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Impact of water quality/quantity on agricultural policy

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International Food Policy Research Institute (IFPRI)
International Food Policy Research Institute (IFPRI)

Presented by IFPRI Senior Research Fellow Claudia Ringler at the International Workshop on Innovation in Modelling Coupled Natural and Human Systems Related to Water, Tübingen, May 31 & June 1, 2017.

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Claudia Ringler, IFPRI International Workshop on Innovation in Modelling Coupled Natural and Human Systems Related to Water Tübingen, May 31 & June 1, 2017 IMPACT OF WATER QUALITY/QUANTITY ON AGRICULTURAL POLICY www.ifpri.org/topic/water-policy
Uniting agriculture and nature for poverty reduction Growing water stress Source: Ringler et al. (2016) 36% 39% 22% 2.5 US$9.4 TRILLION Water stress risk BILLION PEOPLE TODAY Total population living in water scarce areas Global GDP generated in water scarce regions 52% 49% 45% US$63 TRILLION Total population living in water scarce areas 4.7 BILLION PEOPLE 90% 570% By 2050 Global GDP generated in water scarce regions population grain production global GDP
Uniting agriculture and nature for poverty reduction Growing demand for more water intensive calories (meats/fruits/ vegetables) surpasses demand for R&T and cereals (SSP2, NoCC) 2010=1.0 Source: IFPRI, IMPACT version 3.2, September 2015
Uniting agriculture and nature for poverty reduction Key Questions on the Agriculture-Water Interface 1. When and where is water the limiting constraint to food production and food security and what are policies to address this? 2. How can we improve crop per drop (WUE) without increasing water consumption? (broad view—from policies to technologies to breeding to post-harvest losses, etc.) 3. How does climate change (CC) affect water & agriculture and how does agriculture affect CC? (How does climate mitigation [f.ex. biofuels/avoided deforestation/CSA] and adaptation [f.ex. high-efficiency irrigation] affect water for food?)  Which irrigation technologies and systems are climate resilient/- ’proof’?  How much water do renewables use?
Uniting agriculture and nature for poverty reduction Maximum temperature (°C) Annual precipitation (mm) Climate change affects water for food The case of maize yields using HadGEM (RCP8.5), DSSAT, and IMPACT (SSP2) Change in rainfed maize yields before economic adjustments Change in rainfed maize yields after economic adjustments Source: IFPRI, IMPACT version 3.2, November 2015
Uniting agriculture and nature for poverty reduction Key Questions on the Agriculture-Water Interface 4. What is the impact of groundwater use and depletion on global and regional food security. What is the role of solar power in accelerating depletion and what are sustainable management mechanisms? 5. How can we stem rapidly growing agricultural water pollution? 6. Given growing natural resource scarcity what Food, Energy and Water Solutions can reduce natural resource use and increase efficiency?  Does hydropower production reduce water availability for irrigation?  How do regional power pools affect water for food?  What are energy needs of modern irrigation systems?
Uniting agriculture and nature for poverty reduction Key Modeling Tools at IFPRI for Water for Food Modeling 1) Partial agriculture equilibrium model linked with global CGE model, global gridded crop modeling system and water supply and demand projections model (water supply/demand, food supply and demand) (global and regional) 2) Some form of HEM (f.ex. ABM-SWAT combination or GAMS- based optimization) (basin level) 3) SWAT hydrological model (irrigation potential assessment, water pollution, ecosystem services, sedimentation and HP productivity) (watershed to global level) 4) CGE model linked to energy and water models (national level) (national to global levels)
Uniting agriculture and nature for poverty reduction Global PE-CGE linked modeling framework Source: Ringler et al. 2016 IMPACT IMPACT Global Hydrological Model IMPACT Water Simulation Model DSSAT Crop Models GCM Climate Forcing Effective P Potential ET IRW Irrigation Water Demand & Supply Crop Management WATER STRESS Pop & GDP growth Area & yield growth Food Projections • Crop area / livestock numbers, yields, and production • Agricultural commodity demand • Agricultural commodity trade and prices • Hunger and Mal- nourishment Water Projections • Water demand and supply for domestic, industrial, livestock and irrigation users • Water supply reliability GLOBE CGE model Change in GDP, cost of agrochemicals and biofuel mix Food models Water models Energy price shocks
