The scarcity of water can result in a direct conflict between the protection of aquatic resources and water use. For many agencies, environmental flow (EF) methods are essential in environmental impact assessments and in the protection of important fisheries resources. The objective of this paper is to compare selected hydrological and hydraulic methods and determine the scientifically acceptable and cost-effective way to environmental flow within a section of a mountain river with high naturalness, on the example of the Wisłoka. In this paper, environmental flow was calculated using conventional hydrological methods: Tennant’s, Tessman’s, flow duration curve and hydraulic methods, wetted perimeter method (WPM) and method based directly on ichthyofauna habitat requirements (spawn and migration). The novelty is the combined use of the hydraulic and hydrological methods which relates to flow hydraulics based directly on ichthyofauna habitat conditions. The hydraulic methods provide lower values of environmental flow in comparison with the hydrological methods. The key issue in the use of the hydraulic methods is the choice of criteria. The development of the required set of parameters while taking into account their seasonal nature shifts the method toward habitat modeling methods. However, the scope of habitat requirements of ecosystems must be defined, including the set of aquatic organisms and watercourse type before a hydraulic method may be widely used. Being generally low-cost and simple, the methods presented in this paper can be applied in the water management legislative process.

The lower Ebro River experiences long-term hydrological and sedimentary adjustments following major regulation. Alterations in water and sediment fluxes have enhanced a massive macrophyte colonization that, in turn, generates a series of ecological and socio-economic problems. Controlled water releases, so-called flushing flows (FFs), have been designed and implemented since 2002 in this part of the river with the objectives of controlling macrophyte populations and maintaining sediment transport in the channel. FFs may produce adverse geomorphic effects, such as bed incision driven by the increased sediment transport capacity and the lack of sediment replacement from upstream. It is thus important to evaluate the potential geomorphic responses to a specific FF design, and redesign FFs regularly to maximize macrophyte removal while minimizing the undesired consequences. Geomorphic responses associated with FFs can be assessed using hydraulic and sediment transport models. In this paper, we use the hydrodynamic model CCHE2D W to evaluate the role of a monitored FF on a river's geomorphology. The designed FF had a duration of 13 h, attaining a maximum discharge of 1350 m 3 s À1 . A total of 3375 t of fine material were transported during that event. CCHE2D W model performance is evaluated in terms of hydraulics and sediment transport by comparing observed with modelled values (i.e. discharge, water surface elevation, sediment loads). Overall, objective functions indicate that simulations are in agreement with field observations. For instance, the Root Mean Square Error (RMSE) between the observed and modelled FF hydrograph was 93 m 3 s À1 , whereas the RMSE of the total load was 71 t. The example modelled here shows that the FF design typically implemented in the lower Ebro does not cause severe geomorphic impacts. The model provides visualization of the spatial patterns of erosion and deposition for the first time, allowing identification of critical zones where degradation or aggradation may occur.

The aim of the study was to analyze the possibility of using selected rainfall-runoff models to determine the design hydrograph and the related peak flow in a mountainous catchment. The basis for the study was the observed series of hydrometeorological data for the Grajcarek catchment area (Poland) for the years 1981–2014. The analysis was carried out in the following stages: verification of hydrometeorological data; determination of the design rainfall; and determination of runoff hydrographs with the following rainfall-runoff models: Snyder, NRCS-UH, and EBA4SUB. The conducted research allowed the conclusion that the EBA4SUB model may be an alternative to other models in determining the design hydrograph in ungauged mountainous catchments. This is evidenced by the lower values of relative errors in the estimation of peak flows with an assumed frequency for the EBA4SUB model, as compared to Snyder and NRCS-UH.

Two sets of triangular hydrographs were generated in a 12-m-long laboratory flume for two sets of initial bed conditions: intact and water-worked gravel bed. Flowrate ranging from 0.0013 m 3 s -1 to 0.0456 m 3 s -1 , water level ranging from 0.02 m to 0.11 m, and cumulative mass of transported sediment ranging from 4.5 kg to 14.2 kg were measured. Then, bedload transport rate, water surface slope, bed shear stress, and stream power were evaluated. The results indicated the impact of initial bed conditions and flow unsteadiness on bedload transport rate and total sediment yield. Difference in ratio between the amount of supplied sediment and total sediment yield for tests with different initial conditions was observed. Bedload rate, bed shear stress, and stream power demonstrated clock-wise hysteretic relation with flowrate. The study revealed practical aspects of experimental design, performance, and data analysis. Water surface slope evaluation based on spatial water depth data was discussed. It was shown that for certain conditions stream power was more adequate for the analysis of sediment transport dynamics than the bed shear stress. The relations between bedload transport dynamics, and flow and sediment parameters obtained by dimensional and multiple regression analysis were presented.

