Jens de Bruijn

Vrije Universiteit Amsterdam | VU · The Institute for Environmental Studies (IVM)

Accurate hydrological modeling is vital to characterizing how the terrestrial water cycle responds to climate change. Pure deep learning (DL) models have shown to outperform process-based ones while remaining difficult to interpret. More recently, differentiable, physics-informed machine learning models with a physical backbone can systematically i...

Here, we present the Geographical, Environmental and Behavioural model (GEB), a coupled agent-based hydrological model that simulates the behaviour and daily bi-directional interaction of more than 10 million individual farm households with the hydrological system on a personal laptop. Farmers exhibit autonomous heterogeneous behaviour based on the...

In this study, we couple an integrated flood damage and agent-based model (ABM) with a gravity model of internal migration and a flood risk module (DYNAMO-M) to project household adaptation and migration decisions under increasing coastal flood risk in France. We ground the agent decision rules in a framework of subjective expected utility theory....

Drought is a persistent hazard that impacts the environment, people's livelihoods, access to education and food security. Adaptation choices made by people can influence the propagation of this drought hazard. However, few drought models incorporate adaptive behavior and feedbacks between adaptations and drought. In this research, we present a dyna...

In the context of changing climate and increasing water demand, large-scale hydrological models are helpful for understanding and projecting future water resources across scales. Groundwater is a critical freshwater resource and strongly controls river flow throughout the year. It is also essential for ecosystems and contributes to evapotranspirati...

Humans play a large role in the hydrological system; for example, by extracting large amounts of water for irrigation, often resulting in water stress and ecosystem degradation. By implementing large-scale adaptation measures, such as the construction of irrigation reservoirs, water stress and ecosystem degradation can be reduced. Yet we know that...

In the context of changing climate and increasing water demand, large-scale hydrological models are helpful for understanding and projecting future water resources across scales. Groundwater is a critical freshwater resource and strongly controls river flow throughout the year. It is also essential for ecosystems and contributes to evapotranspirati...

Neural networks have been shown to be extremely effective rainfall-runoff models, where the river discharge is predicted from meteorological inputs. However, the question remains: what have these models learned? Is it possible to extract information about the learned relationships that map inputs to outputs, and do these mappings represent known hy...

Rapid impact assessments immediately after disasters are crucial to enable rapid and effective mobilization of resources for response and recovery efforts. These assessments are often performed by analysing the three components of risk: hazard, exposure and vulnerability. Vulnerability curves are often constructed using historic insurance data or e...

Neural networks have been shown to be extremely effective rainfall-runoff models, where the river discharge is predicted from meteorological inputs. However, the question remains, what have these models learned? Is it possible to extract information about the learned relationships that map inputs to outputs? And do these mappings represent known hy...

Traditionally, building-level disaster risk reduction (DRR) measures are aimed at a single natural hazard. However, in many countries the society faces the threat of multiple hazards. Building-level DRR measures that aim to decrease earthquake vulnerability can have opposing or conflicting effects on flood vulnerability, and vice versa. In a case s...

Rapid impact assessments immediately after disasters are crucial to enable rapid and effective mobilization of resources for response and recovery efforts. These assessments are often performed by analysing the three components of risk: hazard, exposure and vulnerability. Vulnerability curves are often constructed using historic insurance data or e...

While text classification can classify tweets, assessing whether a tweet is related to an ongoing flood event or not, based on its text, remains difficult. Inclusion of contextual hydrological information could improve the performance of such algorithms. Here, a multilingual multimodal neural network is designed that can effectively use both textua...

Early event detection and response can significantly reduce the societal impact of floods. Currently, early warning systems rely on gauges, radar data, models and informal local sources. However, the scope and reliability of these systems are limited. Recently, the use of social media for detecting disasters has shown promising results, especially...

In many semiarid regions with irrigation, the depletion rate of groundwater resources has increased substantially during the last decades. A possible reason for this is that the price that users pay for their water does not reflect its scarcity and value. An alternative way to assess the perceived value of water is calculating its shadow price, whi...

This paper provides a description of the MediaEval 2018 Multimedia Satellite Task. The primary goal of the task is to extract and fuse content associated with events represent in Satellite Imagery and Social Media. Establishing a link from Satellite Imagery to Social Multi-media can yield to a comprehensive event representation which is vital for n...

Timely and accurate information about ongoing events are crucial for relief organizations seeking to effectively respond to disasters. Recently, social media platforms, especially Twitter, have gained traction as a novel source of information on disaster events. Unfortunately, geographical information is rarely attached to tweets, which hinders the...

The availability of timely and accurate information about ongoing events is important for relief organizations seeking to effectively respond to disasters. Recently, social media platforms, and in particular Twitter, have gained traction as a novel source of information on disaster events. Unfortunately, geographical information is rarely attached...