Sensitivity of simulated crop yield and nitrate leaching of the wheat-maize cropping system in the North China Plain to model parameters

Process-based crop simulation models are often over-parameterised and are therefore difficult to calibrate properly. Following this rationale, the Morris screening sensitivity method was carried out on the DAISY model to identify the most influential input parameters operating on selected model outputs, i.e. crop yield, grain nitrogen (N), evapotranspiration and N leaching. The results obtained refer to the winter wheat-summer maize cropping system in the North China Plain. In this study, four different N fertiliser treatments over six years were considered based on a randomised field experiment at Luancheng Experimental Station to elucidate the impact of weather and nitrogen inputs on model sensitivity. A total of 128 parameters were considered for the sensitivity analysis. The ratios [output changes/parameter increments] demonstrated high standard deviations for the most relevant parameters, indicating high parameter non-linearity/interactions. In general, about 34 parameters influenced the outputs of the DAISY model for both crops. The most influential parameters depended on the output considered with sensitivity patterns consistent with the expected dominant processes. Interestingly, some parameters related to the previous crop were found to affect output variables of the following crop, illustrating the importance of considering crop sequences for model calibration. The developed RDAISY toolbox used in this study can serve as a basis for following sensitivity analysis of the DAISY model, thus enabling the selection of the most influential parameters to be considered with model calibration

Future socioeconomic conditions may have a larger impact than climate change on nutrient loads to the Baltic Sea

The Baltic Sea is suffering from eutrophication caused by nutrient discharges from land to sea, and these loads might change in a changing climate. We show that the impact from climate change by mid-century is probably less than the direct impact of changing socioeconomic factors such as land use, agricultural practices, atmospheric deposition, and wastewater emissions. We compare results from dynamic modelling of nutrient loads to the Baltic Sea under projections of climate change and scenarios for shared socioeconomic pathways. Average nutrient loads are projected to increase by 8% and 14% for nitrogen and phosphorus, respectively, in response to climate change scenarios. In contrast, changes in the socioeconomic drivers can lead to a decrease of 13% and 6% or an increase of 11% and 9% in nitrogen and phosphorus loads, respectively, depending on the pathway. This indicates that policy decisions still play a major role in climate adaptation and in managing eutrophication in the Baltic Sea region.Peer reviewe

Impacts of changing society and climate on nutrient loading to the Baltic Sea

This paper studies the relative importance of societal drivers and changing climate on anthropogenic nutrient inputs to the Baltic Sea. Shared Socioeconomic Pathways and Representative Concentration Pathways are extended at temporal and spatial scales relevant for the most contributing sectors. Extended socioeconomic and climate scenarios are then used as inputs for spatially and temporally detailed models for population and land use change, and their subsequent impact on nutrient loading is computed. According to the model simulations, several factors of varying influence may either increase or decrease total nutrient loads. In general, societal drivers outweigh the impacts of changing climate. Food demand is the most impactful driver, strongly affecting land use and nutrient loads from agricultural lands in the long run. In order to reach the good environmental status of the Baltic Sea, additional nutrient abatement efforts should focus on phosphorus rather than nitrogen. Agriculture is the most important sector to be addressed under the conditions of gradually increasing precipitation in the region and increasing global demand for food. (C) 2020 The Authors. Published by Elsevier B.V.Peer reviewe

Influence of weather and endogenous cycles on spatiotemporal yield variation in oil palm

Oil palm is the major source of vegetable oil in the world and Indonesia is the main palm oil producing country. There is limited knowledge on the factors accounting for spatial and temporal variation in fresh fruit bunches (FFB) yield. Here we investigated relationships between weather and endogenous factors with FFB yield and its components (bunch number and individual bunch weight) using data collected from well-managed plantations in Indonesia. The database included many sites and years (total of 136 block-years observations), portraying a wide range of FFB yield and environmental conditions. We used average annual values to detect spatial variations in yield associated with weather, and monthly values to detect temporal yield variations in yield associated with weather and endogenous cycles. We found that water stress was the key factor accounting for the spatial and/or temporal variation in FFB yield. Our analysis also highlights the importance of vapor pressure deficit (VPD) as a stress factor in oil palm, with this study being the first to demonstrate the negative relationship between yield and VPD and yield and water-use efficiency at the block level. Meteorological anomalies during the bunch failure, anthesis, and sex differentiation periods had the largest impact on yield. Besides climate factors, we confirmed the existence of endogenous yield cycles, with high-yield cycles typically followed by low-yield cycles and vice versa. Our findings extend current knowledge about sources of variation in oil palm yield, providing useful information to describe oil palm production environments and improve oil palm modeling and yield forecasting.Fil: Monzon, Juan Pablo. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; ArgentinaFil: Jabloun, Mohamed. University of Agriculture Wageningen; Países BajosFil: Cock, James. Centro Internacional de Agricultura Tropical; ColombiaFil: Caliman, Jean Pierre. Smart Research Institute; IndonesiaFil: Couëdel, Antoine. Universidad de Nebraska - Lincoln; Estados UnidosFil: Donough, Christopher R.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Vui, Philip Ho Vun. Wilmar International; IndonesiaFil: Lim, Ya Li. Universidad de Nebraska - Lincoln; Estados UnidosFil: Mathews, Joshua. Research Centre Pt Bumitama Gunajaya Agro; IndonesiaFil: Oberthür, Thomas. Mohammed Vi Polytechnic University; MarruecosFil: Prabowo, Noto E.. Jln. A. Yani No. 2; IndonesiaFil: Rattalino Edreira, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina. Universidad de Nebraska - Lincoln; Estados UnidosFil: Sidhu, Manjit. Tebing Tinggi Deli; IndonesiaFil: Slingerland, Maja A.. University of Agriculture Wageningen; Países BajosFil: Sugianto, Hendra. Universidad de Nebraska - Lincoln; Estados UnidosFil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados Unido

