107 citations as recorded by crossref.

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11. The Critical Importance of Citizen Science Data A. de Sherbinin et al. 10.3389/fclim.2021.650760
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24. Citizens’ Campaigns for Environmental Water Monitoring: Lessons From Field Experiments T. Assumpcao et al. 10.1109/ACCESS.2019.2939471
25. Citizen Science and the Sustainable Development Goals: Building Social and Technical Capacity through Data Collection in the Upper Blue Nile Basin, Ethiopia G. Rigler et al. 10.3390/su14063647
26. Pluvial flood risk and opportunities for resilience B. Rosenzweig et al. 10.1002/wat2.1302
27. A Mixed-Methods Investigation into Barriers for Sharing Geospatial and Resilience Flood Data in the UK L. Waterman et al. 10.3390/w13091235
28. Evaluation of factors affecting the quality of citizen science rainfall data in Akaki catchment, Addis Ababa, Ethiopia H. Tedla et al. 10.1016/j.jhydrol.2022.128284
29. A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya D. Shugar et al. 10.1126/science.abh4455
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31. Filling data gaps using citizen science for flood modeling in urbanized catchment of Akaki A. Alemu et al. 10.1016/j.nhres.2023.05.002
32. Assessment of the Susceptibility of Urban Flooding Using GIS with an Analytical Hierarchy Process in Hanoi, Vietnam H. Nguyen et al. 10.3390/su16103934
33. Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model M. Mazzoleni et al. 10.1029/2018WR023768
34. Can the Quality of the Potential Flood Risk Maps be Evaluated? A Case Study of the Social Risks of Floods in Central Spain J. Garrote et al. 10.3390/w11061284
35. Citizen Scientists Contribute to Real-Time Monitoring of Lake Water Quality Using 3D Printed Mini Secchi Disks G. George et al. 10.3389/frwa.2021.662142
36. Leveraging catchment scale automated novel data collection infrastructure to advance urban hydrologic-hydraulic modeling A. Shrestha et al. 10.1016/j.envsoft.2024.106046
37. Estimating the likelihood of roadway pluvial flood based on crowdsourced traffic data and depression-based DEM analysis A. Safaei-Moghadam et al. 10.5194/nhess-23-1-2023
38. Rapid Mapping for Simple Flood Mitigation Using Commercial Drone at Way Galih Village, Lampung, Indonesia A. Rohman & D. Prasetya 10.23917/forgeo.v33i1.8421
39. Investigating Pedestrian Behavioral Patterns Under Different Floodwater Conditions: A Video Analysis on Real Flood Evacuations E. Quagliarini et al. 10.2139/ssrn.4167684
40. Predictive multi-watershed flood monitoring using deep learning on integrated physical and social sensors data S. Dong et al. 10.1177/23998083211069140
41. Utilization of social media in floods assessment using data mining techniques Q. Khan et al. 10.1371/journal.pone.0267079
42. Opportunities for crowdsourcing in urban flood monitoring A. Helmrich et al. 10.1016/j.envsoft.2021.105124
43. Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information Y. Lin et al. 10.3390/rs12040706
44. Value of quality controlled citizen science data for rainfall-runoff characterization in a rapidly urbanizing catchment G. Kebede Mengistie et al. 10.1016/j.jhydrol.2024.130639
45. Generative deep learning for data generation in natural hazard analysis: motivations, advances, challenges, and opportunities Z. Ma et al. 10.1007/s10462-024-10764-9
46. An automatic quality evaluation procedure for third-party daily rainfall observations and its application over Australia M. Li et al. 10.1007/s00477-023-02401-8
47. Exploring the Emotional Factors in College English Classroom Teaching Based on Computer-Aided Model F. Fu & Q. Li 10.1155/2022/4383254
48. CNS: Application of Distributed Indexing Based on Large-Scale Graph Data in Legal Protection of Network Personal Information P. Han 10.1142/S0218843021500039
49. Urban hydrological model (UHM) developed for an urban flash flood simulation and analysis of the flood intensity sensitivity to urbanization H. Hu et al. 10.1080/19475705.2024.2302561
50. An integrated socio-environmental framework for mapping hazard-specific vulnerability and exposure in urban areas P. Alves et al. 10.1080/1573062X.2021.1913505
