Contaminant exposure of willets feeding in agricultural drainages of the Lower Rio Grande Valley of South Texas

1991 ◽  
Vol 16 (2) ◽  
pp. 189-200 ◽  
Author(s):  
Thomas W. Custer ◽  
Christine A. Mitchell
Keyword(s):  
Rio Grande Valley ◽  
Rio Grande ◽  
South Texas ◽  
Lower Rio Grande Valley ◽  
Contaminant Exposure ◽  
Agricultural Drainages ◽  
Lower Rio Grande

scholarly journals Decision-Support System for LID Footprint Planning and Urban Runoff Mitigation in the Lower Rio Grande Valley of South Texas

2020 ◽  
Vol 12 (8) ◽  
pp. 3152
Author(s):  
Javier Guerrero ◽  
Taufiqul Alam ◽  
Ahmed Mahmoud ◽  
Kim D. Jones ◽  
Andrew Ernest
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Rio Grande Valley ◽  
Rio Grande ◽  
The United States ◽  
South Texas ◽  
Lower Rio Grande Valley ◽  
Commercial Development ◽  
Lower Rio Grande

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).

scholarly journals 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 ◽  
Vol 11 (9) ◽  
pp. 1865 ◽  
Author(s):  
Taufiqul Alam ◽  
Ahmed Mahmoud ◽  
Kim D. Jones ◽  
Juan César Bezares-Cruz ◽  
Javier Guerrero
Keyword(s):  
Rio Grande Valley ◽  
Rio Grande ◽  
Concrete Pavement ◽  
South Texas ◽  
Lower Rio Grande Valley ◽  
Permeable Pavements ◽  
Runoff Reduction ◽  
Semi Arid ◽  
Lower Rio Grande ◽  
Hydrologic Performance

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%.

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