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.
2024
Authors
Brigitta Szabó Piroska Kassai Svajunas Plunge Attila Nemes Péter Braun Michael Strauch Felix Witing János Mészáros Natalja ČerkasovaAbstract
To effectively guide agricultural management planning strategies and policy, it is important to simulate water quantity and quality patterns and to quantify the impact of land use and climate change on soil functions, soil health, and hydrological and other underlying processes. Environmental models that depict alterations in surface and groundwater quality and quantity at the catchment scale require substantial input, particularly concerning movement and retention in the unsaturated zone. Over the past few decades, numerous soil information sources, containing structured data on diverse basic and advanced soil parameters, alongside innovative solutions to estimate missing soil data, have become increasingly available. This study aims to (i) catalogue open-source soil datasets and pedotransfer functions (PTFs) applicable in simulation studies across European catchments; (ii) evaluate the performance of selected PTFs; and (iii) present compiled R scripts proposing estimation solutions to address soil physical, hydraulic, and chemical data needs and gaps in catchment-scale environmental modelling in Europe. Our focus encompassed basic soil properties, bulk density, porosity, albedo, soil erodibility factor, field capacity, wilting point, available water capacity, saturated hydraulic conductivity, and phosphorus content. We aim to recommend widely supported data sources and pioneering prediction methods that maintain physical consistency and present them through streamlined workflows.
Abstract
Precompression stress, compression index, and swelling index are used for characterizing the compressive behavior of soils, and are essential soil properties for establishing decision support tools to reduce the risk of soil compaction. Because measurements are time-consuming, soil compressive properties are often derived through pedotransfer functions. This study aimed to develop a comprehensive database of soil compressive properties with additional information on basic soil properties, site characteristics, and methodological aspects sourced from peer-reviewed literature, and to develop random forest models for predicting precompression stress using various subsets of the database. Our analysis illustrates that soil compressive properties data primarily originate from a limited number of countries. There is a predominance of precompression stress data, while little data on compression index or recompression index are available. Most precompression stress data were derived from the topsoils of conventionally tilled arable fields, which is not compatible with knowledge that subsoil compaction is a serious problem. The data compilation unveiled considerable variations in soil compression test procedures and methods for calculating precompression stress across different studies, and a concentration of data at soil moisture conditions at or above field capacity. The random forest models exhibited unsatisfactory predictive performance although they performed better than previously developed models. Models showed slight improvement in predictive power when the underlying data were restricted to a specific precompression stress calculation method. Although our database offers broader coverage of precompression stress data than previous studies, the lack of standardization in methodological procedures complicates the development of predictive models based on combined datasets. Methodological standardization and/or functions to translate results between methodologies are needed to ensure consistency and enable data comparison, to develop robust models for precompression stress predictions. Moreover, data across a wider range of soil moisture conditions are needed to characterize soil mechanical properties as a function of soil moisture, similar to soil hydraulic functions, and to develop models to predict the parameters of such soil mechanical functions.
Authors
Tobias Karl David Weber Lutz Weihermüller Attila Nemes Michel Bechtold Aurore Degré Efstathios Diamantopoulos Simone Fatichi Vilim Filipović Surya Gupta Tobias L. Hohenbrink Daniel R. Hirmas Conrad Jackisch Quirijn de Jong van Lier John Koestel Peter Lehmann Toby R. Marthews Budiman Minasny Holger Pagel Martine van der Ploeg Shahab Aldin Shojaeezadeh Simon Fiil Svane Brigitta Szabó Harry Vereecken Anne Verhoef Michael Young Yijian Zeng Yonggen Zhang Sara BonettiAbstract
Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil information to soil hydraulic properties (SHPs) for applications in a wide range of process-based and empirical models, thereby enabling the assessment of soil hydraulic effects on hydrological, biogeochemical, and ecological processes. At least more than 4 decades of research have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental concerns related to the scope and adequacy of current PTFs, particularly when applied to parameterise models used at the field scale and beyond. Most of the PTF development process has focused on refining and advancing the regression methods, while fundamental aspects have remained largely unconsidered. Most soil systems are not represented in PTFs, which have been built mostly for agricultural soils in temperate climates. Thus, existing PTFs largely ignore how parent material, vegetation, land use, and climate affect processes that shape SHPs. The PTFs used to parameterise the Richards–Richardson equation are mostly limited to predicting parameters of the van Genuchten–Mualem soil hydraulic functions, despite sufficient evidence demonstrating their shortcomings. Another fundamental issue relates to the diverging scales of derivation and application, whereby PTFs are derived based on laboratory measurements while often being applied at the field to regional scales. Scaling, modulation, and constraining strategies exist to alleviate some of these shortcomings in the mismatch between scales. These aspects are addressed here in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim of systematising PTF research and providing a roadmap guiding both PTF development and use. We close with a 10-point catalogue for funders and researchers to guide review processes and research.
