Subsea cables underpin global communications, carrying more than 99 % of all digital data traffic worldwide. While this >1.6 million km-long network has been designed to be highly resilient, subsea cables can be damaged by a number of natural hazards that occur across all water depths in the ocean. Here, we explore the diversity of natural hazards that can damage cables, considering a broad frequency-magnitude spectrum. This paper is the first global perspective of actual and potential hazards affecting cables. As such, it is an accessible overview of the regional variability and complexity of hazards. Relatively rare and extreme events, such as super typhoons, submarine landslides or associated turbidity currents and volcanic eruptions, can synchronously cause widespread damage to multiple systems, in some cases disconnecting entire countries or dramatically slowing data traffic. We show that damage is rarely linked to an initial event, instead arising from cascades of processes that can lag by years. Not all instances of cable damage that relate to natural processes are linked to extreme events. We show that much smaller intensity meteorological and oceanographic processes such as storms and continuous seafloor currents that have been overlooked by previous studies can also damage subsea cables. New analysis of past instances of cable damage reveals that a significant proportion of previously unattributed faults may relate to such low-level but sustained impacts. It is these hazards that are most likely to change in frequency and magnitude in response to ongoing climate change but are also more predictable. Through mapping of exposure to these different hazards, we identify geographically-constrained hazard hotspots and identify various mitigation measures to enhance the evidence base and further strengthen subsea telecommunications network resilience.

Uncertainty plays a key role in hydrological modeling and forecasting, which can have tremendous environmental, economic, and social impacts. Therefore, it is crucial to comprehend the nature of this uncertainty and identify its scope and effects in a way that enhances hydrological modeling and forecasting. During recent decades, hydrological researchers investigated several approaches for reducing inherent uncertainty considering the limitations of sensor measurement, calibration, parameter setting, model conceptualization, and validation. Nevertheless, the scope and diversity of applications and methodologies, sometimes brought from other disciplines, call for an extensive review of the state-of-the-art in this field in a way that promotes a holistic view of the proposed concepts and provides textbook-like guidelines to hydrology researchers and the community. This paper contributes to this goal where a systematic review of the last decade's research (2010 onward) is carried out. It aims to synthesize the theories and tools for uncertainty reduction in surface hydrological forecasting, providing insights into the limitations of the current state-of-the-art and laying down foundations for future research. A special focus on remote sensing and multi-criteria-based approaches has been considered. In addition, the paper reviews the current state of uncertainty ontology in hydrological studies and provides new categorizations of the reviewed techniques. Finally, a set of freely accessible remotely sensed data and tools useful for uncertainty handling and hydrological forecasting are reviewed and pointed out.