The hydrologic sciences and water resources management have long depended on a combination of in situ measurements and remotely sensed data for research and regulatory purposes. In situ measurements are constrained in their spatial distribution by both logistics and costs. Satellite‐ and manned aircraft‐based remote sensing provide spatially broad data, but often of a coarse resolution. Furthermore, all these data collection methods are often limited in their ability to respond to specific short‐term events when the data and imagery could inform real‐time assessment and decision‐making, especially during and immediately after natural disasters. Researchers and regulators are increasingly using unmanned aerial vehicles (UAVs) to fill these gaps in both spatial and temporal data resolution. UAVs are often more cost‐effective than traditional remote sensing or in situ data collection methodologies and the availability of new advancements in UAV design, power supply, payload capacity, and sensors has been driving rapid innovations in their use in the hydrological sciences. This in‐depth review explores these UAV technologies and how they are being employed for on‐demand and cost‐effective characterization, monitoring, assessment, and modeling of soil and water resources. Our discussion addresses both key opportunities and challenges in surface water and groundwater studies, land‐atmosphere interaction studies, water management in agriculture and forestry, ecosystem monitoring, and hydrological modeling.

Foundation scour is among the main causes of bridge collapse worldwide, resulting in significant direct and indirect losses. A vast amount of research has been carried out during the last decades on the physics and modelling of this phenomenon. The purpose of this paper is, therefore, to provide an up-to-date, comprehensive, and holistic literature review of the problem of scour at bridge foundations, with a focus on the following topics: (i) sediment particle motion; (ii) physical modelling and controlling dimensionless scour parameters; (iii) scour estimates encompassing empirical models, numerical frameworks, data-driven methods, and non-deterministic approaches; (iv) bridge scour monitoring including successful examples of case studies; (v) current approach for assessment and design of bridges against scour; and, (vi) research needs and future avenues.

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade–Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12–0.14 m s ${}^{-1}$ , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s ${}^{-1}$ image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s ${}^{-1}$ of the ADCP measurements, on average.

Since the turn of the 21st century, image-based velocimetry techniques have become an increasingly popular approach for determining open-channel flow in a range of hydrological settings across Europe and beyond. Simultaneously, a range of large-scale image velocimetry algorithms have been developed that are equipped with differing image pre-processing and analytical capabilities. Yet in operational hydrometry, these techniques are utilised by few competent authorities. Therefore, imagery collected for image velocimetry analysis (along with reference data) is required both to enable inter-comparisons between these differing approaches and to test their overall efficacy. Through benchmarking exercises, it will be possible to assess which approaches are best suited for a range of fluvial settings, and to focus future software developments. Here we collate and describe datasets acquired from seven countries across Europe and North America, consisting of videos that have been subjected to a range of pre-processing and image velocimetry analyses (Perks et al., 2020, https://doi.org/10.4121/uuid:014d56f7-06dd-49ad-a48c-2282ab10428e). Reference data are available for 12 of the 13 case studies presented, enabling these data to be used for reference and accuracy assessment.

Bridges are critical-infrastructure components of road and rail transport networks. A large number of these critical assets cross or are adjacent to waterways and floodplains and are therefore exposed to flood actions such as scour, hydrodynamic loading, and inundation, all of which are exacerbated by debris accumulations. These stressors are widely recognized as responsible for the vast majority of bridge failures around the world, and they are expected to be exacerbated due to climate change. While efforts have been made to increase the robustness of bridges to the flood hazard, many scientific and technical gaps remain. These gaps were explored during an expert workshop that took place in April 2021 with the participation of academics, consultants, and decision makers operating mainly in the United Kingdom and specializing in the fields of bridge risk assessment and management and flood resilience. The objective of the workshop was to identify and prioritize the most urgent and significant impediments to bridge flood resilience. In particular, the following issues, established at different levels and scales of bridge flood resilience, were identified and analysed in depth: (i) characterization of the effects of floods on different bridge typologies, (ii) uncertainties in formulae for scour depth assessment, (iii) evaluation of consequences of damage, (iv) recovery process after flood damage, (v) decision-making under uncertainty for flood-critical bridges, and (vi) use of event forecasting and monitoring data for increasing the reliability of bridge flood risk estimations. These issues are discussed in this paper to inform other researchers and stakeholders worldwide, guide the directions of future research in the field, and influence policies for risk mitigation and rapid response to flood warnings, ultimately increasing bridge resilience.

The time-dependent bridge pier scour during flood waves is analysed. Scour experiments were conducted in a novel installation able to produce complex hydrographs with high precision. Experimental data were used to test scour formulas including a new mathematical model. Results confirm the reliability and superior performance of the proposed dimensionless, effective flow work based model under steady and unsteady hydraulic conditions. Analyses highlight the impact of different hydrographs on scour, demonstrating the strong control by the hydrograph shape of the temporal evolution of scour depth and scour rate, although final scour after a flood only depends on the total effective flow work exerted by the hydrograph on the sediment bed. Hysteresis between flow discharge and scour rate is reported and explained. Flow acceleration is shown to play a minor role in scouring. The proposed model is a promising alternative for computation of local scour under highly unsteady hydraulic conditions.