A Bayesian Belief Network approach to evaluating complex effects of irrigation-driven agricultural intensification scenarios on future aquatic environmental and economic values in a New Zealand catchment

Abstract

Agricultural intensification often has complex effects on a wide range of environmental and economic values, presenting planners with challenging decisions for optimising sustainable benefits. Bayesian Belief Networks (BBNs) can be used as a decision-support tool for evaluating the influence of development scenarios across a range of values. A BBN was developed to guide decisions on water abstraction and irrigation-driven land use intensification in the Hurunui River catchment, New Zealand. The BBN examines the combined effects of different irrigation water sources and four land development scenarios, with and without a suite of on-farm mitigations, on ground and surface water quality, key socioeconomic values (i.e. farm earnings and jobs, and contribution to regional gross domestic production (GDP)) and aquatic values (i.e. salmon, birds, waterscape, contact recreation, periphyton and invertebrates). It predicts high farm earnings, jobs and regional GDP with 150% increase in irrigated area, but a range of positive and negative aquatic environmental outcomes, depending on the location of water storage dams and the application of a suite of on-farm mitigations. This BBN synthesis of a complex system enhanced the ability to include aquatic values alongside economic and social values in land-use and water resource planning and decision making, and has influenced objective setting in Hurunui planning processes.