Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2022
Authors
Muhammad NaseerAbstract
The growing global population levels and the resulting increasing demands for food has put a lot of pressure on the food production systems and made the agricultural sector highly energy-intensive. The intensification in global food production has led to the need to adapt production systems according to the local climatic conditions, making food production possible in areas where it was di cult before and also making the production process environmentally sustainable. One way to adapt food production systems is through protected cultivation techniques, such as greenhouses, that enable controlled indoor climate, crop protection from extreme climate conditions, pests and diseases and the possibility to extend production seasons for certain crops. Yet these techniques a ect the investments, economic performance, used resources and have certain environmental consequences. Norway, for instance, is one such region in which one of the biggest challenges associated with protected cultivation systems is the issue of low availability of natural light and heat, especially during the cold winter months. Production in such regions requires high levels of energy, yet some of these regions also have significant availability of renewable energy resources. The challenge of low light and heat can be overcome by bringing about changes in the production techniques, including greenhouse design elements, production seasons and energy sources. However, this also in turn raises the issue of environmental impact of greenhouse vegetable production in high latitude regions and especially from the use of renewable energy that is present in significant amounts in many regions with considerable greenhouse vegetable production. While there exist several studies on the di erent aspects of greenhouse vegetable production in various regions, and their resulting environmental effects, works related to the use of renewable energy sources, especially in high latitude regions such as Norway are limited. Moreover, studies regarding the environmental impact of greenhouse production of vegetables often show that there is a trade-off between the economic performance and the environmental impact. Local climate and light variability call for regionally adapted greenhouse production techniques. Moreover, the impact of a certain greenhouse design on the economic performance may not always be correlated to the environmental impact. Thus, there is a need to evaluate the impact of various production strategies on the economic potential, resource use and the environment in instances where the traditional fossil fuel is supplemented and/or replaced by energy from renewable resources. In the present work, an attempt has been made to provide a broad picture of greenhouse tomato production at high latitude regions as a result of adapting production strategies in line with the local climates in Norway, with a particular emphasis on renewable energy sources in order to evaluate the environmental impact of locally produced tomatoes that are also economically profitable. The study has been divided into three stages. In the first part, an economic evaluation of seasonal (mid-March to mid-October) greenhouse tomato production in southestern, southwestern, central and northern Norway was performed. In the second part, an economic evaluation and energy use of extended season (from 20th January to 20th November) and year-round production of greenhouse tomatoes in the selected locations in Norway was performed. Sets of plausible design elements, greenhouse climate management, different artificial lighting strategies were assessed to evaluate the impact of the greenhouse design on the Net Financial Return (NFR), energy use and CO2 emissions of the production process. In the third part, a life cycle impact assessment was conducted for a selected number of designs from the first two stages that yielded high NFR or was associated with low energy use in order to assess whether the designs that performed well economically are also environmentally sustainable. The study found clear region-dependent differences in the NFR, its underlying elements, energy use and the resulting environmental impact of different greenhouse designs with differing energy-saving and internal climate control equipment. Our results show that economic profitability can be combined with a low environmental impact under certain regions and production techniques. It was found that Kise (southeastern) was the most favorable location for seasonal greenhouse tomato production in Norway, while Orre (southwestern) was the most favorable location in terms of the economic performance and environmental impact during the extended and year-round production seasons. Moreover, our results show that night energy screens, electric heat pumps and light sources had the most impacts of the elements that were investigated on the NFR and the resulting environmental impact across the three production seasons and need to be considered while constructing greenhouses for tomato production in regions having similar climate as that of Norway. The results of this study provide interesting insights on works related to the greenhouse vegetable production and energy resources in high latitude regions with considerable supplies of renewable energy. The findings can enable local producers across Norway to design greenhouses keeping in mind the local climate, the economic profitability and the environmental sustainability and can help policymakers in devising policies that encourage local growers to adapt production strategies aimed at increasing local production that is both economically profitable and environmentally sustainable.
