Contextualizing Water Stress In Agricultural Regions Globally

Transcription

1 Contextualizing Water Stress In Agricultural Regions Globally Marty D. Matlock, PhD, PE, CSE Area Director, Center for Agricultural and Rural Sustainability Professor, Biological and Agricultural Engineering 233 Engineering Hall University of Arkansas Fayetteville, AR (office) (cell) April 14, 2010

2 Metrics and Indices Metrics are things we measure. Indices are metrics standardized to something we value. Water scarcity is a physical process that has many facets. Each facet can be measured. Aggregating those measurements creates indices of water scarcity. Think of them as Attributional vs Consequential LCAs

3 Which Indices Are Best? Indices are normative they reflect values Indices are metrics standardized to something we value. Water has so many value facets: Human right sustenance Ecosystem service refugia and provisioning Commodity to support economic sectors Agriculture Industry Urban/Residential/Municipal

4 Falkenmark 1989 Proposed that the most common indicator of water scarcity is the ratio of the annual water withdrawal in a certain area to the total annual runoff in that area. A value of 1700m 3 per capita per year is widely accepted as a threshold below which varying degrees of water stress are likely to occur. Water barrier differentiation proposed by Falkenmark (1989) Index Category/Condition (m 3 per capita) >1,700 No Stress 1,000-1,700 Stress 500-1,000 Scarcity <500 Absolute Scarcity

5 42nd AIFST Convention, Brisbane 2009 WSI and WF (Ridoutt and Pfister) Inventory Blue water consumption Gray water requirement Volumetric impact on freshwater availability Impact of land use on blue water resources

6 42nd AIFST Convention, Brisbane 2009 WSI and WF (Ridoutt and Pfister) Inventory Water footprint Blue water consumption Regional water stress characterisation factors (-) Gray water requirement Volumetric impact on freshwater availability Stress-weighted water footprint Impact of land use on blue water resources

7 42nd AIFST Convention, Brisbane 2009 WSI and WF (Ridoutt and Pfister) Inventory Water footprint Communication Blue water consumption Regional water stress characterisation factors (-) WSI relevant to audience (-) Gray water requirement Volumetric impact on freshwater availability Stress-weighted water footprint Equivalent water footprint Impact of land use on blue water resources

8 Inputs to the impact pathway: (a) relation between WSI and WTA* (blue line, logistic function), (b) DALYmalnutrition,rate for each country (blue stars) and HDF modeled (red line, R2 = 0.71) based on HDI, (c) DALYmalnutrition,rate for each country (blue stars) against corresponding MN% and linear regression (red line, R2 = 0.26). Published in: Stephan Pfister; Annette Koehler; Stefanie Hellweg; Environ. Sci. Technol. 2009, 43, DOI: /es802423e Copyright 2009 American Chemical Society

9 Characterization and damage factors on the watershed level per m3 water consumed: (a) Water stress index, (b) damage on resources, (c) damage on ecosystem quality, (d) damage on human health, and (e) aggregated Eco-indicator-99 damage factor. Map (f) shows the aggregated Eco-indicator-99 damage per kg cotton textile on the country level. Published in: Stephan Pfister; Annette Koehler; Stefanie Hellweg; Environ. Sci. Technol. 2009, 43, DOI: /es802423e Copyright 2009 American Chemical Society

10 Global Water Budget for Corn Funded by Monsanto Company National Corn Growers Association

11 Major Questions Regarding Ag Water Use 1. What's the value of biotech that increases efficiency by 25%? 2. What's the value of irrigation innovation? 3. What impact will biofuel economies have on water resource demand? 4. How does that compare with ongoing changes in demand for corn (e.g. changed in meat demand)? 5. To what extent could change in agricultural trade policy reduce water pressures related to corn? 6. What impact will global climate change likely have on water resource availability? 7. Can hydrologically connected processes (surface water irrigation and runoff) be managed to enhance resource sustainability?

12 Corn Growth Model Analyses

13 Scales of Analysis: Global

14 Scales of Analysis: Regional

15 Input Parameter: Temperature

16 Input Parameter: Temperature

17 Input Parameter: Soil Unit

18 Input Parameter: Soil Unit

19 Calibration Parameters 1. Genetic Coefficients 2. Filling Period 3. Nitrogen Balance 4. Nitrogen Remobilization 5. Root Zone Soil Moisture Content 6. Soil Water Upper and Lower Limits 7. Root Hospitality 8. Soil Root Growth Factor 9. Hardpan (Soil Impedence Factor) 10. Leaf Area Index 11. Grain Yield 12. Date of Emergence

20 Calibration Strategy Calibrate using a spatial subset of regional data. Validate at the regional level. Analyze for major zones at multiple scales Country Major Basin WWF Ecoregion

21 Calibration Data 2000 Corn Yield

22 Calibration Challenges Resolution of Yield

23 Agricultural WSI Challenges Lack of regional data at high spatial resolution Lack of regional data at high temporal resolution Lack of integrative models of outcomes of concern