Attila Nemes

Research Professor

(+47) 920 10 865
attila.nemes@nibio.no

Place
Ås F20

Visiting address
Fredrik A. Dahls vei 20, 1430 Ås

Attachments

CV

Biography

Expert Area:
soil physics, soil hydrology, data mining, environmental modeling

Language Skills:    English, Hungarian
 

Read more
To document

Abstract

Soil macroporosity affects field-scale water-cycle processes, such as infiltration, nutrient transport and runoff1,2, that are important for the development of successful global strategies that address challenges of food security, water scarcity, human health and loss of biodiversity3. Macropores—large pores that freely drain water under the influence of gravity—often represent less than 1 per cent of the soil volume, but can contribute more than 70 per cent of the total soil water infiltration4, which greatly magnifies their influence on the regional and global water cycle. Although climate influences the development of macropores through soil-forming processes, the extent and rate of such development and its effect on the water cycle are currently unknown. Here we show that drier climates induce the formation of greater soil macroporosity than do more humid ones, and that such climate-induced changes occur over shorter timescales than have previously been considered—probably years to decades. Furthermore, we find that changes in the effective porosity, a proxy for macroporosity, predicted from mean annual precipitation at the end of the century would result in changes in saturated soil hydraulic conductivity ranging from −55 to 34 per cent for five physiographic regions in the USA. Our results indicate that soil macroporosity may be altered rapidly in response to climate change and that associated continental-scale changes in soil hydraulic properties may set up unexplored feedbacks between climate and the land surface and thus intensify the water cycle.

To document

Abstract

The saturated hydraulic conductivity of soil, Ks, is a critical parameter in hydrological models that remains notoriously difficult to predict. In this study, we test the capability of a model based on percolation theory and critical path analysis to estimate Ks measured on 95 undisturbed soil cores collected from contrasting soil types. One parameter (the pore geometry factor) was derived by model fitting, while the remaining two parameters (the critical pore diameter, dc, and the effective porosity) were derived from X‐ray computed tomography measurements. The model gave a highly significant fit to the Ks measurements (p < 0.0001) although only ~47% of the variation was explained and the fitted pore geometry factor was approximately 1 to 2 orders of magnitude larger than various theoretical values obtained for idealized porous media and pore network models. Apart from assumptions in the model that might not hold in reality, this could also be attributed to experimental error induced by, for example, air entrapment and changes in the soil pore structure occurring during sample presaturation and the measurement of Ks. Variation in the critical pore diameter, dc, was the dominant source of variation in Ks, which suggests that dc is a suitable length scale for predicting soil permeability. Thus, from the point of view of pedotransfer functions, it could be worthwhile to direct future research toward exploring the correlations of dc with basic soil properties and site attributes.

To document

Abstract

Several mathematical models have been proposed for describing particle‐size distribution (PSD) data, but their characteristics and accuracy have not been investigated for the < 0.002, 0.002–0.05 and 0.05–2.0‐mm fractions separately. Therefore, the primary objective of this study was to examine the characteristics of various PSD models and to evaluate the accuracy of fitting to the entire PSD curve and to each of the three fractions separately. Thirty‐six PSD models were fitted to the experimental data of 160 soil samples from Iran. The beerkan estimation of soil transfer (BEST), Fredlund unimodal and bimodal, two‐ and three‐parameter Weibull, Rosin–Rammler and van Genuchten models provided the best fit to the experimental data of the three size fractions above, but with a different order of performance for the different fractions. For all textural fractions, the following models performed substantially less well than the other models: the offset‐non‐renormalized lognormal, simple lognormal, S‐curve, Schuhmann, Yang, Turcotte and Gompertz models. A comparison of the overall accuracy and simplicity of the models indicated that the BEST, two‐ and three‐parameter Weibull and Rosin–Rammler models provided the best fit to the experimental data for the entire curve, which is similar but does not correspond fully to the findings of a similar, earlier study. We found that the number of model parameters and the type of equation did not explain the models' fitting capabilities. We also found that the iterated function system (IFS) model performed better than the PSD models for all fractions. Comprehensive comparisons of PSD models will be of value to future model users, but it is important to note that such comparisons will remain dataset dependent. This is likely to continue until they are tested on a near‐infinite synthetic dataset that covers all possible data options.

To document

Abstract

Soil, through its various functions, plays a vital role in the Earth’s ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

To document

Abstract

Bangladesh often suffers from droughts and floods that cause substantial harm to households and communities. The frequency of such events is expected to increase with climate change. Assessing the vulnerability to climate change is a promising evaluation tool that can assist in identifying and improving adaptation strategies at various geographical scales. In this paper, we examine the vulnerability status of two regions in Bangladesh, one in the north, which is frequently impacted by severe droughts, and one in the south, which is exposed to regular flooding, high water, and salinity. We evaluate the exposure, sensitivity and adaptive capacity of each region using demographic, agro-economic, infrastructural, and biophysical indicators. We consider information obtained in a literature review, interviews with local experts, household surveys, and field visits in the study areas. We use principal components analysis to assess vulnerability to climate change between and within the north and south regions. The flood-prone, saline region in the south appears less vulnerable to climate change the northern drought prone areas, although further validation is needed.

To document

Abstract

The development of water storage schemes in Sub-Saharan Africa (SSA) is considered a major aid for those regions with unequal water distribution, limited accessibility and anticipated climate change impacts. Great attention is given by many SSA countries to set up different water storage schemes that may improve rural and urban development on a national level. The funding for the water storage schemes is often derived from foreign agencies which conduct feasibility studies for the financing of potential investments. Often however, the feasibility studies rely on a single monetary criterion which may not identify the most appropriate water storage in each case. In addition, limited data availability in many SSA countries increases the difficulty of identifying the most suitable storage option. This paper develops a multicriteria framework for the integrated evaluation of water storage strategies in Sub-Saharan African countries. A set of economic, agronomic and opinion-based criteria are assessed through the PROMETHEE II outranking approach. The introduction of crop modeling complements the limited field data available in agronomic criteria and enhances the scientific rigor of the method. Ethiopia is adopted as a representative case of SSA countries where a diverse set of water storage options is currently under construction, often financed by foreign agencies.

To document

Abstract

Riverine inputs and direct discharges to Norwegian coastal waters in 2013 have been estimated in accordance with the requirements of the OSPAR Commission. Nutrients, metals and organic pollutants have been monitored in rivers; discharges from point sources have been estimated from industry, sewage treatment plants and fish farming; and nutrient inputs from diffuse sources have been modelled. Trends in riverine inputs have been analysed. Concentrations above given threshold levels have been detected for both metals and organic pollutants in some rivers.

To document

Abstract

There is a common need for reliable hydropedological information in Europe. In the last decades research institutes, universities and government agencies have developed local, regional and national datasets containing soil physical, chemical, hydrological and taxonomic information often combined with land use and landform data. A hydrological database for western European soils was also created in the mid-1990s. However, a comprehensive European hydropedological database, with possible additional information on chemical parameters and land use is still missing. A comprehensive joint European hydropedological inventory can serve multiple purposes, including scientific research, modelling and application of models on different geographical scales. The objective of the joint effort of the participants is to establish the European Hydropedological Data Inventory (EU-HYDI). This database holds data from European soils focusing on soil physical, chemical and hydrological properties. It also contains information on geographical location, soil classification and land use/cover at the time of sampling. It was assembled with the aim of encompassing the soil variability in Europe. It contains data from 18 countries with contributions from 29 institutions. This report presents an overview of the database, details the individual contributed datasets and explains the quality assurance and harmonization process that lead to the final database.