Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Forfattere
Chathura Palliyaguru Vindhya Basnayake Randika K. Makumbura Miyuru Gunathilake Nitin Muttil Eranga M. Wimalasiri Upaka RathnayakeSammendrag
Det er ikke registrert sammendrag
Forfattere
Ravindu Panditharathne Miyuru Gunathilake Imiya M. Chathuranika Upaka Rathnayake Mukand S. Babel Manoj K. JhaSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Eva FarkasSammendrag
Det er ikke registrert sammendrag
Sammendrag
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Forfattere
Erik J. JonerSammendrag
Det er ikke registrert sammendrag
Forfattere
Siv Mari Aurdal Tomasz Leszek Woznicki Trond Haraldsen Krzysztof Kusnierek Anita Sønsteby Siv Fagertun RembergSammendrag
Det er ikke registrert sammendrag
2022
Forfattere
Brigitta Szabó János Mészáros Piroska Kassai Péter Braun Attila Nemes Csilla Farkas Natalja Cerkasova Federica Monaco Enrico Antonio Chiaradia Felix WitingSammendrag
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.
Forfattere
Čerkasova, Natalja Nemes, Attila Szabó, Brigitta Idzelytė, Rasa Cüceloğlu, Gökhan Mészáros, János Kassai, Piroska Moritz Shore Csilla Farkas Czelnai, LeventeSammendrag
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.
Forfattere
Michael Strauch Christoph Schürz Natalja Cerkasova Svajūnas Plungė Mikołaj Piniewski Csilla Farkas Petr Fučík Brigitta Toth (Szabó) Štěpán Marval, Attila Nemes Felix Witing Martin VolkSammendrag
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.