Authors
Brigitta Szabó János Mészáros Piroska Kassai Péter Braun Attila Nemes Csilla Farkas Natalja Cerkasova Federica Monaco Enrico Antonio Chiaradia Felix WitingAbstract
An important aim of the OPTAIN project is to derive missing information on necessary model input variables in a harmonized way to allow for a sound cross-case study assessment of NSWRM effectiveness. Therefore, in this report we provide approaches applicable for all OPTAIN case studies (CS) to fill data gaps. The specific objective of OPTAINs task 3.3 was to provide methods to cover missing input data that is required for the environmental modelling and socio-economic analysis. The deliverable includes guidelines with detailed explanations about the derivation of missing data for the CS leaders. Based on the information provided by CS leaders in the OPTAIN milestone “MS7 Data inventory of input data for integrated modelling collected from all case studies”, the following information had to be covered by approaches provided by WP3 to fulfil the input requirements of the models and analysis: 1) soil phosphorus content, 2) effective bulk density, 3) moist soil albedo of the top layer, 4) USLE soil erodibility (K) factor, 5) available water capacity, 6) saturated hydraulic conductivity, 7) time series crop data. The mapping of soil phosphorus content is based on the LUCAS topsoil dataset. During the mapping the geometric mean phosphorus content by land use types – characteristic for the region of the CS – is applied. Further required data are the LUCAS Land Use / Cover Area Frame Survey, European agro-climate zone map and the land use or land cover map of the CS – a local one, if available. For the calculation of soil physical and hydraulic properties we apply methods available from the literature. The derivation of crop maps is based on remote sensing data. A crop classification model was trained on the cropland data of the LUCAS Land Use / Cover Area Frame Survey of the years 2015 and 2018, merged with the Sentinel-1A and -1B satellite radar images. The pixel based crop classification was carried out with a random forest algorithm on the Google Earth Engine platform. The method can be applied for 2015 and all following years. By adding a map of field boundaries, the pixel based crop prediction can be aggregated to field level using the majority of the predicted crop. Regarding the socio-economic data, missing information is planned to be covered from official statistics. The EU database does not account properly for the Norwegian and Swiss sites, therefore required data will be retrieved ex novo from local sources or literature.
Authors
Čerkasova, Natalja Nemes, Attila Szabó, Brigitta Idzelytė, Rasa Cüceloğlu, Gökhan Mészáros, János Kassai, Piroska Moritz Shore Csilla Farkas Czelnai, LeventeAbstract
Deliverable report D3.3 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756) Description of the pre-processing scripts and routines for the harmonisation of the data to be used as input, adapted to the needs of the modelling approaches. Summary The OPTAIN project aims to identify efficient measures for the retention and reuse of water and nutrients (NSWRM - Natural/Small Water Retention Measures) in small agricultural catchments based on empirical data and scale-adapted integrated modelling approaches. The project involves international partners with case study sites in 14 small agricultural catchments (including one cross-border), all having different data availability, measurement protocols, data handling policies and formats. Based on the agreed data harmonisation procedures within the OPTAIN project, this deliverable D3.3 provides data pre-processors for input data restructuring to overcome the aforementioned differences among the partners. The projects’ case study leaders collected the input data necessary for the modelling tasks structured according to the derived guidelines. Available input information from different sources (both national and global or European scale) and formats had to be harmonised and standardised where relevant and reasonable. Pre-processing tools have been developed, which were used for data compilation and reformatting of the input data in line with the needs of basin-scale (SWAT+) and the field scale (SWAP) modelling approaches. Freely available and distributable software, programming languages, and technologies (Python, R, JavaScript) were used for these tasks.
