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Malone, R. W., Kersebaum, K. C., Kaspar, T. C., Ma, L., Jaynes, D. B., & Gillette, K. (2017). Winter rye as a cover crop reduces nitrate loss to subsurface drainage as simulated by HERMES. Agric. Water Manage., 184, 156–169.
Abstract: HERMES is a widely used agricultural system model; however, it has never been tested for simulating N loss to subsurface drainage. Here, we integrated a simple drain flbw component into HERMES. We then compared the predictions to four years of data (2002-2005) from central Iowa fields in corn-oybean with winter rye as a cover crop (CC) and without winter rye (NCC). We also compared the HERMES predictions to the more complex Root Zone Water Quality Model (RZWQM) predictions for the same dataset. The average annual observed and simulated N loss to drain flow were 43.8 and 44.4 kg N/ha (NCC) and 17.6 and 18.9 kg N/ha (CC). The slightly over predicted N loss for CC was because of over predicted nitrate concentration, which may be partly caused by slightly under predicted average annual rye shoot N (observed and simulated values were 47.8 and 46.0 kg N/ha). Also, recent research from the site suggests that the soil field capacity may be greater in CC while we used the same soil parameters for both treatments. A local sensitivity analysis suggests that increased field capacity affects HERMES simulations, which includes reduced drain flow nitrate concentrations, increased denitrification, and reduced drain flow volume. HERMES-simulated cumulative monthly drain flow and annual drain flow were reasonable compared to field data and HERMES performance was comparable to other published drainage model tests. Unlike the RZWQM simulations, however, the modified HERMES did riot accurately simulate the year to year variability in nitrate concentration difference between NCC and CC, possibly due in part to the lack of partial mixing and displacement of the soil solution. The results suggest that 1) the relatively simple model HERMES is a promising tool to estimate annual N loss to drain flow under corn-soybean rotations with winter rye as a cover crop and 2) soil field capacity is a critical parameter to investigate to more thoroughly understand and appropriately model denitrification and N losses to subsurface drainage. Published by Elsevier B.V.
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Lorite, I. J., Gabaldon-Leal, C., Ruiz-Ramos, M., Belaj, A., de la Rosa, R., Leon, L., et al. (2018). Evaluation of olive response and adaptation strategies to climate change under semi-arid conditions. Agric. Water Manage., 204, 247–261.
Abstract: AdaptaOlive is a simplified physically-based model that has been developed to assess the behavior of olive under future climate conditions in Andalusia, southern Spain. The integration of different approaches based on experimental data from previous studies, combined with weather data from 11 climate models, is aimed at overcoming the high degree of uncertainty in the simulation of the response of agricultural systems under predicted climate conditions. The AdaptaOlive model was applied in a representative olive orchard in the Baeza area, one of the main producer zone in Spain, with the cultivar ‘Picual’. Simulations for the end of the 21st century showed olive oil yield increases of 7.1 and 28.9% under rainfed and full irrigated conditions, respectively, while irrigation requirements decreased between 0.5 and 6.2% for full irrigation and regulated deficit irrigation, respectively. These effects were caused by the positive impact of the increase in atmospheric CO2 that counterbalanced the negative impacts of the reduction in rainfall. The high degree of uncertainty associated with climate projections translated into a high range of yield and irrigation requirement projections, confirming the need for an ensemble of climate models in climate change impact assessment. The AdaptaOlive model also was applied for evaluating adaptation strategies related to cultivars, irrigation strategies and locations. The best performance was registered for cultivars with early flowering dates and regulated deficit irrigation. Thus, in the Baeza area full irrigation requirements were reduced by 12% and the yield in rainfed conditions increased by 7% compared with late flowering cultivars. Similarly, regulated deficit irrigation requirements and yield were reduced by 46% and 18%, respectively, compared with full irrigation. The results confirm the promise offered by these strategies as adaptation measures for managing an olive crop under semi-arid conditions in a changing climate.
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Kopacz, M., & Twardy, S. (2013). Analysis of changes of permanent grasslands in the Carpathians based on the example of upper Dunajec and Raba river catchments (Vol. 133).
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Kersebaum, K., Kroes, J., Gobin, A., Takáč, J., Hlavinka, P., Trnka, M., et al. (2016). Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat. Water, 8(12), 571.
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 CO2 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.
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Gobin, A., Kersebaum, K., Eitzinger, J., Trnka, M., Hlavinka, P., Takáč, J., et al. (2017). Variability in the Water Footprint of Arable Crop Production across European Regions. Water, 9(2), 93.
Abstract: Crop growth and yield are affected by water use during the season: the green water footprint (WF) accounts for rain water, the blue WF for irrigation and the grey WF for diluting agri-chemicals. We calibrated crop yield for FAO’s water balance model “Aquacrop” at field level. We collected weather, soil and crop inputs for 45 locations for the period 1992–2012. Calibrated model runs were conducted for wheat, barley, grain maize, oilseed rape, potato and sugar beet. The WF of cereals could be up to 20 times larger than the WF of tuber and root crops; the largest share was attributed to the green WF. The green and blue WF compared favourably with global benchmark values (R² = 0.64–0.80; d = 0.91–0.95). The variability in the WF of arable crops across different regions in Europe is mainly due to variability in crop yield (c̅v̅ = 45%) and to a lesser extent to variability in crop water use (c̅v̅ = 21%). The WF variability between countries (c̅v̅ = 14%) is lower than the variability between seasons (c̅v̅ = 22%) and between crops (c̅v̅ = 46%). Though modelled yields increased up to 50% under sprinkler irrigation, the water footprint still increased between 1% and 25%. Confronted with drainage and runoff, the grey WF tended to overestimate the contribution of nitrogen to the surface and groundwater. The results showed that the water footprint provides a measurable indicator that may support European water governance.
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