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52. Flood Risk in Urban Areas: Modelling, Management and Adaptation to Climate Change. A Review L. Cea & P. Costabile 10.3390/hydrology9030050
53. Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: A case study of Hurricane Harvey Y. Feng et al. 10.1016/j.isprsjprs.2020.09.011
54. Stochastic Modeling for Estimating Real-Time Inundation Depths at Roadside IoT Sensors Using the ANN-Derived Model S. Wu et al. 10.3390/w13213128
55. Anomalous human activity fluctuations from digital trace data signal flood inundation status H. Farahmand et al. 10.1177/23998083211069990
56. Participatory Mapping and Visualization of Local Knowledge: An Example from Eberbach, Germany C. Klonner et al. 10.1007/s13753-020-00312-8
57. Reconstituting past flood events: the contribution of citizen science B. Sy et al. 10.5194/hess-24-61-2020
58. Citizens AND HYdrology (CANDHY): conceptualizing a transdisciplinary framework for citizen science addressing hydrological challenges F. Nardi et al. 10.1080/02626667.2020.1849707
59. Opportunities and risks of disaster data from social media: a systematic review of incident information M. Wiegmann et al. 10.5194/nhess-21-1431-2021
60. GFPLAIN and Multi-Source Data Assimilation Modeling: Conceptualization of a Flood Forecasting Framework Supported by Hydrogeomorphic Floodplain Rapid Mapping A. Annis & F. Nardi 10.3390/hydrology8040143
61. A Review of Citizen Science and Crowdsourcing in Applications of Pluvial Flooding L. See 10.3389/feart.2019.00044
62. A Probabilistic, Parcel‐Level Inundation Prediction Tool for Medium‐Range Flood Forecasting in Large Lake Systems K. Semmendinger et al. 10.1111/1752-1688.12893
63. Hydrologic–hydraulic assessment of SUDS control capacity using different modeling approaches: a case study in Bogotá, Colombia A. Ortega Sandoval et al. 10.2166/wst.2023.173
64. Blue and grey urban water footprints through citizens’ perception and time series analysis of Brazilian dynamics F. Souza et al. 10.1080/02626667.2021.1879388
65. Utilising social media data to evaluate urban flood impact in data scarce cities K. Guo et al. 10.1016/j.ijdrr.2023.103780
66. Success factors for citizen science projects in water quality monitoring A. San Llorente Capdevila et al. 10.1016/j.scitotenv.2020.137843
67. Citizen science flow – an assessment of simple streamflow measurement methods J. Davids et al. 10.5194/hess-23-1045-2019
68. Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions F. Zheng et al. 10.1029/2018RG000616
69. The Techno-politics of Crowdsourced Disaster Data in the Smart City E. Wolff & F. Muñoz 10.3389/frsc.2021.695329
70. Floodplain reconstitution based on data collected via smartphones: a methodological approach to hydrological risk mapping A. Ribeiro et al. 10.1590/2318-0331.252020190179
71. Flood resilience through crowdsourced rainfall data collection: Growing engagement faces non-uniform spatial adoption A. Chen et al. 10.1016/j.jhydrol.2022.127724
72. Evaluating terrain-based HAND-SRC flood mapping model in low-relief rural plains using high resolution topography and crowdsourced data H. Sabeh et al. 10.1016/j.jhydrol.2024.132649
73. Analysing the value of environmental citizen-generated data: Complementarity and cost per observation L. Alfonso et al. 10.1016/j.jenvman.2021.114157
74. Testing the theoretical principles of citizen science in monitoring stream water levels through photo-trap frames A. Spasiano et al. 10.3389/frwa.2023.1050378
75. Participatory Framework for Urban Pluvial Flood Modeling in the Digital Twin Era S. Park et al. 10.1016/j.scs.2024.105496
76. Improving Hydrological Models With the Assimilation of Crowdsourced Data P. Avellaneda et al. 10.1029/2019WR026325
77. From Extreme Weather Events to ‘Cascading Vulnerabilities’: Participatory Flood Research Methodologies in Brazil During COVID-19 N. Calvillo et al. 10.1142/S2345737622410020
78. Terrestrial and airborne laser scanning and 2-D modelling for 3-D flood hazard maps in urban areas: new opportunities and perspectives P. Costabile et al. 10.1016/j.envsoft.2020.104889
79. Identification of flood depth levels in urban waterlogging disaster caused by rainstorm using a CBAM-improved ResNet50 L. Wu et al. 10.1016/j.eswa.2024.124382
80. The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models M. Drews et al. 10.1016/j.scitotenv.2023.164962
