Development of Decision Making Tool (DMT) for Determining LID Stormwater Detention Requirements

Dr. Kim Jones & Taufiqul Alam

Texas A&M University-Kingsville,

Institute for Sustainable Energy and the Environment


Javier Guerrero

Civil Engineering, University of Texas Rio Grande Valley


To address localized flooding in the Lower Rio Grande Valley (LRGV), Texas region and U.S.- Mexico border water quality issues associated with non-point source pollution within the Arroyo Colorado watershed, the LRGV TPDES Stormwater Task Force, in partnership with the NADB BECC U.S. EPA Border 2020 program, supported the development of an innovative Decision Making Tool (DMT) for determining stormwater detention requirements while incorporating Green Infrastructure. TAMUK has partnered with the LRGV TPDES Stormwater Task Force (STF) in the planning and delivery of the DMT with this report.  In addition to this descriptive report, the Project Team is also delivering a copy of the developed Excel spreadsheet tool along with a User’s Manual document for the Tool.

Local governments in the LRGV control flooding and stormwater runoff by adopting strict drainage design policies. The flat terrain characteristic of the LRGV provides stormwater engineers with complicated flow, detention and flood design problems. According to an existing drainage policy, stormwater runoff generated from new commercial developments within the LRGV is generally required to be detained at on-site for a 50- year frequency storm event and released into the receiving system at a pre-developed rate for a 10-year frequency storm event.

One conventional approach to meet the discharge goal of retaining this huge volume of runoff is to design a detention pond with large footprints. Although traditional methods of designing detention ponds are somewhat cost-effective and calculation of storage is simple using excel spreadsheet, this approach may be a cause for lost land cover and aesthetic, safety, operating, and maintenance issues in the long run. With the use of innovated practices and green infrastructure strategies, the traditional design of a large detention pond footprint can be reduced by allowing the storage volume of Low Impact Development (LID) Best Management Practices (BMPs) to be incorporated into conventional design detention calculations. The challenge is to decide how to plan those BMPs design effectively within the development boundary to meet the 10 years frequency storm discharge goal.

The developed DMT tool and project achieves the two following principal objectives-

1. To provide a unique innovative calculator that can be used to determine stormwater detention requirements at urban and rural developments in the LRGV using LID

2. To conduct educational outreach activities in order to promote this tool to local school districts officials, colonies, institutes of higher education, city and county officials, water professionals, professional organizations and water-related organizations.

The link below is the Development of Decision Making Tool (DMT) for Determining
LID Stormwater Detention Requirements full report submitted to the NADB.

Fact Sheet PDF

The link below takes you to the RGV LID Program webpage where you can find an interactive map of the LID program.

LID Interactive Map

The link below takes you to the EPAs website where you will learn about the role EPA has with the North American Development Bank (NADB) is
I. DMT for LRGV LID stormwater management and planning

Project Partners:

  • Border Environmental Cooperation Commission
  • US EPA Border 2020 program
  • Texas A&M University Kingsville
  • LRGV TPDES Stormwater Task Force
  • University of Texas Rio Grande Valley
  • Cameron County and Cities of Edinburg, Weslaco, Donna
  • South Texas College
  • Regional EDC
II. Project Objectives
  • Develop a user friendly design tool (DMT) to reduce reliance on traditional detention pond solutions and promote innovative LID/GI technologies to reduce BMP footprints, conserve land resources and improve water quality by incorporating subsurface and LID storage and runoff reduction calculations into the design process for the LRGV
  • Incorporate outreach and education into workshops and seminars to facilitate training and implementation of the DMT into design and construction
III. Example Hydrograph for bioretention cell at South Texas College
  • Storm event on 8 November 2016, 0.78 inch rainfall over 24 hours
IV. Methodology and Modeling
  • DMT will incorporate extensive LID runoff and pollutant reduction data collected over several years from LID implementation program led by TAMUK and LRGV SW TF supported by TCEQ NPS 319 Program
  • WinSLAMM model for SW BMP modeling peer reviewed and accepted by scientists, engineers and agencies
  • Model calibration and validation achievable for unique BMPs in the LRGV such as pervious pavements, bioswales, biodetention cells, others
Methodology and Modeling, continued.
  • Extensive modeling runs of various combinations and connection of BMPs to be developed
  • Outputs coalesced into user friendly approaches such as Excel spreadsheets and tables (DMT) for use by cities, counties, planners, and stakeholders
  • DMT training and workshops implemented and enhanced for additional BMPs and connections
   V. Milestones and Updates
  • Modeling QAP developed
  • Example prototypes for typical LRGV mixed use communities and development scenarios in development
  • Several initial meetings with DMT workgroup implemented
  • Modeling QAP developed
  • DMT WQ Conference roll out and engagement
  • Modeling scenarios and post processing completed October 2017
VI. Example development
  • Traditional detention basin
  • Olusola Fasae, TAMUK-ISEE
VII. Example development
  • Connections of pervious pavement and bio-detention cells
  • Olusola Fasae, TAMUK-ISEE
VIII. Example development
  • Connections of pervious pavement and bioswales
  • Olusola Fasae, TAMUK-ISEE


Border Environmental Cooperation Commission

U.S. EPA Border 2020 Contract SOLTA-15-010

Lower Rio Grande Valley -Storm Water Task Force Partners- George Hernandez

University of Texas – Rio Grande Valley