Date palms are a cash crop and commonly irrigated using saline water. A better understanding of the processes involved in water use by date palms and their carbon budget is key to sustainable cultivation and saline irrigation scheduling. In this study, the process-oriented CoupModel was used to investigate the linked water and carbon fluxes in date palms under saline irrigation conditions. We compared experimental data for actual evapotranspiration (ETc act) and yield from trees grown in weighing lysimeters and irrigated at two salinity levels in 2006–2007 with an uncertainty-based calibration approach. The daily ETc act and annual yield of trees with the low-salinity irrigation in 2006 were used to calibrate the selected parameters, investigate model performance, and analyze parameter correlations. Further tests were undertaken, including the application of low-salinity irrigation in 2007 and high-salinity irrigation over two years. Dynamic modeling of the tree canopy and a radiation use efficiency approach, along with incorporating the salinity effects on plant respiration and consideration of internal water storage, accurately simulated the measured data. The model determined the direct responses of the date palms to varying irrigation water amounts and salinity, and atmospheric conditions. It robustly determined the characteristics of daily ETc act and annual yield for both irrigation salinities in each year. Based on the selected parameterization, the daily ETc act was accurately simulated for both irrigation salinities in each year. However, the yield was only accurately simulated for both irrigation salinities in 2006. In addition, the simulated amounts and calculated electrical conductivity of daily drainage water suggested that the model performed well in simulating the soil water and salinity conditions, particularly during the fruit growing season. In general, the lysimeter-based parameterization of the CoupModel applied to inter-yearly growth of palms under saline irrigation conditions helps long-term continuous simulations and agronomic applications.

Crop models are useful tools for predicting changes in yield and nitrogen losses in response to changes in agricultural management practices and climate. We used a soil-crop model (CoupModel) to interpret trends in yields, drainage, and nitrate leaching observed for two contrasting treatments (fertilized and unfertilized cereals) in a long-term field experiment (35 years) on a sandy loam in southern Sweden. The model was calibrated using a Monte Carlo-based method, in which the 30 best simulations of 10,000 model runs were identified based on multiple criteria. The posterior distributions differed significantly between the two treatments for 6 of the 16 parameters included. For example, the decomposition rate coefficient of the slow organic matter pool was significantly larger in the unfertilized treatment. The model simulated yearly drainage and nitrate leaching well overall, but did not fully capture between-year variations. Although the simulated mean annual nitrate leaching was 1.4 times greater in the fertilized treatment, N leached per unit of N harvest was twice as large in the unfertilized plot. The model simulated substantial decreases in yield for both treatments in 2018 in response to an extremely hot and dry summer, although not as large as that observed. The range in simulated annual N mineralization due to parameter uncertainty was wider in the fertilized treatment. We conclude that model calibration strategies require careful attention to how different management practices may influence decomposition and long-term N balance components in agroecosystems and that more data on especially belowground biomass would help in reducing uncertainties.

Globally, boreal forests act as important carbon sinks, however, drought and forest management could substantially alter the sink strength, though the controlling mechanisms of drought and management remain unclear. In this study, we combined the detailed process-based CoupModel with multiple measurements to study the impacts of recent drought and forest thinning on a boreal forest during 2018–2021. CoupModel after calibration showed high ability to represent the dynamics of long-term net ecosystem exchange and its responses to environmental changes. The model simulation showed that the canopy temperature exacerbated the dominant role in regulating the boreal forest growth during the 2018 extreme drought year with slight increase in the annual mean net carbon uptake by 76.65 g C/m2/yr compared to 2017. The posterior model simulations ensemble suggested that thinning of trees in 2019–2020 caused the boreal forest in 2020 to be a sink to slight source ([−229.95, 94.90] g C/m2/yr, 90 % confidence interval), while the observations depicted a small source (69.35 g C/m2/yr). Moreover, rapid recovery of the boreal forest to a carbon sink was found in 2021, though remaining smaller than the carbon sink in 2017. Overall, the negative impacts from drought and harvest (2018–2021) were found to have offset the positive impacts from climate by 8 % - 92 %, on the net carbon uptake. This study highlights the resilience of boreal forests as carbon sink and provides new insights into the boreal forests' responses to both climate change and management.

A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. We propose an original, detailed approach for calibration of such models, which we refer to as a calibration protocol. The protocol covers all the steps in the calibration workflow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values, and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are "obligatory" parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their "usual" calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and reduced prediction error by 11%.