Authors
Thomas Pabst Attila Nemes Andreas Olaus Harstad Ann-Cathrin Stridal Marie Wagner Gudny OkkenhaugAbstract
No abstract has been registered
Abstract
The evolution of soil structure in agricultural soils is driven by natural and anthropogenic factors including inherent soil properties, climate and soil management interventions, all acting at different spatial and temporal scales. Although the causal relationships between soil structure and these individual factors are increasingly understood, their relative importance and complex interactive effects on soil structure have so far not been investigated across a geo-climatic region. Here we present the first attempt to identify the relative importance of factors that drive the evolution of soil structure in agricultural soils as well as their direction of effect with a focus on the temperate-boreal zone. This was done using a random forest (RF) approach including soil, climate, time, and site factors as covariates. Relative entropy, as quantified by the Kullback-Leibler (KL) divergence, was used as a quantitative index of soil structure, which is derived from the particle-size distribution and soil water retention data, and integrates the effects of soil structure on pores from the micrometre-scale to large macropores. Our dataset includes 431 intact topsoil and subsoil samples from 89 agricultural sites across Sweden and Norway, which were sampled between 1953 and 2017. The relative importance of covariates for the evolution of soil structure was identified and their non-linear and non-monotonic effects on the KL divergence were investigated through partial dependence analysis. To reveal any differences between topsoils (0–30 cm; n = 174) and subsoils (30–100 cm; n = 257), the same analysis was repeated separately on these two subsets. The covariates were able to explain on average more than 50% of the variation in KL divergence for all soil samples and when only subsoil samples were included. However, the predictions were poorer for topsoil samples (≈ 35%), underlining the complex dynamics of soil structure in agricultural topsoils. Parent material was the most important predictor for the KL divergence, followed by clay content for all soil samples and sampling year for only subsoil samples. Mean annual air temperature ranked third and annual precipitation ranked fourth for subsoil samples. However, it remains unclear whether the effects of climate factors are direct (e.g., freezing and thawing, wetting and drying, rainfall impact) or indirectly expressed through interactions with soil management. The partial dependence analysis revealed a soil organic carbon threshold of around 3% below which soil structure starts to deteriorate. Besides this, our results suggest that subsoil structure in the agricultural land of Sweden deteriorated steadily during the 1950′s to 1970′s, which we attribute to traffic compaction as a consequence of agricultural intensification. We discuss our findings in the light of data bias, laboratory methods and multicollinearity and conclude that the approach followed here gave valuable insights into the drivers of soil structure evolution in agricultural soils of the temperate-boreal zone. Theses insights will be of use to inform soil management interventions that address soil structure or soil properties and functions related to it.
Authors
Attila Nemes Trond Haraldsen Lorna Dawson Monica Jayesingha Johanna Skrutvold Maria Dietrich Sigrid Esmeralda ArnestadAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Lillian Øygarden Åsmund Kvifte Jannes Stolte Sigrun Hjalmarsdottir Kværnø Marianne Bechmann Johannes DeelstraAbstract
https://drive.google.com/file/d/1mcbITzR1wfY1b4vLAaceHAyg_y_K3vzq/view Abstract book; abstract no 133567,page 217.
2023
Authors
Csilla Farkas Moritz Shore Gökhan Cüceloglu Levente Czelnai Attila Nemes Brigitta Szabó Natalja Čerkasova Rasa Idzelyté Sinja WeilandAbstract
The H2020 OPTAIN project involves both, catchment-, and field-scale modelling of the transport of water and nutrients. The catchment-scale modelling is performed at fourteen case study catchments across Europe using the SWAT+ model. At seven OPTAIN case studies, field-scale modelling is applied using the SWAP model. The aim of the SWAP modelling is to provide data on soil water balance elements using a more detailed (at field-scale) soil hydrological model and to cross-validate this data with the relevant fields in SWAT+. As the official manual from the SWAP model developers is rather detailed and complex, the OPTAIN SWAP modelling protocol focuses on practical issues, without overwhelming the modellers with information unnecessary for their case-studies. It also describes new tools, such as rswap, developed within the OPTAIN project for reference data quality check, model calibration and visualisation of the model results.
Abstract
Soil loss by erosion threatens food security and reduces the environmental quality of water bodies. Prolonged and extreme rainfalls are recognized as main drivers of soil erosion, and climate change predictions for large parts of the world foresee such increases in precipitation. Erosion rates are additionally affected by land use, which may change as a result of the shift from a fossil fuel-based economy to an economy relying on using renewable biomass, a “Bioeconomy”. In this study we aimed at investigating, through modelling, i) if future changes in land use, due to a bioeconomy, would increase the risk for soil loss and enhance suspended sediment yields in streams and ii) if these changes, when combined with climate change effects, would further aggravate suspended sediment conditions in a catchment. We used hydrological and bias adjusted climate models to compare the effect of seven land use pathways on discharge and sediment transport relative to a baseline scenario under present and future climate conditions. The study was carried out based on data from a small headwater stream, representative for cereal production areas of S-E Norway. By modelling our scenarios with the PERSiST and INCA-P models, we found that land use change had a greater influence on both future water discharge and sediment losses than a future climate. Changes from climate showed strongest differences on a seasonal basis. Out of the modelled land use pathways, a sustainable pathway manifested the least occurrence of extreme flood and sediment loss events under future climate; whereas a pathway geared towards self-sufficiency indicated the highest occurrence of such extreme events. Our findings show that careful attention must be placed on the land use and soil management in the region. To maintain freshwater quality, it will be increasingly important to implement environmental mitigation measures.