PMID- 26734840 OWN - NLM STAT- MEDLINE DCOM- 20160927 LR - 20181202 IS - 1095-8630 (Electronic) IS - 0301-4797 (Linking) VI - 168 DP - 2016 Mar 1 TI - Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management. PG - 260-72 LID - S0301-4797(15)30392-3 [pii] LID - 10.1016/j.jenvman.2015.11.038 [doi] AB - Effective watershed management requires the evaluation of agricultural best management practice (BMP) scenarios which carefully consider the relevant environmental, economic, and social criteria involved. In the Multiple Criteria Decision-Making (MCDM) process, scenarios are first evaluated and then ranked to determine the most desirable outcome for the particular watershed. The main challenge of this process is the accurate identification of the best solution for the watershed in question, despite the various risk attitudes presented by the associated decision-makers (DMs). This paper introduces a novel approach for implementation of the MCDM process based on a comparative neutral risk/risk-based decision analysis, which results in the selection of the most desirable scenario for use in the entire watershed. At the sub-basin level, each scenario includes multiple BMPs with scores that have been calculated using the criteria derived from two cases of neutral risk and risk-based decision-making. The simple additive weighting (SAW) operator is applied for use in neutral risk decision-making, while the ordered weighted averaging (OWA) and induced OWA (IOWA) operators are effective for risk-based decision-making. At the watershed level, the BMP scores of the sub-basins are aggregated to calculate each scenarios' combined goodness measurements; the most desirable scenario for the entire watershed is then selected based on the combined goodness measurements. Our final results illustrate the type of operator and risk attitudes needed to satisfy the relevant criteria within the number of sub-basins, and how they ultimately affect the final ranking of the given scenarios. The methodology proposed here has been successfully applied to the Honeyoey Creek-Pine Creek watershed in Michigan, USA to evaluate various BMP scenarios and determine the best solution for both the stakeholders and the overall stream health. CI - Copyright (c) 2015 Elsevier Ltd. All rights reserved. FAU - Javidi Sabbaghian, Reza AU - Javidi Sabbaghian R AD - Department of Civil Engineering, Ferdowsi University of Mashhad (FUM), Mashhad, Iran; Department of Biosystems and Agricultural Engineering, Michigan State University (MSU), East Lansing, MI, 48824, USA. Electronic address: re_ja268@stu.um.ac.ir. FAU - Zarghami, Mahdi AU - Zarghami M AD - Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Department of Civil and Environmental Eng. and Tufts Institute of the Environment, Tufts University, Medford, MA, 02155, USA; Sociotechnical Systems Research Center, Massachusetts Institute of Technology, Cambridge, 02142 USA. Electronic address: mzarghami@tabrizu.ac.ir. FAU - Nejadhashemi, A Pouyan AU - Nejadhashemi AP AD - Department of Biosystems and Agricultural Engineering, Michigan State University (MSU), East Lansing, MI, 48824, USA. Electronic address: pouyan@msu.edu. FAU - Sharifi, Mohammad Bagher AU - Sharifi MB AD - Department of Civil Engineering, Ferdowsi University of Mashhad (FUM), Mashhad, Iran. Electronic address: mbsharif@um.ac.ir. FAU - Herman, Matthew R AU - Herman MR AD - Department of Biosystems and Agricultural Engineering, Michigan State University (MSU), East Lansing, MI, 48824, USA. FAU - Daneshvar, Fariborz AU - Daneshvar F AD - Department of Biosystems and Agricultural Engineering, Michigan State University (MSU), East Lansing, MI, 48824, USA. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20151228 PL - England TA - J Environ Manage JT - Journal of environmental management JID - 0401664 RN - 0 (Water Pollutants) SB - IM MH - Agriculture/*methods MH - *Decision Making MH - Decision Support Techniques MH - Environment MH - Humans MH - Michigan MH - Models, Theoretical MH - Risk Assessment MH - Water Pollutants/*chemistry OTO - NOTNLM OT - Effective watershed management OT - Induced ordered weighted averaging OT - Ordered weighted averaging OT - Scenario ranking OT - Simple additive weighting EDAT- 2016/01/07 06:00 MHDA- 2016/09/28 06:00 CRDT- 2016/01/07 06:00 PHST- 2015/08/22 00:00 [received] PHST- 2015/11/13 00:00 [revised] PHST- 2015/11/19 00:00 [accepted] PHST- 2016/01/07 06:00 [entrez] PHST- 2016/01/07 06:00 [pubmed] PHST- 2016/09/28 06:00 [medline] AID - S0301-4797(15)30392-3 [pii] AID - 10.1016/j.jenvman.2015.11.038 [doi] PST - ppublish SO - J Environ Manage. 2016 Mar 1;168:260-72. doi: 10.1016/j.jenvman.2015.11.038. Epub 2015 Dec 28.