WinSLAMM Simulation of Hydrologic Performance of Permeable Pavements—A Case Study in the Semi-Arid Lower Rio Grande Valley of South Texas, United States
Abstract
:1. Introduction
2. Methods
- City of Brownsville (COB)—porous concrete pavement (PCP)
- City of La Feria (COLF)—permeable interlocking concrete pavement (PICP)
- Cameron County Drainage District #1 Cascade Park (CCDD#1)—interlocking block pavement with gravel (IBPG).
2.1. Field and Laboratory Data Preparation
2.2. Model Development
2.3. Initial Model Simulation
2.4. Model Calibration and Validation
- (i)
- The overlapping of the model-simulated runoff reduction-rainfall trend line with the observed runoff reduction trend line appears optimal.
- (ii)
- A higher or acceptable value of (R2 > 0.8) and NSE (close to 1) corresponded with a perfect match of model-simulated results to the observed data. However, this criterion may vary depending upon the quality of the observed data [53].
- (iii)
- A lower RMSE (<30%) resulted in model-simulated outcomes [54].
- (iv)
- A p-value less than 0.05 or within a 95% confidence interval boundary better supports the regression correlation between observed and model-predicted results [55].
3. Results and Discussion
3.1. Model Calibration and Validation Results
3.2. WinSLAMM Application in Hydrologic Performance Assessment
3.2.1. Runoff Reduction over Varying Rainfall Depths
3.2.2. Peak Discharge over Varying Impervious Drainage Areas and Pavement Installation Sizes
3.2.3. Runoff Reduction with Varying Sensitive Design Parameters
4. Conclusions
- The model calibration equations (correlating simulated runoff reduction and rainfall depth) appear to be helpful in predicting surface runoff reduction from permeable pavements over a wide range of rainfall events.
- The model calibration runs suggested that PCP and IBPG designs might be capable of handling rainfall events as large as a 50-year frequency event over a 24-h time period in the semi-arid climatic region of the LRGV, depending on the pavement designs and field conditions. However, the PCP installation showed the optimal runoff reduction when compared to the other monitored types of pavements.
- The PCP performance was also evaluated over a broad range for different sizes of commercial developments in the LRGV region. The model-simulated results suggested that it should require a comparatively smaller PCP footprint within a commercial development than other types to achieve the same amount of discharge goal.
- The existing PCP design was highly sensitive to its base aggregate porosity. Higher storage of infiltrated runoff could be achieved if conventional angular aggregates were replaced with crushed stone or similar #4 aggregates with higher porosity during PCP construction.
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Site ID | Drainage Sources | Area (m2) | No. of Flow Monitoring Events | Monitoring Period |
---|---|---|---|---|
COB-PCP | Pavement Section | 37.16 | 14 | September 2014–November 2014 |
Impervious Cover (driveway, concrete trail, etc.) | 52.61 | |||
Total Drainage Area | 89.77 | |||
CCDD#1-PICP | Pavement Section | 372.31 | 14 | August 2014–February 2015 |
Impervious Cover (driveway, concrete trail, etc.) | 246.86 | |||
Total Drainage Area | 619.17 | |||
COLF-IBPG | Pavement Section | 210.33 | 56 | May 2015–March 2016 |
Impervious Cover (concrete sidewalk) | 40.47 | |||
Large Landscape | 538.23 | |||
Total Drainage Area | 789.03 |
Parameters | COB-PCP | COLF-IBPG | CCDD#1-PICP | Source |
---|---|---|---|---|
Porous Pavement Area (acres) | 0.009 | 0.052 | 0.092 | Field-Measured |
Pavement Surface Thickness (inch) | 3.0 | 3.0 | 3.0 | Design Sheet |
Pavement Surface Porosity | 0.20 | 0.25 | 0.35 | Lab-Measured |
Aggregate Bedding Thickness (inch) | 6.0 | 1.0 | 2.0 | Design Sheet |