81. Threshold-based flood early warning in an urbanizing catchment through multi-source data integration: Satellite and citizen science contribution H. Tedla et al. 10.1016/j.jhydrol.2024.131076
82. The citizen-led information practices of ICT4D in rural communities of China: A mixed-method study L. Ye et al. 10.1016/j.ijinfomgt.2020.102248
83. A simple framework for calibrating hydraulic flood inundation models using Crowd-sourced water levels A. Dasgupta et al. 10.1016/j.jhydrol.2022.128467
84. Experimental and Numerical Study of the Effect of Model Geometric Distortion on Laboratory Modeling of Urban Flooding X. Li et al. 10.1029/2021WR029666
85. Multiscale Observation Product (MOP) for Temporal Flood Inundation Mapping of the 2015 Dallas Texas Flood E. Sava et al. 10.3390/rs15061615
86. Collaborating With Communities: Citizen Science Flood Monitoring in Urban Informal Settlements E. Wolff et al. 10.17645/up.v6i4.4648
87. Using social cartographies for the calibration of two-dimensional hydraulic flood models B. Alarcón et al. 10.1007/s11069-024-06838-0
88. Flood data platform governance: Identifying the technological and socio-technical approach(es) differences M. Fadmastuti et al. 10.1016/j.envsci.2024.103938
89. The benefits and negative impacts of citizen science applications to water as experienced by participants and communities D. Walker et al. 10.1002/wat2.1488
90. Modelling support to citizen observatories for strategic Danube Delta planning: Sontea-Fortuna case study A. Venturini et al. 10.1080/09640568.2018.1523787
91. A Nationwide Flood Forecasting System for Saudi Arabia: Insights from the Jeddah 2022 Event G. Sofia et al. 10.3390/w16141939
92. High‐resolution urban flood model for risk mitigation validated with records collected by the affected community M. Re et al. 10.1111/jfr3.12524
93. Analysis of Dynamic Influence Mechanism of Network Public Opinion Based on Simulation Feature Extraction Y. Zhang & Z. Cai 10.1155/2022/8423643
94. Floodability: A New Paradigm for Designing Urban Drainage and Achieving Sustainable Urban Growth G. La Loggia et al. 10.1007/s11269-020-02620-6
95. Integrating VGI and 2D hydraulic models into a data assimilation framework for real time flood forecasting and mapping A. Annis & F. Nardi 10.1080/10095020.2019.1626135
96. Invited perspectives: How machine learning will change flood risk and impact assessment D. Wagenaar et al. 10.5194/nhess-20-1149-2020
97. The potential of proxy water level measurements for calibrating urban pluvial flood models M. Moy de Vitry & J. Leitão 10.1016/j.watres.2020.115669
98. The Role of Realistic Channel Geometry Representation in Hydrological Model Predictions J. Brackins et al. 10.1111/1752-1688.12865
99. Free Global DEMs and Flood Modelling—A Comparison Analysis for the January 2015 Flooding Event in Mocuba City (Mozambique) J. Garrote 10.3390/w14020176
100. Propagation of radar rainfall uncertainties into urban pluvial flood modeling during the North American monsoon A. Hjelmstad et al. 10.1080/02626667.2021.1980216
101. Crowdsourcing and interactive modelling for urban flood management E. Gebremedhin et al. 10.1111/jfr3.12602
102. Exploring an Innovative Moral Education Cultivation Model in Higher Education through Neural Network Perspective: A Preliminary Study X. Shi 10.1080/08839514.2023.2214767
103. The promise of a “people-centred” approach to floods: Types of participation in the global literature of citizen science and community-based flood risk reduction in the context of the Sendai Framework E. Wolff 10.1016/j.pdisas.2021.100171
104. Temporary flood marks proposal: What we learned after losing the baroque artifact from Cracow, Poland R. Szczepanek et al. 10.1016/j.ijdrr.2022.102942
105. Assessment of crowdsourced social media data and numerical modelling as complementary tools for urban flood mitigation M. Re et al. 10.1080/02626667.2022.2075266
106. Exploring the influence of citizen involvement on the assimilation of crowdsourced observations: a modelling study based on the 2013 flood event in the Bacchiglione catchment (Italy) M. Mazzoleni et al. 10.5194/hess-22-391-2018
107. Risk-Based Early Warning System for Pluvial Flash Floods: Approaches and Foundations J. Hofmann & H. Schüttrumpf 10.3390/geosciences9030127