Abutment scour is a complex three-dimensional phenomenon, which is one of the leading causes of marine structure damage. Structural integrity is potentially attainable through the precise estimation of local scour depth. Due to the high complexity of scouring hydrodynamics, existing regression-based relations cannot make accurate predictions. Therefore, this study presented a novel expansion of extreme learning machines (ELM) to predict abutment scour depth (d_s) in clear water conditions. The model was built using the relative flow depth (h/L), excess abutment Froude number (F_e), abutment shape factor (K_s), and relative sediment size (d₅₀/L). A wide range of experimental samples was collected from the literature, and data was utilized to develop the ELM model. The ELM model reliability was evaluated based on the estimation results and several statistical indices. According to the results, the sigmoid activation function (correlation coefficient, R = 0.97; root mean square error, RMSE = 0.162; mean absolute percentage error, MAPE = 7.69; and scatter index, SI = 0.088) performed the best compared with the hard limit, triangular bias, radial basis, and sine activation functions. Eleven input combinations were considered to investigate the impact of each dimensionless variable on the abutment scour depth. It was found that d_s/L = f (F_e, h/L, d₅₀/L, K_s) was the best ELM model, indicating that the dimensional analysis of the original data properly reflected the underlying physics of the problem. Also, the absence of one variable from this input combination resulted in a significant accuracy reduction. The results also demonstrated that the proposed ELM model significantly outperformed the regression-based equations derived from the literature. The ELM model presented a fundamental equation for abutment scours depth prediction. Based on the simulation results, it appeared the ELM model could be used effectively in practical engineering applications of predicting abutment scour depth. The estimated uncertainty of the developed ELM model was calculated and compared with the conventional and artificial intelligence-based models. The lowest uncertainty with a value of ±0.026 was found in the proposed model in comparison with ±0.50 as the best uncertainty of the other models.

Planning and implementation of effective restoration projects require appropriate assessment of a river’s hydromorphological status. Two European standards on hydromorphological assessment of rivers and hydromorphological assessment methods used in Poland are reviewed in the context of their applicability for river restoration purposes. River Hydromorphological Quality assessment method is presented with a case study of the Biała River, Polish Carpathians, where this assessment was used as basis for a restoration project aimed to establish an erodible river corridor. The results of the assessment revealed significant differences in hydromorphological quality between unmanaged and channelized river cross-sections, indicating channel regulation as a major cause of the hydromorphological degradation of the Biała and confirming the choice of the erodible river corridor as an appropriate method of its restoration. The assessment indicated hydromorphological features of the river that were severely modified within the channelized reaches and which are likely to improve the most with the removal of bank protection and allowing free channel migration.

The method based on original metric called Hydromorphological Index for Rivers (HIR) was developed in 2017 for the purpose of the monitoring of the hydromorphological status of flowing waters in Poland. It fulfils requirements of the EU Water Framework Directive (WFD). It allows assessment of...

Urban development causes multiple water losses. Some of them may be ignored but some could have a huge influence on the whole catchment, including soil drought. As urban sprawl rises, space for unaffected infiltration and retention is increasingly limited. The objective of this study was to backcast and to estimate water-retention loss due to urbanization during the period of 1990–2018. We used landcover data, meteorological and hydrological data and data on soil water-holding capacity. Water-retention loss was expressed as soil water retention capacity loss, net precipitation loss and total sum of precipitation loss. Historical change in urban extension has led to large impacts on the hydrological cycle of the study area. Progressive urban development caused water-retention losses which range from 3.380 to 14.182 millions of cubic meters—depending on the methodology used. Hydrological analysis showed the lack of a significant trend (decrease trend) of low flow which is caused by the high percentage of natural land use in the upper part of catchment. Our results show that backcasting of water retention change using CLC data (a) brings new and plausible data on retention loss, (b) is possible to replicate and (c) data used are common and easy-to-get.

Background: Some swimmers reach high performance level at a relatively young age. The purpose of this study is to determine the relationship between adolescent female swimmers’ 100 m front crawl race ($V_{total100}$) and several anthropometry, body composition, and physiological and specific strength indices. Methods: Nineteen adolescent female swimmers were examined for biological age (BA) and body composition. Oxygen uptake was measured during water-flume stage-test front crawl swimming with ventilatory thresholds examination. Specific strength indices were assessed during 30 s of tethered swimming. Stroke rate (SR), stroke length (SL), and stroke index (SI) were also examined. Results: BA was strongly correlated with anthropometrics and tethered swimming strength indices, and showed moderate to strong correlation with ventilatory thresholds. Speed of swimming in the race was moderately to largely correlated with speed at $\dot{V}{O}_{2 }max$−$V_{\dot{V}{O}_{2}max}$ (r = 0.47–0.55; p < 0.05)—ventilatory thresholds ($V_{AT}$,$V_{RCP}$) (r = 0.50–0.85; p < 0.05), SL (r = 0.58–0.62; p < 0.05), and SI (r = 0.79–0.81; p < 0.01). Conclusion: Results confirmed a significant role of biological maturation mediation on body composition and body size, ventilatory indices, and specific strength indices. BA was not a significant mediation factor influencing the swimming kinematics (SL, SI) and speeds of $V_{AT}$, $V_{RCP}$ or $V_{\dot{V}{O}_{2 }max}$, which were strong predictors of the 100 m race.

The increase of impermeable areas in a catchment is known to elevate flood risk. To adequately understand and plan for these risks, changes in the basin water cycle must be quantified as imperviousness increases, requiring the use of hydrological modeling to obtain design runoff volumes and peak flow rates. A key stage of modeling is adopting the structure of the model and estimating its parameters. Due to the fact that most impervious basins are uncontrolled, hydrological models that do not require parameter calibration are advantageous. At the same time, it should be remembered that these models are sensitive to the values of assumed parameters. The purpose of this work is to determine the effect of catchment impermeability on the flow variability in the Sudół Dominikański stream in Cracow, Poland, and assess the influence of the frequency of rainfall on values of time of concentration (here it is meant as critical storm duration). The major finding in this work is that the critical storm duration for all different scenarios of catchment imperviousness depends on the rainfall exceedance probability. In the case of rainfall probability lower than 5.0%, the critical storm duration was equal to 2 h, for higher probabilities (p ≥ 50%) it was equal to 24 h. Simulations showed that the increase of impermeable areas caused peak time abbreviation. In the case of rainfall with exceedance probability p = 1.0% and critical storm duration D_kr = 2 h, the peak time decreased about 12.5% and for impermeable areas increased from 22.01 to 44.95%.