Uniting agriculture and nature for poverty reduction ABM-SWAT basin model for ecosystem/services modeling
Uniting agriculture and nature for poverty reduction Global Agricultural Water Pollution Assessment: Modeling Framework IMPACT IGWQM (SWAT) National statistics Pixel estimates Nitrogen & phosphorus in fertilizer & livestock excreta to agricultural land FAOSTAT (base year data) Crop area/yield Livestock population Projections for scenario analysis Downscaling Metrics: Nitrogen and phosphorus loadings from global agricultural production system
Uniting agriculture and nature for poverty reduction Estimated nutrient loading intensity, agriculture, base period (Nitrogen, kg/km2): 46 mt/yr Source: Xie and Ringler (under review). Brazil/India/China account for 3/4
Uniting agriculture and nature for poverty reduction Estimated nutrient loading intensity, base period (Phosphorous, kg/km2): 2.7 mt/yr Source: Xie and Ringler (under review). Brazil/India/China account for 72%
Uniting agriculture and nature for poverty reduction 68mt 74mt Growth in N loadings, projected 2000-2050 Source: Xie and Ringler (under review). Growth in P loadings, projected 2000-2050
Uniting agriculture and nature for poverty reduction Source: Flachsbarth et al. 2015. Changes in nitrogen-emission rates in Latin America and the Caribbean between the base year 2000 and 2050 (in%). Opportunities for agricultural nutrient pollution reduction
Uniting agriculture and nature for poverty reduction IMPACT Groundwater Module GW pumping from “GW reservoir“ in the Global Hydrological Model Two sources to pump GW: conceptual shallow & deep aquifers Procedures of GW pumping simulation in the integrated model: 1. Run the global water resource model IWSM and extract projected GW pumping by FPU 2. Downscale FPU-level GW pumping to 0.5 degree grid cells 3. Run the global hydrological model by applying gridded GW pumping demand to GW reservoir balance in the IGHM. Pumping from deep aquifer is trigged only when shallow aquifer storage is depleted. 4. Aggregate the sum of pumping from shallow and deep aquifers at grid cell level to FPUs. 5. Re-run the IWSM water resource model using updated GW pumping.
Uniting agriculture and nature for poverty reduction Simulated groundwater depletion in the base year, 2005
Uniting agriculture and nature for poverty reduction Simulated groundwater depletion, maize, 2050
Uniting agriculture and nature for poverty reduction References  Al-Riffai, P., C. Breisinger, A. Mondal. C. Ringler, M. Wiebelt and T. Zhu. 2017. Linking the economics of water, energy, and food: A nexus modeling approach. An ESSP Working Paper. Washington DC: IFPRI. http://ebrary.ifpri.org/cdm/singleitem/collection/p15738coll2/id/131154  Flachsbarth, I., B. Willaarts, H. Xie, G. Pitois, N.D. Mueller, C. Ringler and A. Garrido. 2015. The Role of Latin America’s Land and Water Resources for Global Food Security: Environmental Trade-Offs of Future Food Production Pathways. PLOS ONE. DOI:10.1371/journal.pone.0116733.  IFPRI and Veolia. 2015. The murky future of global water quality. New global study projects rapid deterioration in water quality. https://www.ifpri.org/publication/murky-future-global-water-quality-new- global-study-projects-rapid-deterioration-water  Ringler, C., D. Willenbockel, N. Perez, M. Rosegrant, T. Zhu and N. Matthews. 2016. Global linkages among energy, food and water: an economic assessment. Journal of Environmental Studies and Sciences: 6(1): 161-171. DOI 10.1007/s13412-016-0386-5  Ringler, C., T. Zhu, S. Gruber, R. Treguer, L. Auguste, L. Addams, N. Cenacchi and T.B. Sulser. 2016. “Role of water security for agricultural and economic development – concepts and global scenarios,” in C. Pahl-Wostl, J. Gupta and A. Bhaduri (eds) Handbook on water security. (Aldershot, Edward Elgar Publishing Ltd).  Yang, Y-C. Ethan, C. Ringler, C. Brown, A. Mondal. 2016. Modeling the Agricultural Water-Energy-Food Nexus in the Indus River Basin of Pakistan. Journal of Water Resources Planning and Management 142(12) 04016062. http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000710  Zeng, R., X. Cai, C. Ringler and T. Zhu. 2017. Hydropower versus Irrigation – An Analysis of Global Patterns. 2017. Environmental Research Letters 12 (2017) 034006 https://doi.org/10.1088/1748- 9326/aa5f3f.

