Effective modeling for Integrated Water Resource Management : A guide to contextual practices by phases and steps and future opportunities

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Jennifer Badham
  • Sondoss Elsawah
  • Joseph Guillaume

  • Serena H. Hamilton
  • Randall J. Hunt
  • Anthony J. Jakeman
  • Suzanne A. Pierce
  • Valerie O. Snow
  • Meghna Babbar-Sebens
  • Baihua Fu
  • Patricia Gober
  • Mary C. Hill
  • Takuya Iwanaga
  • Daniel P. Loucks
  • Wendy S. Merritt
  • Scott D. Peckham
  • Amy K. Richmond
  • Fateme Zare
  • Daniel Ames
  • Gabriele Bammer

Research units

  • Queen's University Belfast
  • University of New South Wales
  • Australian National University
  • Edith Cowan University
  • United States Geological Survey
  • University of Texas at Austin
  • AgResearch
  • Oregon State University
  • Arizona State University
  • University of Kansas
  • Cornell University
  • University of Colorado Boulder
  • United States Military Academy at West Point
  • Brigham Young University

Abstract

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management.

Details

Original languageEnglish
Pages (from-to)40-56
Number of pages17
JournalEnvironmental Modelling and Software
Volume116
Publication statusPublished - 1 Jun 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Calibration, Decision making, Integrated modeling, IWRM, Social learning, Stakeholders, Uncertainty

ID: 32620461