Influence of weather and endogenous cycles on spatiotemporal yield variation in oil palm

Oil palm is the major source of vegetable oil in the world and Indonesia is the main palm oil producing country. There is limited knowledge on the factors accounting for spatial and temporal variation in fresh fruit bunches (FFB) yield. Here we investigated relationships between weather and endogenous factors with FFB yield and its components (bunch number and individual bunch weight) using data collected from well-managed plantations in Indonesia. The database included many sites and years (total of 136 block-years observations), portraying a wide range of FFB yield and environmental conditions. We used average annual values to detect spatial variations in yield associated with weather, and monthly values to detect temporal yield variations in yield associated with weather and endogenous cycles. We found that water stress was the key factor accounting for the spatial and/or temporal variation in FFB yield. Our analysis also highlights the importance of vapor pressure deficit (VPD) as a stress factor in oil palm, with this study being the first to demonstrate the negative relationship between yield and VPD and yield and water-use efficiency at the block level. Meteorological anomalies during the bunch failure, anthesis, and sex differentiation periods had the largest impact on yield. Besides climate factors, we confirmed the existence of endogenous yield cycles, with high-yield cycles typically followed by low-yield cycles and vice versa. Our findings extend current knowledge about sources of variation in oil palm yield, providing useful information to describe oil palm production environments and improve oil palm modeling and yield forecasting

The chaos in calibrating crop models

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of system models and has an important impact on simulated values. Here we propose and illustrate a novel method of developing guidelines for calibration of system models. Our example is calibration of the phenology component of crop models. The approach is based on a multi-model study, where all teams are provided with the same data and asked to return simulations for the same conditions. All teams are asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.HighlightsWe propose a new approach to deriving calibration recommendations for system modelsApproach is based on analyzing calibration in multi-model simulation exercisesResulting recommendations are holistic and anchored in actual practiceWe apply the approach to calibration of crop models used to simulate phenologyRecommendations concern: objective function, parameters to estimate, software usedCompeting Interest StatementThe authors have declared no competing interest

Similar estimates of temperature impacts on global wheat yield by three independent methods

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.<br/

Reconciling estimates of climate change effects on nitrate leaching from agricultural crops

Nitrate leaching from agricultural systems constitutes a severe environmental effect in regions with valuable groundwater resources and vulnerable aquatic ecosystems. Therefore cropping systems should in many parts of Europe reduce the amount of nitrate leached from the root zone. Since soil nitrogen transformation and loss processes are highly influenced by climate, including temperature and precipitation, estimates of climate change effects on nitrate leaching is in high demand for evaluating future groundwater and surface water protection policies. Modelling studies using both the FASSET and Daisy models for cereal crops as well as arable crop rotations in Denmark have shown increased nitrate leaching under projected climate change. Sensitivity analyses using these models have shown a higher response to changes in temperature than to precipitation, although in particular precipitation responses differ between soil types. Simulations for crop rotations show that current catch crop management may not be sufficient to maintain low nitrate leaching levels in future. These effects of temperature and precipitation as well as crop management are confirmed in an empirical analysis of nitrate leaching from a long-term cropping system experiment in Denmark. The main uncertainties on climate change effects on future nitrate leaching appears to be related to effects of climate change on soil organic matter and thus on the amount of soil total N available for mineralization as well as the effects of enhanced atmospheric CO2 concentration on crop residue quality and N mineralization

Effect of temperature and precipitation on nitrate leaching from organic cereal cropping systems in Denmark

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