article · Sustainability
Global water demand is projected to rise by 20 to 30 percent by 2050, increasing annual withdrawals from 4,600 cubic kilometres to between 5,500 and 6,000 cubic kilometres. An integrated econometric, hydrological, and reduced-form economic framework evaluates these trends alongside macroeconomic risks. Agriculture currently accounts for 70 percent of withdrawals, while industry and domestic sectors use 20 percent and 10 percent respectively. Simulation findings identify the Middle East, Asia, and Africa as primary regional stress hotspots. Under an unmitigated high-demand scenario of 6,000 cubic kilometres per year, calibrated estimates indicate potential global gross domestic product losses of approximately 16 trillion dollars, representing 5.5 percent of projected global economic output. However, interventions encompassing efficiency improvements, pricing reforms, and artificial intelligence allocation tools could decrease demand by up to 40 percent, mathematically eliminating calibrated economic losses within the model.
Unchecked water scarcity threatens global macroeconomic stability, particularly in vulnerable regions such as Africa, Asia, and the Middle East. Quantifying future sectoral demand and associated gross domestic product losses provides essential baseline data. This helps governments, international agencies, and planners assess the necessity of proactive mitigation policies, including demand management and modern allocation systems, before scarcity generates severe financial and humanitarian disruption.
The modelling framework highlights opportunities for developers of water efficiency technologies, water pricing mechanisms, and artificial intelligence-driven water allocation tools. Potential users include water resource managers, agricultural operators, and economic policymakers addressing regional water stress. As an analytical framework reliant on calibrated reduced-form damage functions and continuous linear programming simulations, the work represents early-stage decision-support research that requires further operational integration before direct deployment in live water markets.
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Water scarcity threatens global stability, with demand set to surge 20–30% by 2050, pushing withdrawals from 4600 km3 yr−1 today to 5500–6000 km3 yr−1 under rising demographic and climatic pressures. This study presents a sequentially coupled econometric–hydrological–reduced-form economic framework that couples water supply dynamics with demand forecasting and macroeconomic impact assessment. Agriculture dominates current withdrawals at 70% (FAO AQUASTAT), followed by industry (20%) and domestic use (10%). Monte Carlo simulations (n = 1000) identify critical regional hotspots: Asia (stress ratio = 1.06), the Middle East (1.18), and Africa (0.99). The reduced-form economic module uses a target-calibrated scarcity elasticity (ε = 0.1865) applied against a fixed economic reference threshold (4600 km3 yr−1). This internally calibrated parameter yields a first-order GDP loss estimate of approximately $16.0 trillion under the high-demand (+30%) 2050 scenario (6000 km3 yr−1 demand), equivalent to 5.5% of projected 2050 global GDP ($290 trillion, PwC 2017 baseline). The resulting magnitude is broadly consistent with the order of GDP impacts discussed by OECD (2012) and GCEW (2024), although neither publication reports this specific elasticity value. This is not an independently predicted outcome; it is a calibrated scenario estimate produced by a reduced-form damage function designed to reproduce first-order magnitudes consistent with published structural model results. Mitigation strategies including efficiency improvements, pricing reforms, and AI-driven allocation can reduce demand by up to 40%, which within the model’s mathematical structure reduces the calibrated economic loss to zero. Sectoral water distribution is addressed through continuous linear programming with proportional rationing. This framework advances transparent, reproducible scenario-based understanding and informs policy decisions aimed at mitigating future water scarcity challenges globally, while explicitly acknowledging limitations relative to full structural CGE models and empirically estimated panel econometric models.
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DOI: 10.3390/su18178734
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