Scale Parameter Research Articles

SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains

Abstract. Floodplains are a vital part of the global riverine system. Among all the global floodplain delineation strategies empowered by remote sensing, digital elevation model (DEM)-based delineation is considered to be computationally efficient with relatively low uncertainties, but the parsimonious model struggles with incorporating the basin-level spatial heterogeneity of the hydrological and geomorphic influences into the map. In this study, we propose a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. Specifically, we develop a stepwise approach to estimate the floodplain hydraulic geometry (FHG) scaling parameters for river basins worldwide at the scale of the level-3 HydroBASINS to best respect the scaling law while approximating the spatial extent of two publicly available global flood maps derived from hydrodynamic modeling. The estimated FHG exponent exhibits a significant positive relationship with the basins' hydroclimatic conditions, particularly in 33 of the world's major river basins, indicating the ability of the approach to capture fingerprints from heterogeneous hydrological and geomorphic influences. Based on the spatially varying FHG parameters, a ∼ 90 m resolution global floodplain map named the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT) is delineated, which takes the hydrologically corrected MERIT Hydro dataset as the DEM inputs and the height above nearest drainage (HAND) as the terrain attribute. Our results demonstrate that SHIFT validates better with reference maps than both hydrodynamic-modeling- and DEM-based approaches with universal parameters. The improved delineation mainly includes better differentiation between main streams and tributaries in major basins and a more comprehensive representation of stream networks in aggregated river basins. SHIFT estimates the global floodplain area to be 9.91×106 km2, representing 6.6 % of the world's total land area. SHIFT data layers are available at two spatial resolutions (90 m and 1 km), along with the updated parameters, at https://doi.org/10.5281/zenodo.11835133 (Zheng et al., 2024). We anticipate that SHIFT will be used to support applications requiring boundary delineations of the global geomorphic floodplains.

Scale parameters of soft structures for surrounding rock erosion prevention in rockburst-prone roadways

Practical experience in coal mines has suggested that establishing a loose and soft structure in the surrounding rock of roadways can play a role in wave attenuation, energy absorption and erosion prevention, which is conducive to the prevention of and reduction in the severity of rockburst disasters in coal mines. The scale parameters of soft structures includes two aspects: the size and the fracture degree of soft structures. The FLAC3D numerical simulation software was used to study the failure characteristics of roadways with different impact positions (roof impact, side impact) and different impact energies (104, 105, 106, and 107 J). The stress reduction rates of soft structures with different sizes and fracture degrees were calculated. Based on the stress reduction rate of the soft structure, the energy absorption effect of the soft structure around the roadway was obtained as a logarithmic function of the soft structure size, which is a power function related to its fracture degree, and the intersection range of the two curves was fitted. The stress reduction rate was 30% when the soft structure size of the surrounding rock of the roadway was 10–15 m and the fracture degree was represented by 30–40% of the coal strength, which was the most reasonable range of scale parameters. The research conclusions provide a parametric basis for improving the theory and practice of rockburst prevention and support in coal mine roadways.

Thermodynamics and dynamics of coupled complex SYK models.

It has been known that the large-q complex SYK model falls under the same universality class as that of van der Waals (mean-field) and saturates the Maldacena-Shenker-Stanford bound, both features shared by various black holes. This makes the SYK model a useful tool in probing the fundamental nature of quantum chaos and holographic duality. This work establishes the robustness of this shared universality class and chaotic properties for SYK-like models by extending to a system of coupled large-q complex SYK models of different orders. We provide a detailed derivation of thermodynamic properties, specifically the critical exponents for an observed phase transition, as well as dynamical properties, in particular the Lyapunov exponent, via the out-of-time correlator calculations. Our analysis reveals that, despite the introduction of an additional scaling parameter through interaction strength ratios, the system undergoes a continuous phase transition at low temperatures, similar to that of the single SYK model. The critical exponents align with the Landau-Ginzburg (mean-field) universality class, shared with van der Waals gases and various AdS black holes. Furthermore, we demonstrate that the coupled SYK system remains maximally chaotic in the large-q limit at low temperatures, adhering to the Maldacena-Shenker-Stanford bound, a feature consistent with the single SYK model. These findings establish robustness and open avenues for broader inquiries into the universality and chaos in complex quantum systems. We provide a detailed outlook for future work by considering the ``very" low-temperature regime, where we discuss relations with the Hawking-Page phase transition observed in the holographic dual black holes. We present preliminary calculations and discuss the possible follow-ups that might be be taken to make the connection robust.

