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158 results on '"Yeluripati, Jagadeesh"'

5. Management and spatial resolution effects on yield and water balance at regional scale in crop models

Author

Constantin, Julie, Raynal, Helene, Casellas, Eric, Hoffmann, Holger, Bindi, Marco, Doro, Luca, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balász, Haas, Edwin, Kersebaum, Kurt-Christian, Klatt, Steffen, Kuhnert, Matthias, Lewan, Elisabet, Maharjan, Ganga Ram, Moriondo, Marco, Nendel, Claas, Roggero, Pier Paolo, Specka, Xenia, Trombi, Giacomo, Villa, Ana, Wang, Enli, Weihermüller, Lutz, Yeluripati, Jagadeesh, Zhao, Zhigan, Ewert, Frank, and Bergez, Jacques-Eric

Published
2019
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10. Modeling denitrification: can we report what we don’t know?

Author

Grosz, Balázs Péter, primary, Matson, Amanda, additional, Butterbach-Bah, Klaus, additional, Clough, Timothy, additional, Davidson, Eric A., additional, Dechow, Rene, additional, DelGrosso, Stephen, additional, Diamantopoulos, Efstathios, additional, Dörsch, Peter, additional, Haas, Edwin, additional, He, Hongxing, additional, Henri, Christopher Vincent, additional, Hui, Dafeng, additional, Kleineidam, Kristina, additional, Kraus, David, additional, Kuhnert, Matthias, additional, Léonard, Joël, additional, Mueller, Christoph, additional, Petersen, Søren O., additional, Sihi, Debjani, additional, Vogeler, Iris, additional, Well, Reinhard, additional, Yeluripati, Jagadeesh Babu, additional, Zhang, Jie, additional, and Scheer, Clemens, additional

Published
2023
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13. Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables

Author

Zhao, Gang, Hoffmann, Holger, van Bussel, Lenny G. J., Enders, Andreas, Specka, Xenia, Sosa, Carmen, Yeluripati, Jagadeesh, Tao, Fulu, Constantin, Julie, Raynal, Helene, Teixeira, Edmar, Grosz, Balázs, Doro, Luca, Zhao, Zhigan, Nendel, Claas, Kiese, Ralf, Eckersten, Henrik, Haas, Edwin, Vanuytrecht, Eline, Wang, Enli, Kuhnert, Matthias, Trombi, Giacomo, Moriondo, Marco, Bindi, Marco, Lewan, Elisabet, Bach, Michaela, Kersebaum, Kurt-Christian, Rötter, Reimund, Roggero, Pier Paolo, Wallach, Daniel, Cammarano, Davide, Asseng, Senthold, Krauss, Gunther, Siebert, Stefan, Gaiser, Thomas, and Ewert, Frank

Published
2015

15. Does green vertical farming offer a sustainable alternative to conventional methods of production?: A case study from Scotland.

Author

Sandison, Frances, Yeluripati, Jagadeesh, and Stewart, Derek

Subjects
*VERTICAL farming, *SUSTAINABLE agriculture, *GREENHOUSE gases, *AGRICULTURE, *ELECTRIC power production, *LETTUCE, *TRADITIONAL farming
Abstract

Climate change is an existential global reality that is placing considerable stress on agriculture sectors. With the recognition of the impacts of climate change on food security, there has been a greater uptake of controlled environment agriculture (CEA) to provide climate‐resilient and high‐quality production. Vertical farming (VF) can allow primary production in urban locations as well as reducing seasonality and variability in produce. It is emerging as an alternative to traditional farming methods. This research aimed to explore the major environmental impacts of VF produce in comparison with conventional farming methods, using lettuce as an example crop. Life cycle analysis indicate that electricity consumption by VF account for 91% of the carbon footprint. Under the 2019 Scottish electricity mix, VF did not offer a viable competitor for UK open‐farmed lettuce or Spanish imports in terms of low greenhouse gas emissions (at approximately 1.49 kgCO2 eq. kg−1). However, with increasing use of renewable electricity in the national mix, by 2020, this had dropped to 0.42 kgCO2 eq. kg−1 making it comparable with UK open‐field agriculture (at approximately 0.46 kgCO2 eq. kg−1). Under a 100% renewable electricity generation scenario, VF‐related emissions drop further (to 0.33 kgCO2 eq. kg−1). This would potentially offer a low‐carbon production method not subject to seasonality which is better than that reported by most other production methods and offers higher water and nutrient efficiency. This research highlights green VF as potential alternative for sustainable future produce especially under changing climate scenarios. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Systems approaches in global change and biogeochemistry research

