Trade in commodities embeds virtual water, and when goods flow from high- to low-water-productivity regions it can 'save' water — but whether it saves scarce water depends on a stress-weighted counterfactual that assumes the importing region could have produced the goods itself, keeps the water stress index (WSI) fixed despite the added withdrawals that local production would cause, and relies on globally derived stress data. Zhao et al. (2018) quantified China's interprovincial scarce-water savings under exactly these assumptions and flagged all of them as unresolved limitations. No study has yet quantified China's interregional scarce-water savings with an endogenously updated WSI under a hydrology–economy coupled counterfactual, a production-feasibility constraint applied economy-wide, or locally validated stress data. The problem is to deliver such a corrected, policy-usable quantification.

Background

When a region imports a good instead of producing it domestically, the water that would have been used to produce the good locally is 'saved' — the water embodied in traded commodities is called virtual water. Because water productivity (output per unit of water) differs across regions, trade from high- to low-productivity regions can reduce total water use at the national or global scale; this is the standard global water saving calculation. A multi-region input–output (MRIO) table is an economic accounting framework that traces how production in one region satisfies final and intermediate demand in others, and is the standard tool for mapping virtual water flows between provinces or countries. However, productivity-based water savings ignore where water is scarce: a saving realized in a water-abundant exporter at the cost of intensified scarcity in a water-stressed exporter may worsen, not relieve, the resource problem. To capture this, Feng et al. (2014) introduced the virtual scarce water index for China, weighting water use in production by a water stress index (WSI) — a dimensionless index of water scarcity developed by Pfister, Koehler and Hellweg (2009) for life-cycle assessment (LCA, a method for quantifying the environmental impacts of products and services across their full supply chains), computed from withdrawals relative to availability — so that scarce water is defined as water use multiplied by the WSI of the region where the withdrawal occurs. Zhao et al. (2018) applied this index to measure the scarce-water savings and losses of China's interprovincial trade. Stress-weighted (impact-oriented) water accounting of this kind originates with Ridoutt and Pfister (2010) and is contested: Hoekstra (2016) argued that scarcity-weighted 'water footprints' conflate volume and impact, while Pfister et al. (2017) defended the stress-weighted approach as an impact indicator compatible with volumetric accounting; the two families of metrics remain in parallel use, with the AWARE consensus model of Boulay et al. (2018) — AWARE stands for 'available water remaining', a consensus characterization factor for relative water scarcity at a location, developed for use in life-cycle impact assessment — standardizing impact assessment within LCA but not reconciling it with volumetric conservation targets. Using China's 2010 MRIO table, Zhao et al. (2018) found that interprovincial trade caused 14.2 km³ of volumetric water loss but only 0.4 km³ of scarce-water loss, with 254 trade links saving 20.2 km³ and 175 links losing 20.6 km³ of scarce water, and Xinjiang implicated in 66% of the national scarce-water loss. The authors themselves identified the load-bearing assumptions that limit this result: (i) the counterfactual assumes every imported good could have been produced by the importing province, which is false for products infeasible there (an inland province cannot produce seafood); (ii) the WSI is treated as fixed, although the added local withdrawals that counterfactual production would entail would themselves change the importing region's water stress — quantifying this requires a dynamic coupling between hydrology and the economy that was not performed; and (iii) the WSI dataset derives from a global hydrological model and can misrepresent provincial stress in China (the paper notes Heilongjiang is classified as under minor stress against domestic data showing at least moderate stress). Separately, in discussing the rationality of scarce water accounting, the authors acknowledge that the volumetric-versus-stress-weighted metric debate is still ongoing, while arguing that scarce-water saving accounting can show the compatibility of the volumetric and stress-weighted families rather than flagging a missing joint decision rule as a limitation of their study. Reviews by Liu et al. (2019) and Liao et al. (2024) confirm that linking water savings to actual scarcity alleviation and improving water scarcity indices remain open research needs.

Problem Statement

Construct a corrected quantification of the scarce-water savings and losses generated by China's interregional virtual water flows — the assessment that Zhao et al. (2018) performed under simplifying assumptions they themselves flagged — by jointly removing those assumptions. Specifically, the corrected quantification: (1) replaces the unconditional assumption that every imported good could have been produced by the importing province with an explicit production-feasibility counterfactual, in which counterfactual local production is constrained by agronomic and economic feasibility (climate, arable land, irrigation infrastructure, marine vs inland production) and products infeasible for local production are handled by a stated rule rather than silently credited with savings; (2) makes the water stress index endogenous — recomputing the importing region's WSI from the water availability and the increased withdrawals that the counterfactual local production would entail, via a stated hydrology–economy coupling (closed, convergent procedure), instead of holding WSI fixed; and (3) uses water-availability and water-use data for China at provincial or finer (catchment) resolution, correcting documented misclassifications such as Heilongjiang. The corrected quantification comprises: (a) a revised province-to-province scarce-water saving/loss assessment for China (on a stated MRIO year); (b) a decomposition showing the contribution of each correction — feasibility constraint, endogenous WSI, localized stress data — to the change from the fixed-WSI, unconditional-counterfactual baseline; (c) a sensitivity analysis over the defensible choices in counterfactual construction; and (d) an interpretation of whether China's interprovincial trade still saves scarce water once all corrections are applied. The three corrections and (a)–(d) are jointly required, and each open modelling choice (the feasibility rule, the hydrology–economy coupling, and the water-availability and water-use datasets together with their validation for China) is part of the corrected quantification; the decomposition in (b) quantifies, not merely asserts, each correction's contribution to the change from the baseline.

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