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

Abstract. Future projections on irrigational water under a changing climate are highly dependent on meteorological data derived from general circulation models (GCMs). Since climate projections include biases, bias correction is widely used to adjust meteorological elements, such as the atmospheric temperature and precipitation, but less attention has been paid to biases in humidity. Hence, in many cases, raw GCM outputs have been directly used to analyze the impact of future climate change. In this study, we examined how the biases remaining in the humidity data of five GCMs propagate into the estimation of irrigational water demand and abstraction from rivers using the global hydrological model (GHM) H08. First, to determine the effects of humidity bias across GCMs, we used meteorological data sets to which a state-of-the-art bias correction method was applied except to the humidity. Uncorrected GCM outputs were used for the humidity. We found that differences in the monthly relative humidity of 11.7 to 20.4% RH (percent used as the unit of relative humidity) from observations across the GCMs caused the estimated irrigational water abstraction from rivers to range between 1217.7 and 1341.3 km3 yr−1 for 1971–2000. Differences in humidity also propagate into future projections. Second, sensitivity analysis with hypothetical humidity biases of ±5% RH added homogeneously worldwide revealed the large negative sensitivity of irrigational water abstraction in India and East China, which have high areal fractions of irrigated cropland. Third, we performed another set of simulations with bias-corrected humidity data to examine whether bias correction of the humidity can reduce uncertainties in irrigational water across the GCMs. The results showed that bias correction, even with a primitive methodology that only adjusts the monthly climatological relative humidity, helped reduce uncertainties across the GCMs. Although the GHMs have different sensitivities to atmospheric humidity because of the implementation of different types of potential evapotranspiration formulae, bias correction of the humidity should be included in hydrological analysis, particularly for the evaluation of evapotranspiration and irrigational water.