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Walega A., Ksiazek L. (2016): Influence of rainfall data on the uncertainty of flood simulation. Soil & Water Res., 11: 277−284.The aim of this paper was to determine the influence of factors related to rainfall data on the uncertainty flood simulation. The calculations were based on a synthetic unit hydrograph NRCS-UH. Simulation uncertainty was determined by means of GLUE method. The calculations showed that in the case of a catchment with limited meteorological data, it is better to use rainfall data from a single station located within the catchment, than to take into account the data from higher number of stations, but located outside the catchment area. The parameters of the NRCS-UH model (curve number and initial abstraction) were found to be less variable when the input contained rainfall data from a single rainfall station. It was also manifested by a lower uncertainty of the simulation results for the variant with one rainfall station, as compared to the variant based on the use of averaged rainfall in the catchment.Keywords: calibration; GLUE method; model quality; rainfall-runoff model Modelling of hydrological processes requires knowledge on local conditions related to the water cycle (Kovář et al. 2015). To accurately estimate floods with hydrological models, the model parameters and the initial state variables must be known. Good estimations of parameters and initial state variables are required to enable the models to make accurate estimations (Lü et al. 2013). According to Butts et al. (2004), the key factors determining the simulation accuracy involve input parameters and the hydrologist's knowledge of the model structure. Important factor, affecting the model outcomes, is the quality of information constituting the model input, mainly the precipitation data. Bormann (2006) indicated that high quality simulation results require high quality input data, but not necessarily always highly resolved data. The studies performed by Bárdossy and Das (2008) showed that the number and spatial distribution of the rain gauges affect the simulation results. Anctil et al. (2006) showed that model performance was rapidly reduced when the mean area rainfall was computed using a number of rain gauges lower than a certain number. Spatial distribution and the accuracy of the rainfall input to a rainfall-runoff model considerably influence the volume of storm runoff, peak runoff, and time-to-peak. Errors in storm-runoff estimation were directly related to spatial data distribution and the representation of spatial conditions across a catchment.The assessment of uncertainty of hydrological models is of major importance in hydrologic modelling. Generally, there are three principal sources contributing to modelling uncertainty: errors associated with input data and data for calibration, imperfection in a model structure, and uncertainty in model parameters . Xu et al. (2006) showed that the quality of precipitation data influenced both simulation errors and calibrated model parameters. The effect of input ...

This work was aimed at comparing the instream flow environment of four basic hydromorphological units of a mountain gravel-bed river: pools, runs, riffles and rapids. A survey was performed during the average flow stage on the Skawa River in southern Poland. In the 3.5 km long reach, 31 physical habitats were surveyed: eight pools, eight runs, nine riffles and seven rapids. Using Micro ADV Sontek equipment, instantaneous velocity time series components were measured at eight locations in three positions—z/h = 0.2, 0.4 and 0.6—in each unit. Turbulence descriptors—the mean components of velocity, turbulence intensities calculated as the root mean square of velocity component time series, turbulent kinetic energy TKE, Reynolds shear stresses and standard hydraulic attribute, i.e., Froude number—were estimated. Although there was a wide dispersion of the turbulence variable distributions, a standard tendency of decreased mean velocity and increased turbulence towards the bottom was observed. Most turbulence parameters—streamwise velocity, turbulence intensities, TKE and streamwise-vertical Reynolds shear stresses—reveal differences of instream flow environment between the pools, runs and riffles. In addition, the mean turbulence intensities suggested a 1:2:3:3 proportion of turbulence intensity in pools, runs, riffles and rapids, respectively. Riffles and rapids, in general, have similar turbulence values, whereas rapids are deeper and visually more energetic.

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