On the development and analysis of coupled surface-subsurface models of catchments. Part 2. A three-dimensional benchmark model and its properties

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface and subsurface flows are considered. In this second part, we construct a benchmark catchment scenario and investigate the effects of parameters within their typical ranges. Previous research on coupled surface–subsurface models have focused on numerical simulations of site-specific catchments. Here, our focus is broad, emphasising the study of general solutions to the mathematical models, and their dependencies on dimensionless parameters. This study provides a foundation based on the examination of a geometrically simple three-dimensional benchmark scenario. We develop a non-dimensional coupled surface–subsurface model and extract the key dimensionless parameters. Asymptotic methods demonstrate under what conditions the model can be reduced to a two-dimensional form, where the principal groundwater and overland flows occur in the hillslope direction. Numerical solutions provide guidance on the validity of such reductions, and demonstrate the parametric dependencies corresponding to a strong rainfall event.</p

On the development and analysis of coupled surface-subsurface models of catchments. Part 2. A three-dimensional benchmark model and its properties

The objective of this three-part work is the formulation and rigorous analysis of a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled effects of surface and subsurface flows are considered. In this second part, we construct a benchmark catchment scenario and investigate the effects of parameters within their typical ranges. Previous research on coupled surface-subsurface models have focused on numerical simulations of site-specific catchments; here our focus is broader and emphasises the study of general solutions to the mathematical models, and their dependencies on dimensionless parameters. This study provides a foundation based on the examination of a geometrically simple three-dimensional benchmark scenario. We develop a nondimensional coupled surface-subsurface model, and extract the key dimensionless parameters. We then apply asymptotic methods in order to discuss some potential simplifications, including the reduction of the geometry to a two-dimensional form, where the principal groundwater and overland flows occur in the hillslope direction. Numerical solutions demonstrate the effects of model parameters and provide guidance on the validity of the dimensional reductions

On the development and analysis of coupled surface-subsurface models of catchments. Part 3. Analytical solutions and scaling laws

The objective of this three-part work is the formulation and rigorous analysis of a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled effects of surface and subsurface flows are considered. In this third part, we focus on the development of analytical solutions and scaling laws for a benchmark catchment model that models the river flow (runoff) generated during a single rainfall. We demonstrate that for catchments characterised by a shallow impenetrable bedrock, the shallow-water approximation allows a reduction of the governing formulation to a coupled system of one-dimensional time-dependent equations for the surface and subsurface flows. Asymptotic analysis is used to derive semi-analytical solutions of the model. We provide simple asymptotic scaling laws describing the peak flow formation. These scaling laws can be used as an analytical benchmark for assessing the validity of other physical, conceptual, or statistical models of catchments

On the development and analysis of coupled surface-subsurface models of catchments. Part 1. Parameter estimation and sensitivity analysis of catchment properties

The objective of this three-part work is the formulation and rigorous analysis of a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled effects of surface and subsurface flows are considered. In this first part, we identify and analyse the key physical parameters that appear in governing formulations used within hydrodynamic rainfall-runoff models. Such parameters include those related to the catchment dimensions, topography, soil and rock properties, rainfall intensities, Manning's coefficients, and river channel dimensions. Despite the abundance of research that has produced data sets describing properties of specific river basins, there have been few studies that have investigated the ensemble of typical scaling of key physical properties; these are needed in order to perform a proper dimensional analysis of rainfall-runoff models. Therefore, in this work, we perform an extensive analysis of the parameters; our results form a benchmark and provide guidance to practitioners of the typical parameter sizes and interdependencies. Crucially, the analysis is presented in a fashion that can be reproduced and extended by other researchers, and wherever possible, uses publicly available data sets for catchments in the United Kingdom

