Csilla Farkas

Senior Research Scientist

(+47) 948 14 727
csilla.farkas@nibio.no

Place
Ås F20

Visiting address
Fredrik A. Dahls vei 20, 1430 Ås

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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.

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Abstract

Climate change is expected to have a vigorous impact on soils and ecosystems due to elevated temperature and changes in precipitation (amount and frequency), thereby altering biogeochemical and hydrological cycles. Several phenomena associated with climate change and anthropogenic activity affect soils indirectly via ecosystem functioning (such as higher atmospheric CO2 concentration and N deposition). Continuous interactions between climate and soils determine the transformation and transport processes. Long-term gradual changes in abiotic environmental factors alter naturally occurring soil forming processes by modifying the soil water regime, mineral composition evolution, and the rate of organic matter formation and degradation. The resulting physical and chemical soil properties play a fundamental role in the productivity and environmental quality of cultivated land, so it is crucial to evaluate the potential outcomes of climate change and soil interactions. This paper attempts to review the underlying long-term processes influenced by different aspects of climate change. When considering major soil forming factors (climate, parent material, living organisms, topography), especially climate, we put special attention to soil physical properties (soil structure and texture, and consequential changes in soil hydrothermal regime), soil chemical properties (e.g. cation exchange capacity, soil organic matter content as influenced by changes in environmental conditions) and soil degradation as a result of longterm soil physicochemical transformations. The temperate region, specifically the Carpathian Basin as a heterogeneous territory consisting of different climatic and soil zones from continental to mountainous, is used as an example to present potential changes and to assess the effect of climate change on soils. The altered physicochemical and biological properties of soils require accentuated scientific attention, particularly with respect to significant feedback processes to climate and soil services such as food security.

Abstract

The determination of environmentally minimum water level in lakes is essential for the protection of their ecosystems. The assessment of minimum water level depends on a number of biotic and abiotic factors of the lake ecosystem; however, in many cases these factors are not easy to collect and assess in their entirety. At the same time, the lakes in many cases consist an important water reserve to meet the requirements arising from economic activities, e.g. industry, agriculture. In this paper, the morphological features in four lakes – Vegoritida, Petron, Cheimaditida and Zazari – of Northern Greece are analysed in order to assess their environmentally minimum water level. The morphological analysis is based on the relationship of the lake surface area and volume with the water level. An optimization method is applied taking into account that the biodiversity is favoured as the surface area covered by the lake is increased and the human water requirements are satisfied to the greatest possible extent by the available water volume of the lake. The environmentally minimum water level determined by the morphological analysis in the four lakes is compared with the minimum water level based on the analysis of the requirements of fish fauna and macrophytes.

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Abstract

Catchment scale hydrological models are promising tools for simulating the effect of catchment-specific processes and management on soil and water resources. Here, we present a model intercomparison study of runoff simulations using three different semi-distributed rainfall-runoff catchment models. The objective of this study was to demonstrate the applicability of the Hydrologiska Byrans Vattenavdelning (HBV-Light); Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport (PERSiST); and INtegrated CAtchment (INCA) models on Somogybabod Catchment, near Lake Balaton, Hungary. The models were calibrated and validated against observed discharge data at the outlet of the catchment for the period of January 1, 2006 –July 12, 2015. Model performance was evaluated using graphical representations, e.g. daily and monthly hydrographs and Flow Duration Curves (FDC) and model evaluation statistic; Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2). The simulation results showed that the models provided good estimates of monthly average discharge (0.60–0.90 NSE; 0.60–0.91 R2) and satisfactory results for daily discharge (0.46–0.62 NSE; 0.50–0.67 R2). We found that the application of hydrological models serves as a powerful basis for ensemble modelling of average runoff and could enhance our understanding of the eco-hydrological and transport processes within catchments. On the other hand, it can highlight the uncertainty of model forecasts and the importance of goal specific evaluation.

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Abstract

The main environmental stressor of the Baltic Sea is elevated riverine nutrient loads, mainly originating from diffuse agricultural sources. Agricultural practices, intensities, and nutrient losses vary across the Baltic Sea drainage basin (1.75 × 106 km2 , 14 countries and 85 million inhabitants). Six “Soil and Water Assessment Tool” (SWAT) models were set up for catchments representing the major agricultural systems, and covering the different climate gradients in the Baltic Sea drainage basin. Four fertilizer application scenarios were run for each catchment to evaluate the sensitivity of changed fertilizer applications. Increasing sensitivity was found for catchments with an increasing proportion of agricultural land use and increased amounts of applied fertilizers. A change in chemical fertilizer use of ±20% was found to affect watershed NO3-N loads between zero effect and ±13%, while a change in manure application of ±20% affected watershed NO3-N loads between zero effect and −6% to +7%.

Abstract

Knowledge of hydrological processes and water balance elements are important for climate adaptive water management as well as for introducing mitigation measures aiming to improve surface water quality. Mathematical models have the potential to estimate changes in hydrological processes under changing climatic or land use conditions. These models, indeed, need careful calibration and testing before being applied in decision making. The aim of this study was to compare the capability of five different hydrological models to predict the runoff and the soil water balance elements of a small catchment in Norway. The models were harmonised and calibrated against the same data set. In overall, a good agreement between the measured and simulated runoff was obtained for the different models when integrating the results over a week or longer periods. Model simulations indicate that forest appears to be very important for the water balance in the catchment, and that there is a lack of information on land use specific water balance elements. We concluded that joint application of hydrological models serves as a good background for ensemble modelling of water transport processes within a catchment and can highlight the uncertainty of models forecast.

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Abstract

Soil biological properties and CO 2 emission were compared in undisturbed grass and regularly disked rows of a peach plantation. Higher nutrient content and biological activity were found in the undisturbed, grass-covered rows. Significantly higher CO 2 fluxes were measured in this treatment at almost all the measurement times, in all the soil water content ranges, except the one in which the volumetric soil water content was higher than 45%. The obtained results indicated that in addition to the favourable effect of soil tillage on soil aeration, regular soil disturbance reduces soil microbial activity and soil CO 2 emission

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Abstract

The Hungarian Detailed Soil Hydrophysical Database, called MARTHA ver2.0 has been developed to collect information on measured soil hydraulic and physical characteristics in Hungary. Recently this is the largest detailed national hydrophysical database, containing controlled information from a total of 15,005 soil horizons. Two commonly used pedotransfer functions were tested to evaluate the accuracy of the predictions on the MARTHA data set, representative for Hungarian soils. In general, the application of both examined pedotransfer functions (Rajkai, 1988; Wösten et al., 1999) was not very successful, because these PTFs are representative for other soil groups. The classification tree method was used to evaluate the effect of soil structure on the goodness of estimations. It was found that using the soil structure data the inaccuracies of soil water retention predictions are more explainable and the structure may serve as a grouping variable for the development of class PTFs.