Unveiling multi-regional water footprints towards equity and sustainability: A non-deterministic optimization-driven input-output model

Intensifying regional and sectoral competition for scarce water under rapid economic growth has heightened water-use inequities, calling for rational water resource planning in arid regions. This study develops a non-deterministic optimization-driven input-output model (abbreviated as IFFP-MRIO) through coupling interval-fuzzy full-infinite programming (IFFP) with multi-regional input-output model (MRIO). IFFP-MRIO can (i) explore optimal water allocation schemes under uncertainties expressed as functional intervals and fuzzy memberships through IFFP, (ii) link the optimization outputs to MRIO to identify sectoral direct and indirect water footprints along supply chains, and (iii) disclose impacts of various water-use policies on system benefits and sectoral water-allocation schemes. IFFP-MRIO is then applied to Inner-Shaan-Ning region in the Yellow River Basin, where five policy scenarios are designed to examine the impacts of policy incentives and technology progress on sectoral water footprints as well as address the inequity caused by water resource shortage. Results demonstrate that (i) when introducing equity principles, the water allocation to sectors to high economic benefits (i.e., construction, other service, other advanced manufacturing, metal manufacturing, food) would reduce by [5.71, 11.13] × 109 m3; (ii) compared to BAU, regional groundwater use would reduce [0.22, 4.52] × 109 m3 under resource sustainability scenario; (iii) uncertainties have significant impacts on system benefit and sectoral water-allocation schemes. The results can effectively balance the equity, economy and sustainability of water-resource allocation at both the regional and the sectoral levels.