Author

Smith, Pete, Albanito, Fabrizio, Bell, Madeleine, Bellarby, Jessica, Blagodatskiy, Sergey, Datta, Arindam, Dondini, Marta, Fitton, Nuala, Flynn, Helen, Hastings, Astley, Hillier, Jon, Jones, Edward O., Kuhnert, Matthias, Nayak, Dali R., Pogson, Mark, Richards, Mark, Sozanska-Stanton, Gosia, Wang, Shifeng, Yeluripati, Jagadeesh B., Bottoms, Emily, Brown, Chris, Farmer, Jenny, Feliciano, Diana, Hao, Cui, Robertson, Andy, Vetter, Sylvia, Wong, Hon Man, and Smith, Jo

Published
2012

19. Estimating changes in Scottish soil carbon stocks using ECOSSE. II. Application

Author

Smith, Jo, Gottschalk, Pia, Bellarby, Jessica, Chapman, Stephen, Lilly, Allan, Towers, Willie, Bell, John, Coleman, Kevin, Nayak, Dali, Richards, Mark, Hillier, Jon, Flynn, Helen, Wattenbach, Martin, Aitkenhead, Matt, Yeluripati, Jagadeesh, Farmer, Jenny, Milne, Ronnie, Thomson, Amanda, Evans, Chris, Whitmore, Andy, Falloon, Pete, and Smith, Pete

Published
2010

21. What makes an operational farm soil carbon code? Insights from a global comparison of existing soil carbon codes using a structured analytical framework

Author

Black, Helaina I. J., primary, Reed, Mark S., additional, Kendall, Helen, additional, Parkhurst, Robert, additional, Cannon, Nicola, additional, Chapman, Pippa J., additional, Orman, Matthew, additional, Phelps, Jenny, additional, Rudman, Hannah, additional, Whaley, Sarah, additional, Yeluripati, Jagadeesh, additional, and Ziv, Guy, additional

Published
2022
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22. Mathematical Modeling of Greenhouse Gas Emissions from Agriculture for Different End Users

Author

Hillier, Jon, primary, Abdalla, Mohammed, additional, Bellarby, Jessica, additional, Albanito, Fabrizio, additional, Datta, Arindam, additional, Dondini, Marta, additional, Fitton, Nuala, additional, Hallett, Paul, additional, Hastings, Astley, additional, Jones, Edward, additional, Kuhnert, Matthias, additional, Nayak, Dali, additional, Pogson, Mark, additional, Richards, Mark, additional, Smith, Jo, additional, Vetter, Sylvia, additional, Yeluripati, Jagadeesh, additional, and Smith, Pete, additional

Published
2015
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23. Uncertainties in Scaling-Up Crop Models for Large-Area Climate Change Impact Assessments

Author

Ewert, Frank, primary, van Bussel, Lenny G. J., additional, Zhao, Gang, additional, Hoffmann, Holger, additional, Gaiser, Thomas, additional, Specka, Xenia, additional, Nendel, Claas, additional, Kersebaum, Kurt-Christian, additional, Sosa, Carmen, additional, Lewan, Elisabet, additional, Yeluripati, Jagadeesh, additional, Kuhnert, Matthias, additional, Tao, Fulu, additional, Rötter, Reimund, additional, Constantin, Julie, additional, Raynal, Helene, additional, Wallach, Daniel, additional, Teixeira, Edmar, additional, Grosz, Balasz, additional, Bach, Michaela, additional, Doro, Luca, additional, Roggero, Pier Paolo, additional, Zhao, Zhigan, additional, Wang, Enli, additional, Kiese, Ralf, additional, Haas, Edwin, additional, Eckersten, Henrik, additional, Trombi, Giacomo, additional, Bindi, Marco, additional, Klein, Christian, additional, Biernath, Christian, additional, Heinlein, Florian, additional, Priesack, Eckart, additional, Cammarano, Davide, additional, Asseng, Senthold, additional, Elliott, Joshua, additional, Glotter, Michael, additional, Basso, Bruno, additional, Baigorria, Guillermo A., additional, Romero, Consuelo C., additional, and Moriondo, Marco, additional

Published
2015
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32. Estimating agro-ecosystem carbon balance of northern Japan, and comparing the change in carbon stock by soil inventory and net biome productivity

Author

Li, Xi, Toma, Yo, Yeluripati, Jagadeesh, Iwasaki, Shinya, Bellingrath-Kimura, Sonoko D., Jones, Edward O., and Hatano, Ryusuke

Subjects
Carbon sequestration, Soil inventory, Regional scale, Uncertainty, Net biome productivity, Agriculture
Abstract

