Selecting Reliable Models for Total Maximum Daily Load Development: Holistic Protocol

Vamsi Krishna Sridharan, Nigel W.T. Quinn, Saurav Kumar, Steven C. McCutcheon, Ebrahim Ahmadisharaf, Xing Fang, Harry X. Zhang, Andrew Parker

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Computer models and simpler methods must be used to reliably determine total maximum daily loads (TMDLs) for impaired waters of the US. Models are also useful to develop implementation plans that allocate load reductions to meet water quality standards. During model selection, practical considerations sometimes override the fundamental requirements of parsimony and defensibility. For the first time, a rationale for efficiently selecting reliable models for TMDL determinations is presented in this paper, based on deliberations of the TMDL Analysis and Modeling Task Committee of the Environmental and Water Resources Institute of ASCE. This protocol is based on technical criteria (waterbody, water quality, and data requirements) and management constraints (state plans and priorities, stakeholder and expert engagement, and state authority to manage pollution sources and state allocation priorities). Uncertainties due to changes in economic activity, population, land use, climate, sea level, and policies are also included. To reduce wasteful trial-and-error iterations during model selection, an optimal conceptual modeling framework is identified and subsequently refined in a flowchart based on practical considerations. The proposed protocol holistically defines the state of the science in model selection and is anticipated to soon define the state of the practice for TMDL determination.

Original languageEnglish (US)
Article number04021031
JournalJournal of Hydrologic Engineering
Volume26
Issue number10
DOIs
StatePublished - 2021
Externally publishedYes

ASJC Scopus subject areas

  • Environmental Chemistry
  • Civil and Structural Engineering
  • Water Science and Technology
  • General Environmental Science

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