MCDA approach for agricultural water management in the context of water-energy-land-food nexus

An integrated methodological framework, combining methods for environmental analysis with multi-criteria decision aid (MCDA), is proposed for decision problems related to the selection of agricultural water management measures in river basins. The proposed framework for environmental analysis combines the driving forces-pressures-state-impacts-responses model with the water-energy-land-food (WELF) nexus model to ensure structured, comprehensive and systemic thinking regarding the definition of the alternatives, the points of view and the criteria of the decision problem. The MCDA framework follows a multi-attribute value/utility theory approach for the estimation of marginal value functions for the selected criteria. This process is supported by the multicriteria interactive intelligence decision aiding system. The estimation of points of view and criteria weights is conducted following the newly-established weights assessment through prioritisation method (WAP), which is supported by the relevant WAP software. The MCDA framework includes strong interaction with a decision maker (DM) to elicit the required information for the above methods. Feedback loops and indicators for robustness analysis are applied, aiming at concluding to a robust value system, which models the preferences of the DM as close as possible. An additive value model is used to aggregate all the criteria and express the global value of all examined alternatives. The framework concludes to a recommended alternative for selection by the DM. The strengths and weaknesses of the proposed framework are identified. The framework is applied in a demonstration example from the Pinios river basin in Greece to showcase its use. The outcomes on the potential WELF nexus trade-offs and the identified sources of uncertainty are discussed.

Automated summary

This study proposes an integrated methodological framework that combines environmental analysis methods with multi-criteria decision aid for decision problems related to agricultural water management measures in river basins. The framework combines various models to ensure structured and comprehensive thinking, and utilizes a multi-criteria intelligent decision support system. A new method for weight assessment is applied, in conjunction with input from decision makers to recommend alternative solutions.