On the Convergence of the Drainage Network with Branching

The Drainage Network is a system of coalescing random walks, exhibiting long-range dependence before coalescence, introduced by Gangopadhyay, Roy, and Sarkar [14]. Coletti, Fontes, and Dias [5] proved its convergence to the Brownian Web under diffusive scaling. In this work, we introduce a perturbation of the system allowing branching of the random walks with low probabilities varying with the scaling parameter. When the branching probability is inversely proportional to the scaling parameter, we show that this drainage network with branching consists of a tight family such that any weak limit point contains a Brownian Net. We conjecture that the limit is indeed the Brownian Net.

On the Applications of a New Advanced PEPFG Mathematical Model for HTM Dynamic Behavior of SDF Sandwich Plates

Considering the crucial role of the flexoelectricity phenomena (the electrical polarization–strain gradient coupling) in the mechanical behavior of different structures on the micro/nanoscale, this paper is derives the motion equations of a size-dependent flexoelectric (SDF) sandwich plate to study its hygro-thermo-mechanical (HTM) dynamic behavior. The model is a three-layer microplate including a porous exponential and power–law functionally graded (PEPFG) mid-layer, and two flexoelectric face sheets. The whole structure is under hygrothermal loading and the Vlasov foundation serves as the stand for the structure. Then, Hamilton’s principle and modified couple stress theory (MCST) are implemented to derive the motion equations. The new PEPFG utilization besides evaluating the impact of the length scale parameter, hygrothermal loading, materials composition, porosity, foundation parameter, and boundary conditions on the normalized natural frequency (NNF) of such an SDF sandwich model is the novelty of this paper. It is revealed that the lateral ratio enhancement causes NNF and stiffness reduction in the model. Furthermore, among all considered boundary types, simply supported and clamped refer to the lowest and the highest NNFs, respectively. This paper serves as a good source to provide a better understanding of the dynamic response of high stiffness-to-weight ratio structures to different variable variations.

Inference of multi‐sample stage life testing model under Weibull distribution

AbstractIn this article we consider the meta‐analysis of stage life testing experiments. We propose a method to combine the data obtained from number of independent stage life testing experiments. We have assumed that there are only two stress levels for each stage life testing experiment and lifetime of the experimental units follows Weibull distribution at each stress level. The distributions under two stress levels are connected through Khamis–Higgings model assumption. We assume that the shape parameters of Weibull distribution are same for all the samples; however, the scale parameters are different. We provide the maximum likelihood estimation and the asymptotic confidence intervals of the model parameters. We also provide the Bayesian inference of the model parameters. The Bayes estimates and the associated credible intervals are obtained using Gibbs sampling technique since the explicit forms of the Bayes estimates do not exist. We have performed an extensive simulation study to see the performances of the different estimators, and the analyses of two data sets for illustrative purpose. The results are quite satisfactory.

Mathematical Modelling of the Thermosolutal Effect on Blood Flow through a Micro-Channel in the Presence of a Magnetic Field

Substances such as mass concentrations in the blood cause circulation challenges. Blood is a substance made up of 55% plasma and 45% hemoglobin, which flows through the blood vessels and is aided by the heart in pumping to all organs and other tissues and cells in the human body. Mathematical modelling plays an important role in understanding the blood circulation problem in the human body, and it helps transform the real-life cardiovascular problem into a system of mathematical equations. In this research, we transformed the real-life cardiovascular problem of the heat effect on mass concentration and blood flow through blood vessels into a system of partial differential equations representing blood momentum, energy, and mass concentration equations after modifying the Navier-Stoke equation. The models are scaled from dimensional to dimensionless using specific scaling parameters. The scaled dimensionless equations were further perturbed and reduced to a system of ordinary differential equations, and the system of ODEs was solved using the Laplace method, where mathematical models representing blood velocity profiles, temperature profiles, and mass concentration profiles were obtained. A numerical simulation was performed using Wolfram Mathematica, version 12, where the effect of the pertinent parameters on the flow profiles was investigated and the results were presented graphically. The variation of the pertinent parameters such as the Grashof number, solutal Grashof number, Prandtl number, Soret number, Schmidt number, Darcy number, and magnetic field affect the flow profile such that the increase in Grashof number and solutal Grashof number causes the blood velocity to increase substantially at the centre of the vessel before decreasing to zero as the wall boundary layer increases, while the increase in Prandtl number and Soret number increases the blood temperature and velocity.