Aggregate Bedding Porosity | 0.35 | 0.40 | 0.38 | Lab-Measured |
Aggregate Base Reservoir (base + sub-base) Thickness (inch) | 9.0 | 18 | 10.0 | Design Sheet |
Aggregate Base Reservoir Porosity | 0.35 | 0.35 | 0.35 | Lab-Measured |
Pavement Area to Aggregate Base Area Ratio | 1.00 | 1.00 | 1.00 | Calculated |
Perforated Pipe Underdrain Diameter (inch) | 4.0 | 0 | 8.0 | Design Sheet |
Pipe Underdrain Invert Elevation (inch) | 0.5 | 0 | 0.5 | Design Sheet |
No. of Underdrain Pipes | 1 | 0 | 1 | Design Sheet |
Subgrade Seepage Rate (inch/h) | 0.05 | 0.05 | 0.05 | Geotechnical Report |
Initial/max Surface Infiltration Rate (inch/h) | 2000 | 900 | 900 | Field-Measured |
Rainfall (mm) | COB-PCP 1 | CCDD#1-PICP 2 | COLF-IBPG 3 | ||
---|---|---|---|---|---|
Initial | Initial | Adjusted | Initial | Adjusted | |
1 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
2 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
3 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
5 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
10 | 0.023 | 0.023 | 0.000 | 0.005 | 0.078 |
15 | 0.038 | 0.038 | 0.013 | 0.007 | 0.109 |
20 | 0.058 | 0.058 | 0.021 | 0.010 | 0.155 |
25 | 0.069 | 0.069 | 0.032 | 0.012 | 0.186 |
30 | 0.076 | 0.076 | 0.038 | 0.014 | 0.217 |
40 | 0.120 | 0.120 | 0.042 | 0.016 | 0.248 |
50 | 0.200 | 0.200 | 0.066 | 0.018 | 0.279 |
60 | 0.200 | 0.200 | 0.110 | 0.019 | 0.295 |
70 | 0.200 | 0.200 | 0.110 | 0.020 | 0.310 |
80 | 0.200 | 0.200 | 0.110 | 0.021 | 0.326 |
90 | 0.200 | 0.200 | 0.110 | 0.022 | 0.341 |
100 | 0.250 | 0.250 | 0.138 | 0.023 | 0.357 |
125 | 0.300 | 0.300 | 0.165 | 0.024 | 0.372 |
Site ID | Events | Rainfall Depth (mm) | Observed Runoff Reduction (mm) | Model-Predicted Runoff Reduction (mm) | %Error | Comments |
---|---|---|---|---|---|---|
COB-PCP | 11/11/2014 | 2 | 6 | 7 | 14 | Over-Predicting |
9/27/2014 | 21 | 50 | 61 | 18 | Over-Predicting | |
CCDD#1-PICP | 8/13/2014 | 2 | 4 | 4 | 0 | Under-Predicting |
3/9/2015 | 4 | 6 | 6 | 0 | Over-Predicting | |
12/9/2014 | 19 | 32 | 28 | 14 | Under-Predicting | |
9/3/2014 | 55 | 64 | 58 | 10 | Under-Predicting | |
COLF-IBPG | 9/13/2015 | 3 | 6 | 7 | 14 | Over-Predicting |
1/3/2016 | 10 | 21 | 22 | 5 | Over-Predicting | |
4/24/2016 | 17 | 27 | 33 | 18 | Over-Predicting | |
2/3/2015 | 18 | 43 | 34 | 26 | Under-Predicting | |
1/2/2016 | 20 | 35 | 38 | 8 | Over-Predicting | |
4/4/2015 | 21 | 52 | 40 | 30 | Under-Predicting |
Size of Commercial Development (acres) | 50 Years-24 h Post-Development Peak Discharge (m3/s) | 10 Years–24 h Pre-Development Peak Discharge (m3/s) | Required PCP Installation Area (m2) 1 | Required PICP Installation Area (m2) 2 | Required IBPG Installation Area (m2) 3 |
---|---|---|---|---|---|
5 | 0.21 | 0.037 | < 8000 | <14,000 | >20,000 |
10 | 0.43 | 0.074 | <16,000 | <35,000 | >40,000 |
15 | 0.64 | 0.110 | <21,000 | <47,000 | >60,000 |
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Alam, T.; Mahmoud, A.; Jones, K.D.; Bezares-Cruz, J.C.; Guerrero, J. WinSLAMM Simulation of Hydrologic Performance of Permeable Pavements—A Case Study in the Semi-Arid Lower Rio Grande Valley of South Texas, United States. Water 2019, 11, 1865. https://doi.org/10.3390/w11091865
Alam T, Mahmoud A, Jones KD, Bezares-Cruz JC, Guerrero J. WinSLAMM Simulation of Hydrologic Performance of Permeable Pavements—A Case Study in the Semi-Arid Lower Rio Grande Valley of South Texas, United States. Water. 2019; 11(9):1865. https://doi.org/10.3390/w11091865
Chicago/Turabian StyleAlam, Taufiqul, Ahmed Mahmoud, Kim D. Jones, Juan César Bezares-Cruz, and Javier Guerrero. 2019. "WinSLAMM Simulation of Hydrologic Performance of Permeable Pavements—A Case Study in the Semi-Arid Lower Rio Grande Valley of South Texas, United States" Water 11, no. 9: 1865. https://doi.org/10.3390/w11091865