Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management.

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.

[1]  Subhasis Giri,et al.  Evaluation of targeting methods for implementation of best management practices in the Saginaw River Watershed. , 2012, Journal of environmental management.

[2]  Mahdi Zarghami,et al.  On the relation between Compromise Programming and Ordered Weighted Averaging operator , 2010, Inf. Sci..

[3]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

[4]  E. Stanley Lee,et al.  An extension of TOPSIS for group decision making , 2007, Math. Comput. Model..

[5]  Dimitar Filev,et al.  Induced ordered weighted averaging operators , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[6]  A. Milani,et al.  The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection , 2005 .

[7]  Claus Rinner,et al.  Exploring multicriteria decision strategies in GIS with linguistic quantifiers: A case study of residential quality evaluation , 2005, J. Geogr. Syst..

[8]  J. Karr.  Assessment of Biotic Integrity Using Fish Communities , 1981 .

[9]  Guillermo A. Mendoza,et al.  Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms , 2006 .

[10]  Piero P. Bonissone,et al.  A fuzzy sets based linguistic approach: Theory and applications , 1980, WSC '80.

[11]  Jiangjiang Wang,et al.  Review on multi-criteria decision analysis aid in sustainable energy decision-making , 2009 .

[12]  Lotfi A. Zadeh,et al.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[13]  Ali Emrouznejad,et al.  Ordered Weighted Averaging Operators 1988–2014: A Citation‐Based Literature Survey , 2014, Int. J. Intell. Syst..

[14]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[15]  Francisco Herrera,et al.  Direct approach processes in group decision making using linguistic OWA operators , 1996, Fuzzy Sets Syst..

[16]  Mahdi Zarghami,et al.  Effective watershed management; Case study of Urmia Lake, Iran , 2011 .

[17]  G. V. Loganathan,et al.  Application of the Analytical Hierarchical Process for Improved Selection of Storm-Water BMPs , 2009 .

[18]  Ching-Lai Hwang,et al.  Multiple attribute decision making : an introduction , 1995 .

[19]  Xinwang Liu,et al.  Orness and parameterized RIM quantifier aggregation with OWA operators: A summary , 2008, Int. J. Approx. Reason..

[20]  Kin Keung Lai,et al.  A distance-based group decision-making methodology for multi-person multi-criteria emergency decision support , 2011, Decis. Support Syst..

[21]  Stefan Hajkowicz,et al.  A Review of Multiple Criteria Analysis for Water Resource Planning and Management , 2007 .

[22]  Ronald R. Yager,et al.  On the cardinality index and attitudinal character of fuzzy measures , 2002, Int. J. Gen. Syst..

[23]  Xinwang Liu,et al.  A Review of the OWA Determination Methods: Classification and Some Extensions , 2011, Recent Developments in the Ordered Weighted Averaging Operators.

[24]  Zekai Sen,et al.  Fuzzy Logic and Hydrological Modeling , 2009 .

[25]  Simona Tondelli,et al.  Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil. , 2011, Journal of environmental management.

[26]  Erik Mostert,et al.  Application of the Ordered Weighted Averaging (OWA) method to the Caspian Sea conflict , 2014, Stochastic Environmental Research and Risk Assessment.

[27]  Agis M. Papadopoulos,et al.  Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems , 2008 .

[28]  Ronny Berndtsson,et al.  Multi-criteria Decision Analysis (MCDA) for Integrated Water Resources Management (IWRM) in the Lake Poopo Basin, Bolivia , 2010 .

[29]  Sergio Barba-Romero,et al.  Multicriterion Decision in Practice , 2000 .

[30]  Zhen Zhang,et al.  Optimization of conservation practice implementation strategies in the context of stream health , 2015 .

[31]  C. Hwang.  Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[32]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[33]  Z. Yue.  A method for group decision-making based on determining weights of decision makers using TOPSIS , 2011 .

[34]  Petros A. Pilavachi,et al.  Technological, economic and sustainability evaluation of power plants using the Analytic Hierarchy Process , 2009 .

[35]  M. Phua,et al.  A GIS-based multi-criteria decision making approach to forest conservation planning at a landscape scale : a case study in the Kinabalu Area, Sabah, Malaysia , 2005 .

[36]  Mark Gershon,et al.  Techniques for multiobjective decision making in systems management , 1986 .

[37]  I. Linkov,et al.  Appendix A : Multi-Criteria Decision Analysis , 2008 .

[38]  Marc Roubens,et al.  Multiple criteria decision making , 1994 .

[39]  R. Yager.  Quantifier guided aggregation using OWA operators , 1996, Int. J. Intell. Syst..

[40]  Haydar Aras,et al.  Multi-criteria selection for a wind observation station location using analytic hierarchy process , 2004 .

[41]  Lucien Duckstein,et al.  Ranking Ground-water Management Alternatives by Multicriterion Analysis , 1994 .

[42]  Subhasis Giri,et al.  Application of analytical hierarchy process for effective selection of agricultural best management practices. , 2014, Journal of environmental management.

[43]  Manoj Kumar Tiwari,et al.  Improved Decision Neural Network (IDNN) based consensus method to solve a multi-objective group decision making problem , 2007, Adv. Eng. Informatics.

[44]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.