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

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. 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. 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. 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. 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. 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. Uniting agriculture and nature for poverty reduction
Input data-base period (2000-2005)

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. 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. 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. 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. 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. 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. Uniting agriculture and nature for poverty reduction
Input data-climate change
CSIRO change in precipitation

15. Uniting agriculture and nature for poverty reduction
Input data-climate change
CSIRO change in temperature

16. Uniting agriculture and nature for poverty reduction
Input data-climate change
MIROC change in precipitation

17. Uniting agriculture and nature for poverty reduction
Input data-climate change
MIROC change in temperature

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. Uniting agriculture and nature for poverty reduction
Nitrogen loading-base period
46 million tons/yr

20. Uniting agriculture and nature for poverty reduction
Phosphorus loading-base period
2.7 million tons/yr

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. 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. Uniting agriculture and nature for poverty reduction
Nitrogen loading growth rate by country

24. Uniting agriculture and nature for poverty reduction
Phosphorus loading growth rate by country

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. 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)