Soil C sequestration in croplands is deemed to be one of the most promising greenhouse gas mitigation options for agriculture. We have used crop-level yields, modeled heterotrophic respiration (Rh) and land use data to estimate spatio-temporal changes in regional scale net primary productivity (NPP), plant C inputs, and net biome productivity (NBP) in northern Japan's arable croplands and grasslands for the period of 1959–2011. We compared the changes in C stocks derived from estimated NBP and using repeated inventory datasets for each individual land use type from 2005 to 2011. For the entire study region of 2193 ha, overall annual plant C inputs to the soil constituted 37% of total region NPP. Plant C inputs in upland areas (excluding bush/fallow) could be predicted by climate variables. Overall NBP for all land use types increased from − 1.26 Mg C ha− 1 yr− 1 in 1959–0.26 Mg C ha− 1 yr− 1 in 2011. However, upland and paddy fields showed a decreased in NBP over the period of 1959–2011, under the current C input scenario. From 1988, an increase in agricultural abandonment (bush/fallow) and grassland cover caused a slow increase in the regional C pools. The comparison of carbon budgets using the NBP estimation method and the soil inventory method indicated no significant difference between the two methods. Our results showed C loss in upland crops, paddy fields and sites that underwent land use change from paddy field to upland sites. We also show C gain in grassland from 2005 to 2011. An underestimation of NBP or an overestimation of repeated C inventories cannot be excluded, but either method may be suitable for tracking absolute changes in soil C, considering the uncertainty associated with these methods.

Published
2016

33. Seasonal patterns of greenhouse gas emissions from a forest‐to‐bog restored site in northern Scotland: Influence of microtopography and vegetation on carbon dioxide and methane dynamics.

Author

Mazzola, Valeria, Perks, Mike P., Smith, Jo, Yeluripati, Jagadeesh, and Xenakis, Georgios

Subjects
CARBON dioxide, BOGS, GAS dynamics, GREENHOUSE gases, CARBON cycle, METHANE, PEATLAND restoration
Abstract

Northern peatlands play an important role in the regulation of the atmospheric greenhouse gas (GHG) balance, functioning as a net carbon sink with low rates of organic decomposition. However, perturbations such as drainage increase peat oxidation, which may lead to enhanced gaseous release of carbon. For this reason, the number of restoration projects that aim to rewet blanket bogs has increased in the last few years, but there is still a lack of understanding of the impact of restoration on emissions of greenhouse gases, such as methane, particularly in sites restored from forestry. In this paper, we investigate the seasonal greenhouse gas dynamics in a forest‐to‐bog restoration site in Scotland. We analyse the effects of restoration on both carbon dioxide and methane fluxes, and investigate which site factors (microtopography, vegetation type, soil moisture and temperature) drive the processes of gaseous exchange between the bog surface and the atmosphere. Our results show that the original surface is near greenhouse gase equilibrium at −0.28 gCO2eq m2·day−1 and that microtopographic features act as a net greenhouse gas sink (ridges = −0.94 gCO2eq m2·day−1 and furrows = −0.86 gCO2eq m2·day−1), whereas the bog pool is a net source of greenhouse gases (0.98 gCO2eq m2·day−1). We found different vegetation species play a key role in greenhouse gas flux dynamics, especially in forestry‐derived microtopographical features, and their presence and influence on greenhouse gas dynamics should be accounted for to provide a more comprehensive understanding of emissions associated with restoration management practices. Highlights: GHG (CO2 and CH4) dynamics in a boreal peatland restored from forestry are mainly affected by microtopography and vegetation.Forestry‐derived microforms (ridges and furrows) are better GHG sinks than pools (GHG emitters) and original surfaces (near GHG equilibrium).The presence of Trichophorum cespitosum leads to higher CH4 emissions.Restoration practices like terraforming may create a short‐term pulse net GHG emission due to an increase of both CH4 and CO2 fluxes. [ABSTRACT FROM AUTHOR]

Published
2021
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34. Simulation of soil organic carbon effects on long-term winter wheat (Triticum aestivum) production under varying fertilizer inputs

Author

Ghaley, Bhim Bahadur, Wosten, Henk, Olesen, Jørgen Eivind, Schelde, Kirsten, Baby, Sanmohan, Karki, Yubaraj K., Borgesen, Christen D., Smith, Pete, Yeluripati, Jagadeesh, Ferrise, Roberto, Bindi, Marco, Kuikman, Peter, Lesschen, Jan-Peter, Porter, John Roy, Ghaley, Bhim Bahadur, Wosten, Henk, Olesen, Jørgen Eivind, Schelde, Kirsten, Baby, Sanmohan, Karki, Yubaraj K., Borgesen, Christen D., Smith, Pete, Yeluripati, Jagadeesh, Ferrise, Roberto, Bindi, Marco, Kuikman, Peter, Lesschen, Jan-Peter, and Porter, John Roy

