Water Quality Control Options in Response to Catchment Urbanization: A Scenario Analysis by SWAT
2. Materials and Methods
2.1. Study Area
2.2. Input Data
2.2.1. Soil Data
2.2.2. Other Input Data
- Digital elevation model (DEM): the 10 m resolution DEM was interpolated from a 10 m contour map provided by the SA Water Corporation.
- Flow burn-in layer: The river network was superimposed onto the DEM to adjust the location of some downstream urban creeks that were not well predicted by DEM due to modification effects from urban land development. The burn-in river layer was provided by the SA Water Corporation.
- Land use maps: a historical land use map at a scale of 1:100,000, which was completed in 2007 and updated with recent data on locations and land uses of the Torrens catchment, was provided by the Department of Environment, Water and Natural Resources. The map classifies the catchment into urban residential, commercial, institutional, industrial, transportation, water, and grassland land uses. For the past land use scenario, a historical map of 2001 of the whole South Australia was provided by the Department of Planning, Transport and Infrastructure.
- Climate data: this includes maximum and minimum air temperature, rainfall, relative humidity, and solar radiation. The daily data for these variables from 2008 to 2015 from five weather stations was extracted from the Scientific Information for Land Owners (SILO) website .
- Streamflow and nutrient data: data of daily streamflow and monthly composite Total Nitrogen (TN) and Total Phosphorous (TP) loads at the outlet of the study area (Holbrooks Road Station, A5040529) were provided by the Adelaide and Mount Lofty Ranges Natural Resources Management Board . Data were extracted for the period from 2008 to 2015.
2.3. Soil and Water Assessment Tool (SWAT) Model Set-Up
2.3.1. Parameter Sensitivity Analysis
2.3.2. Model Calibration, Validation and Uncertainty
2.4. Scenario Analysis
- Scenario ‘Buffer strip application’ (S2) was set up by extending the 30-m width of the filter strip of alfa grass along the main river using the FILTERW parameter in SWAT ‘.mgt’ input file .
- Scenario ‘Wetland development’ (S3) was represented by a wetland with a maximum surface of 3445 m2 and volume of 3700 m3 in the ‘.pnd’ input file, as suggested by Kasan . The nitrogen and phosphorous settling rates were set to 20 m/year using the maximum default value in the ‘.pnd’ input file for systems with high removal efficiency . The bottom hydraulic conductivity was set at 2.3 mm/h , and sediment concentration in the wetland was defined at 10 mg/L. The same parameter values were applied to all wetland scenarios of this study.
- Combined scenario (Sm) which simulated together the three aforementioned scenarios.
3.1. Model Sensitivity
3.2. Model Calibration, Validation and Uncertainty
3.3. Urbanization Scenarios
3.4. Scenarios of Management Practices
- Growing urbanization increases surface flow and TP loads whereas baseflow and TN loads decrease due to extending impervious area.
- Expanded buffer zones and stabilized river banks can retain nutrients while constructing adjacent wetlands may reduce run-off from tributaries to the main stream.
- A combined application of the three management options at pinpointed tributaries and river sites may prove to be the best management practice (BMP) in response to urbanization of the Torrens catchment.
