35 citations as recorded by crossref.

1. Impacts of agriculture and snow dynamics on catchment water balance in the U.S. and Great Britain M. Zaerpour et al. https://doi.org/10.1038/s43247-024-01891-w
2. Climate shapes baseflows, influencing drought severity M. Zaerpour et al. https://doi.org/10.1088/1748-9326/ad975a
3. OCORRÊNCIA HISTÓRICA DE COTAS DE ALERTA E INUNDAÇÃO EM GOVERNADOR VALADARES (MG) E ASSOCIAÇÃO COM SÉRIES FLUVIOMÉTRICAS A MONTANTE C. Ruezzene et al. https://doi.org/10.66104/8y63v150
4. Agriculture’s impact on water–energy balance varies across climates M. Zaerpour et al. https://doi.org/10.1073/pnas.2410521122
5. Scour depth prediction using machine learning and explainable AI: assessment of bridge vulnerability P. Kanishkavardhan et al. https://doi.org/10.3389/fbuil.2026.1790274
6. Long-term spatiotemporal assessment of wetland degradation and ecological resilience in Indian Ramsar sites spanning various agroecological zones M. Rawat et al. https://doi.org/10.1016/j.rsase.2026.101979
7. Inferring causal associations in hydrological systems: a comparison of methods H. Liang et al. https://doi.org/10.1007/s00477-025-02977-3
8. Trends and causal structures of rain-on-snow flooding N. Kumar et al. https://doi.org/10.1016/j.jhydrol.2025.133938
9. When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system H. Zhang et al. https://doi.org/10.1109/MGRS.2024.3496478
10. DAR-type model based on “long memory-threshold” structure: a competitor for daily streamflow prediction under changing environment H. Wang et al. https://doi.org/10.5194/hess-30-1543-2026
11. The Impacts of Hydrology and Climate on Hydrological Connectivity in a Complex River–Lake Floodplain System Based on High Spatiotemporal Resolution Images S. Yang et al. https://doi.org/10.3390/w14121836
12. Identifying Causal Interactions Between Groundwater and Streamflow Using Convergent Cross‐Mapping G. Bonotto et al. https://doi.org/10.1029/2021WR030231
13. Can causal discovery lead to a more robust prediction model for runoff signatures? H. Abbasizadeh et al. https://doi.org/10.5194/hess-29-4761-2025
14. An increasing mutual promotion of economic growth between China and the world observed from nighttime light remote sensing Z. Chen et al. https://doi.org/10.1080/17538947.2024.2426521
15. Beyond prediction accuracy: Causality-driven machine learning models for seasonal flow forecasting in Canada A. Elshorbagy et al. https://doi.org/10.1016/j.ejrh.2026.103876
16. Climate change and human activities amplify runoff variability risks in lower reaches of large rivers J. Gao et al. https://doi.org/10.1038/s43247-025-02759-3
17. Watershed sediment cascades across multiple timescales: Causal relationships with hydroclimate and underlying surface attributes Z. Yue et al. https://doi.org/10.1016/j.jhydrol.2025.134234
18. Causal Inferences on Drought Propagation Dynamics Using Extended Convergent Cross Mapping S. Bilal & V. Gupta https://doi.org/10.1061/JHYEFF.HEENG-6595
19. Quantitative comparison of causal inference methods for climate tipping points N. Lohmann et al. https://doi.org/10.5194/npg-33-313-2026
20. From Monitoring Data to Management Decisions: Causal Network Analysis of Water Quality Dynamics Using CEcBaN S. Hilau et al. https://doi.org/10.3390/w18060764
21. Nonlinear Riparian Interactions Drive Changes in Headwater Streamflow S. Newcomb & S. Godsey https://doi.org/10.1029/2023WR034870
22. Compounding hazards increase flood economic losses across Europe M. Ronco et al. https://doi.org/10.1038/s41467-026-73248-0
23. Framework for extracting multi-objective operation rules for cascade reservoirs based on causal features and physical mechanisms D. Gu et al. https://doi.org/10.1016/j.ejrh.2025.102522
24. A causal-aware artificial intelligence framework for mineral prospectivity mapping Z. Zhang et al. https://doi.org/10.1016/j.gsf.2026.102248
25. Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping S. Lee et al. https://doi.org/10.1038/s41598-023-44071-0
26. Spatial heterogeneity of agricultural drought drivers in irrigation district: A causal inference framework bridging covariation and structural equation modeling X. Shi et al. https://doi.org/10.1016/j.agwat.2025.109978
27. Assessing the Impact of Long-Term ENSO, SST, and IOD Dynamics on Extreme Hydrological Events (EHEs) in the Kelani River Basin (KRB), Sri Lanka V. Wijeratne et al. https://doi.org/10.3390/atmos14010079
28. Cause-effect discovery in hydrometeorological systems: evaluation of causal discovery methods V. Yadav et al. https://doi.org/10.5194/hess-30-3455-2026
29. Revealing joint evolutions and causal interactions in complex ecohydrological systems by a network-based framework L. Wang et al. https://doi.org/10.5194/hess-29-361-2025
30. Unravelling the spatiotemporal causality chain between meteorological and agricultural drought propagation in the China–Pakistan Economic Corridor M. Ismail et al. https://doi.org/10.1016/j.atmosres.2025.108532
31. Explainable and causal machine learning to investigate the spatiotemporal dynamics patterns of coastal water quality in Hong Kong H. Zhang et al. https://doi.org/10.1016/j.watres.2025.125026
32. Optimizing lakeside buffers and extending ecological redlines to key rivers: A multi-scale buffer and causal identification for diagnosing water quality drivers in a plateau lake, China X. Pu et al. https://doi.org/10.1016/j.watres.2026.126444
33. Ecological responses to hydrological connectivity in grassland riparian zones: Insights from vegetation and ground-dwelling arthropods M. Ye et al. https://doi.org/10.1016/j.scitotenv.2024.171196
34. From RNNs to Transformers: benchmarking deep learning architectures for hydrologic prediction J. Liu et al. https://doi.org/10.5194/hess-29-6811-2025
35. Unraveling drought propagation dynamics using causal inference from time series M. Pang & S. Yang https://doi.org/10.1088/1748-9326/ae151e