Webinar2: MODFLOW-USG: Theory, Application, and Implementation of CLNs

TRRP Training: 2022 Program

presented by: GSI Environmetal Inc.

Texas Risk Reduction Program regulations (TRRP; 30 TAC 350) establish consistent risk-based protocols for assessment and response to soil, groundwater, or surface water impacts associated with environmental releases of regulated wastes or substances.

Presented by GSI Environmental Inc., this popular and informative training series is a must for professionals who need a working understanding of TRRP and those needing to stay up-to-date with the latest TCEQ TRRP guidance and policies.

TRRP Training Course (2 Days): Provides an overview of the TRRP framework and step-by-step training on property assessment and response action procedures established under the TRRP rule

Attendees will become acquainted with rules, key guidance and policies covering affected property assessments, protective concentration levels, and response actions. The course material presents strategies for efficient project management in compliance with TRRP and explains the various report forms adopted by TCEQ.

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Sponsored by: ​
Texas Association of Environmental Professionals (TAEP) TAEP is the premier organization for environmental professionals in the State of Texas. The goals of TAEP include the advancement of the environmental profession and the establishment of a forum to discuss important environmental issues. TAEP members receive a 10% discount. Please call 713.522.6300 for the code.

Dates and Location

Dates

June 14th and 15th, 2022

Location

Crowne Plaza River Oaks 2712 SW Freeway Houston, Texas 77098 713.523.8448 http://www.crowneplaza.com/

Price and Registration

Early-Bird Price

(Paid by May 1, 2022)
$XXX

Standard Price

(Paid after May 1, 2022)
$XXX

TAEP Membership Price

$XXX

Government Price

$XXX
Lodging and meals are not
included in course cost
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Webinar2: MODFLOW-USG: Theory, Application, and Implementation of CLNs

Webinar2: MODFLOW-USG: Theory, Application, and Implementation of CLNs

Category

$200.00

Description

MODFLOW-USG was first released in 2013 by the USGS as an alternative version of the popular MODFLOW groundwater modeling software, that provided flexible gridding capability as compared to the previous standard finite difference versions. The concept of Connected Linear Networks (CLNs) was introduced in MODFLOW-USG to provide a mechanism for the inclusion, in a groundwater flow model, of any 1-D hydrogeologic or hydrologic water feature that is much smaller than the size of the model cell encompassing it. The CLN process, therefore, allows for the inclusion of features with much smaller cross-sectional areas than the model grid cell size without the necessity of having to refine the model grid cell size to the size of the CLN feature. CLN features may include pumping and monitoring wells (vertical, horizontal, or angled); radial collector wells or audits; underground mine workings such as developments, ramps, and stopes; geologic complexities such as karst features or faulting; or surface-water bodies such as connected canals, rivers, and stream channels. CLNs can also be used conceptually to connect different parts of a domain. Further developments on the CLN concept have been included in USG-Transport by GSI Environmental which adds simulation capabilities such as solute transport through CLN and groundwater flow domains, density dependent flow and transport, and various turbulent flow formulations. This webinar will review the capabilities and flexibility of using the CLN package in groundwater flow and transport simulations.

The webinar has been developed for better understanding and use of the CLN module. The course covers the theory, application, and implementation of CLNs in groundwater flow models. Specific topics that will be covered include:

  • History of MODFLOW & MODFLOW-USG
  • CLNs in MODFLOW-USG and USG-Transport – what CLNs can and cannot do
  • Demonstration examples
  • Compatibility / use of CLNs with other packages
  • CLN input parameters
  • Example workflow – Pre and post processing CLNs
  • Running models with CLNs
  • Pitfalls and troubleshooting strategies