Published
2018

35. Simulation of soil organic carbon effects on long-term winter wheat (Triticum aestivum) production under varying fertilizer inputs

Author

Ghaley, Bhim B., Wösten, Henk, Olesen, Jørgen E., Schelde, Kirsten, Baby, Sanmohan, Karki, Yubaraj K., Børgesen, Christen D., Smith, Pete, Yeluripati, Jagadeesh, Ferrise, Roberto, Bindi, Marco, Kuikman, Peter, Lesschen, Jan Peter, Porter, John R., Ghaley, Bhim B., Wösten, Henk, Olesen, Jørgen E., Schelde, Kirsten, Baby, Sanmohan, Karki, Yubaraj K., Børgesen, Christen D., Smith, Pete, Yeluripati, Jagadeesh, Ferrise, Roberto, Bindi, Marco, Kuikman, Peter, Lesschen, Jan Peter, and Porter, John R.

Abstract

Soil organic carbon (SOC) has a vital role to enhance agricultural productivity and for mitigation of climate change. To quantify SOC effects on productivity, process models serve as a robust tool to keep track of multiple plant and soil factors and their interactions affecting SOC dynamics. We used soil-plant-atmospheric model viz. DAISY, to assess effects of SOC on nitrogen (N) supply and plant available water (PAW) under varying N fertilizer rates in winter wheat (Triticum aestivum) in Denmark. The study objective was assessment of SOC effects on winter wheat grain and aboveground biomass accumulation at three SOC levels (low: 0.7% SOC; reference: 1.3% SOC; and high: 2% SOC) with five nitrogen rates (0–200 kg N ha−1) and PAW at low, reference, and high SOC levels. The three SOC levels had significant effects on grain yields and aboveground biomass accumulation at only 0–100 kg N ha−1 and the SOC effects decreased with increasing N rates until no effects at 150–200 kg N ha−1. PAW had significant positive correlation with SOC content, with high SOC retaining higher PAW compared to low and reference SOC. The mean PAW and SOC correlation was given by PAW% = 1.0073 × SOC% + 15.641. For the 0.7–2% SOC range, the PAW increase was small with no significant effects on grain yields and aboveground biomass accumulation. The higher winter wheat grain and aboveground biomass was attributed to higher N supply in N deficient wheat production system. Our study suggested that building SOC enhances agronomic productivity at only 0–100 kg N ha−1. Maintenance of SOC stock will require regular replenishment of SOC, to compensate for the mineralization process degrading SOC over time. Hence, management can maximize realization of SOC benefits by building up SOC and maintaining N rates in the range 0–100 kg N ha−1, to reduce the off-farm N losses depending on the environmental zones, land use and the production system.

Published
2018

37. Response to Letter to the Editor “Comments on “Modelling soil organic carbon storage with RothC in irrigated Vertisols under cotton cropping systems in the sub-tropics” (Nimai Senapati, Nilantha R. Hulugalle, Pete Smith, Brian R. Wilson, Jagadeesh B. Yeluripati, Heiko Daniel, Subhadip Ghosh, Peter Lockwood. Soil & Tillage Research 143 (2014) 38–49)”

Author

Senapati, Nimai, Hulugalle, Nilantha R., Smith, Pete, Wilson, Brian R., Yeluripati, Jagadeesh B., Daniel, Heiko, Ghosh, Subhadip, and Lockwood, Peter

Published
2016
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38. Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs

Author

Ghaley, Bhim B., primary, Wösten, Henk, additional, Olesen, Jørgen E., additional, Schelde, Kirsten, additional, Baby, Sanmohan, additional, Karki, Yubaraj K., additional, Børgesen, Christen D., additional, Smith, Pete, additional, Yeluripati, Jagadeesh, additional, Ferrise, Roberto, additional, Bindi, Marco, additional, Kuikman, Peter, additional, Lesschen, Jan-Peter, additional, and Porter, John R., additional

Published
2018
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41. Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

Author

Kuhnert, Matthias, Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Van Oijen, Marcel, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balász, Haas, Edwin, Kersebaum, Kurt-Christian, Kiese, Ralf, Klatt, Steffen, Lewan, Elisabet, Nendel, Claas, Raynal, Helene, Sosa, Carmen, Specka, Xenia, Teixeira, Edmar, Wang, Enli, Weihermüller, Lutz, Zhao, Gang, Zhao, Zhigan, Ogle, Stephen, Ewert, Frank, Kuhnert, Matthias, Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Van Oijen, Marcel, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balász, Haas, Edwin, Kersebaum, Kurt-Christian, Kiese, Ralf, Klatt, Steffen, Lewan, Elisabet, Nendel, Claas, Raynal, Helene, Sosa, Carmen, Specka, Xenia, Teixeira, Edmar, Wang, Enli, Weihermüller, Lutz, Zhao, Gang, Zhao, Zhigan, Ogle, Stephen, and Ewert, Frank