Generative adversarial networks with deep blind degradation powered terahertz ptychography

Ptychography is an imaging technique that uses the redundancy of information generated by the overlapping of adjacent light regions to calculate the relative phase of adjacent regions and reconstruct the image. In the terahertz domain, in order to make the ptychography technology better serve engineering applications, we propose a set of deep learning terahertz ptychography system that is easier to realize in engineering and plays an outstanding role. To address this issue, we propose to use a powerful deep blind degradation model which uses isotropic and anisotropic Gaussian kernels for random blurring, chooses the downsampling modes from nearest interpolation, bilinear interpolation, bicubic interpolation and down-up-sampling method, and introduces Gaussian noise, JPEG compression noise, and processed detector noise. Additionally, a random shuffle strategy is used to further expand the degradation space of the image. Using paired low/high resolution images generated by the deep blind degradation model, we trained a multi-layer residual network with residual scaling parameters and dense connection structure to achieve the neural network super-resolution of terahertz ptychography for the first time. We use two representative neural networks, SwinIR and RealESRGAN, to compare with our model. Experimental result shows that the proposed method achieved better accuracy and visual improvement than other terahertz ptychographic image super-resolution algorithms. Further quantitative calculation proved that our method has significant advantages in terahertz ptychographic image super-resolution, achieving a resolution of 33.09 dB on the peak signal-to-noise ratio (PSNR) index and 3.05 on the naturalness image quality estimator (NIQE) index. This efficient and engineered approach fills the gap in the improvement of terahertz ptychography by using neural networks.

Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling

In a Hilbert setting we aim to study a second order in time differential equation, combining viscous and Hessian-driven damping, containing a time scaling parameter function and a Tikhonov regularization term. The dynamical system is related to the problem of minimization of a nonsmooth convex function. In the formulation of the problem as well as in our analysis we use the Moreau envelope of the objective function and its gradient and heavily rely on their properties. We show that there is a setting where the newly introduced system preserves and even improves the well-known fast convergence properties of the function and Moreau envelope along the trajectories and also of the gradient of Moreau envelope due to the presence of time scaling. Moreover, in a different setting we prove strong convergence of the trajectories to the element of minimal norm from the set of all minimizers of the objective. The manuscript concludes with various numerical results.

The analysis of scaled cracked components

A recent arrival in the open literature is the scaling theory finite similitude bringing into existence a countably infinite number of new similitude rules. The application of the theory to fracture mechanics has revealed that the first-order similitude rule is applicable in the sense that information gleaned from two fractured scaled components can be combined to capture the response of a third. This paper examines an unexplored aspect of the finite similitude theory, in that, it is shown how it can be re-configured for the purposes of scaling analysis. This is achieved by retaining the first derivative (with respect to scale) in the first-order rule and on involving an additional transport equation. The approach assumes the first-order rule to be exact, which is confirmed here, but in addition, has the advantage of automatically accounting for any defect-size related size effects that are present. It is a top-down scheme with analysis performed under the constraint of an imposed rule. To instigate the methodology, fracture mechanics for the first time is defined on a new scaling space, where all physical quantities are deemed dependent on a single dimensional scaling parameter β. This approach is demonstrated to facilitate the imposition of similitude rules and has led to the discovery of new relationships that connect fatigue responses at two sizes. Although analysis here is limited to linear elastic fracture mechanics (LEFM), it is demonstrated through proof, analytical, and experimentally validated numerical models, that the approach provides an exact scaling theory for fatigue.