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Impact of water quality/quantity on agricultural policy

  • 1. Claudia Ringler, IFPRI International Workshop on Innovation in Modelling Coupled Natural and Human Systems Related to Water Tübingen, May 31 & June 1, 2017 IMPACT OF WATER QUALITY/QUANTITY ON AGRICULTURAL POLICY www.ifpri.org/topic/water-policy
  • 2. Uniting agriculture and nature for poverty reduction Growing water stress Source: Ringler et al. (2016) 36% 39% 22% 2.5 US$9.4 TRILLION Water stress risk BILLION PEOPLE TODAY Total population living in water scarce areas Global GDP generated in water scarce regions 52% 49% 45% US$63 TRILLION Total population living in water scarce areas 4.7 BILLION PEOPLE 90% 570% By 2050 Global GDP generated in water scarce regions population grain production global GDP
  • 3. Uniting agriculture and nature for poverty reduction Growing demand for more water intensive calories (meats/fruits/ vegetables) surpasses demand for R&T and cereals (SSP2, NoCC) 2010=1.0 Source: IFPRI, IMPACT version 3.2, September 2015
  • 4. Uniting agriculture and nature for poverty reduction Key Questions on the Agriculture-Water Interface 1. When and where is water the limiting constraint to food production and food security and what are policies to address this? 2. How can we improve crop per drop (WUE) without increasing water consumption? (broad view—from policies to technologies to breeding to post-harvest losses, etc.) 3. How does climate change (CC) affect water & agriculture and how does agriculture affect CC? (How does climate mitigation [f.ex. biofuels/avoided deforestation/CSA] and adaptation [f.ex. high-efficiency irrigation] affect water for food?)  Which irrigation technologies and systems are climate resilient/- ’proof’?  How much water do renewables use?
  • 5. Uniting agriculture and nature for poverty reduction Maximum temperature (°C) Annual precipitation (mm) Climate change affects water for food The case of maize yields using HadGEM (RCP8.5), DSSAT, and IMPACT (SSP2) Change in rainfed maize yields before economic adjustments Change in rainfed maize yields after economic adjustments Source: IFPRI, IMPACT version 3.2, November 2015
  • 6. Uniting agriculture and nature for poverty reduction Key Questions on the Agriculture-Water Interface 4. What is the impact of groundwater use and depletion on global and regional food security. What is the role of solar power in accelerating depletion and what are sustainable management mechanisms? 5. How can we stem rapidly growing agricultural water pollution? 6. Given growing natural resource scarcity what Food, Energy and Water Solutions can reduce natural resource use and increase efficiency?  Does hydropower production reduce water availability for irrigation?  How do regional power pools affect water for food?  What are energy needs of modern irrigation systems?
  • 7. Uniting agriculture and nature for poverty reduction Key Modeling Tools at IFPRI for Water for Food Modeling 1) Partial agriculture equilibrium model linked with global CGE model, global gridded crop modeling system and water supply and demand projections model (water supply/demand, food supply and demand) (global and regional) 2) Some form of HEM (f.ex. ABM-SWAT combination or GAMS- based optimization) (basin level) 3) SWAT hydrological model (irrigation potential assessment, water pollution, ecosystem services, sedimentation and HP productivity) (watershed to global level) 4) CGE model linked to energy and water models (national level) (national to global levels)
  • 8. Uniting agriculture and nature for poverty reduction Global PE-CGE linked modeling framework Source: Ringler et al. 2016 IMPACT IMPACT Global Hydrological Model IMPACT Water Simulation Model DSSAT Crop Models GCM Climate Forcing Effective P Potential ET IRW Irrigation Water Demand & Supply Crop Management WATER STRESS Pop & GDP growth Area & yield growth Food Projections • Crop area / livestock numbers, yields, and production • Agricultural commodity demand • Agricultural commodity trade and prices • Hunger and Mal- nourishment Water Projections • Water demand and supply for domestic, industrial, livestock and irrigation users • Water supply reliability GLOBE CGE model Change in GDP, cost of agrochemicals and biofuel mix Food models Water models Energy price shocks
