• Six bias-corrected CMIP5 models project escalating maize irrigation demand across Mymensingh through 2085 (2026–2085). • Quantile mapping reduced raw precipitation bias from −76.3% to −3.2%, confirming reliable climate inputs. • Gross irrigation requirements peak at 640.5 mm/season under RCP4.5-DF and 629.9 mm/season under RCP8.5-DF, indicating mounting water deficits from mid-century. • GIS-based IDW interpolation identifies the northwestern corridor as the district's highest irrigation stress zone. • Effective rainfall declines up to 28.6%, compounding thermally driven maize water deficits across all scenarios. Intensifying climate change amplifies evapotranspiration demand while suppressing dry-season rainfall across South Asian cereal-producing landscapes, yet spatially distributed, multi-model assessments of maize-specific irrigation requirements remain absent at the district scale in Bangladesh. As the first district-scale, multi-metric GIS-based projection of its kind, this study quantifies spatiotemporal irrigation water requirements for dry-season rabi maize across Mymensingh District, north-central Bangladesh. Six bias-corrected CMIP5 general circulation models — BCC-CSM1-1, BCC-CSM1-1-M, HadGEM2-ES, IPSL-CM5A-LR, MIROC5, and MRI-CGCM3 — were integrated within the CROPWAT 8.0 framework under RCP4.5 and RCP8.5 across three future periods (2026–2085) at 40 georeferenced sites; quantile mapping achieved R² ≥ 0.93, NSE ≥ 0.88, and PBIAS within ±3.2% during independent validation. Seasonal reference evapotranspiration intensified from 2.72 to 3.03 mm/day (+11.8%) under RCP8.5-DF, while effective rainfall declined by up to 28.6%, jointly amplifying irrigation deficits across all scenario–period combinations. Potential crop water requirements reached 391.5 mm/season (+13.0%, RCP8.5-DF); net irrigation requirements peaked at 448.4 mm/season (+15.2%, RCP4.5-DF); and gross irrigation requirements attained 640.5 mm/season (+15.1%, RCP4.5-DF). Inverse distance weighting interpolation validated by leave-one-out cross-validation (R² = 0.623; PBIAS within ±0.23%) revealed a pronounced northwest–southeast irrigation stress gradient, providing spatially explicit, upazila-level guidance for climate-adaptive water infrastructure planning in north-central Bangladesh.
Islam et al. (Fri,) studied this question.