Hydrological Evaluation with SWAT Model and Numerical ...
Transcript of Hydrological Evaluation with SWAT Model and Numerical ...
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Kasetsart University
Winai WANGPIMOOL1
2012 International SWAT Conference & Workshops
Hydrological Evaluation with SWAT Model and Numerical Weather Prediction for Flash Flood Forecast System: a Case Study for Upper Nan Basin in Thailand.
New Delhi, India 20 July 2012
1 Ph.D. Student, Kasetsart University 2 Associate Professor, Ph.D., Kasetsart University 3 Associate Professor, Ph.D., Chiang Mai University 4 Thai Meteorological Department 5 Mekong River Commission
Kobkiat PONGPUT2 , Thanaporn SUPRIYASILP3
Kamol P.N. SAKOLNAKHON4 , Ornanong VONNARART5
Presented by:
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1. Introduction
2. Methodology 3. Model configuration &Results 4. Discussions & Recommendations 5. Conclusions
Contents
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Study area
Nan province
General Information
Catchment area 5,663 km2
River length 240 km
Average Temperature 25.6 degree Celsius
Annual rainfall 1,382 mm
Annual runoff 1,638 MCM
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Kasetsart University 1. ∆”¢À¥“¡€¬÷ºƒ“‡∏…ª ƒ÷‡»¥∂ç∫ ∫ ÌÈ‘ Topography: Long Profile
แม่น�ําน่านตอนบนที�มีความลาดชันสูง
Tung Chang Chiang Klang Muang Wiang Sa
1:480
1:3,500 1:5,300
1:3,000
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Problems
Nan City Mountainous area terrain with steep slope Rainfall and runoff stations are less because the access to the station area is difficult and high cost for maintenance
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Kasetsart University 2. ∆”¢À¥“øŸÈ∫∏◊˺å‘∂ç∫ ∫ ÌÈ‘
Chiang Klang, Pua and Bo Klure district area
Upstream
Problems
Sources: Department of Water Resources, 2011
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Kasetsart University Flooded on June 2011
Nan City
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Kasetsart University Flooded on June 2011
Nan City
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Kasetsart University Flash Flood on June 2006
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Objectives and Scope
1. Used Soil and Water Assessments Tool (SWAT) model for the hydrologic study to evaluate runoff occurring in the watershed system
2. Numerical Weather Prediction (NWP) weather data forecast for the next 3 days was used for stream flow estimation by SWAT model.
3. Stream flow estimation at outlets and can then be used for hydrodynamic models to create a flood map for flash flood warning system.
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Overall Methodology
•GIS Data
•Time Series Data
•Model Simulation Data
•Miscellaneous Data
Hydrological Model (SWAT)
Numerical Weather Prediction Model
(NWP)
Hydrodynamic Model
(HEC-RAS)
Extension (HEC-GeoRAS)
Flood risk map (ArcGIS)
Displays
(Google Earth)
Decision Maker
For Technical user
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Methodology SWAT Model
Results:
Stream flow were estimated at outlets in next 3 days
Forecasting Data by NWP in next 3 days
Weather (Precipitation, Temperature, Solar radiation, Humidity, Wind speed)
Validated NWP–SWAT
(Reanalysis NWP data Year 2006)
NWP Model
Calibrated /Validated
Y
N
Y
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1-Spatial Data 1.1-Administrative Data from DWR
Administrative boundaries River layouts Catchment's boundaries Drainage network Hydro-meteorological station
1.2-Physical Data from LDD Digital elevation model: 30m x30m Land use /Land cover map Soil classification map
Data Used
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2-Time Series Data 2.1-Weather Data
Maximum / Minimum Temperature Solar radiation Wind speed Relative humidity Evaporation
2.2-Hydrological Data
River flow 4 stations from RID and 2 sta. from DWR
Rainfall 11 stations ,From TMD
Only 1 station ,From TMD for
Data Used
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Global scale/synoptic scale
Regional scale Local scale
Downscaling technique for NWP
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Kasetsart University NWP Data from TMD.
