Southern Europe is becoming drier. Adverse climatic conditions may reduce rainfed agricultural production and farmers are likely to adapt by increasing their irrigation demand. With high confidence, water demand for crop irrigation is expected to increase by more than 40% up to 2080, further strengthening the irrigation expansion trend of the last 50 years. Declining runoff and groundwater resources in Mediterranean catchments will fall increasingly often short of expanding irrigation demand, giving rise to more frequent and intense drought events. Higher environmental standards and inelastic supply suggest that future drought response will demand more frequent and intense restrictions in irrigation withdrawals. In this context, there is a pressing need to better understand the economic impacts of irrigation restrictions, including their microeconomic and economy-wide repercussions.
Decision Support Systems (DSS) at different geographical scales play a key role in this respect, providing the data to inform decision making in drought contexts. DSS typically optimize an objective function subject to a series of physical and management constraints following agronomic, hydrological, hydro-economic or economic criteria. The analysis conducted in this paper falls in the latter category.
This paper presents a methodological framework that nests a bottom-up microeconomic Revealed Preference Model (RPM) into a top-down macroeconomic Input Output (IO) model. The goal is to assess the economic impacts of seasonal irrigation restrictions, including their microeconomic and economy-wide repercussions. The methodology is resolved in two stages: in the first stage, a microeconomic RPM estimates the impacts of alternative irrigation restrictions on the income of agents; in the second stage, estimated impacts are imported into a macroeconomic input-output model (MRIA model) to assess economy-wide losses across sectors and regions within the economy. To the best of our knowledge, this is the first time both models are integrated.
Methods are illustrated with an application in the Lower Po River Basin in Northeastern Italy. The Po River Basin has been increasingly hit by drought events after the turn of the century. Droughts hit the basin in the years 2003, 2006, 2007 and 2015, with the State of Emergency (SoE) being declared in 2003, 2006 and 2007 for a total duration of 20 months. The negative consequences of drought were especially felt in the irrigated areas of the LPRB, and climate projections indicate this trend will aggravate in the future. Despite its growing drought exposure and inflating agricultural losses, decision-making in the LPRB is based on hydrological information only. By means of a thorough representation of agents’ preferences and response and related economy-wide repercussions, this research can be used to estimate the abatement costs of overallocation and support decision-making processes.