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Future projections on irrigation water under a changing climate arehighly dependent on meteorological data derived from generalcirculation models (GCMs). Since climate projections include biases,bias correction is widely used to adjust meteorological elements, suchas the atmospheric temperature and precipitation, but less attentionhas been paid to biases in humidity. Hence, in many cases,uncorrected humidity datahave been directly used to analyze the impact of futureclimate change. In this study, we examined how the biases remainingin the humidity data of five GCMs propagate into the estimation ofirrigation water demand and consumption from rivers using the globalhydrological model (GHM) H08. First, to determine the effects ofhumidity bias across GCMs, we ran H08 with GCM-basedmeteorological forcing data setsdistributed by the Inter-Sectoral Impact Model Intercomparison Project(ISI-MIP).A state-of-the-art bias correction method was applied to the data setswithout correcting biases in humidity.Differences in the monthly relative humidityamounted to 11.7 to 20.4 % RH (percentagerelative humidity)across the GCMs and propagated into differences inthe estimated irrigation water demand, resulting in a rangebetween 1152.6 and 1435.5 km3 yr−1 for 1971–2000.Differences in humidityalso propagated into future projections. Second, sensitivity analysiswith hypothetical humidity biases of ±5 % RH added homogeneouslyworldwide revealed the large negative sensitivity of irrigationwater abstraction in India and East China,which are heavily irrigated. Third, we performed another set ofsimulations with bias-corrected humidity data to examine whether biascorrection of the humidity can reduce uncertainties in irrigationwater across the GCMs. The results showed that bias correction, evenwith a primitive methodology that only adjusts the monthlyclimatological relative humidity, helped reduce uncertainties acrossthe GCMs: by using bias-corrected humidity data,the uncertainty ranges of irrigation water demand across the five GCMswere successfully reduced from 282.9 to 167.0 km3 yr−1for the present period, and from 381.1 to 214.8 km3 yr−1for the future period (RCP8.5, 2070–2099).Although different GHMs have different sensitivities toatmospheric humidity because different typesof potential evapotranspiration formulae are implemented in them,bias correction of thehumidity should be applied to forcing data, particularly forthe evaluation of evapotranspiration and irrigation water

Propagation of biases in humidity in the estimation of global irrigation water