Authors
Michael Strauch Christoph Schürz Natalja Cerkasova Svajūnas Plungė Mikołaj Piniewski Csilla Farkas Petr Fučík Brigitta Toth (Szabó) Štěpán Marval, Attila Nemes Felix Witing Martin VolkAbstract
Natural/Small Water Retention Measures (NSWRMs) can help to mitigate conflicts among agricultural water uses and other human and environmental demands for water. Moreover, they can significantly contribute to an improved water quality and more resilient agriculture. Despite the existing comprehensive set of techniques to increase water and nutrient retention on both catchment and farm levels, knowledge is still lacking on the effectiveness of different scale- and region-specific measures across various soil climatic regions and agricultural systems, especially under changing climate conditions. The EU Horizon 2020 project OPTAIN aims to (i) identify efficient techniques for the retention and reuse of water and nutrients in small agricultural catchments across different biogeographical regions of Europe, and - in close cooperation with local actors - (ii) select NSWRMs at farm and catchment level and optimize their spatial allocation and combination based on environmental and economic sustainability indicators. All gained knowledge will be translated into a Learning Environment allowing analysis of trade-offs and synergies between multiple values/goals in the management and design of NSWRMs. The presentation will discuss the flow of the project that comprises of: a) the establishment of Multi-Actor Reference Groups in each case study, b) identifying and documenting NSWRMs and its potentials and constraints, c) modelling the environmental (SWAT+ for the catchment scale and SWAP (Soil Water Atmosphere Plant) for the field-scale) and socio-economic performance of NSWRMs in 14 case studies, d) a multi-objective allocation and combination of NSWRMs, e) policy analysis and recommendations, and f) the establishment of the Learning Environment. More specifically, we will highlight the challenge of constructing SWAT+ model setups that are methodologically harmonized across all case studies and allow for a routing between contiguous field-scale objects. We will briefly introduce into workflows currently developed to overcome this challenge, which we believe can provide great benefit for the wider model community as well as the potential for implementation of the attained knowledge into practice.
Authors
Štěpán Marval Petr Fučík Natalja Čerkasova Christoph Schürz Michael Strauch Felix Witing Mikolaj Piniewski Svajunas Plunge Csilla Farkas Dominika Krzeminska Sinja Weiland Tatenda LemannAbstract
The deliverable D2.3 of the OPTAIN project introduces a framework and scale specific guidelines for the parameterization of Natural/Small Water Retention Measures (NSWRM) in modelling approaches. More specifically, it provides a detailed translation of NSWRM into parameters and design approaches for the application in the SWAT+ (catchment scale) and SWAP (field-scale) models, which were selected as the main modelling tools in the OPTAIN project. This document can also be considered as an extension of the well-known Conservation Practice Modelling Guide for SWAT and APEX (Waidler et al., 2011), which is frequently used by the SWAT modelling community for testing the effectiveness of conservation practices. However, besides of conservation practices, the report focuses mainly on NSWRMs, and how they can be implemented in SWAT+, the new and restructured version of SWAT. Analogously, the NSWRM parameters are also described for the SWAP model, which is addressing the field-scale. Compared to previous NSWRM modelling approaches, this methodology enables the setting of NSWRM parameters in the two selected models to improve the description of the related hydrological and hydrochemical processes.
Authors
Gunnhild JaastadAbstract
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Abstract
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Authors
Shaochun Huang Stephanie Eisner Ingjerd Haddeland Zelalem Tadege MengistuAbstract
Lack of national soil property maps limits the studies of soil moisture (SM) dynamics in Norway. One alternative is to apply the global soil data as input for macro-scale hydrological modelling, but the quality of these data is still unknown. The objectives of this study are 1) to evaluate two recent global soil databases (Wise30sec and SoilGrids) in comparison with data from local soil profiles; 2) to evaluate which database supports better model performance in terms of river discharge and SM for three macro-scale catchments in Norway and 3) to suggest criteria for the selection of soil data for models with different complexity. The global soil databases were evaluated in three steps: 1) the global soil data are compared directly with the Norwegian forest soil profiles; 2) the simulated discharge based on the two global soil databases is compared with observations and 3) the simulated SM is compared with three global SM products. Two hydrological models were applied to simulate discharge and SM: the Soil and Water Integrated Model (SWIM) and the Variable Infiltration Capacity (VIC) model. The comparison with data from local soil profiles shows that SoilGrids has smaller mean errors than Wise30sec, especially for upper soil layers, but both soil databases have large root mean squared errors and poor correlations. SWIM generally performs better in terms of discharge using SoilGrids than using Wise30sec and the simulated SM has higher correlations with the SM products. In contrast, the VIC model is less sensitive to soil input data and the simulated SM using Wise30sec is higher correlated with the SM products than using SoilGrids. Based on the results, we conclude that the global soil databases can provide reasonable soil property information at coarse resolutions and large areas. The selection of soil input data should depend on the characteristics of both models and study areas.
Authors
Jogeir N. Stokland Kjersti Holt Hanssen Delphine Derrien Bernhard Zeller Alice Budai Daniel RasseAbstract
No abstract has been registered
Authors
Alice BudaiAbstract
No abstract has been registered