A review of sustainable urban drainage systems considering the climate change and urbanization impacts Q Zhou Water 6 (4), 976-992, 2014 | 598 | 2014 |
Framework for economic pluvial flood risk assessment considering climate change effects and adaptation benefits Q Zhou, PS Mikkelsen, K Halsnæs, K Arnbjerg-Nielsen Journal of Hydrology 414, 539-549, 2012 | 441 | 2012 |
Comparison of urbanization and climate change impacts on urban flood volumes: Importance of urban planning and drainage adaptation Q Zhou, G Leng, J Su, Y Ren Science of the Total Environment 658, 24-33, 2019 | 403 | 2019 |
Comparing methods of calculating expected annual damage in urban pluvial flood risk assessments AS Olsen, Q Zhou, JJ Linde, K Arnbjerg-Nielsen Water 7 (1), 255-270, 2015 | 163 | 2015 |
Adaption to extreme rainfall with open urban drainage system: An integrated hydrological cost-benefit analysis Q Zhou, TE Panduro, BJ Thorsen, K Arnbjerg-Nielsen Environmental management 51, 586-601, 2013 | 137 | 2013 |
Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations Q Zhou, G Leng, M Huang Hydrology and Earth System Sciences 22 (1), 305-316, 2018 | 110 | 2018 |
Predictability of state-level flood damage in the conterminous United States: The role of hazard, exposure and vulnerability Q Zhou, G Leng, L Feng Scientific reports 7 (1), 5354, 2017 | 56 | 2017 |
Automatic sewer defect detection and severity quantification based on pixel-level semantic segmentation Q Zhou, Z Situ, S Teng, H Liu, W Chen, G Chen Tunnelling and Underground Space Technology 123, 104403, 2022 | 46 | 2022 |
Verification of flood damage modelling using insurance data Q Zhou, TE Panduro, BJ Thorsen, K Arnbjerg-Nielsen Water science and technology 68 (2), 425-432, 2013 | 45 | 2013 |
A GIS-based hydrological modeling approach for rapid urban flood hazard assessment Q Zhou, J Su, K Arnbjerg-Nielsen, Y Ren, J Luo, Z Ye, J Feng Water 13 (11), 1483, 2021 | 30 | 2021 |
Convolutional neural networks–based model for automated sewer defects detection and classification Q Zhou, Z Situ, S Teng, G Chen Journal of Water Resources Planning and Management 147 (7), 04021036, 2021 | 29 | 2021 |
Automated sewer defects detection using style-based generative adversarial networks and fine-tuned well-known CNN classifier Z Situ, S Teng, H Liu, J Luo, Q Zhou IEEE Access 9, 59498-59507, 2021 | 28 | 2021 |
Adaptation to urbanization impacts on drainage in the city of Hohhot, China Q Zhou, Y Ren, M Xu, N Han, H Wang Water Science and Technology 73 (1), 167-175, 2016 | 27 | 2016 |
Real-time sewer defect detection based on YOLO network, transfer learning, and channel pruning algorithm Z Situ, S Teng, X Liao, G Chen, Q Zhou Journal of Civil Structural Health Monitoring 14 (1), 41-57, 2024 | 24 | 2024 |
Comparison of multiobjective optimization methods applied to urban drainage adaptation problems Q Wang, Q Zhou, X Lei, DA Savić Journal of Water Resources Planning and Management 144 (11), 04018070, 2018 | 24 | 2018 |
A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions Q Zhou, S Teng, Z Situ, X Liao, J Feng, G Chen, J Zhang, Z Lu Hydrology and Earth System Sciences 27 (9), 1791-1808, 2023 | 23 | 2023 |
Recent changes in the occurrences and damages of floods and droughts in the United States Q Zhou, G Leng, J Peng Water 10 (9), 1109, 2018 | 23 | 2018 |
Economic assessment of climate adaptation options for urban drainage design in Odense, Denmark Q Zhou, K Halsnæs, K Arnbjerg-Nielsen Water Science and Technology 66 (8), 1812-1820, 2012 | 23 | 2012 |
Optimising the combination strategies for pipe and infiltration‐based low impact development measures using a multiobjective evolution approach Q Zhou, Z Lai, A Blohm Journal of Flood Risk Management 12 (2), e12457, 2019 | 22 | 2019 |
A transfer learning-based YOLO network for sewer defect detection in comparison to classic object detection methods Z Situ, S Teng, W Feng, Q Zhong, G Chen, J Su, Q Zhou Developments in the Built Environment 15, 100191, 2023 | 21 | 2023 |