Abstract

For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km2), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m−2 d−1 and 2.7–6.1 g C m−2 d−1 for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (s

Published
2017

42. DATA Aggregation effects in regional yield simulations

Author

Hoffmann, Holger, Kersebaum, Kurt Christian, Zhao, Gang, Asseng, Senthold, Bindi, Marco, Cammarano, Davide, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Doro, Luca, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balazs, Haas, Edwin, Kassie, Belay T., Kiese, Ralf, Klatt, Steffen, Kuhnert, Matthias, Lewan, Elisabet, Moriondo, Marco, Nendel, Claas, Raynal, Helene, Roggero, Pier Paolo, Rötter, Reimund Paul, Siebert, Stefan J., Sosa, Carmen, Specka, Xenia, Tao, Fulu, Teixeira, Edmar, Trombi, Giacomo, Yeluripati, Jagadeesh, Vanuytrecht, Eline, Wallach, Daniel, Wang, Enli, Weihermueller, Lutz, Zhao, Zhigan, Ewert, Frank, Institute of Crop Science and Resource Conservation, University of Bonn-Division of Plant Nutrition, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), INRES, Rheinische Friedrich-Wilhelms-Universität Bonn, University of Florida [Gainesville], University of Florence (UNIFI), The James Hutton Institute, UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Department of Soil and Environment, Swedish University of Agricultural Sciences (SLU), Thünen Institute of Climate Smart Agriculture, Texas A&M University System, Department of Crop Production Ecology, Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT), Agricultural and Biological Engineering, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Biological and Environmental Sciences, University of Stirling, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Università degli Studi di Sassari, Department of Crop Sciences, University of Goettingen, Instutute of Landscape Biogeochemistry, Climate Impacts Group, New Zealand Institute for Plant and Food Research Limited, Department of Agri-Food Production and Environmental Sciences, University delgi Studi di Firenze, Information and Computational Sciences Group, Department of Earth and Environmental Sciences [Leuven] (EES), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), CSIRO, Institute of Bio- and Geosciences Agrosphere (IBG-3), China Agricultural University, Institute of Crop Science and Resource Conservation [Bonn] (INRES), University of Florida [Gainesville] (UF), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Departement of Soil and Environment, Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), University of Göttingen - Georg-August-Universität Göttingen, Plant & Food Research, and China Agricultural University (CAU)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Session: AgMIP: Advances in Crop & Soil Model Intercomparison and Improvement Oral; Regional yield simulations with process-based models often rely on input data of coarse spatial resolution (Ewert et al., 2015; Zhao et al., 2015). Using aggregated data as input for process-based models entails the risks of introducing so-called aggregation errors (AE). Such AE depend on the model structure in combination with the aggregation method, the type of aggregated data as well as its spatial heterogeneity. While the regional crop yield bias is usually

Published
2016

43. Effects of climate data aggregation on regional NPP modelling

Author

Kuhnert, Matthias, Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Van Oijen, Marcel, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balázs, Haas, Edwin, Kersebaum, Kurt-Christian, Kiese, Ralf, Klatt, Steffen, Lewan, Elisabeth, Nendel, Claas, Raynal, Helene, Sosa, Carmen, Specka, Xenia, Teixeira, Edmar, Wang, Enli, Weihermüller, Lutz, Zhao, Gang, Zhao, Zhigan, Ogle, Stephen, Ewert, Frank, Institute of Biological and Environmental Sciences, (SFIRC), The James Hutton Institute, Crop Science Group, INRES, Rheinische Friedrich-Wilhelms-Universität Bonn, Centre for Ecology and Hydrology, UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Swedish University of Agricultural Sciences (SLU), Thünen Institute of Climate-Smart Agriculture, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Systems Modelling Team (Sustainable Production Group), New Zealand Institute for Plant and Food Research Limited, CSIRO, Institute of Bio- and Geosciences Agrosphere (IBG-3), Natural Resource Ecology Laboratory [Fort Collins] (NREL), Colorado State University [Fort Collins] (CSU), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and Plant & Food Research

Subjects
npp, extreme events, data aggregation, [SDV]Life Sciences [q-bio], scaling, net primary production, crop modelling
Abstract

