Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat

Abstract

Crop productivity and water consumption form the basis to calculate the water footprint (WF) of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%-19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%-39%. Models responded differently to elevated CO 2 in a FACE (Free-Air Carbon Dioxide Enrichment) experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%-49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%-68% of the total actual evapotranspiration.

Variability in the Water Footprint of Arable Crop Production across European Regions

“…The modelled results relied on calibrated crop phenological and growth development on experimental fields [21] or on farmers' fields. The best agreement between modelled and statistical yields was obtained for rapeseed (R 2 = 0.60; MAE = 0.7; RMSE = 0.8) and barley (R 2 = 0.62; MAE = 1.1; RMSE = 1.3), followed by wheat (R 2 = 0.50; MAE = 1.5; RMSE = 1.8) and maize (R 2 = 0.48; MAE = 2.1; RMSE = 2.5).…”

“…The crop growth parameters were set using experimental field data collected for each region (Appendix A, [21]). For regions without experimental field data available, crop growth parameters were derived from farmers' fields' data.…”

Advancing Water Footprint Assessment Research: Challenges in Monitoring Progress towards Sustainable Development Goal 6

“…A complicating factor is the uncertainty in estimating WFs in crop production. This is well illustrated in the paper by Kersebaum et al [16], who assess uncertainties in WFs of crop production using an ensemble model approach. Their study reveals that the uncertainty of crop yield prediction, arising from the use of different models, contributes more to the uncertainty in the assessment of water-use efficiency and water footprints than the estimation of evapotranspiration.…”

“…Early WF studies often focused on accounting (quantifying WFs), without adequate consideration of variabilities and uncertainties and without putting numbers in the wider environmental, economic, or social context. The studies by Gobin et al [14] and Evangelou et al [15] focus on showing the variability in WFs of crop production, while Kersebaum et al [16] quantify uncertainties in WF estimations. Some of the papers focus on understanding the driving forces behind increasing WFs [19][20][21][22][23].…”

“…Thirteen of the fourteen papers in this special issue consider green and blue WFs [14][15][16][17][18][19][20][21][22][23][24][25][26], while eight papers include grey WF estimation. All papers that include the grey WF specifically focus on pollution through nitrogen [14,15,17,19,21,22,25,27].…”