A calibration-free physicality-based model for predicting peak river flows

Many simple hydrologic models are based on parametric statistical relations between the river flow and catchment properties such as its area, precipitation rates, soil properties, etc., fitted to the available data. The main objective of this work is to explain how these statistical relations emerge from the physical laws governing surface and subsurface flow at a catchment scale. The main achievement of this work is the derivation of an analytic formula for predicting peak monthly and annual river flows. It does not require any parameter calibration, but requires a measurement or estimation of the mean flow at the given catchment's outlet. We found that this model 1) has a simple physical interpretation, 2) provides more precise estimates than the median maximum annual flow (QMED) estimation method from the Flood Estimation Handbook (FEH), commonly used to estimate flood risk in the ungauged catchments in the UK, and 3) is highly accurate for all types of catchments, including the small catchments, for which the standard FEH method is the least accurate

On the development and analysis of coupled surface–subsurface models of catchments. Part 1. Analysis of dimensions and parameters for UK catchments

The objective of this three-part work is the formulation and rigorous analysis of a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled effects of surface and subsurface flows are considered. In this first part, we identify and analyse the key physical parameters that appear in governing formulations used within hydrodynamic rainfall-runoff models. Such parameters include those related to the catchment dimensions, topography, soil and rock properties, rainfall intensities, Manning's coefficients, and river channel dimensions. Despite the abundance of research that has produced data sets describing properties of specific river basins, there have been few studies that have investigated the ensemble of typical scaling of key physical properties; these are needed in order to perform a proper dimensional analysis of rainfall-runoff models. Therefore, in this work, we perform an extensive analysis of the parameters; our results form a benchmark and provide guidance to practitioners of the typical parameter sizes and interdependencies. Crucially, the analysis is presented in a fashion that can be reproduced and extended by other researchers, and wherever possible, uses publicly available data sets for catchments in the United Kingdom

On the development and analysis of coupled surface-subsurface models of catchments. Part 3. Analytical solutions and scaling laws

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface and subsurface flows are considered. In this third part, we focus on the development of analytical solutions and scaling laws for a benchmark catchment model that models the river flow (runoff) generated during a single rainfall. We demonstrate that for catchments characterised by a shallow impenetrable bedrock, the shallow-water approximation allows a reduction of the governing formulation to a coupled system of one-dimensional time-dependent equations for the surface and subsurface flows. Asymptotic analysis is used to derive semi-analytical solutions for the model. We provide simple asymptotic scaling laws describing the peak flow formation, and demonstrate its accuracy through a comparison with the two-dimensional model developed in Part 2. These scaling laws can be used as an analytical benchmark for assessing the validity of other physical, conceptual or statistical models of catchments.</p

Malicious Keccak

In this paper, we investigate Keccak --- the cryptographic hash function adopted as the SHA-3 standard. We propose a malicious variant of the function, where new round constants are introduced. We show that for such the variant, collision and preimage attacks are possible. We also identify a class of weak keys for the malicious Keccak working in the MAC mode. Ideas presented in the paper were verified by implementing the attacks on the function with the 128-bit hash

Finding Differential Paths in ARX Ciphers through Nested Monte-Carlo Search

We propose the adaptation of Nested Monte-Carlo Search algorithm for finding differential trails in the class of ARX ciphers. The practical application of the algorithm is demonstrated on round-reduced variants of block ciphers from the SPECK family. More specifically, we report the best differential trails,up to 9 rounds, for SPECK32

Hebbian continual representation learning

Continual Learning aims to bring machine learning into a more realistic scenario, where tasks are learned sequentially and the i.i.d. assumption is not preserved. Although this setting is natural for biological systems, it proves very difficult for machine learning models such as artificial neural networks. To reduce this performance gap, we investigate the question whether biologically inspired Hebbian learning is useful for tackling continual challenges. In particular, we highlight a realistic and often overlooked unsupervised setting, where the learner has to build representations without any supervision. By combining sparse neural networks with Hebbian learning principle, we build a simple yet effective alternative (HebbCL) to typical neural network models trained via the gradient descent. Due to Hebbian learning, the network have easily interpretable weights, which might be essential in critical application such as security or healthcare. We demonstrate the efficacy of HebbCL in an unsupervised learning setting applied to MNIST and Omniglot datasets. We also adapt the algorithm to the supervised scenario and obtain promising results in the class-incremental learning