Stream B: Methods in Environmental Modelling including optimization, sensitivity, uncertainty issues, model development and modelling frameworks; In ecosystem modelling studies, data are often collected at a small scale but are used in models topredict ecosystem responses e.g. net primary production (NPP) at coarser scale, using dataaggregation. The data aggregation causes errors that are difficult to predict, because of modelcomplexity and our limited knowledge of the spatial heterogeneity underlying our aggregated inputvalues. Input aggregation thus adds to the uncertainty associated with model predictions. One way ofreducing uncertainty related to input aggregation error is to evaluate models at different resolutions forareas where high-resolution input data are available. The objective of this study was the quantificationof the aggregation error on modelled NPP introduced by climate data aggregation. Therefore, climatedata at 1 km x 1 km resolution (>30 000 grid cells) were used as baseline to simulate NPP with 11different crop and biogeochemical models for the federal state North Rhine-Westphalia (Germany).These results, for 29 year monocultures of wheat and maize cropping systems, respectively, werecompared with simulation results using aggregated climate data for four resolutions (10, 25, 50, 100km grid cell side length).The aggregation effect is represented by the maximum differences betweenthe NPP, averaged for wheat and maize cropping systems over the growing season, simulated for thefive different resolutions. Input data aggregation had little impact on NPP of 29 year averages (0.5 –7.8 % for wheat and 0.3 – 10 % for maize), while the climate data aggregation effect was higher forsingle years; up to 9 % and 13 % for wheat and maize, respectively, gradually decreasing to loweffects for averages over 10 year periods or longer. The scale effect differed among models andshows only a minor impact (2%) for an ensemble run.

Published
2016

44. Impact of climate aggregation over different scales on regional NPP modelling

Author

Kuhnert, Matthias, Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Zhao, Gang, Constantin, Julie, Raynal, Helene, Wallach, Daniel, Coucheney, Elsa, Lewan, Elisabet, Eckersten, Henrik, Specka, Xenia, Kersebaum, Kurt Christian, Nendel, Claas, Grosz, Balázs, Dechow, Rene, Kiese, Ralf, Haas, Edwin, Klatt, Steffen, Teixeira, Edmar, Bindi, Marco, Trombi, Giacomo, Moriondo, Marco, Doro, Luca, Roggero, Pier Paolo, Zhao, Zhigan, Wang, Enli, Vanuytrecht, Eline, Tao, Fulu, Rötter, Reimund P., Cammarano, Davide, Asseng, Senthold, Weihermüller, Lutz, Siebert, Stefan, Gaiser, Thomas, Ewert, Frank, Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, The James Hutton Institute, Institute of Crop Science and Resource Conservation /Crop Science Group, Rheinische Friedrich-Wilhelms-Universität Bonn, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Swedish University of Agricultural Sciences (SLU), Department of Crop Production Ecology, Institute of Landscape Systems Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Thünen Institute of Climate Smart Agriculture, Karlsruhe Institute of Technology (KIT), Plant & Food Research, Department of Agri - food Production and Environmental Sciences, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Istituto di Biometeorologia [Firenze] (IBIMET), Consiglio Nazionale delle Ricerche (CNR), Desertification Research Group, University of Sassari, CSIRO, Université Catholique de Louvain = Catholic University of Louvain (UCL), Climate Impacts Group, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Institute of Bio- and Geosciences Agrosphere (IBG-3), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, New Zealand Institute for Plant and Food Research Limited, University of Florence (UNIFI), Université Catholique de Louvain, Agricultural & Biological Engineering Department, and University of Florida [Gainesville]

Subjects
[SDV]Life Sciences [q-bio]
Abstract

In spatial modelling of Net Primary Productivity (NPP), predictability and uncertainty depends on the availability of input data, as well as on the scale of the available data sets. Therefore, the study presented here quantifies the impact of aggregation effect of input data of different scales for a regional modelling approach using 5 different resolutions. As part of this study, the presentation focuses on the impact of the climate aggregation on the simulation of NPP. The effect is investigated on the model results of 11 different crop and biogeochemical modelssimulating NPP for wheat and maize for the area of the German state of North Rhine-Westphalia. The focus of the study is on the impact of drought effects across the scales considered. The data are analysed on annual time steps we followed two approaches to investigate the impact of water limitation on primary production: First, two model runs, one considers water limitation and the other one ignores the impacts of water limitation on plant production second, an external definition of dry conditions by a drought index, only considering climate data, enables a separation of grid-cells and years with drought impacts, independent of the model internal functions. The results show hardly any difference between the overall average NPP across the scales, but some variability for the impact of extreme weather conditions on the simulated NPP.

