1. Impact of biofuel production on hydrology: A case study of Khlong Phlo Watershed in Thailand BIKESH SHRESTHA ID108202(WEM/SET) Committee Members: Dr. Mukand S. Babel (Chairperson) Dr. Sylvain R. Perret (Co-chairperson) Dr. S. L. Ranamukhaarachchi Dr. Shahriar Md. Wahid

2. Presentation Outline  Introduction  Study area  Methodology  Results and Discussion  Conclusions & Recommendations 2

3. Rationale 3  Biofuel “as an alternative to fossil fuel”  57 billion L to reach151 billion L in 2017  Thailand: 5 billion L by 2022  Land use change for biofuel production  Water quantity and quality impacts  Impacts on the water resources and hydrology not fully understood  Very few studies BeforeAfter

4. 4 Objectives Analyze the impact of biofuel production on the water resource and hydrology of the Khlong Phlo watershed Specific objectives: 1.Estimate water footprints of biofuel and biofuel energy 2.Evaluate impact on annual and seasonal water balance 3.Quantify impact on water quality

5. 5 Scope  Review of global and Thailand’s biofuel status and plan  Collection of secondary data  Estimation of green, blue and grey water footprint  Calibration and validation of SWAT model  Simulation of SWAT model for several scenarios

6. 6 Study Area Location:  Khlong Prasae  Rayong  12 0 57’-13 0 10’N  101 0 35’-101 0 45’E Area :202.8 km 2 Rainfall :1,734 mm Temperature:27 to 31 0 Humidity :69 to 83% Elevation :13 to 723 msl Land use :Agri. (66%) Forest (33%) Soils :S – Cl - L S – L

7. 7 Water footprint: Methodology Climatic Parameters Crop Coefficient Effective Rainfall Reference crop ET Crop ET Green WF CP Irrigation required Pollutant emission Agreed water quality Step 1: Water footprint of crops (WF CP ) Blue WF CP Grey WF CP Biofuel conversion rate Green WF CP Blue WF CP Grey WF B Grey WF CP Step 2: Water footprint of biofuel (WF B ) Green WF B Blue WF B Energy of biofuel Green WF B Blue WF B Grey WF BE Grey WF B Step 3: Water footprint of biofuel energy (WF BE ) Green WF BE Blue WF BE

8. Formulae used for Water footprint (WF)  Green WF= min (Evapotranspiration, Effective Rain)  Blue WF= Irrigation requirement  Grey WF= max (Pollutant released/Permissible limit)  WF CP = Water use for crop production / crop yield  WF B = WF CP / biofuel conversion rate  WF BE = WF B / energy per liter biofuel  Energy /L biofuel= HHV X density 8

9. 9 Impact on water balance and water quality: Methodology (SWAT), Pre-processing Phase DEM Drainage SoilLand use Sub-watersheds Hydrological Response Units

10. 10 Impact on water balance and water quality: Methodology (SWAT), Processing Phase Meteorological data Model calibration and validation Scenarios Simulation Land use change scenarios Evaluation  Water balance  Water quality Hydrological Response Units Management data Model Evaluation

11. 11 Data Collected DataFrequencyPeriodSource RainfallDaily1984-2006RID/TMD TemperatureDaily1984-2006TMD Wind speedDaily1984-2006TMD Relative HumidityDaily1984-2006TMD Sunshine durationDaily1984-2006TMD DischargeDaily1984-2006RID Sediment loadDaily1997-2005RID DataTypeSource DEM30 m resolutionhttp://www.gdem.aster. or.jp Land use map1:25,000 mLDD Soil map1:100,000 mLDD Drainage mapRID DataSource Soil propertiesLDD, www.iiasa.ac.at Fertilizer useDOA, www.fao.org/ag/agl/fertistat/fst.fubc.en.asap Cropping patternFarmers, DOA of Thailand Meterological data: Spatial data: Additional data:

12. 12 Land use (2006) Code Land Use Area Percent km 2 3Rice1.820.90 8Cashew Nut4.842.39 9Cassava9.884.87 21Evergreen Forest66.3632.73 27Deciduous Forest0.050.03 41Institutional Land0.510.25 43Water bodies0.890.44 47Residential0.280.14 57Wet Land0.01 64Orchard27.9613.79 67Oil Palm1.120.55 70Rubber85.1241.98 82Range grass1.830.90 89Sugarcane2.111.04 Total 202.80100.00

13. 13 Land use change scenarios A. Oil Palm expansion (Biodiesel) Scenario A1 - Orchard to oil Palm - Oil palm <1 to 17% Scenario A2 - Rubber to oil Palm - Oil palm <1 to 43% Scenario A3 - Orchard + rubber to oil palm - Oil palm < 1 to 59% Scenario A4 - Forest to oil palm - Oil palm <1 to 33% B. Cassava expansion (Bio-ethanol) Scenario B1 - Orchard to cassava - Cassava 5 to 21% Scenario B2 - Rubber to cassava - Cassava 5 to 47% Scenario B3 - Orchard + rubber to cassava - Cassava 5 to 63% Scenario B4 - Forest to cassava - Cassava 5 to 38% C. Sugarcane expansion (Bio-ethanol) Scenario C1 - Orchard to sugarcane - Sugarcane 1 to 17% Scenario C2 - Rubber to sugarcane - Sugarcane 1 to 43% Scenario C3 - Orchard + rubber to sugarcane - Sugarcane 1 to 59% Scenario C4 - Forest to sugarcane - Sugarcane 1 to 34%