Efforts to develop effective climate mitigation strategies for agriculture require methods to estimate nitrous oxide (N2O) emissions from soil. Process-based biogeochemical models have been often used for field- and large-scale estimates, while the sensitivity and uncertainty of model applications to incubation experiments are less investigated. In this study, a process-oriented model (CoupModel) was used to simulate N2O and CO2 fluxes and soil mineral nitrogen (N) contents in a short-term (43 d) factorial incubation experiment (16 treatments). A global sensitivity analysis (GSA) approach, "Morris screening", was applied to quantify parameter sensitivity. The GSA suggested that a higher number of sensitive parameters was associated with N2O flux estimates and that inter-treatment variations in parameter sensitivities were distinguished by soil moisture levels or NO3- content and residue types. Important parameters regarding N2O flux estimates were linked to the decomposability of soil organic matter (e.g., organic C pool sizes) and the denitrification process (e.g., Michaelis constant and denitrifier respiratory rates). After calibration, the model better captured temporal variations and magnitude of gas fluxes and mineral N in unamended soils than in residue-amended soils. Low-magnitude daily and cumulative N2O fluxes were well simulated with mean errors (MEs) close to zero, but the model tended to underestimate N2O fluxes, as observed daily values increased by over 0.1 gNm 2 d 1, in which the major mismatch was due to limited success of the model to describe the high emissions during the first few days after crop residue addition. A larger uncertainty was also seen in the magnitude of pulse emissions by the posterior simulations. We also evaluated ancillary variables regarding N cycling, which indicated that more frequent measurements and additional types of observed data such as soil oxygen content and the microbial sources of emitted N2O are required to further evaluate model performance and biases. The major challenges for calibration were associated with high sensitivities of denitrification parameters to initial soil abiotic conditions and the instantaneous residue amendment. Model structure uncertainties and improved modeling practices in the context of incubation experiments were discussed.

Future Arctic tundra primary productivity and vegetation community composition will partly be determined by nitrogen (N) availability in a warmer climate. N mineralization rates are predicted to increase in both winter and summer, but because N demand and –mobility varies across seasons, the fate of mineralized N remains uncertain. N mineralized in winter is released in a “pulse” upon snowmelt and soil thaw, with the potential for lateral redistribution in the landscape. In summer, the release is into an active rhizosphere with high local biological N demand. In this study, we investigated the ecosystem sensitivity to increased lateral N input and near-surface warming, respectively and in combination, with a numerical ecosystem model (CoupModel) parameterized to simulate ecosystem biogeochemistry for a tundra heath ecosystem in West Greenland. Both measurements and model results indicated that plants were poor utilizers of increased early-season lateral N input, indicating that higher winter N mineralization rates may have limited impact on plant growth and carbon (C) sequestration for a hillslope ecosystem. The model further suggested that, although deciduous shrubs were the plant type with overall most lateral N gain, evergreen shrubs appear to have a comparative advantage utilizing early-season N. In contrast, near-surface summer warming increased plant biomass and N uptake, moving N from soil to plant N pools, and offered an advantage to deciduous plants. Neither simulated high lateral N fluxes nor near-surface soil warming suggests that mesic tundra heaths will be important sources of N2O under warmer conditions. Our work highlights how winter and summer warming may play different roles in tundra ecosystem N and C budgets depending on plant community composition.

Globally, water-saving irrigation plays a vital role in agricultural ecosystems to achieve sustainable food pro-duction under climate change. Irrigation under mulch (IUM) system has been widely used in modern agricultural ecosystems due to its high water use efficiency, but it remains unclear how each component of the water and energy processes responds to this agricultural management practice. Current modeling approaches are inade-quate in investigating the impacts of IUM management on water-energy balance, which have shown more complicated than non-mulched management. Therefore, this study provided an explicit simulation of water and energy fluxes in IUM system using a process-oriented ecosystem model-CoupModel and the three years of the eddy covariance (EC) measurements. Based on Monte Carlo and the multiple model performance evaluation criteria, most of the model sensitive parameters were well constrained and 32 potentially important parameters, e.g., iscovevap, the fraction of mulch coverage, were identified to characterize the impacts of plastic mulching on energy balance and water transport. After proper calibration, the coefficient of determination (R2) for measured and simulated soil temperature (T) and soil water content (SWC) was 0.79 and 0.60, respectively, and the R2 for T and SWC during the validation period were 0.91 and 0.71, respectively. Furthermore, we found that there was a strong coupling between the parameters of the water and energy processes, which would restrict the simulation results due to the correlation between the parameters and the evaluation indices. This study presented a sys-tematic model parameters calibration in the agricultural ecosystem implemented with IUM and provided with a more comprehensive understanding of the water and energy balance in cropland. These results would help agricultural model development with more detailed considerations of the water-saving management.