Published
2016

45. Impacts of soil and weather data aggregation in spatial modelling of net primary production of croplands

Author

Matthias Kuhnert, Yeluripati, Jagadeesh B., Pete Smith, Holger Hoffmann, Julie Constantin, Elsa Coucheney, Rene Dechow, Henrik Eckersten, Thomas Gaiser, Balázs Grosz, Edwin Haas, Kurt-Christian Kersebaum, Ralf Kiese, Klatt, S., Elisabet Lewan, Claas Nendel, Helene Raynal, Sosa, C., Xenia Specka, Edmar Teixeira, Wang, E., Lutz Weihermueller, Gang Zhao, Zhigan Zhao, Frank Ewert, School of Biological Sciences [Aberdeen], University of Aberdeen, The James Hutton Institute, Crop Science Group, Rheinische Friedrich-Wilhelms-Universität Bonn, UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Department of Soil and Environment, Swedish University of Agricultural Sciences (SLU), Thünen Institute of Climate Smart Agriculture, Department of Crop Production Ecology, Karlsruhe Institute of Technology (KIT), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), New Zealand Institute for Plant and Food Research Limited, CSIRO, Institute of Bio- and Geosciences Agrosphere (IBG-3), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Departement of Soil and Environment, and Plant & Food Research

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Impacts of soil and weather data aggregation in spatial modelling of net primary production of croplands. iCROPM 2016 International Crop Modelling Symposium "Crop Modelling for Agriculture and Food Security under Global Change"

Published
2016

46. Impacts of soil and weather data aggregation in spatial modelling of net primary production of croplands

Author

Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balazs, Haas, Edwin, Kersebaum, Kurt Christian, Kiese, Ralf, Klatt, Steffen, Lewant , E., Nendel, Claas, Raynal, Helene, Sosa, Carola, Specka, Xenia, Teixeira, Edmar, Wang , Enli, Weihermüller, Lutz, Zhao, Gang, Zhao, Zhihua, Ewert, Frank, and Kuhnert, Matthias

Published
2016

47. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

Author

Hoffmann, Holger, Zhao, Gang, Asseng, Senthold, Bindi, Marco, Biernath, Christian, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Doro, Luca, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balázs, Heinlein, Florian, Kassie, Belay T., Klein, Christian, Kuhnert, Matthias, Lewan, Elisabet, Moriondo, Marco, Nendel, Claas, Priesack, Eckart, Raynal, Helene, Roggero, Pier P., Rötter, Reimund P., Siebert, Stefan, Specka, Xenia, Tao, Fulu, Teixeira, Edmar, Trombi, Giacomo, Wallach, Daniel, Weihermüller, Lutz, Yeluripati, Jagadeesh, Ewert, Frank, Kersebaum, Kurt Christian, Crop Science Group, Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Department of Agri-Food Production and Environmental Sciences, University delgi Studi di Firenze, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Department of Soil and Environment, University of Agricultural Sciences (UAS), Johann Heinrich von Thünen Institut, Desertification Research Group, University of Sassari, Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), Institute of landscape systems analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), University of Aberdeen, Consiglio Nazionale delle Ricerche (CNR), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Environmental Impacts Group, Natural resources institute Finland, Plant & Food Research, Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association, Craigiebuckler, The James Hutton Institute, German Federal Ministry of Food and Agriculture (BMEL) through Federal Office for Agriculture and Food (BLE) [2851ERA01J], FACCE MACSUR through Finnish Ministry of Agriculture and Forestry (MMM) [3200009600], Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning [220-2007-1218], faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences), INRA ACCAF metaprogram, UR MIAT INRA, Helmholtz project 'REKLIM - Regional Climate Change', HGF Alliance 'Remote Sensing and Earth System Dynamics' (EDA), German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) [FOR1695], German Science Foundation [EW 119/5-1], Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), and Hoffmann, Holger

Subjects
winter-wheat, 010504 meteorology & atmospheric sciences, Databases, Factual, SYSTEMS SIMULATION, NITROGEN DYNAMICS, WINTER-WHEAT, CROP MODELS, DATA RESOLUTION, SCALE, WATER, VARIABILITY, CALIBRATION, WEATHER, [SDV]Life Sciences [q-bio], nitrogen dynamics, 01 natural sciences, [SHS]Humanities and Social Sciences, Geographical Locations, Soil, Yield (wine), Agricultural Soil Science, Germany, Range (statistics), [MATH]Mathematics [math], Triticum, 2. Zero hunger, Multidisciplinary, Simulation and Modeling, Sampling (statistics), Agriculture, 04 agricultural and veterinary sciences, Plants, data resolution, Europe, Agricultural soil science, [SDE]Environmental Sciences, Wheat, Medicine, ddc:500, Seasons, Maize, Simulation and modeling, Winter, Cereal crops, Research Article, Crops, Agricultural, Climate Change, Science, Soil Science, Soil science, Crops, Research and Analysis Methods, Zea mays, crop models, scale, Model Organisms, Plant and Algal Models, Calibration, [INFO]Computer Science [cs], Computer Simulation, Grasses, Agricultural Science, 0105 earth and related environmental sciences, AGR/02 Agronomia e coltivazioni erbacee, variability, Crop yield, Ecology and Environmental Sciences, Organisms, Biology and Life Sciences, Water, Oryza, 15. Life on land, calibration, Data aggregator, 13. Climate action, People and Places, 040103 agronomy & agriculture, Earth Sciences, 0401 agriculture, forestry, and fisheries, Environmental science, systems, Scale (map), water, Crop Science, Cereal Crops
Abstract