Research on the Effects of Spatial Forms in Residential Blocks on Road Traffic Noise Distribution in Typical City of China

Integrating the block system into construction is the current trend in the development of residential areas in China. Road traffic noise is the major noise source in residential blocks, and its relationship with spatial forms of blocks remains unclear. In this study, 852 block models (258 block road network models and 594 models with buildings inside) were established and simulated with SoundPLAN 8.2 software, in order to reveal the impact of spatial forms (road network morphology, neighborhood scale, and architectural texture) on the road traffic noise distribution in residential blocks. Meantime, a prediction model based on spatial morphology parameters is proposed. It was found that (1) Without considering the impact of buildings, both the road network morphology and neighborhood scale parameters have significant effects on the distribution of road traffic noise, but road network morphology has a larger effect than neighborhood scale. (2) In the presence of buildings within the block, architectural texture parameters have effects on the distribution of road traffic noise, but to a lesser extent than road network morphology and neighborhood scale parameters. (3) This research employs principal component analysis to reduce the dimensionality of urban spatial form parameters. Subsequently, a model was developed to predict overall noise exposure levels in residential areas, which was validated by example. This model can be used as a tool for rapid prediction and diagnosis of the block acoustic environment. These findings offer insights for the planning and design of residential blocks from the perspective of optimizing the acoustic environment.

A size-dependent nonlinear isogeometric approach of bidirectional functionally graded porous plates

Recent progress in materials science and fabrication technologies, such as additive manufacturing (AM) or 3D printing, has facilitated the design and production of intricate multi-directional functionally graded (FG) materials which are playing a pivotal role in interdisciplinary engineering applications. Developing mathematical modeling for such nanostructures, however, remains challenging. The primary objective of this research, therefore, is to present a mathematical model for studying the static bending characteristics considering the geometric nonlinearity of bidirectional FG nanoplates with internal pores. The mathematical formulations are established by utilizing the first-order shear deformation theory and the von-Kármán assumption within the framework of an isogeometric approach based on NURBS basis functions. To account for the influence of both strain gradient and nonlocal elasticity, we adopt the nonlocal strain gradient theory including two independent material length scale parameters to predict the geometric nonlinearity performance of structures at small-scale levels. The mechanical properties of multi-directional FG material models are assumed to be continuously graded in two directions based on power law, while internal pores can be dispersed into two typical distribution patterns. Several numerical investigations are performed to evaluate the substantial impact of certain parameters on the nonlinear deflections of bidirectional FG nanoplates with pores under various conditions. Compared to existing studies, the key contribution is to present a robust numerical model aimed at elucidating both the stiffness-softening and stiffness-hardening mechanisms of multi-directional FG nanostructures under static bending conditions with geometric nonlinearity. These findings enhance our insights into nonlinear bending performance and contribute valuable design guidelines for future small-scale engineering structures. These innovative designs have become popular and are now crucial in state-of-the-art engineering applications, such as aerospace, nuclear systems, or thermal resistance devices.

The Evaluation Value of the Modified Lund-Kennedy Nasal Endoscopy Score on the Efficacy of Sublingual Immunotherapy for Allergic Rhinitis.

Allergic rhinitis (AR) is a growing public health problem worldwide. Respecting the significance of the modified Lund-Kennedy (MLK) score in rhinitis assessment, we delved into its evaluation value on the sublingual immunotherapy (SLIT) efficacy in AR patients. Totally 100 AR patients were enrolled, with pre- and post-SLIT MLK score, total nasal symptoms score (TNSS), total medication score (TMS), visual analogue scale (VAS), inflammatory cytokines, and immune function-related parameters compared. The correlations of MLK score with TNSS/TMS/VAS, as well as with IL-4/INF-γ/eosinophil (EOS)/percentage/specific immunoglobulin (sIgE)/sIgG were assessed by Spearman correlation analysis. The value of MLK score on assessing SLIT efficacy in AR patients was analyzed. SLIT treatment reduced MLK/TNSS/TMS/VAS scores, abated IL-4 level/EOS percentage/sIgE, and elevated INF-γ/sIgG levels. MLK score was positively correlated with pre- and post-SLIT TNSS score (rpre-treatment = 0.592, rpost-treatment = 0.756), TMS score (rpre-treatment = 0.385, rpost-treatment = 0.718), VAS score (rpre-treatment = 0.369, rpost-treatment = 0.704), IL-4 (rpre-treatment = 0.553, rpost-treatment = 0.639), EOS percentage (rpre-treatment = 0.511, rpost-treatment = 0.632), and sIgE (rpre-treatment = 0.472, rpost-treatment = 0.524), and negatively with INF-γ (rpre-treatment = -0.418, rpost-treatment = -0.578) and sIgG4 (rpre-treatment = -0.460, rpost-treatment = -0.613). The MLK score had an area under curve of 0.846 (77.01% sensitivity, 76.92% specificity, 4 cut-off value) and 0.944 (91.67% sensitivity, 92.11% specificity, 2 cut-off value) for assessing SLIT treatment as effective and markedly effective for the patients, respectively. The MLK score had good evaluation value on the efficacy of SLIT treatment in AR patients.