Conflicts of Interest
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|Soil Profile||Layer (s)||Soil Parameters *||Data Source|
|1||975||1.379||0.131||21.6||2.25||43||27||30||0.17||0.051||Drill holes |
|Parameters||Description||Unit||Fitted Value||Parameter Sensitivity|
|CN2.mgt||Moisture condition II runoff curve number||-||−0.25 b||−63.56||0.00||1|
|ALPHA_BNK.rte||Baseflow alpha factor for bank storage||-||0.72||29.20||0.00||2|
|SOL_BD (1,2) a.sol||Moist bulk density||g/cm3||−0.19 b||−24.50||0.00||3|
|GWQMN.gw||Threshold depth of water in the shallow aquifer required for return flow to occur||mm H2O||1854||17.00||0.00||4|
|ESCO.hru||Soil evaporation compensation factor||-||0.75||−11.91||0.00||5|
|SOL_K (1,2) a.sol||Saturated hydraulic conductivity||mm/h||−0.17 b||−8.66||0.00||6|
|SOL_AWC (1,2) a||Available water capacity of the soil layer||mm H20/mm soil||−0.02 b||7.40||0.00||7|
|CH_K2.rte||Effective hydraulic conductivity in main channel alluvium||mm/h||59.6||−7.08||0.00||8|
|CH_N2.rte||Manning’s "n" value for the main channel||-||0.04||−5.98||0.00||9|
|GW_REVAP.gw||Groundwater "revap" coefficient||mm H2O||0.19||3.66||0.00||10|
|RCHRG_DP.gw||Deep aquifer percolation fraction||-||0.17||−2.94||0.00||12|
|Total Suspended Solid Load|
|USLE_P.mgt||USLE equation support practice factor||-||0.39||−63.26||0.00||1|
|CH_COV1.rte||Channel erodibility factor||-||0.32||1.98||0.05||2|
|SPEXP.bsn||Exponent parameter for calculating sediment re-entrained in channel sediment routing||-||1.12||1.76||0.08||3|
|CH_EROD.rte||Channel erodibility factor||-||0.56||1.30||0.19||4|
|SPCON.bsn||Linear parameter for calculating the maximum amount of sediment that can be reentrained during channel sediment routing||-||0.006||0.38||0.70||5|
|CH_COV2.rte||Channel cover factor||-||0.62||0.04||0.97||6|
|Total Nitrogen Load|
|LAT_ORGN.gw||Organic N in the baseflow||mg/L||6.33||−167.44||0.00||1|
|CDN.bsn||Denitrification exponential rate coefficient||-||0.56||−7.49||0.00||2|
|SDNCO.bsn||Denitrification threshold water content||-||0.73||3.8||0.00||3|
|ERORGN.hru||Organic nitrogen enrichment ratio||-||1.27||−1.08||0.28||4|
|NPERCO.bsn||Nitrogen percolation coefficient||-||0.15||−0.23||0.82||5|
|Total Phosphorous Load|
|PHOSKD.bsn||Phosphorus soil partitioning coefficient||-||187.03||−0.88||0.38||1|
|PSP.bsn||Phosphorus sorption coefficient||-||0.06||−0.78||0.43||2|
|ERORGP.hru||Organic phosphorus enrichment ratio||-||2.51||0.49||0.62||3|
|Scenarios||Flow||TN Load||TP Load|
|Mean Values (m3/s)||Relative Change (%)||Mean Values (tons/year)||Relative Change (%)||Mean Values (tons/year)||Relative Change (%)|
|River bank stabilization—S1||0.88||<1||31.65 a||−1.22||2.57 a||−2.73|
|30-m buffer strips—S2||0.88||<1||25.67 a||−19.88||2.53 a||−4.13|
|Wetland development—S3||0.86 a||−2.27||31.76 a||−0.87||2.58 a||−2.44|
|Combined BMPs—Sm||0.86 a||−2.28||25.21 a||−21.30||2.47 a||−6.40|
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Nguyen, H.H.; Recknagel, F.; Meyer, W. Water Quality Control Options in Response to Catchment Urbanization: A Scenario Analysis by SWAT. Water 2018, 10, 1846. https://doi.org/10.3390/w10121846
Nguyen HH, Recknagel F, Meyer W. Water Quality Control Options in Response to Catchment Urbanization: A Scenario Analysis by SWAT. Water. 2018; 10(12):1846. https://doi.org/10.3390/w10121846Chicago/Turabian Style
Nguyen, Hong Hanh, Friedrich Recknagel, and Wayne Meyer. 2018. "Water Quality Control Options in Response to Catchment Urbanization: A Scenario Analysis by SWAT" Water 10, no. 12: 1846. https://doi.org/10.3390/w10121846