International audience; We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by

Published
2016

48. Impact of climate aggregation over different scales on regional NPP modelling

Author

Yeluripati, Jagadeesh, Smith, Pete, Hoffmann, Holger, Zhao, Gang, Constantin, Julie, Raynal, Helene, Wallach, Daniel, Coucheney, Elsa, Lewan, Elisabet, Eckersten, Henrik, Specka, Xenia, Kersebaum, Kurt Christian, Nendel, Claas, Grosz, Balázs, Dechow, Rene, Kiese, Ralf, Haas, Edwin, Klatt, Steffen, Teixeira, Edmar, Bindi, Marco, Trombi, Giacomo, Moriondo, Marco, Doro, Luca, Roggero, Pier Paolo, Zhao, Zhigan, Wang, Enli, Vanuytrecht, Eline, Tao, Fulu, Rötter, Reimund P., Cammarano, Davide, Asseng, Senthold, Weihermüller, Lutz, Siebert, Stefan, Gaiser, Thomas, Ewert, Frank, and Kuhnert, Matthias

Abstract

In spatial modelling of Net Primary Productivity (NPP), predictability and uncertainty depends on the availability of input data, as well as on the scale of the available data sets. Therefore, the study presented here quantifies the impact of aggregation effect of input data of different scales for a regional modelling approach using 5 different resolutions. As part of this study, the presentation focuses on the impact of the climate aggregation on the simulation of NPP. The effect is investigated on the model results of 11 different crop and biogeochemical models simulating NPP for wheat and maize for the area of the German state of North Rhine-Westphalia. The focus of the study is on the impact of drought effects across the scales considered. The data are analysed on annual time steps we followed two approaches to investigate the impact of water limitation on primary production: First, two model runs, one considers water limitation and the other one ignores the impacts of water limitation on plant production second, an external definition of dry conditions by a drought index, only considering climate data, enables a separation of grid-cells and years with drought impacts, independent of the model internal functions. The results show hardly any difference between the overall average NPP across the scales, but some variability for the impact of extreme weather conditions on the simulated NPP.

Published
2016

49. The implication of input data aggregation on up-scaling soil organic carbon changes

Author

Grosz, Balázs, primary, Dechow, Rene, additional, Gebbert, Sören, additional, Hoffmann, Holger, additional, Zhao, Gang, additional, Constantin, Julie, additional, Raynal, Helene, additional, Wallach, Daniel, additional, Coucheney, Elsa, additional, Lewan, Elisabet, additional, Eckersten, Henrik, additional, Specka, Xenia, additional, Kersebaum, Kurt-Christian, additional, Nendel, Claas, additional, Kuhnert, Matthias, additional, Yeluripati, Jagadeesh, additional, Haas, Edwin, additional, Teixeira, Edmar, additional, Bindi, Marco, additional, Trombi, Giacomo, additional, Moriondo, Marco, additional, Doro, Luca, additional, Roggero, Pier Paolo, additional, Zhao, Zhigan, additional, Wang, Enli, additional, Tao, Fulu, additional, Rötter, Reimund, additional, Kassie, Belay, additional, Cammarano, Davide, additional, Asseng, Senthold, additional, Weihermüller, Lutz, additional, Siebert, Stefan, additional, Gaiser, Thomas, additional, and Ewert, Frank, additional

Published
2017
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50. Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

Author

Kuhnert, Matthias, primary, Yeluripati, Jagadeesh, additional, Smith, Pete, additional, Hoffmann, Holger, additional, van Oijen, Marcel, additional, Constantin, Julie, additional, Coucheney, Elsa, additional, Dechow, Rene, additional, Eckersten, Henrik, additional, Gaiser, Thomas, additional, Grosz, Balász, additional, Haas, Edwin, additional, Kersebaum, Kurt-Christian, additional, Kiese, Ralf, additional, Klatt, Steffen, additional, Lewan, Elisabet, additional, Nendel, Claas, additional, Raynal, Helene, additional, Sosa, Carmen, additional, Specka, Xenia, additional, Teixeira, Edmar, additional, Wang, Enli, additional, Weihermüller, Lutz, additional, Zhao, Gang, additional, Zhao, Zhigan, additional, Ogle, Stephen, additional, and Ewert, Frank, additional

Published
2017
Full Text
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