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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Identification of Sensitive Parameters of Urban Flood Model Based on Artificial Neural Network
Zening Wu, Bingyan Ma, Huiliang Wang, et al.
Water Resources Management (2021) Vol. 35, Iss. 7, pp. 2115-2128
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Process-oriented SWMM real-time correction and urban flood dynamic simulation
Bingyan Ma, Zening Wu, Caihong Hu, et al.
Journal of Hydrology (2021) Vol. 605, pp. 127269-127269
Closed Access | Times Cited: 79
Artificial neural network approaches for disaster management: A literature review
Sreeparna Guha, Rabin K. Jana, Manas Kumar Sanyal
International Journal of Disaster Risk Reduction (2022) Vol. 81, pp. 103276-103276
Closed Access | Times Cited: 58
Tool for fast assessment of stormwater flood volumes for urban catchment: A machine learning approach
Bartosz Szeląg, Dariusz Majerek, Anna Laura Eusebi, et al.
Journal of Environmental Management (2024) Vol. 355, pp. 120214-120214
Closed Access | Times Cited: 14
Research on Urban Storm Flood Simulation by Coupling K-means Machine Learning Algorithm and GIS Spatial Analysis Technology into SWMM Model
Chengshuai Liu, Caihong Hu, Chenchen Zhao, et al.
Water Resources Management (2024) Vol. 38, Iss. 6, pp. 2059-2078
Closed Access | Times Cited: 10
Urban storm flood simulation using improved SWMM based on K‐means clustering of parameter samples
Yue Sun, Chengshuai Liu, Xian Du, et al.
Journal of Flood Risk Management (2022) Vol. 15, Iss. 4
Open Access | Times Cited: 38
Variance-based Global Sensitivity Analysis of Surface Runoff Parameters for Hydrological Modeling of a Real Peri-urban Ungauged Basin
Carlo Giudicianni, Irene Di Cicco, Armando Di Nardo, et al.
Water Resources Management (2024) Vol. 38, Iss. 8, pp. 3007-3022
Closed Access | Times Cited: 6
Using Machine Learning to Identify and Optimize Sensitive Parameters in Urban Flood Model Considering Subsurface Characteristics
Hengxu Jin, Zhao Yu, Pengcheng Lu, et al.
International Journal of Disaster Risk Science (2024) Vol. 15, Iss. 1, pp. 116-133
Open Access | Times Cited: 5
Study on Runoff Simulation with Multi-source Precipitation Information Fusion Based on Multi-model Ensemble
Runxi Li, Chengshuai Liu, Yehai Tang, et al.
Water Resources Management (2024)
Closed Access | Times Cited: 5
Optimal Domain Scale for Stochastic Urban Flood Damage Assessment Considering Triple Spatial Uncertainties
Hong Lv, Zening Wu, Yu Meng, et al.
Water Resources Research (2022) Vol. 58, Iss. 7
Closed Access | Times Cited: 18
A Novel Flood Classification Method Based on Machine Learning to Improve the Accuracy of Flood Simulation: A Case Study of Xunhe Watershed
Xi Cai, Xiaoxiang Zhang, Changjun Liu, et al.
Water (2025) Vol. 17, Iss. 4, pp. 489-489
Open Access
The Sensitivity Analysis of Parameters in the 1D–2D Coupled Model for Urban Flooding
Zhenchen Tang, Junying Chu, Zuhao Zhou, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2157-2157
Open Access
Capturing Urban Pluvial River Flooding Features Based on the Fusion of Physically Based and Data-Driven Approaches
Chenlei Ye, Zongxue Xu, Weihong Liao, et al.
Sustainability (2025) Vol. 17, Iss. 6, pp. 2524-2524
Open Access
An Uncertainty Analysis of Low-Impact Development Based on the Hydrological Process with Invariant Parameters and Equivalent Effects: Supporting Sustainable Urban Planning
Xinyi Shu, Chenlei Ye, Zongxue Xu
Sustainability (2025) Vol. 17, Iss. 6, pp. 2587-2587
Open Access
Stormwater Management Modeling in “Sponge City” Construction: Current State and Future Directions
Qianhui Liu, Wenhui Cui, Zhan Tian, et al.
Frontiers in Environmental Science (2022) Vol. 9
Open Access | Times Cited: 16
Parameter Optimization of SWMM Model Using Integrated Morris and GLUE Methods
Baoling Zhong, Zongmin Wang, Haibo Yang, et al.
Water (2022) Vol. 15, Iss. 1, pp. 149-149
Open Access | Times Cited: 15
Sensitivity Analysis: An Operational Picture
Aronne Dell’Oca
Water Resources Research (2023) Vol. 59, Iss. 6
Open Access | Times Cited: 9
Image Recognition of Mine Water Inrush Based on Bilinear Convolutional Neural Network with Few-Shot Learning
Shuai Zhang, Yuanze Du, Yingwang Zhao, et al.
ACS Omega (2024) Vol. 9, Iss. 10, pp. 12027-12036
Open Access | Times Cited: 3
Use of Artificial Intelligence Modelling for the Dynamic Simulation of Urban Catchment Runoff
Harshanth Balacumaresan, Monzur Alam Imteaz, Md. Abdul Aziz, et al.
Water Resources Management (2024) Vol. 38, Iss. 10, pp. 3657-3683
Open Access | Times Cited: 3
An intelligent framework for spatiotemporal simulation of flooding considering urban underlying surface characteristics
Hengxu Jin, Yiyin Liang, Haipeng Lu, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 130, pp. 103908-103908
Open Access | Times Cited: 3
Parameter sensitivity analysis of SWMM: a case study of airport airfield area
Jing Peng, Hucheng Zhao, Rui Li, et al.
Natural Hazards (2024) Vol. 120, Iss. 7, pp. 6551-6568
Closed Access | Times Cited: 2
A New Urban Waterlogging Simulation Method Based on Multi-Factor Correlation
Yue Yang, Cuilin Pan, Guangwei Fan, et al.
Water (2022) Vol. 14, Iss. 9, pp. 1421-1421
Open Access | Times Cited: 10
Simultaneous Optimization of SWMM Parameters by the Dynamic System Response Curve with Multi-Objective Function
Yao Du, Qiongfang Li, Pengfei He, et al.
Water Resources Management (2023) Vol. 37, Iss. 13, pp. 5061-5079
Closed Access | Times Cited: 4
Real-time Flood Classification Forecasting Based on k-means++ Clustering and Neural Network
Caihong Hu, Xueli Zhang, Changqing Li, et al.
Water Resources Management (2021) Vol. 36, Iss. 1, pp. 103-117
Open Access | Times Cited: 9
Design of a Control System Using an Artificial Neural Network to Optimize the Energy Efficiency of Water Distribution Systems
Laís Régis Salvino, Heber Pimentel Gomes, Saulo de Tarso Marques Bezerra
Water Resources Management (2022) Vol. 36, Iss. 8, pp. 2779-2793
Closed Access | Times Cited: 6
Prediction of flood events in the city of Bandar Lampung using the artificial neural network
Ramadhan Nurpambudi, Eka Suci Puspita Wulandari, RZ Abdul Aziz
JURNAL INFOTEL (2023) Vol. 15, Iss. 1, pp. 34-45
Open Access | Times Cited: 2
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