Closed-form energy-based signal detection analysis in presence of a Lomax fading channel in full hyper-Rayleigh regime

The presented research examines the energy-based spectrum sensing problem of a signal transmitted over a wireless communication channel with severe fading. To account for the most challenging propagation conditions, a recently developed Lomax wireless channel model was utilized, which exhibits hyper-Rayleigh characteristics over the entire range of possible parameter values. For the channel model under consideration, the existence of the specific hyper-Rayleigh regimes (i.e., weak, strong, and full) are identified asymptotically and studied numerically for a finite signal-to-noise ratio. For the most severe fading conditions, the system’s performance was assessed in terms of the average probability of detection, receiver operating characteristics, and area under the curve. These metrics were derived in closed-form for the cases of Maximum Ratio Combining at the receiver and without diversity reception. The obtained expressions were analyzed via numerical and statistical simulation as functions of system and channel parameters, including the sensing base, average signal-to-noise ratio, and scale parameter for the signal-to-noise probability distribution. The results from numerical simulations were compared with existing regulations specified in the 5G standard for energy-based detection in medium access procedures.

Wave solutions in nonlocal integral beams

Wave propagation in slender beams is addressed in the framework of nonlocal continuum mechanics. The elastodynamic problem is formulated exploiting consistent methodologies of pure integral, mixture and nonlocal strain gradient elasticity. Relevant wave solutions are analytically provided, with peculiar attention to reflection and near field phenomena occurring in presence of boundaries. Notably, the solution field is got as superimposition of incident, reflected, primary near field and secondary near field waves. The latter contribution represents a further effect due to the size dependent mechanical behaviour. Limit responses for vanishing nonlocal parameter are analytically evaluated, consistently showing a zero amplitude of the secondary near field wave. Parametric analyses are carried out to show how length scale parameter, amplitude of incident wave and geometric and elastic properties of the beam affect the amplitudes of reflected, primary near field and secondary near field waves. The results obtained exploiting different nonlocal integral elasticity approaches are compared and discussed.

Dynamic J-A model improved by waveform scale parameters and R-L type fractional derivatives

PurposeThe purpose of this study is to model the global dynamic hysteresis properties with an improved Jiles–Atherton (J-A) model through a unified set of parameters.Design/methodology/approachFirst, the waveform scaling parameters β, λk and λc are used to improve the calculation accuracy of hysteresis loops at low magnetic flux density. Second, the Riemann–Liouville (R-L) type fractional derivatives technique is applied to modified static inverse J-A model to compute the dynamic magnetic field considering the skin effect in wideband frequency magnetization conditions.FindingsThe proposed model is identified and verified by modeling the hysteresis loops whose maximum magnetic flux densities vary from 0.3 to 1.4 T up to 800 Hz using B30P105 electrical steel. Compared with the conventional J-A model, the global simulation ability of the proposed dynamic model is much improved.Originality/valueAccurate modeling of the hysteresis properties of electrical steels is essential for analyzing the loss behavior of electrical equipment in finite element analysis (FEA). Nevertheless, the existing inverse Jiles–Atherton (J-A) model can only guarantee the simulation accuracy with higher magnetic flux densities, which cannot guarantee the analysis requirements of considering both low magnetic flux density and high magnetic flux density in FEA. This paper modifies the dynamic J-A model by introducing waveform scaling parameters and the R-L fractional derivative to improve the hysteresis loops’ simulation accuracy from low to high magnetic flux densities with the same set of parameters in a wide frequency range.

