Water scarcity is a significant global challenge, exacerbated by leakages in water distribution networks. This paper addresses the challenge of detecting leakages in rural and urban–rural water supply systems through hydraulic modelling and a sensitivity analysis. Two distinct real-world network models were studied to assess real and simulated leakage scenarios varying in location and magnitude. A distinct leakage detection approach utilizing outflow measurements from hydrants was tested. Additionally, the effectiveness of various statistical measures—such as correlation, angular closeness, Euclidean distance, Manhattan distance, Chebyshev distance, cosine similarity, and Spearman correlation—were evaluated to determine their efficacy in leakage detection. Different methods for identifying leak candidates were explored and compared, either by selecting a single leak candidate based on similarity measures or by identifying a group of candidates to mark leak hotspots. Density-based spatial clustering of applications with noise was used to assess the number of potential leak candidate groups. The study’s findings contribute to the optimization of leak detection strategies in water supply networks, particularly in rural settings, where detection is challenging due to scarce measurement datasets, budget restrictions, and operational constraints.

The age of water in the municipal water supply system is one of the main factors influencing water quality. To create a good quality hydraulic model, one must achieve a high level of calibration accuracy with real life measurement data. Before we start building our model, we must decide on the model’s level of detail, that is, its complexity. We must know if skeletonization of the network graph and different hydraulic timesteps have an influence on simulation results. This study strives to prove that this decision can lead to unforeseen problems during the calibration process, thus making it impossible to achieve the required calibration precision. In order to prove this, two different model variants were created with different levels of graph detail, and simulation data results were used to determine which model variant is best suited to achieve the highest fidelity simulation results. Following this, the chosen model was run with different hydraulic timestep settings, which made it possible to showcase the large influence this setting has on achieved results.

Most of the small water companies supplying a small number of consumers with water are struggling with the extremely tight budget, often making any large-scale modernisation impossible. In effect network managed by these companies is often very leaky and unreliable. One possible and cheap way of leakage reduction is the reduction of average pressure in the network. Thanks to new computing technologies, the device selection process for pressure reduction is accurate and easy to do. This study uses the hydraulic model to select required pressure-reducing valves and correct locations accurately and adequately approximate the resulting absolute water loss reduction thanks to this approach.

Deciding on the level of model complexity is one of the first decisions that has to be made before engaging in the creation of a functional hydraulic model of a municipal water supply system. There are a number of influencing factors such as time needed to simulate the network, time needed to create such model and ease of use. The aim of this work is to prove that level of detail has influence on parameters such as pressure at measurement points, spread of flow speed and flow volume at different parts of mains. The Voronoi polygon method is one of the basic demand allocation methods, which, in the event of a different number of junctions depending on model complexity, has to generate a varying number of polygons of different sizes used to aggregate the demands.