Understanding N budgets of tundra ecosystems is crucial for projecting future changes in plant community composition, greenhouse gas balances and soil N stocks. Winter warming can lead to higher tundra winter nitrogen (N) mineralization rates, while summer warming may increase both growing season N mineralization and plant N demand. The undulating tundra landscape is inter-connected through water and solute movement on top of and within near-surface soil, but the importance of lateral N fluxes for tundra N budgets is not well known. We studied the size of lateral N fluxes and the fate of lateral N input in the snowmelt period with a shallow thaw layer, and in the late growing season with a deeper thaw layer. We used 15N to trace inorganic lateral N movement in a Low-arctic mesic tundra heath slope in West Greenland and to quantify the fate of N in the receiving area. We found that half of the early-season lateral N input was retained by the receiving ecosystem, whereas half was transported downslope. Plants appear as poor utilizers of early-season N, indicating that higher winter N mineralization may influence plant growth and carbon (C) sequestration less than expected. Still, evergreen plants were better at utilizing early-season N, highlighting how changes in N availability may impact plant community composition. In contrast, later growing season lateral N input was deeper and offered an advantage to deeper-rooted deciduous plants. The measurements suggest that N input driven by future warming at the study site will have no significant impact on the overall N2O emissions. Our work underlines how tundra ecosystem N allocation, C budgets and plant community composition vary in their response to lateral N inputs, which may help us understand future responses in a warmer Arctic.

This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, referred to as Coup-CNP). The extended Coup-CNP, which explicitly considers the symbiosis between soil microbes and plant roots, enables simulations of coupled carbon (C), nitrogen (N), and P dynamics for terrestrial ecosystems. The model was evaluated against observed forest growth and measured leaf C/P, C/N, and N/P ratios in four managed forest regions in Sweden. The four regions form a climatic and fertility gradient from 64°N (northern Sweden) to 56°N (southern Sweden), with mean annual temperature varying from 0.7-7.1 °C and soil C/N and C/P ratios varying between 19.8-31.5 and 425-633, respectively. The growth of the southern forests was found to be P-limited, with harvested biomass representing the largest P losses over the studied rotation period. The simulated P budgets revealed that southern forests are losing P, while northern forests have balanced P budgets. Symbiotic fungi accounted for half of total plant P uptake across all four regions, which highlights the importance of fungal-tree interactions in Swedish forests. The results of a sensitivity analysis demonstrated that optimal forest growth occurs at a soil N/P ratio between 15-20. A soil N/P ratio above 15-20 will result in decreased soil C sequestration and P leaching, along with a significant increase in N leaching. The simulations showed that Coup-CNP could describe shifting from being mostly N-limited to mostly P-limited and vice versa. The potential P-limitation of terrestrial ecosystems highlights the need for biogeochemical ecosystem models to consider the P cycle. We conclude that the inclusion of the P cycle enabled the Coup-CNP to account for various feedback mechanisms that have a significant impact on ecosystem C sequestration and N leaching under climate change and/or elevated N deposition.

Soil freezing/thawing is an important mechanism to control soil water and heat redistribution in mid-to-high latitudes. Salt in the agricultural soil from mid-to-high latitudes can alter characteristics of soil freezing/thawing cycle and then affect soil thermal and hydrological processes in winter and finally cause salinization in spring. To quantify the impacts of soil salinization on soil water and heat transport in saline soils, we conducted field experiments on soil water and heat dynamics in two typical agricultural regions of northern China with different climate and soil conditions. The coupled soil heat and water model—CoupModel has been extended to account for the dynamic impacts of salt on freezing point depression. The newly-added module improved the representation of soil freezing point depression by significantly improving model performance between simulated and measured soil temperatures, especially around freezing point, with mean error (ME) for the soil temperature at various depths reduced by 16% to 77% for the entire winter period. With a systematic model calibration approach, processes related to energy balance and soil freezing/thawing have been well constrained for both study sites with different characteristics for soil hydrology and energy balance. The model generally showed good performance with respect to soil moisture and temperature for both the calibration and validation periods. Our study has demonstrated a new modeling approach to successfully account for the impacts of salt on soil freezing/thawing and the new module can be a useful tool to address the salinization problems in mid-to-high latitudes with respect to climate change and water management.