Improved Temperature-Scalable DC model for SiC power MOSFET including Quasi-Saturation effect

In this paper, accurate temperature-dependent static model for Silicon-Carbide (SiC) power MOSFET is presented. The proposed model is formed by two equations relating to linear and saturation operating regions. In this model, new formalism of the saturation drain current is introduced to consider the peculiar features observed in the I-V static characteristics of the SiC power MOSFET: a) moderate inversion region, or region of low gate voltages and b) quasi-saturation region, region of high gate voltages at which the drain current becomes less sensitive to the increase of gate voltage. In addition, the model captures with high-precision the transition region between linear and saturation region, pinch-off region, noticed in the output characteristics of the SiC power MOSFETs. It will be shown that the model equations ensure continuity and smooth transition between all operating regions. Temperature scaling of the model is carried out by its temperature scaling parameters. The proposed compact model is simple and efficient using reduced number of technology independent parameters. Simple parameter extraction procedure is described that uses an optimizer algorithm based on good experimental initial guess. Excellent agreement is obtained by comparing model to TCAD simulation and device measurement.

Size-Dependent Finite Element Analysis of Functionally Graded Flexoelectric Shell Structures Based on Consistent Couple Stress Theory

The functionally graded (FG) flexoelectric material is a potential material to determine the structural morphing of aircrafts. This work proposes the penalty 20-node element based on the consistent couple stress theory for analyzing the FG flexoelectric plate and shell structures with complex geometric shapes and loading conditions. Several numerical examples are examined and prove that the new element can predict the size-dependent behaviors of FG flexoelectric plate and shell structures effectively, showing good convergence and robustness. Moreover, the numerical results reveal that FG flexoelectric material exhibits better bending performance and higher flexoelectric effect compared to homogeneous materials. Moreover, the increase in the material length scale parameter leads to a gradual increase in the natural frequencies of the out-of-plane modes of FG flexoelectric plate/shell, while the natural frequencies of the in-plane modes change minimally, resulting in the occurrence of mode-switching phenomena.

An Optimal Strategy for Estimating Weibull distribution Parameters by Using Maximum Likelihood Method

Several methods have been used to estimate the Weibull parameters such as least square method (LSM), weighted least square method (WLSM), method of moments (MOM), and maximum likelihood (MLE). The maximum likelihood method is the most popular method (MLE). Newton-Raphson method has been applied to solve the normal equations of MLE’s in order to estimate the Weibull parameters. The method was used to find the optimal values of the Weibull distribution parameters for which the log-likelihood function is maximized. We tried to find the approximation solution to the normal equations of the MLE’s because there is no close form for get analytical solution. In this work, we tried to carry out a study that show the difference between two strategies to solve the MLE equations using Newton-Raphson algorithm. Both two strategies are provided an optimal solution to estimate the Weibull distribution parameters but which one more easer and which one converges faster. Therefore, we applied both strategies to estimate the Weibull’s shape and scale parameters using two different types of data (Real and simulation). We compared between the results that we got by applying the two strategies. Two studies have been done for comparing and selecting the optimal strategy to estimate Weibull distribution parameters using maximum likelihood method. We used some measurements to compare between the results such as number of steps for convergence (convergence condition), the estimated values for AIC, BIC and the RMSE value. The results show the numerical solution that we got by applying first strategy convergence faster than the solution that we got by applying second strategy. Moreover, the MRSE estimated by applying the first strategy is lower than the MRSE estimated by applying second strategy for the simulation study with different noise levels and different samples size.

Continental Scale Regional Flood Frequency Analysis: Combining Enhanced Datasets and a Bayesian Framework

Flood frequency analysis at large scales, essential for the development of flood risk maps, is hindered by the scarcity of gauge flow data. Suitable methods are thus required to predict flooding in ungauged basins, a notoriously complex problem in hydrology. We develop a Bayesian hierarchical model (BHM) based on the generalized extreme value (GEV) and the generalized Pareto distribution for regional flood frequency analysis at high resolution across a large part of North America. Our model leverages annual maximum flow data from ≈20,000 gauged stations and a dataset of 130 static catchment-specific covariates to predict extreme flows at all catchments over the continent as well as their associated statistical uncertainty. Additionally, a modification is made to the data layer of the BHM to include peaks over threshold flow data when available, which improves the precision of the discharge level estimates. We validated the model using a hold-out approach and found that its predictive power is very good for the GEV distribution location and scale parameters and improvable for the shape parameter, which is notoriously hard to estimate. The resulting discharge return levels yield a satisfying agreement when compared with the available design peak discharge from various government sources. The assessment of the covariates’ contributions to the model is also informative with regard to the most relevant underlying factors influencing flood-inducing peak flows. According to the developed aggregate importance score, the key covariates in our model are temperature-related bioindicators, the catchment drainage area and the geographical location.