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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
APPLICATION OF THE SWAT MODEL TO INVESTIGATE NITRATE LEACHING IN - - PowerPoint PPT Presentation
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
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HEN MANURE
About 90% of main crop production (wheat and potato) is located in the vicinity of drinking water wells.
Introduction
Objective Materials & Methods Conclusion Results
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Introduction
Objective Materials & Methods Conclusion Results The Hamadan-Bahar Plain is a region where nonpoint source nitrate loading has significantly impacted groundwater nitrate concentrations. 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
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Introduction
Objective Materials & Methods Conclusion Results 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
- ptimized to simulate nitrate.
W R W R W R W R W R W R W R
C C I I T T S S A A R R D D + + + + + + = Index DRASTIC
Conditioning DRASTIC Model to Simulate Nitrate Pollution in Hamadan-Bahar Plain, Submitted paper.
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- 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
- To determine vulnerability of aquifers to nitrate pollution in
Hamadan-Bahar plain with DRASTIC model
Introduction Objective Materials & Methods Conclusion Results
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Hamadan- Bahar watershed 2459 Km2 Hamadan- Bahar plain 520 Km2 Mountainous area 1579 Km2 Outlet of watershed Koshkabad Average annual rainfall 324.5 mm Average annual temperature 11.3 0C
Site information
Outlet of watershed Koshkabad Alvand Mountains
Introduction Objective
Materials & Methods
Conclusion Result Introduction Objective
Materials & Methods
Conclusion Results
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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
Introduction Objective
Materials & Methods
Conclusion Result Introduction Objective
Materials & Methods
Conclusion Results
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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].
SUFI-2 (Sequential Uncertainty Fitting, ver. 2) procedure
http://www.eawag.ch/organisation/abteilungen/siam/software/swat/index_EN
Faramarzi et al., 2009 Abbaspour et al., 2007 Schuol et al., 2008 Yang et al., 2008
Large-Scale: Small-Scale:
Rostamian et al., 2008 Introduction Objective
Materials & Methods
Conclusion Result Introduction Objective
Materials & Methods
Conclusion Results
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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).
20 40 60 80 100 120 140 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69
Introduction Objective
Materials & Methods
Conclusion Result Introduction Objective
Materials & Methods
Conclusion Results
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> ≤ = Φ
−
1 1
2 1 2
b if R b b if R b
( )
∑
=
− =
n i i sim
- bs
Y Y n MSE
1 2 2
1 σ Objective function for discharge and nitrate: Objective function for crop yield:
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.
Introduction Objective
Materials & Methods
Conclusion Result Introduction Objective
Materials & Methods
Conclusion Results
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P-factor=0.24 R-factor=0.93 P-factor=0.40 R-factor=0.84
Koshkabad 5 10 15 20 25 30 35 40 45 Sep 00 Sep 01 Sep 02 Sep 03 Sep 04 Sep 05 Sep 06 Sep 07 Sep 08 River discharge (m
3 s-1)
Koshkabad 5 10 15 20 25 30 35 40 45 Jan 92 Jan 93 Jan 94 Jan 95 Jan 96 Jan 97 Jan 98 Jan 99 River discharge (m 3 s-1)
Introduction Objective Materials & Methods Conclusion
Results
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Artificial recharge Small dams
Region‘s Management Map Introduction Objective Materials & Methods Conclusion
Results
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Abbasabad 1 2 3 4 5 6 Jan 00 Jan 01 Jan 02 Jan 03 Jan 04 Jan 05 Jan 06 Jan 07 Jan 08 River discharge (m 3 s-1)
P-factor=0.18 R-factor=0.41
Abbasabad 1 2 3 4 5 6 7 Jan 00 Jan 01 Jan 02 Jan 03 Jan 04 Jan 05 Jan 06 Jan 07 Jan 08 River discharge (m
3 s-1)
Spring Effect
P-factor=0.43 R-factor=0.4
Introduction Objective Materials & Methods Conclusion
Results
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P-factor=0.88 R-factor=3.29
10 20 30 40 50 60 2000 2001 2002 2003 2005 2006 2007 2008 Year Potato Yield (ton ha-1)
10 20 30 40 potato Potato Yield (ton ha-1)
Potato Yield
Long-term average for validation
Introduction Objective Materials & Methods Conclusion
Results
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5000 10000 15000 20000 25000 30000 2007.12 2008.01 2008.02 2008.03 2008.04
Date
Nitrate (kg/ha)
P-factor=1 R-factor=7.75 Modified R-factor=1.98
Nitrate Calibration
Introduction Objective Materials & Methods Conclusion
Results
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DRASTIC Vulnerability map SWAT Nitrate leaching map
Introduction Objective Materials & Methods Conclusion
Results
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Introduction Objective Materials & Methods
Conclusion
Results
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.
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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.
Introduction Objective Materials & Methods
Conclusion
Results
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
Using crop yield in the calibration process increases model
reliability
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