Economic Losses from Hydrological Anomalies in Irrigated Agriculture: An Integrated Assessment Model for Brazilian Hydrographic Regions

This study develops and applies an Integrated Assessment Modelling (IAM) framework to evaluate the economic impacts of hydrological anomalies on irrigated agriculture productivity across Brazil’s twelve hydrographic regions. The framework integrates three components: (i) an econometric model estimating the sensitivity of irrigated yields to reductions in Blue Water availability; (ii) a set of seven hydrological models projecting Blue Water supply across the twelve hydrographic regions under two climate scenarios (Shared Socioeconomic Pathways (SSP)2-4.5 and SSP5-8.5) between 2015 and 2099; and (iii) a Computable General Equilibrium (CGE) model (B-MARIA-12RH) capturing direct, regional, indirect, and interregional economic effects of productivity shocks under uncertainty. The results show that if the average reduction in Blue Water availability projected under SSP2-4.5 (2015–2099) had affected irrigated agricultural productivity in 2015, Brazil’s real Gross Domestic Product would have declined by approximately -0.0052% (USD 95 million in 2015 values). This effect is mainly driven by a contraction in export volumes (up to -0.0322%) and a reduction in aggregate capital income (up to -0.0101%), disproportionately affecting capital-intensive sectors. Employment losses are most pronounced in S01-Agriculture, including support (-0.0389%), S12-Tobacco products (-0.0342%), S20-Biofuels (-0.0182%), and S09-Refined sugar (-0.0168%). Regionally, the largest contractions in Gross Regional Product occur in HR10-São Francisco (-0.0168%), HR2-Eastern Atlantic (-0.0154%), and HR12-Uruguay (-0.016%), underscoring vulnerabilities in irrigation-dependent territories. By linking physical and economic dimensions of climate change, the proposed IAM framework provides policy-relevant insights into adaptive strategies that strengthen resilience in water-intensive sectors and regions. This study contributes to ecological and climate economics by operationalizing a multi-scale, interdisciplinary modelling approach for evaluating adaptation options.