems Photo: Wikimedia Commons.
  4. 4. Uniting agriculture and nature for poverty reduction Methodology Land model Transport model N&P concentrations in water environment N&P emissions from agricultural production system on land Hydrologic model Stream flow
  5. 5. Uniting agriculture and nature for poverty reduction Methodology  Process-based simulation of nitrogen and phosphorus in agricultural production  Soil and Water Assessment Tool (SWAT)  Spatial resolution: 0.5˚ × 0.5˚ lat/long grid
  6. 6. Uniting agriculture and nature for poverty reduction Input data-base period (2000-2005) Data Source Topography HydroSHEDS Soil HWSD Precipitation GPCP Temperature GEOS-4 & GEOS-5 Solar radiation GEWEX SRB 3.0 Fertilizer use1 University of Minnesota (Muller et al., 2012) Cropland area McGill University (Monfreda et al., 2008) Nitrogen atmospheric deposition ORNL 1. Simulated crops: maize, wheat, rice, cotton, sorghum, millet, soybean
  7. 7. Uniting agriculture and nature for poverty reduction Input data-base period (2000-2005)
  8. 8. Uniting agriculture and nature for poverty reduction Six agricultural intensification pathways Input data –scenario analysis Socioeconomic growth Climate change Optimistic CSIRO (A1B) Medium MIROC (A1B) Pessimistic
  9. 9. Uniting agriculture and nature for poverty reduction Input data –scenario analysis (population) 2 4 6 8 10 12 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Population(billionpeople) CSIRO&MIROC-medium CSIRO&MIROC-optimistic CSIRO&MIROC-pessimistic
  10. 10. Uniting agriculture and nature for poverty reduction Input data –scenario analysis (GDP) 0 40 80 120 160 200 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 GDP(billionUSD) CSIRO&MIROC-medium CSIRO&MIROC-optimistic CSIRO&MIROC-pessimistic
  11. 11. Uniting agriculture and nature for poverty reduction Input data –scenario analysis (cropland) 1400 1450 1500 1550 1600 1650 1700 1750 1800 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Croppingarea(millionha) CSIRO-medium CSIRO-optimistic CSIRO-pessimistic MIROC-medium MIROC-optimistic MIROC-pessimistic
  12. 12. Uniting agriculture and nature for poverty reduction Input data-scenario analysis (livestock) 200 250 300 350 400 450 500 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Totalmeatproduction(milliontons/yr) CSIRO-medium CSIRO-optimistic CSIRO-pessimistic MIROC-medium MIROC-optimistic MIROC-pessimistic
  13. 13. Uniting agriculture and nature for poverty reduction Input data-scenario analysis (NUE) ─ Optimistic scenario: 40% NUE improvement ─ Medium scenario: 20% NUE improvement ─ Pessimistic scenario: no NUE improvement 𝑁𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝑢𝑠𝑒 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 𝑁𝑈𝐸 = 𝑐𝑟𝑜𝑝 𝑦𝑖𝑒𝑙𝑑 (𝑘𝑔) 𝑛𝑢𝑡𝑟𝑖𝑒𝑛𝑡 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 (𝑘𝑔) (Partial Productivity Factor, PFP)
  14. 14. Uniting agriculture and nature for poverty reduction Input data-climate change CSIRO change in precipitation
  15. 15. Uniting agriculture and nature for poverty reduction Input data-climate change CSIRO change in temperature
  16. 16. Uniting agriculture and nature for poverty reduction Input data-climate change MIROC change in precipitation
  17. 17. Uniting agriculture and nature for poverty reduction Input data-climate change MIROC change in temperature
  18. 18. Uniting agriculture and nature for poverty reduction Input data-climate change CNRM-CM3 model with A1B scenario for 2050 CNRM-CM3 model with A2 scenario for 2050 CNRM-CM3 model with B1 scenario for 2050 CSIRO-Mk3.0 model with A1B scenario for 2050 CSIRO-Mk3.0 model with A2 scenario for 2050 CSIRO-Mk3.0 model with B1 scenario for 2050 ECHam5 model with A1B scenario for 2050 ECHam5 model with A2 scenario for 2050 ECHam5 model with B1 scenario for 2050 MIROC 3.2 (medium resolution) model with A1B scenario for 2050 MIROC 3.2 (medium resolution) model with A2 scenario for 2050 MIROC 3.2 (medium resolution) model with B1 scenario for 2050 (Jones et al., 2009)
  19. 19. Uniting agriculture and nature for poverty reduction Nitrogen loading-base period 46 million tons/yr
  20. 20. Uniting agriculture and nature for poverty reduction Phosphorus loading-base period 2.7 million tons/yr
  21. 21. Uniting agriculture and nature for poverty reduction Nitrogen loading-2050 46 62 68 73 68 74 81 0 10 20 30 40 50 60 70 80 90 Milliontons/yr
  22. 22. Uniting agriculture and nature for poverty reduction Phosphorus loading-2050 2.7 2.8 2.9 3.0 3.1 3.3 3.4 0 0.5 1 1.5 2 2.5 3 3.5 4 Milliontons/yr
  23. 23. Uniting agriculture and nature for poverty reduction Nitrogen loading growth rate by country
  24. 24. Uniting agriculture and nature for poverty reduction Phosphorus loading growth rate by country
  25. 25. Uniting agriculture and nature for poverty reduction Key messages The outlook is alarming—large additional N and P emissions from agriculture projected by 2050 What can be done ─ better fertilizer policy and knowledge of fertilizer use ─ land conservation ─ Manure management
  26. 26. Uniting agriculture and nature for poverty reduction Acknowledgement This study is supported by Veolia North America under the CGIAR Research Program on Water, Land and Ecosystems (WLE)

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