51 citations as recorded by crossref.

1. Flood Modeling Using HEC-RAS Based on Extreme Rainfall Data G. San-Deo
2. Improving flood forecast accuracy based on explainable convolutional neural network by Grad-CAM method X. Xiang et al.
3. Feature Importance in Machine Learning with Explainable Artificial Intelligence (XAI) for Rainfall Prediction M. Patel et al.
4. Classification and mechanism of spring and summer floods in northern Xinjiang from 2006 to 2011 P. Chen et al.
5. Applying Machine Learning Methods to Improve Rainfall–Runoff Modeling in Subtropical River Basins H. Yu & Q. Yang
6. Model-based assessment of flood generation mechanisms over Poland: The roles of precipitation, snowmelt, and soil moisture excess N. Venegas-Cordero et al.
7. Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach M. Fan et al.
8. Shifting cold regions streamflow regimes in North America affect flood frequency analysis D. Burn & P. Whitfield
9. Extreme and compound ocean events are key drivers of projected low pelagic fish biomass N. Le Grix et al.
10. Research on river velocity and flow estimation based on scalar transport equation J. Wang et al.
11. Using explainable artificial intelligence (XAI) methods to understand the nonlinear relationship between the Three Gorges Dam and downstream flood X. Wei et al.
12. Diverging trends in large floods across Europe in a warming climate B. Fang et al.
13. Interpretable feature incorporation machine-learning framework for flood magnitude estimation E. Ford et al.
14. Evolution of flood generating processes under climate change in France Y. Tramblay et al.
15. Changes in Mediterranean flood processes and seasonality Y. Tramblay et al.
16. Winter flood significantly changes salinity and nutrient export from land to sea I. Bussmann et al.
17. Innovative daily runoff prediction model integrating black-winged kite algorithm and Mamba2–Transformer architecture D. Xu et al.
18. Drivers of high-frequency extreme sea levels around northern Europe – synergies between recurrent neural networks and random forest C. Heuzé et al.
19. Winter climate preconditioning of summer vegetation extremes in the Northern Hemisphere M. Anand et al.
20. Transformed-stationary EVA 2.0: a generalized framework for non-stationary multivariate extremes analysis M. Bahmanpour et al.
21. Associated influence of moisture sources and catchment drivers on the flood mechanism of a tropical basin R. Choudhary & C. Dhanya
22. Unveiling summer marine heatwave onset mechanisms in the South China sea using an explainable deep learning method M. Guo et al.
23. Enhancing flood prediction in the Lower Mekong River Basin by a scale-independent interpretable deep learning model Y. Qiu et al.
24. River-lake connectivity modulates lake droughts: Comparative insights from China’s two largest river-connected lakes C. Xue et al.
25. Clustering of causal graphs to explore drivers of river discharge W. Günther et al.
26. Significant roles of snow and vegetation cover in modulating altitudinal gradients of land surface temperature over Asia high mountains H. Zhang et al.
27. Flash Flood Assessment using Geospatial data: A Case Study of Semel City, Kurdistan Region-Iraq. S. Abdi et al.
28. Identification of time-varying parameters of a monthly Budyko function in US MOPEX catchments and its implications W. Liu et al.
29. Revealing long-term runoff mechanisms using the deep learning model interpretable framework driven by global and local information B. Yang et al.
30. Event duration matters: spatial–temporal patterns of United States daily and multi-day precipitation extremes S. Eero et al.
31. Basin-informed flood frequency analysis using deep learning exhibits consistent projected regional patterns over CONUS R. Lazin et al.
32. Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method M. Fan et al.
33. Explainable deep learning identifies patterns and drivers of freshwater harmful algal blooms S. Chen et al.
34. A method of applying deep learning based optical flow algorithm to river flow discharge measurement J. Wang et al.
35. Challenges and opportunities of ML and explainable AI in large-sample hydrology L. Slater et al.
36. Compounding effects in flood drivers challenge estimates of extreme river floods S. Jiang et al.
37. Exploring the influence of hydrological indicators on flow regimes through a data-driven modeling approach in the Huai river basin, China Q. Wei et al.
38. Spatially resolved rainfall streamflow modeling in central Europe M. Vischer et al.
39. Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning W. Liang et al.
40. Toward real-time high-resolution fluvial flood forecasting: A robust surrogate approach based on overland flow models G. Nguyen et al.
41. Direct and lagged climate change effects intensified the 2022 European drought E. Bevacqua et al.
42. Forecasting of compound ocean-fluvial floods using machine learning S. Moradian et al.
43. Fine-tuning long short-term memory models for seamless transition in hydrological modelling: From pre-training to post-application X. Chen et al.
44. Rhine flood stories: Spatio‐temporal analysis of historic and projected flood genesis in the Rhine River basin E. Rottler et al.
45. Research progresses and prospects of multi-sphere compound extremes from the Earth System perspective Z. Hao & Y. Chen
46. An increase in the spatial extent of European floods over the last 70 years B. Fang et al.
47. Space-time image velocity measurement method based on improved GhostNetV2 Y. Feng et al.
48. Enhancing flood forecasting performance using effective and transparent explainable hybrid deep learning model M. Hasan et al.
49. Explainable Earth Surface Forecasting Under Extreme Events O. Pellicer‐Valero et al.
50. Runoff concentration decline for Tarim river due to a dramatic increasing of runoff in cold season and hydro-junction regulation: Past and future S. Qianjuan et al.
51. Rain-on-wet-soil compound floods in lowlands: the combined effect of large rain events and shallow groundwater on discharge peaks in a changing climate C. Brauer et al.