Volumen 65 (2017): Heft 2 (June 2017)

A three-dimensional numerical simulation of particle motion in a pipe with a rough bed is presented. The simulation based on the Lattice Boltzmann Method (LBM) employs the hybrid diffuse bounce-back approach to model moving boundaries. The bed of the pipe is formed by stationary spherical particles of the same size as the moving particles. Particle movements are induced by gravitational and hydrodynamic forces. To evaluate the hydrodynamic forces, the Momentum Exchange Algorithm is used. The LBM unified computational frame makes it possible to simulate both the particle motion and the fluid flow and to study mutual interactions of the carrier liquid flow and particles and the particle–bed and particle–particle collisions. The trajectories of simulated and experimental particles are compared. The Particle Tracking method is used to track particle motion. The correctness of the applied approach is assessed.

Hydrological monitoring in small headwater catchments provides the basis for examining complex interrelating hydraulic processes that govern the runoff generation. Contributions of different subsurface runoff mechanisms to the catchment discharge formation at two small forested headwater catchments are studied with the help of their natural isotopic signatures. The Uhlirska catchment (Jizera Mts., Czech Republic) is situated in headwater area of the Lusatian Neisse River. The catchment includes wetlands at the valley bottom developed over deluviofluvial granitic sediments surrounded by gentle hillslopes with shallow soils underlain by weathered granite. The Liz catchment (Bohemian Forest, Czech Republic) is situated in headwater area of the Otava River. It belongs to hillslope-type catchments with narrow riparian zones. The soil at Liz is developed on biotite paragneiss bedrock. The basic comparison of hydrological time series reveals that the event-related stream discharge variations at the Uhlirska catchment are bigger and significantly more frequent than at Liz. The analysis of isotope concentration data revealed different behavior of the two catchments during the major rainfall-runoff events. At Uhlirska, the percentage of the direct runoff formed by the event water reaches its maximum on the falling limb of the hydrograph. At Liz, the event water related fraction of the direct outflow is maximal on the rising limb of the hydrograph and then lowers. The hydraulic functioning of the Uhlirska catchment is determined by communication between hillslope and riparian zone compartments.

This paper investigates the impact of surface soil moisture assimilation on the estimation of both parameters and states in the Soil and Water Assessment Tool (SWAT) model using the ensemble Kalman filter (EnKF) method in upper Huai River basin. The investigation is carried out through a series of synthetic experiments and real world tests using a merged soil moisture product (ESA CCI SM) developed by the European Space Agency, and considers both the joint state-parameter updating and only state updating schemes. The synthetic experiments show that with joint state-parameter update, the estimation of model parameter SOL_AWC (the available soil water capacity) and model states (the soil moisture in different depths) can be significantly improved by assimilating the surface soil moisture. Meanwhile, the runoff modeling for the whole catchment is also improved. With only state update, the improvement on runoff modeling shows less significance and robustness. Consistent with the synthetic experiments, the assimilation of the ESA CCI SM with joint state-parameter update shows considerable capability in the estimation of SOL_AWC. Both the joint state-parameter update and the only state update scheme could improve the streamflow modeling although the optimal model and observation error parameters for them are quite different. However, due to the high vegetation coverage of the study basin, and the strong spatial mismatch between the satellite and the model simulated soil moisture, it is still challenging to significantly benefit the runoff estimates by assimilating the ESA CCI SM.

This paper represents an index model developed for the assessment of risk caused by river floods. The main purpose of this model is to evaluate the flood risk in the western coastal region of Mazandaran Province/Iran. The model assesses the risk at triple components, i.e. the flood occurrence probability, vulnerability and consequences, through identification and evaluation of effective criteria categorized into seven indexes (environmental, technical, economic, social, depth, population and sensitivity ones) that are involved in all stages of flooding (source, pathway and receptor). The flood risk in the developed model is defined by a dimensionless magnitude called as risk score between 0 and 100 for each zone of the area under assessment by calculating and combining of two newly defined factors: occurrence and vulnerability factor and impact factor. The model was applied in a case study, the Nowshahr flood in 2012. The results showed that: (i) the flood risk zoning was compared with observed data for aspect of the damages, and general agreement between them was obtained; (ii) for urban zones, which surrounded by two rivers, would easily be in critical condition and rescue operations face difficulties; and (iii) it is necessary to review the location of the emergency services, according the flood risk zoning.

The paper discusses changes in the hydrological regime of high mountain Lake Morskie Oko located in the Tatra Mountains, in the Tatra Mountains National Park, a UNESCO biosphere reserve (MaB). According to the research conducted in the years 1971–2015, its water stages decreased by 3.5 cm·dec⁻¹, mean annual water temperature increased by 0.3°C·dec⁻¹ and the duration of ice phenomena and ice cover was reduced by 10 day·dec⁻¹. No considerable changes in maximum values of ice cover thickness were recorded. Such tendencies are primarily caused by long-term changes in climatic conditions – air temperature and atmospheric precipitation. The hydrological regime of the lake was also determined by changes in land use in the lake’s catchment and its location in high mountains.

