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Advances in Total Maximum Daily Load Implementation Planning by Modeling Best Management Practices and Green Infrastructures.

Authors :
Borah, Deva K.
Zhang, Harry X.
Zellner, Moira
Ahmadisharaf, Ebrahim
Babbar-Sebens, Meghna
Quinn, Nigel W. T.
Kumar, Saurav
Sridharan, Vamsi Krishna
Leelaruban, Navaratnam
Lott, Craig
Source :
Journal of Environmental Engineering; Jul2024, Vol. 150 Issue 7, p1-12, 12p
Publication Year :
2024

Abstract

In this paper, a review of advances in total maximum daily load (TMDL) implementation planning by modeling best management practices (BMPs) and green infrastructure (GI) practices along with enhanced (hybrid/streamlining) approaches is presented. The review emanates from Chapter 12 of the recent ASCE Manual of Practice on TMDLs. The latest models and modeling tools, specifically the United States Environmental Protection Agency's (USEPA's) GI Modeling Toolkit and the Landscape and Green Infrastructure Design (L-GrlD) model for formulating GI strategies with flexibility to support stakeholder engagement, are reviewed. In addition, other decision support tools that can help advance the state-of-the-practice of TMDL implementation are included in the synthesis. Advances in incorporating model uncertainties related to BMPs and GI practices in TMDL analysis are briefly discussed. Furthermore, enhanced approaches to cost-effective TMDL implementation measures are discussed, which can be combined with other watershed management strategies for greater synergy between TMDL modelers and other watershed stakeholders. Some emerging technologies such as remote sensing can be useful for monitoring the effectiveness of the TMDL implementation measures over time. Several emerging technologies are discussed through an example illustrating the long-term efficacy of implementation practices. Finally, an enhanced approach to the full TMDL life cycle that explicitly incorporates BMPs and GI practices in the TMDL is proposed, and expected benefits of this approach are demonstrated with conceptual diagrams. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07339372
Volume :
150
Issue :
7
Database :
Complementary Index
Journal :
Journal of Environmental Engineering
Publication Type :
Academic Journal
Accession number :
177251785
Full Text :
https://doi.org/10.1061/JOEEDU.EEENG-7578