The accumulation of sediments in stormwater systems negatively affects their functioning. For example, the re-suspension of these sediments can lead to serious pollution of surface water bodies through combined sewer overflows (CSOs). In addition, the persistent accumulation of sediments reduces the storage and hydraulic capacity of stormwater systems, resulting in an increased risk of flooding. Stormwater managers spend considerable resources cleaning these systems, but we still lack reliable and easy-to-use monitoring methods to provide information on the location, volume and composition of sediments. This study explores the use of temperature sensors combined with the analysis of heat transfer processes to measure sediment depth in sand trap gully pots. To this end, a laboratory-scale experimental campaign was carried out using a 1 : 1 scale gully pot model, with different sediment types, hydrographs and inflow temperature conditions. The experiments were designed using field measurements to reproduce the temperature changes in gully pots and thus the heat transfer processes. The results showed maximum differences between reference measurements and estimated depths of less than 30 mm. Finally, the use of temperature sensors as a cost-effective solution for monitoring sediment accumulation is discussed.

Urban drainage systems are composed of subsystems. The ratio of the storage and discharge capacities of the subsystems determines the performance. The performance of the urban water system may deteriorate as a result of the change in the ratio of storage to discharge capacity due to aging, urbanisation and climate change. We developed the graph-based weakest link method (GBWLM) to analyse urban drainage systems. Flow path analysis from graph theory is applied instead of hydrodynamic model simulations to reduce the computational effort. This makes it practically feasible to analyse urban drainage systems with multi-decade rainfall series. We used the GBWLM to analyse the effect of urban water system aging and/or climate scenarios on flood extent and frequency. The case study shows that the results of the hydrodynamic models and the GBWLM are similar. The rainfall intensities of storm events are expected to increase by approximately 20% in the Netherlands due to climate change. For the case study, such an increase in load has little impact on the flood frequency and extent caused by gully pots and surface water. However, it could lead to a 50% increase in the storm sewer flood frequency and an increase in the extent of flooding.

The main application of the mobile geo-electrical measurement is the detection of the presence and determining the location of leakage in sewer systems. To do so, this method relies on the increase in the measured electrical current between an electrode inside and an electrode outside the sewer system. To use this technique for the quantification of leakages further assumptions on the measured current are required. In this study, a model to simulate the geo-electrical measurement system is developed. Laboratory experiments are conducted to investigate the influence and contribution of the model components on the measured current and the validity of the assumptions. The experimental results demonstrate that multiple components significantly contribute to the measured current apart from the leakage in the pipe. As a consequence, the properties of the leakage in the pipe are likely to be significantly under- or overestimated in most measuring systems currently applied in practice.

Hydrodynamic models are used to analyse water networks (water distribution, drainage, surface water, district heating, etc.). The non-linear nature of water flows necessitates the use of iterative solution methods in hydraulic modelling. This requires a relatively large computational effort. To reduce this effort, networks, network forcing and/or the flow in networks are often simplified and analysed using the Graph Theory. The simplification options depend on the network characteristics. There are many topological features to describe Graph-based networks. In this paper, these characteristics are summarised, applied on 7 urban drainage networks and discussed. As the topological features do not describe the networks in a uniform manner, a new type of topological characterisation of looped drainage networks (Network Linearisation Parameter, NLP) is proposed based on linearized hydraulics and bottlenecks identified in paths to outfalls.