APPLICATION OF THE SWAT MODEL TO INVESTIGATE NITRATE LEACHING IN - PowerPoint PPT Presentation

APPLICATION OF THE SWAT MODEL TO INVESTIGATE NITRATE LEACHING IN THE HAMADAN-BAHAR WATERSHED, IRAN Samira Akhavan Isfahan University of Technology, Iran Akhavan_samira@yahoo.com August 2009

Materials & Introduction Objective Results Conclusion Methods

Materials & Introduction Objective Results Conclusion Methods About 90% of main crop production (wheat and potato) is located in the vicinity of drinking water wells. HEN MANURE

Materials & Introduction Objective Results Conclusion Methods Hydrologic models of nitrate leaching could help to determine the amount of nitrate loss from root zones and, therefore, the potential impact on nitrate concentration in groundwater The Hamadan-Bahar Plain is a region where nonpoint source nitrate loading has significantly impacted groundwater nitrate concentrations.

Materials & Introduction Objective Results Conclusion Methods Conditioning DRASTIC Model to Simulate Nitrate Pollution in Hamadan-Bahar Plain, Submitted paper. In this study, the DRASTIC model was used to construct groundwater vulnerability maps based on the “intrinsic” (natural conditions) and “specific” (including management) concepts. As DRASTIC has drawbacks to simulate specific contaminants, the rates were conditioned and the weights were optimized to simulate nitrate. = + + + + + + DRASTIC Index D D R R A A S S T T I I C C R W R W R W R W R W R W R W

Introduction Objective Materials & Results Conclusion Methods  To determine vulnerability of aquifers to nitrate pollution in Hamadan-Bahar plain with DRASTIC model  To calibrate and validate a SWAT model for Hamadan- Bahar watershed with uncertainty analysis accounting for crop yield (potato, irrigated wheat, rainfed wheat) and nitrate  To predict temporal and spatial variability of nitrate leaching dynamics for the present agricultural situation  To analyze scenarios to reduce nitrate leaching in the vulnerable areas

Materials & Materials & Introduction Objective Introduction Objective Results Result Conclusion Conclusion Methods Methods Site information Outlet of watershed Koshkabad  Hamadan- Bahar watershed 2459 Km 2  Hamadan- Bahar plain 520 Km 2  Mountainous area 1579 Km 2  Outlet of watershed Koshkabad  Average annual rainfall 324.5 mm  Average annual temperature 11.3 0 C Alvand Mountains

Materials & Materials & Introduction Objective Introduction Objective Results Result Conclusion Conclusion Methods Methods Fertilizer 2004-2005 2005-2006 2006-2007 Mean Hamadan Urea (kg ha -1 ) 791 905 301 666 Hen manure (ton ha -1 ) 28 21 24 24 Bahar Urea (kg ha -1 ) 390 482 393 422 Hen manure (ton ha -1 ) 9 15 10 11

Materials & Materials & Introduction Objective Introduction Objective Results Result Conclusion Conclusion Methods Methods SUFI-2 (Sequential Uncertainty Fitting, ver. 2) procedure Abbaspour, K. C. (2007) User Manual for SWAT-CUP, SWAT Calibration and Uncertainty Analysis Programs. Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland. [Last accessed June 2009]. http://www.eawag.ch/organisation/abteilungen/siam/software/swat/index_EN Large-Scale: Schuol et al., 2008 Yang et al., 2008 Faramarzi et al., 2009 Small-Scale: Abbaspour et al., 2007 Rostamian et al., 2008

Materials & Materials & Introduction Objective Introduction Objective Results Result Conclusion Conclusion Methods Methods P-factor , which is the percentage of measured data bracketed by the 95% prediction uncertainty (95PPU). R-factor , which is the average thickness of the 95PPU band divided by the standard deviation of the measured data SUFI-2 seeks to bracket most of the measured data (large P-factor, maximum 100%) with the smallest possible value of the R-factor (minimum 0). 140 120 100 80 60 40 20 0 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Materials & Materials & Introduction Objective Introduction Objective Results Result Conclusion Conclusion Methods Methods Objective function for discharge and nitrate:  ≤ 2 b R if b 1  Φ =  − 1 >  2 b R if b 1  Objective function for crop yield: n 1 ( ) ∑ = − 2 MSE Y Y σ obs sim i 2 n = i 1 The simulation period for calibration was 1997–2008; the first 3 years were used as warm-up period. The validation period was 1989–1999, also using 3 years as warm-up period.

Materials & Introduction Results Objective Conclusion Methods 45 3 s -1 ) Koshkabad 40 P-factor=0.24 R-factor=0.93 River discharge (m 35 30 25 20 15 10 5 0 Sep 00 Sep 01 Sep 02 Sep 03 Sep 04 Sep 05 Sep 06 Sep 07 Sep 08 45 River discharge (m 3 s -1 ) Koshkabad 40 35 30 P-factor=0.40 R-factor=0.84 25 20 15 10 5 0 Jan 92 Jan 93 Jan 94 Jan 95 Jan 96 Jan 97 Jan 98 Jan 99

Materials & Introduction Results Objective Conclusion Methods Region‘s Management Map Artificial recharge Small dams

Materials & Introduction Results Objective Conclusion Methods 6 River discharge (m 3 s -1 ) P-factor=0.18 R-factor=0.41 Abbasabad Spring Effect 5 4 3 2 1 0 Jan 00 Jan 01 Jan 02 Jan 03 Jan 04 Jan 05 Jan 06 Jan 07 Jan 08 7 Abbasabad 3 s -1 ) P-factor=0.43 R-factor=0.4 6 River discharge (m 5 4 3 2 1 0 Jan 00 Jan 01 Jan 02 Jan 03 Jan 04 Jan 05 Jan 06 Jan 07 Jan 08

Materials & Introduction Results Objective Conclusion Methods P-factor=0.88 R-factor=3.29 Potato Yield 60 Potato Yield (ton ha -1 ) 50 40 30 20 10 Long-term average for validation 0 2000 2001 2002 2003 2005 2006 2007 2008 40 Potato Yield (ton ha -1 ) 30 Year 20 10 0 potato

Materials & Introduction Results Objective Conclusion Methods Nitrate Calibration P-factor=1 R-factor=7.75 Modified R-factor=1.98 30000 25000 Nitrate (kg/ha) 20000 15000 10000 5000 0 2007.12 2008.01 2008.02 2008.03 2008.04 Date

Materials & Introduction Results Objective Conclusion Methods DRASTIC SWAT Vulnerability map Nitrate leaching map

Materials & Introduction Conclusion Objective Results Methods Two problems encountered with SWAT In irrigation subroutine 1. In the SWAT model, if the amount of water specified in an irrigation operation exceeds the amount needed to fill the soil layers up to field capacity water, the excess water is returned to the source, but in the study area, farmers usually apply more water than field capacity, so leaching due to irrigation is large. 2. When user select auto-irrigation based on soil water content, then irrigation continuous after harvest operation.

Materials & Introduction Conclusion Objective Results Methods  One of the difficulties and limitations within this study is lack of data on the amount of irrigation water that is removed from rivers and lack of sufficient discharge data for springs. These data help to predict the base flow.  Using crop yield in the calibration process increases model reliability  The model developed will be used to examine the spatial and temporal leaching of nitrate, and application of different scenarios to decrease groundwater nitrate problem

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