  • 9. Uniting agriculture and nature for poverty reduction ABM-SWAT basin model for ecosystem/services modeling
  • 10. Uniting agriculture and nature for poverty reduction Global Agricultural Water Pollution Assessment: Modeling Framework IMPACT IGWQM (SWAT) National statistics Pixel estimates Nitrogen & phosphorus in fertilizer & livestock excreta to agricultural land FAOSTAT (base year data) Crop area/yield Livestock population Projections for scenario analysis Downscaling Metrics: Nitrogen and phosphorus loadings from global agricultural production system
  • 11. Uniting agriculture and nature for poverty reduction Estimated nutrient loading intensity, agriculture, base period (Nitrogen, kg/km2): 46 mt/yr Source: Xie and Ringler (under review). Brazil/India/China account for 3/4
  • 12. Uniting agriculture and nature for poverty reduction Estimated nutrient loading intensity, base period (Phosphorous, kg/km2): 2.7 mt/yr Source: Xie and Ringler (under review). Brazil/India/China account for 72%
  • 13. Uniting agriculture and nature for poverty reduction 68mt 74mt Growth in N loadings, projected 2000-2050 Source: Xie and Ringler (under review). Growth in P loadings, projected 2000-2050
  • 14. Uniting agriculture and nature for poverty reduction Source: Flachsbarth et al. 2015. Changes in nitrogen-emission rates in Latin America and the Caribbean between the base year 2000 and 2050 (in%). Opportunities for agricultural nutrient pollution reduction
  • 15. Uniting agriculture and nature for poverty reduction IMPACT Groundwater Module GW pumping from “GW reservoir“ in the Global Hydrological Model Two sources to pump GW: conceptual shallow & deep aquifers Procedures of GW pumping simulation in the integrated model: 1. Run the global water resource model IWSM and extract projected GW pumping by FPU 2. Downscale FPU-level GW pumping to 0.5 degree grid cells 3. Run the global hydrological model by applying gridded GW pumping demand to GW reservoir balance in the IGHM. Pumping from deep aquifer is trigged only when shallow aquifer storage is depleted. 4. Aggregate the sum of pumping from shallow and deep aquifers at grid cell level to FPUs. 5. Re-run the IWSM water resource model using updated GW pumping.
  • 16. Uniting agriculture and nature for poverty reduction Simulated groundwater depletion in the base year, 2005
  • 17. Uniting agriculture and nature for poverty reduction Simulated groundwater depletion, maize, 2050
  • 18. Uniting agriculture and nature for poverty reduction References  Al-Riffai, P., C. Breisinger, A. Mondal. C. Ringler, M. Wiebelt and T. Zhu. 2017. Linking the economics of water, energy, and food: A nexus modeling approach. An ESSP Working Paper. Washington DC: IFPRI. http://ebrary.ifpri.org/cdm/singleitem/collection/p15738coll2/id/131154  Flachsbarth, I., B. Willaarts, H. Xie, G. Pitois, N.D. Mueller, C. Ringler and A. Garrido. 2015. The Role of Latin America’s Land and Water Resources for Global Food Security: Environmental Trade-Offs of Future Food Production Pathways. PLOS ONE. DOI:10.1371/journal.pone.0116733.  IFPRI and Veolia. 2015. The murky future of global water quality. New global study projects rapid deterioration in water quality. https://www.ifpri.org/publication/murky-future-global-water-quality-new- global-study-projects-rapid-deterioration-water  Ringler, C., D. Willenbockel, N. Perez, M. Rosegrant, T. Zhu and N. Matthews. 2016. Global linkages among energy, food and water: an economic assessment. Journal of Environmental Studies and Sciences: 6(1): 161-171. DOI 10.1007/s13412-016-0386-5  Ringler, C., T. Zhu, S. Gruber, R. Treguer, L. Auguste, L. Addams, N. Cenacchi and T.B. Sulser. 2016. “Role of water security for agricultural and economic development – concepts and global scenarios,” in C. Pahl-Wostl, J. Gupta and A. Bhaduri (eds) Handbook on water security. (Aldershot, Edward Elgar Publishing Ltd).  Yang, Y-C. Ethan, C. Ringler, C. Brown, A. Mondal. 2016. Modeling the Agricultural Water-Energy-Food Nexus in the Indus River Basin of Pakistan. Journal of Water Resources Planning and Management 142(12) 04016062. http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000710  Zeng, R., X. Cai, C. Ringler and T. Zhu. 2017. Hydropower versus Irrigation – An Analysis of Global Patterns. 2017. Environmental Research Letters 12 (2017) 034006 https://doi.org/10.1088/1748- 9326/aa5f3f.