The objective of the study was to evaluate the spatial distribution of peakflow pre-event water contributions and streamwater residence times with emphasis on land use patterns in 38 subcatchments within the 687 km² large mesoscale transboundary catchment Lužická Nisa. Mean residence times between 8 and 27 months and portions of pre-event water between 10 and 97% on a storm event peakflow were determined, using ¹⁸O data in precipitation and streamwater from a weekly monitoring of nearly two years. Only a small tracer variation buffering effect of the lowland tributaries on the main stem was observed, indicating the dominant impact on the mountainous headwaters on the runoff generation. Longest mean streamwater residence times of 27 months were identified in the nearly natural headwaters of the Jizera Mountains, revealing no ambiguous correlation between the catchment area and altitude and the mean residence time of streamwater. Land use control on the pre-event water portions were determined for three land use categories with percentage of urban areas from 0 to 10%, 10 to 20% and more than 20%. The fraction of pre-event water in the first category decreases from 97% to 65% with the increasing percentage of forest from 76% to 100%, revealing that forests may provide only a limited infiltration of precipitation due to leaf interception and soil water use for transpiration. Fractions of pre-event water of 39–87% in the second (agricultural catchments) and of 10–35% in the third (urbanized catchments) category increase with percentage of non-urban areas.

The short-term predictions of annual and seasonal discharge derived by a modified TIPS (Tendency, Intermittency, Periodicity and Stochasticity) methodology are presented in this paper. The TIPS method (Yevjevich, 1984) is modified in such a way that annual time scale is used instead of daily. The reason of extracting a seasonal component from discharge time series represents an attempt to identify the long-term stochastic behaviour. The methodology is applied for modelling annual discharges at six gauging stations in the middle Danube River basin using the observed data in the common period from 1931 to 2012. The model performance measures suggest that the modelled time series are matched reasonably well. The model is then used for the short-time predictions for three annual step ahead (2013–2015). The annual discharge predictions of larger river basins for moderate hydrological conditions show reasonable matching with records expressed as the relative error from −8% to +3%. Irrespective of this, wet and dry periods for the aforementioned river basins show significant departures from annual observations. Also, the smaller river basins display greater deviations up to 26% of the observed annual discharges, whereas the accuracy of annual predictions do not strictly depend on the prevailing hydrological conditions.

Calibration of parameters of mathematical models is still a tough task in several engineering problems. Many of the models adopted for the numerical simulations of real phenomena, in fact, are of empirical derivation. Therefore, they include parameters which have to be calibrated in order to correctly reproduce the physical evidence. Thus, the success of a numerical model application depends on the quality of the performed calibration, which can be of great complexity, especially if the number of parameters is higher than one. Calibration is traditionally performed by engineers and researchers through manual trial-and-error procedures. However, since models themselves are increasingly sophisticated, it seems more proper to look at more advanced calibration procedures. In this work, in particular, an optimization technique for a multi-parameter calibration is applied to a two-phase depth-averaged model, already adopted in previous works to simulate morphodynamic processes, such as, for example, the dike erosion by overtopping.

Narrow particle size distribution basalt pebbles of mean particle size 11.5 mm conveyed by water in the pipe sections of different inclination were investigated on an experimental pipe loop, consisting of smooth stainless steel pipes of inner diameter D = 100 mm. Mixture flow-behaviour and particles motion along the pipe invert were studied in a pipe viewing section, the concentration distribution in pipe cross-section was studied with the application of a gamma-ray densitometer. The study refers to the effect of mixture velocity, overall concentration, and angle of pipe inclination on chord-averaged concentration profiles and local concentration maps, and flow behaviour of the coarse particle-water mixtures. The study revealed that the coarse particle-water mixtures in the inclined pipe sections were significantly stratified, the solid particles moved principally close to the pipe invert, and for higher and moderate flow velocities particle saltation becomes the dominant mode of particle conveying.

In this study, analytical models for predicting groundwater contamination in isotropic and homogeneous porous formations are derived. The impact of dispersion and diffusion coefficients is included in the solution of the advection-dispersion equation (ADE), subjected to transient (time-dependent) boundary conditions at the origin. A retardation factor and zero-order production terms are included in the ADE. Analytical solutions are obtained using the Laplace Integral Transform Technique (LITT) and the concept of linear isotherm. For illustration, analytical solutions for linearly space- and time-dependent hydrodynamic dispersion coefficients along with molecular diffusion coefficients are presented. Analytical solutions are explored for the Peclet number. Numerical solutions are obtained by explicit finite difference methods and are compared with analytical solutions. Numerical results are analysed for different types of geological porous formations i.e., aquifer and aquitard. The accuracy of results is evaluated by the root mean square error (RMSE).