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Projections of global climate models suggest that ongoing human-induced climate change will lead to an increase in the frequency of severe droughts in many important agricultural regions of the world. Eco-hydrological models that integrate current understanding of the interacting processes governing soil water balance and plant growth may be useful tools to predict the impacts of climate change on crop production. However, the validation status of these models for making predictions under climate change is still unclear, since few suitable datasets are available for model testing. One promising approach is to test models using data obtained in “space-for-time” substitution experiments, in which samples are transferred among locations with contrasting current climates in order to mimic future climatic conditions. An important advantage of this approach is that the soil type is the same, so that differences in soil properties are not confounded with the influence of climate on water balance and crop growth. In this study, we evaluate the capability of a relatively simple eco-hydrological model to reproduce 6 years (2013–2018) of measurements of soil water contents, water balance components and grass production made in weighing lysimeters located at two sites within the TERENO-SoilCan network in Germany. Three lysimeters are located at an upland site at Rollesbroich with a cool, wet climate, while three others had been moved from Rollesbroich to a warmer and drier climate on the lower Rhine valley floodplain at Selhausen. Four of the most sensitive parameters in the model were treated as uncertain within the framework of the GLUE (Generalized Likelihood Uncertainty Estimation) methodology, while the remaining parameters in the model were set according to site measurements or data in the literature. The model accurately reproduced the measurements at both sites, and some significant differences in the posterior ranges of the four uncertain parameters were found. In part

The effects of aggregating soil data (DAE) by areal majority of soil mapping units was explored for regional simulations with the soil-vegetation model CoupModel for a region in Germany (North Rhine-Westphalia). DAE were analysed for wheat yield, drainage, soil carbon mineralisation and nitrogen leaching below the root zone. DAE were higher for soil C mineralization and N leaching than for yield and drainage and were strongly related to the presence of specific soils within the study region. These soil types were associated to extreme simulated output variables compared to the mean variable in the region. The spatial aggregation of these key functional soils within sub-regions additionally influenced the DAE. A spatial analysis of their spatial pattern (i.e. their presence/absence, coverage and aggregation) can help in defining the appropriate grid resolution that would minimize the error caused by aggregating soil input data in regional simulations., QC 20180122

Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in southwestern Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM), greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970-1999) for an important agricultural production area in south-western Sweden based on monthly change factors for 2070-2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

The water and heat balances of an arable field and a forest in the boreal zone in Scandinavia were explored using 3 yr of observations and simulations with two different soil - vegetation - atmosphere transfer (SVAT) models over a 30-yr period. Results from a detailed mechanistic model [ coupled heat and mass transfer model ( COUP)] were compared with those obtained with a large-scale type of SVAT model used in the weather prediction model at the European Centre for Medium-Range Weather Forecasts [ECMWF tiled land surface scheme (TESSEL)]. The COUP model simulations agreed well with the observations from a seasonal perspective. The TESSEL model differed significantly from the measurements when standard operational parameter values were used. The introduction of a seasonal variation in leaf-area index values, tuned canopy resistance for forest, and a reduced roughness length over snow-covered open land reduced the discrepancies. Net radiation was 40% higher in the forest when compared with the arable land, based on 30-yr simulations with both models. Furthermore, the forest was a net source of sensible heat flux, whereas the arable land was a net sink. Because of different treatment of winter interception evaporation, forest latent heat flux based on the COUP model considerably exceeded that from the TESSEL model, and suggested that the total annual evaporation was higher from the forest than from arable land. The representation of interception evaporation in winter, as well as seasonal dynamics in vegetation properties are, thus, of considerable importance for adequate simulation of forest and arable land energy fluxes within the boreal zone., QC 20100525 QC 20110915

The objective of the present study was to assess the performance and recent improvements of the land surface scheme used operationally in the European Centre for Medium-Range Weather Forecasts (ECMWF) in a Scandinavian boreal forest climate/ecosystem. The previous (the 1999 scheme of P. Viterbo and A. K. Betts) and the new (Tiled ECMWF Surface Scheme for Exchange Processes over Land, TESSEL) surface schemes were validated by single-column runs against data from NOPEX (Northern Hemisphere Climate-Processes Land-Surface Experiment). Driving and validation datasets were prepared for a 3-yr period (1994-96). The new surface scheme, with separate surface energy balances for subgrid fractions (tiling), improved predictions of seasonal as well as diurnal variation in surface energy fluxes in comparison with the old scheme. Simulated wintertime evaporation improved significantly as a consequence of the introduced additional aerodynamic resistance for evaporation from snow lying under high vegetation. Simulated springtime evaporation also improved because the limitation of transpiration in frozen soils was now accounted for. However, downward sensible heat flux was still underestimated during winter, especially at nighttime, whereas soil temperatures were underestimated in winter and overestimated in summer. The new scheme also underestimated evaporation during dry periods in summer, whereas soil moisture was overestimated. Sensitivity tests showed that further improvements of simulated surface heat fluxes and soil temperatures could be obtained by calibration of parameters governing the coupling between the surface and the atmosphere and the ground heat flux, and parameters governing the water uptake by the vegetation. Model performance also improved when the seasonal variation in vegetation properties was included.

The objective of the present study was to assess the performance and recent improvements of the land surface scheme used operationally in the European Centre for Medium-Range Weather Forecasts (ECMWF) in a Scandinavian boreal forest climate/ecosystem. The previous (the 1999 scheme of P. Viterbo and A. K. Betts) and the new (Tiled ECMWF Surface Scheme for Exchange Processes over Land, TESSEL) surface schemes were validated by single-column runs against data from NOPEX (Northern Hemisphere Climate-Processes Land-Surface Experiment). Driving and validation datasets were prepared for a 3-yr period (1994-96). The new surface scheme, with separate surface energy balances for subgrid fractions (tiling), improved predictions of seasonal as well as diurnal variation in surface energy fluxes in comparison with the old scheme. Simulated wintertime evaporation improved significantly as a consequence of the introduced additional aerodynamic resistance for evaporation from snow lying under high vegetation. Simulated springtime evaporation also improved because the limitation of transpiration in frozen soils was now accounted for. However, downward sensible heat flux was still underestimated during winter, especially at nighttime, whereas soil temperatures were underestimated in winter and overestimated in summer. The new scheme also underestimated evaporation during dry periods in summer, whereas soil moisture was overestimated. Sensitivity tests showed that further improvements of simulated surface heat fluxes and soil temperatures could be obtained by calibration of parameters governing the coupling between the surface and the atmosphere and the ground heat flux, and parameters governing the water uptake by the vegetation. Model performance also improved when the seasonal variation in vegetation properties was included., QC 20100525

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QC 20100614

QC 20100614