This paper presents Iber+, a new parallel code based on the numerical model Iber for two-dimensional (2D) flood inundation modelling. The new implementation, which is coded in C++ and takes advantage of the parallelization functionalities both on CPUs (central processing units) and GPUs (graphics processing units), was validated using different benchmark cases and compared, in terms of numerical output and computational efficiency, with other well-known hydraulic software packages. Depending on the complexity of the specific test case, the new parallel implementation can achieve speedups up to two orders of magnitude when compared with the standard version. The speedup is especially remarkable for the GPU parallelization that uses Nvidia CUDA (compute unified device architecture). The efficiency is as good as the one provided by some of the most popular hydraulic models. We also present the application of Iber+ to model an extreme flash flood that took place in the Spanish Pyrenees in October 2012. The new implementation was used to simulate 24 h of real time in roughly eight minutes of computing time, while the standard version needed more than 15 h. This huge improvement in computational efficiency opens up the possibility of using the code for real-time forecasting of flood events in early-warning systems, in order to help decision making under hazardous events that need a fast intervention to deploy countermeasures.

Stereology is the tridimensional interpretation of bidimensional sections of a structure, widely used in fields such as mineralogy, medicine, and biology. This paper proposes a general software to do stereological analysis, called STERapp, with a friendly graphical interface to enable expert supervision. It includes a module to estimate fish fecundity (number of mature oocytes in the ovary), which has been used by experts in fish biology in two Spanish marine research centers since 2020 to estimate the fecundity of five fish species with different reproductive strategies and oocytes characteristics. This module encloses advanced computer vision and machine learning techniques to automatically recognize and classify the cells in histological images of fish gonads. The automatic recognition algorithm achieved a sensitivity of 55.6%, a specificity of 64.8%, and an average precision of 43.1%. The accuracies achieved for oocyte classification were 84.5% for the maturity stages and 78.5% for the classification regarding presence/absence of the nucleus. This facilitates the analysis and saves experts’ time. Hence, the SUS questionnaire reported a mean score of 81.9, which means that the system was perceived from good to excellent to develop stereological analysis for the estimation of fish fecundity.

The traveling salesman problem (TSP) is a well studied NP-hard optimization problem. We present a novel heuristic to find approximate solutions for the case of the TSP with Euclidean metric. Our pair-center algorithm runs in quasi-linear time and on linear space. In practical experiments on a variety of well known benchmarks the algorithm shows linearithmic (i.e., $\mathcal{O}(nlogn)$) runtime. The solutions found by the pair-center algorithm are very good on smaller problem instances, and better than those generated by any other heuristic with at most quadratic runtime. Eventually, the average gap of the pair-center algorithm on all benchmark instances with less than 1 001 points is 0.94% and for all instances with more than 1000 points up to 100 million points is 4.57%.

Abstract: Floods are one of the most dangerous extreme events that can affect people and properties. These events have intensified worldwide over the last decades due to climate change. Therefore, the capability to predict and analyse, in a quick and accurate way, the effects of these floods is of crucial importance to avoid or minimize the hazards associated to them. This task can be accomplished by means of numerical tools as Iber. Iber is a 2-D numerical model, developed by GEAMA (Universidade da Coruña) and Flumen (Universitat Politècnica de Catalunya), that uses the finite volume technique to solve the 2-D Shallow Water Equations in order to obtain the water depth and velocity components of the flow under different scenarios. To assess the capabilities of Iber a series of test cases have been reproduced following the document “Benchmarking the latest generation of 2D hydraulic modelling packages” published by the non-departmental public body Environment Agency of the U.K. Government. The results show that Iber is a suitable tool to reproduce accurately different flooding scenarios. A new implementation of the model has been developed by EPHYSLAB. This implementation takes advantage of the modern hardware capabilities and provides significant speedups over the original code. The new possibilities offered by a faster code will be studied.