14. Results and Discussion

15. 15 Water footprint of crops (WF CP ) Oil Palm CassavaSugarcane 775 m 3 /t 420 m 3 /t 85 m 3 /t 306 m 3 /t 106 m 3 /t 42 m 3 /t 142 m 3 /t 80 m 3 /t 12 m 3 /t  Sugarcane has low water footprint due to higher yield  WF CP sensitive to yield

16. 16 Water footprint of biofuel (WF B )  5800 L for oil palm = 1 L of biodiesel  2500 L for cassava and 3400L for sugarcane = 1 L of bio-ethanol  Grey water contributes 5-17% for cassava, 3-9% for sugarcane and 3-12% for oil palm

17. 17 Water footprint of biofuel energy (WF BE )  177, 103 & 140 m 3 for oil palm, cassava & sugarcane(5% scenario)  200, 120 & 150 m 3 for oil palm, cassava & sugarcane (20% scenario)

18. 18 Water footprint of biofuel energy (WF BE ) Gerbens Leenes et al. (2008) Crop Green WF BE Blue WF BE Green WF BE Blue WF BE m 3 / GJ of Energy m 3 / GJ of Energy m 3 / GJ of Energy m 3 / GJ of Energy Cassava 7225798 Sugarcane 87496455 WF BE comparison with a study by Gerbens-Leenes et al. (2008).  Sugar 13% and cassava 10% less  Difference in crop water requirement (CWR) and yield  CWR sensitive to climatic data and starting of growing period  Nakhon Ratchasima for sugarcane and Chaing Mai for cassava  Yield 3 production years (2006-2008)(OAE) vs 5 production years (1997-2001)(FAO)  WF of biofuel sensitive to location

19. 19 Irrigation required due to land use change 116 MCM Present land use Land use change scenario Irrigation Required (MCM) Oil palm60 Sugarcane58 Cassava29 Change in irrigation withdrawals under 58.2% land cover replacement scenario Total water yield

20. 20 Change in nitrogen application rate and pollutant loading to Surface water due to land use change N= 57 kg/ha 6 kg/ha Application rate Pollutant loading Present land use LUCS Increase in Nitrogen application rate (%) Oil palm85 Cassava76 Sugarcane36 Under 58.2% land cover replacement scenario

21. 21 Total average annual water yield (Baseline) Root Zone Shallow (unconfined) Aquifer Vadose (unsaturated) Zone Confining Layer Deep (confined) Aquifer Precipitation Evaporation and Transpiration Infiltration/plant uptake/ Soil moisture redistribution Surface Runoff Lateral Flow Return Flow Revap from shallow aquifer Percolation to shallow aquifer Recharge to deep aquifer Flow out of watershed 207 mm 1734 mm 102 mm 289 mm 836 mm TWY = 597mm (S) vs 574mm (Ob) 48% 34% 18% Copyright: Dr. Jeff Arnold, USDA-ARS, Blacklands, Texas

22. 22 Monthly Flow calibration and validation Calibration Validation Mean and SD 0.5, R 2 >0.6

23. 23 Sediment yield calibration and validation Total average annual sediment yield:  Modeled with error 5.13% [0.60 t/ha (Sim) vs 0.57 t/ha (Obs)] Monthly sediment yield: CalibrationValidation Calibration: Mean and SD 0.5, R 2 >0.6 Validation: Mean > 10% and SD < 10%, NS< 0.5, R 2 <0.6

24. 24 Effect of land use change on annual water balance Differences in annual water balance from land use change scenarios to baseline: Oil palm Differences in annual water balance from land use change scenarios to baseline: Cassava Differences in annual water balance from land use change scenarios to baseline: Sugarcane  Oil palm o forest removal increase runoff  Cassava and sugarcane o effect all components  Cassava o runoff high  Sugarcane o base flow high

25. 25 Effect of land use change on monthly water yield Differences in monthly water yield from land use change scenarios to baseline: Max land use Differences in monthly water yield from land use change scenarios to baseline: Rubber replace Differences in monthly water yield from land use change scenarios to baseline: Forest replace  Max land use: less water o Oil palm during Jan - Oct o Cassava in Dec o Sugarcane over Nov – Dec  Forest replace: water yield o Oil palm for seven months (J, M - Jul and S) o Cassava and Sugarcane for all except Nov - Dec

26. 26 Effect of land use change on water quality Differences in NPS pollutants from land use change scenarios to baseline: Oil palm Differences in NPS pollutants from land use change scenarios to baseline: Cassava Differences in NPS pollutants from land use change scenarios to baseline: Sugarcane  Replace forest o increases pollutant loading  Cassava o high soil loss, nitrate, total phosphorus

27. Conclusions and Recommendations

28. 28 Conclusions  Cassava, the most water efficient crop to produce biofuel  Bio-ethanol production will affect the water balance  Biodiesel no impact on water balance o Forest conversion will affect the water balance  Bio-ethanol production will have impact on water quality  Biodiesel production will also effect the water quality due to increased nitrate loading o Conversion of orchard showed less water quality impact  Biofuel production will have negative impact on the environment

29. 29 Recommendations  Cassava to be promoted in water scarce areas but the environmental impacts must be considered  Supports the policy to promote biodiesel replacing orchard  Conversion of rubber no impact on water balance but will affect water quality For Government of Thailand: For further study:  A research at a large scale at basin level  Study effective BMPs  Climate change and land use change for biofuel production

30. THANK YOU