On Forecasting the Rur River: Using hindcasts and forecasts of the 2021 flood event to improve understanding of flood forecasting in the Rur catchment

The Netherlands, Germany, and Belgium were hit by heavy and prolonged precipitation in July 2021. As time passed, weather warnings escalated, leading to evacuations due to predicted floods, including in the Rur catchment. It was difficult to forecast the flooding of the Rur, raising the question of which elements are crucial in a flood...

Modelling Extreme Water Level and its Components for Infrastructure Design: The case of Hook of Holland

The projected increase in sea level is expected to increase the intensity of coastal flooding threatening communities living along the coast. This, in combination with population growth and urban expansion, calls for a better understanding of Extreme Water Levels (EWLs), the mechanisms generating them, and their components, i.e., astronomical...

Exploring Modelling Assumptions and their Impact on Extreme Discharges for the Meuse Catchment

Floods are the most frequent natural disaster and due to climate change the frequency and intensity of these events are increasing. Therefore, it is becoming increasingly important to obtain accurate estimations of extreme discharges. Statistical modelling is widely used to estimate extreme discharges by fitting observed extreme discharges to an...

The Effect of Sea Level Rise on the Operations of the MOSE Barrier in Venice: An Analysis Using the Rosner and an Adapted Framework for Adaptation

Coastal cities and communities are threatened by Sea Level Rise (SLR). Designing adaptations to protect against the rising sea requires a novel approach. With changing conditions, a broader approach considering multiple climate scenarios is required. A city facing an increasing threat from sea levels is Venice, one of the UNESCO world heritage...

A Bivariate Copula Approach to Extreme Water Level Estimation: For the city of Venice

Understanding the factors that drive extreme water levels is key to an accurate assessment of flood hazard. The city of Venice has always been affected by flooding due to extreme water levels. In this study, we examine the factors driving and influencing extreme water levels in the Venice lagoon, aiming at deriving accurate extreme water level...

Predicting fluvial flood arrival times by making use of a deep learning model

Fluvial flooding poses a major threat to mankind and annually leads to major economic losses with many casualties worldwide. The consequences of this can be mitigated when accurate and rapid predictions are available when the water will arrive at which location. Current numerical simulations take a significant amount of time due to their...

A systematic approach to characterize consecutive events in the Netherlands: From extremely dry to extremely wet

Floods and droughts, also known as hydro-hazards, are phenomena that generally involve detrimental consequences to society and environment. Traditional practices for risk assessment consider flood and drought independently. However, they are two opposite extremes of the same hydrological cycle. Omitting their interaction might lead to an under-...

Developing a method to include flood defenses explicitly in flood hazard maps based on limited available information

Flooding is one of the most damaging natural disasters worldwide, and presents a signi_cant risk for a large amount of the global population. For the development of ood disaster management strategies, policy makers make use of ood hazard maps to inform investment strategies to reduce risk. In many current ood hazard mapping methods, the role of...

Financial feasibility of large-scale adaptation strategies for future SLR in northern Europe: NEED vs dike reinforcement

The effects of climate change are felt all around the world. An increased sea level goes hand in hand with an increased risk of flooding. To combat this, the coastlines must be reinforced to withstand future sea levels. However, repeatedly reinforcing coastlines to keep up with the sea level rise (SLR) could prove extremely costly. An...

Inferring rare events: The role of the length of observations

Extreme value analyses (EVA) are often used to determine the frequency of extreme events. The length of the available observations is an important aspect when performing EVA. It is generally known that more available data results in better estimates with less uncertainties. The main objective of this research report was to assess what the...

A Non-Parametric Bayesian Network Hydrologic Model: A Case Study of a Lowland Catchment

The past decades, the increasing availability of data has paved the way for a new, data-driven generation of models. This research proposes a non-parametric Bayesian network (NPBN) to model hydrologic processes. The Bayesian network (BN) is a directed, acyclic graph in which the variables are represented by the nodes, and the conditional...

Forecasting river discharge using machine learning methods: with application to the Geul and Rur river

The objective of this study is find out whether maximum daily discharge of the Geul and Rur catchments can be forecast using machine learning (ML) methods, and if so, to what extent. In addition, these ML models are compared to a conceptual model to see which performs better. A second objective is to test whether soil moisture content (SMC) and...