This study examines the hydrologic and environmental performance of three types of permeable pavement designs: Porous Concrete Pavement (PCP), Permeable Interlocking Concrete (PICP), and Interlocking Block Pavement with Gravel (IBPG) in the semi-arid South Texas. Outflow rate, storage, Normalized Volume Reduction (NVR), Normalized Load Reductions (NLR) of Total Suspended Solids (TSS), and Biochemical Oxygen Demand (BOD₅) were compared to results obtained from adjacent traditional pavements at different regional parking lots. A notable percentage of peak flow attenuation of approximately 31–100% was observed when permeable pavements were constructed and implemented. IBPG was capable to hold runoff from rainfall depths up to 136 mm prior to flooding. PCP was the most satisfactory in reducing surface runoff (NVR: 2.81 × 10⁻³ ± 0.67 × 10⁻³ m³/m²/mm), which was significantly (p < 0.05) higher (98%) than the traditional pavement. PCP was also very effective in TSS removal (NLR: 244 × 10⁻⁵ ± 143 × 10⁻⁵ kg/m²/mm), which was an increase of over 80% removal than traditional pavement. IBPG (NLR: 7.14 × 10⁻⁵ ± 7.19 × 10⁻⁵ kg/m²/mm) showed a significantly (p < 0.05) higher (46%) BOD₅ removal over traditional pavement. These results demonstrate that the type of permeable pavement and the underlying media can significantly influence the runoff reduction and infiltration in this climatic region.

Stormwater runoff introduces several pollutants to the receiving water bodies that may cause degradation of the water quality. Stormwater management systems such as detention facilities and wetland can improve the water quality by removing various pollutants associated with the runoff. The objective of this research project is to determine the performance and efficiency of two major regional detention facilities (RDFs) with different designs and structures in reducing pollutants based on various storm events in McAllen, Texas. The two sites are the McAuliffe RDF and the Morris RDF; each site was incorporated with a constructed wetland with a different design and structure to enhance the pollutant removal process. The McAuliffe RDF reduced the concentration and load of many stormwater constituents in comparison to the Morris RDF. The observed concentrations and pollutant loads of suspended solids were much lower in the runoff of the inlet compared to the outlet for both sites. The McAuliffe RDF showed better concentration and load reduction for nutrients, such as nitrogen and phosphorus, of different species. However, both sites did not show a significant improvement of organic material. In addition, the indicator bacteria concentration represented a fluctuation between the inlet and outlet at each site.

This study used the Source Loading and Management Model for Windows (WinSLAMM) to develop a set of calibrated hydrologic models for three types of regional permeable pavements—porous concrete pavement (PCP), permeable interlocking concrete pavement (PICP), and interlocking block pavement with gravel (IBPG). The objective was to assess the hydrologic performance of permeable pavements, including the runoff depth, peak discharge, percentage increment in runoff reduction of pavements as a function of rainfall depth, development area, and base aggregate porosity, respectively. The permeable pavements were monitored over a wide range of rainfall events in the semi-arid Lower Rio Grande Valley of South Texas. Data regarding rainfall intensities, source characterizations, runoff coefficients, and pavement design were initialized as WinSLAMM input. Validation results showed that the calibrated models could over or under-predict runoff reduction within a 30% error range. PCP and IBPG were very effective and could be capable of handling storms as large as 50-year frequency over a 24-h time period. The modeling results showed that PCP might require a 50–60% lesser footprint area as compared to PICP and IBPG, respectively. Additionally, PCP might be able to store 30% additional runoff if the porosity of base aggregates was increased by 40%.

To address regional flooding in the United States, federal and state agencies are adopting strict drainage policies in any large-scale commercial development within the watershed boundary. The conventional approach of implementing a wet detention pond (WP) reduces the land cover and causes operation and maintenance challenges eventually. The present study developed a decision-support system (DSS) in the Lower Rio Grande Valley region of South Texas for optimal selection of Best Management Practices (BMPs) by substituting a portion of the WP footprint with three regionally promising low-impact development practices, namely, porous concrete pavement (PCP), bioretention (BR), and bioswale (BS). Source Load Assessment and Management Model for Windows (WinSLAMM) was used as the foundation for the DSS database and algorithm development. This tool suggested that the implementation of bioswale alone can considerably reduce the footprint and construction cost. Less than 0.95 ha of installation of BR and BS can mitigate 79–91% of runoff from a maximum of 5 ha of commercial development. A combination of BR, BS, and WP was found to reduce runoff significantly (~100%), which suggests that the successful adoption of DSS might support better planning of the urban stormwater management in the Lower Rio Grande Valley (LRGV).