Jens de Bruijn
Jens de Bruijn
Assistant Professor @ IVM & Research Scholar @ IIASA
Verified email at - Homepage
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A global database of historic and real-time flood events based on social media
JA de Bruijn, H de Moel, B Jongman, MC de Ruiter, J Wagemaker, ...
Scientific data 6 (1), 311, 2019
TAGGS: Grouping tweets to improve global geoparsing for disaster response
JA De Bruijn, H de Moel, B Jongman, J Wagemaker, JCJH Aerts
Journal of Geovisualization and Spatial Analysis 2, 1-14, 2018
The shadow price of irrigation water in major groundwater‐depleting countries
MFP Bierkens, S Reinhard, JA de Bruijn, W Veninga, Y Wada
Water Resources Research 55 (5), 4266-4287, 2019
Hydrological concept formation inside long short-term memory (LSTM) networks
T Lees, S Reece, F Kratzert, D Klotz, M Gauch, J De Bruijn, R Kumar Sahu, ...
Hydrology and Earth System Sciences Discussions 2021, 1-37, 2021
Improving the classification of flood tweets with contextual hydrological information in a multimodal neural network
JA de Bruijn, H de Moel, AH Weerts, MC de Ruiter, E Basar, D Eilander, ...
Computers & Geosciences 140, 104485, 2020
The asynergies of structural disaster risk reduction measures: Comparing floods and earthquakes
MC de Ruiter, JA de Bruijn, J Englhardt, JE Daniell, H de Moel, PJ Ward
Earth's Future 9 (1), e2020EF001531, 2021
Coupling a large-scale hydrological model (CWatM v1. 1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
L Guillaumot, M Smilovic, P Burek, J De Bruijn, P Greve, T Kahil, Y Wada
Geoscientific Model Development 15 (18), 2022
The multimedia satellite task at mediaeval 2018: Emergency response for flooding events
B Benjamin, H Patrick, Z Zhengyu, B Damian
Using rapid damage observations for Bayesian updating of hurricane vulnerability functions: A case study of Hurricane Dorian using social media
JA de Bruijn, JE Daniell, A Pomonis, R Gunasekera, J Macabuag, ...
International Journal of Disaster Risk Reduction 72, 102839, 2022
A coupled agent-based model to analyse human-drought feedbacks for agropastoralists in dryland regions
IN Streefkerk, J de Bruijn, T Haer, AF Van Loon, EA Quichimbo, M Wens, ...
Frontiers in Water 4, 1037971, 2023
GEB v0.1: a large-scale agent-based socio-hydrological model–simulating 10 million individual farming households in a fully distributed hydrological model
JA de Bruijn, M Smilovic, P Burek, L Guillaumot, Y Wada, JCJH Aerts
Geoscientific Model Development 16 (9), 2437-2454, 2023
Deep dive into global hydrologic simulations: Harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1. 0-hydroDL)
D Feng, H Beck, J de Bruijn, RK Sahu, Y Satoh, Y Wada, J Liu, M Pan, ...
Geoscientific Model Development Discussions 2023, 1-23, 2023
A coupled agent-based model for France for simulating adaptation and migration decisions under future coastal flood risk
L Tierolf, T Haer, WJW Botzen, JA de Bruijn, MJ Ton, L Reimann, ...
Scientific Reports 13 (1), 4176, 2023
A global earthquake risk model for the education sector: identifying the institutions, teachers and students at risk
JE Daniell, AM Schaefer, A Pomonis, R Gunasekera, O Ishizawa, ...
17th World Conference on Earthquake Engineering (17WCEE). Sendai, Japan …, 2020
The asynergies of disaster risk reduction measures in Afghanistan
M de Ruiter, J de Bruijn, J Daniell, J Englhardt, P Ward, H de Moel
EGU General Assembly Conference Abstracts, 79, 2020
Natural Hazards in a Digital World: Algorithms for Using Social Media in Disaster Management
JA de Bruijn
Community Water Model CWatM Manual
P Burek, M Smilovic, L Guillaumot, J de Bruijn, P Greve, Y Satoh, A Islaam, ...
IIASA, 2020
Water circles—a tool to assess and communicate the water cycle
M Smilovic, P Burek, D Fridman, L Guillaumot, J de Bruijn, P Greve, ...
Environmental Research Letters 19 (2), 021003, 2024
Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique
K Pandey, JA de Bruijn, H de Moel, W Botzen, JCJH Aerts
EGUsphere 2024, 1-29, 2024
Harnessing the Power of Deep Learning and Physics-informed Differentiable Models for Accurate Global Hydrologic Modeling
D Feng, C Shen, H Beck, J De Bruijn, R Sahu, Y Satoh, Y Wada, J Liu, ...
AGU23, 2023
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