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Kasetsart University DOMAIN2 2 km.(crop) - latitude 17.95 – 19.7 - Longitude 100.3 – 101.4
NWP provided: Rainfall, Temperature, Humidity, Solar radiation and Wind speed data.
NWP Data
Done by Hydrologist team from Thai Meteorological Department (TMD)
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Delineated Watershed into 28 Sub basins
SWAT Model Set up
Simulation Periods: 1. Calibration: 1993 – 2008(16 years) 2. Validation: 2009 (1 year)
6 Calibration Points
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Sensitivity Analysis
1. Surlag 2. SOL_AWC 3. CN2 4. ESCO 5. SOL_Z 6. CH_K2 7. SOL_K 8. CANX 9. ALPHA_BF 10. CH_N
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Kasetsart University Calibration Results
No. Station Name of Station CA. Calibration Sub-basin R2
Volume Ratio Peak Discharge - cms
Code (sq.km.) Period (%) Observe Simulate Sim / Obs (%)
Main river
1. N.1 Muang, Nan. 4,609.0 1994-2007 S_17 0.89 108.95 2,636 2,327 88.29
3. N.64 Ban Pa Khuang 3,440.1 1994-2004 S_12 0.90 110.27 2,281 1,889 82.81
Tributaries
1. N.49 Nam Yao @ Pua 155.0 1994-2004 S_13 0.22 100.47 352 295 83.78
2. N.65 Nam Yao @ Pang Sa 611.8 1997-2002, 2004-2007 S_11 0.87 113.21 442 385 87.08
3. 090201 Nam Pua @ Ban Na Phang 146.7 1994 - 2007 S_7 0.45 99.47 461 284 61.50
4. 090203 Nam Korn @ Ban Pa Dang 176.0 1994-2006 S_5 0.51 99.83 124 125 100.89
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Kasetsart University Nam Korn at d090203 station (Sub-05)
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Kasetsart University Nam Pua at Staion d090201 , Sub-07
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Kasetsart University Nam Yao at N65 station (Sub 10-11)
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Nan river at N64 station , Sub-12
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Nan river at N1 station , Sub-17
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Kasetsart University NWP Application
Using NWP data generated from 2000-2010 to replace on historical data
Before used NWP data in the next 3 days: Checked and Improved by bias correlation technique
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Kasetsart University NWP Results
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Kasetsart University NWP Results
Main River: higher 10-20% Tributary: lower 10-20%
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The result of runoff study with SWAT model in the Upper basin showed that Average annual runoff = 1,638.5 MCM
The average runoff occurred during the rainy season (June-November) was about 1,421 million cubic meters (87% of the average annual runoff) and in the dry season about 217.5 million cubic meters (13 % of the average annual runoff)
SWAT Model Results
Use for inflow boundary of flood study
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Kasetsart University Example results : Flood Risk Map
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Display with GE
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Kasetsart University Discussions
0.00
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Observed
NWP
Historical
NWP provided higher peak than the others. However, considering the shape of hydrograph after the peak, the simulated discharges from NWP decreased faster than the others
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Kasetsart University Recommendations
1. NWP provided weather data in grid format same as DEM, Land use and Soil class. It’s better if we can input weather data directly into SWAT model.
2. For flood season, Necessary to monitor and used hourly data. It should be simulated by use hourly data.
3. In future work, We will develop and improve the system to automatic simulation and display results.
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● SWAT can be done to generated stream flow as well.
● NWP climate data were compatible with the measured data except rainfall data needed to be adjusted by bias correlation before being applied in the SWAT model.
● All data from the NWP can be used with the SWAT model and they were provided a good results.
● NWP data is very useful for hydrologic study in case of lack the weather data from observed station.
● The SWAT output can then be used for Hydrodynamics model to create a flood map for flash flood warnings system.
Conclusions
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Acknowledgements
The authors thank the Thailand Research Fund (TRF) through the Royal Golden Jubilee Ph.D. Program for their financial support.
Thanks to the Department of Water Resources Thai Meteorological Department and other line agencies for supplying the data for the study.
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Thank you for your kind attention…