Volume 24 (2016): Edizione 4 (December 2016)

The main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model), which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments), which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim). As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE) and the logarithmic Nash-Sutcliffe coefficient (logNSE). The model’s efficiency was evaluated by Volume error (VE). Subsequently, we evaluated the relationship between the model’s efficiency (VE) and changes in the climatic indicators (precipitation ΔP, air temperature ΔT). The implications of findings are discussed in the conclusion.

One of the most often-used parameters that describes morphology and runoff from a watershed is the time of concentration (Tc). At gauged watersheds, Tc can be determined using rainfall and a runoff hydrograph, while for ungauged watersheds, empirical equations are used. A good initial estimate of Tc greatly improves the accuracy of runoff predictions. In our study, we applied 14 empirical equations to determine Tc. Tarján Creek, which is located in northeastern Hungary, was selected as the trial gauged watershed. It is located in a mountainous region with an area of 72 km². The input parameters for the empirical equations were determined using geoinformatical tools. To evaluate the accuracy of the empirical equations, HEC-HMS was used to model the runoff. Using the measured runoff data, both continuous and event-based models were calibrated. For direct runoff, Clark’s unit hydrograph was selected. Tc is one of the input parameters for this model. After the calibration, the estimates from the empirical equations for Tc were compared to the HEC-HMS calibrated values for each subwatershed. The empirical estimates varied greatly. The Wisnovszky-equation, which is most often used in Hungary, underestimated Tc.

The way land is used has a significant impact on many hydrological processes that determine the generation of flood runoff or soil erosion. Advancements in remote sensing which took place in the second half of the 20th century have led to the rise of a new research area focused on analyses of land use changes and their impact on hydrological processes. This study deals with an analysis of the changes in land use over a period of almost three centuries in the Myjava River catchment, which has an outlet at Šaštín-Stráže. In order to obtain information about the way the land was used in the past, three historical mappings representing various periods were used: the first (1st) military mapping (1764-1787), second (2nd) military mapping (1807-1869), and a military topographic mapping (1953-1957). The historical mappings have been manually vectorised in an ArcGIS environment to identify various land use categories. The historical evolution of land use was further compared with a concurrent land use mapping, which was undertaken in 2010 and exploited remote sensing techniques. The study also quantifies the impact of these changes on the long-term catchment runoff as well as their impact on flows induced by extreme precipitation events. This analysis was performed using the WetSpa distributed hydrological model, which enables the simulation of catchment runoff in a daily time step. The analysis showed that the selected catchment has undergone significant changes in land use, mainly characterized by massive deforestation at the end of the 18th century and land consolidation in the middle of the 20th century induced by communist collectivisation. The hydrological simulations demonstrated that the highest and lowest mean annual runoffs were simulated in the first (1st military mapping) and the last (concurrent land use monitoring) time intervals respectively with the smallest and largest percentages of forested areas.

Current and ongoing changes in the climate are typified by a rise in global temperatures. Climate change can have a dramatic impact on the water cycle. The aim of this paper was to develop a model based on Thornthwaite-type monthly water balance estimations. The main goals were to calibrate the model parameters using a remote sensing-based evapotranspiration dataset. The calibrated model was used for projection on the basis of four climate model datasets (remo, dmihirham5, smhirca.bcm, knmiracmo2). The four main projection periods were: 1980-2010, 2010-2040, 2040-2070, and 2070-2100. The advantage of this model is its robust structure. It can be applied if temperature and precipitation time series are available. The key parameter is the water storage capacity of the soil (SOILMAX), which can be calibrated using the actual evapotranspiration data available. If the physical properties of the soil are known, the maximal rooting depth is also projectable. The model can be primarily used at the catchment level or for areas without additional amounts of water from below. For testing the model, a mixed parcel of land that is used as a cornfield near Mosonmagyaróvár and a small, forest-covered catchment near Sopron were successfully used as the datasets. Furthermore, we determined the water stress with the calculation of the relative extractable water (REW), soil water deficit (SWD), and the water stress index (IS).

Various data (biological, chemical, hydrological and morphological) have been gathered within the frame of the monitoring of the Water Framework Directive from 2007 in Hungary. This data only used a status assessment of certain water bodies in Hungary. The macroinvertebrates indicate many environmental factors well; therefore, they are very useful in detecting changes in the status of an environment. The main aim in this research was to investigate changes in environmental variables and decide how these variables cause big changes in the macroinvertebrate fauna. The macroinvertebrate data was processed using the ASTERICS 4.0.4 program. The program calculated some important metrics (i.e., microhabitat distributions, longitudinal zonation, functional feeding guilds, etc.). These metrics were compared with the chemical and hydrological data. The main conclusion is that if we have enough of a frequency and quality of macroinvertebrate data, we can understand changes in the environment of an ecosystem.

Many municipalities in Central Europe deal with the problem of invasive species in their natural ecosystems. Invasive vegetation eradicates native species and causes dense stands that damage the natural environment. This work shows how important it is to have an informative tool for municipalities to be successful in their struggles with invasive species. A Driver – Pressure – State – Impact - Response (DPSIR) framework is a decision - making tool, and this one is particularly applied to the species Fallopia japonica. Fallopia japonica is an extremely invasive and aggressive weed, and it is very often found in riverbank vegetation. This specific framework can be used as a tool for municipal managers to highlight all the problems with Fallopia japonica and define all the responses that should be provided by the municipalities. The work points out the steps that show how important it is to have a strategy or a clear concept of how to begin with such a serious issue as the presence of Fallopia japonica in riverbank vegetation and its eradication. This framework provides simple steps that cannot be excluded when a municipality start actions against Fallopia japonica. All the indicators used in the model are based on the information known about Fallopia japonica that are presented in the literature.