@article{wang2026rainfall,
  title = {Rainfall Sensing via Mobile Communication Signals},
  author = {Zhongqin Wang and J. Andrew Zhang and Kai Wu and Y. Jay Guo},
  year = {2026},
  eprint = {2608.16088},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.16088},
}

@article{wang2026conceptual,
  title = {From Conceptual Hydrologic Models to Conceptually Interpretable Neural Networks: A Snow-Water Mass-Conserving-Perceptron Framework for Discovering Catchment-Scale Precipitation-Storage-Runoff Representations},
  author = {Yuan-Heng Wang and Hoshin V. Gupta},
  year = {2026},
  eprint = {2607.26492},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.26492},
}

@article{sikora2026exploratory,
  title = {Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector},
  author = {Piotr Sikora and Sotirios Kontogiannis},
  year = {2026},
  eprint = {2607.10208},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.10208},
}

@article{rodriguezpardo2026harmonised,
  title = {A harmonised dataset for Earth system foundation models},
  author = {Carlos Rodriguez-Pardo and Massimo Tavoni},
  year = {2026},
  eprint = {2607.03298},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.03298},
}

@article{canovasrodriguez2026deep,
  title = {Deep Learning for Soil Moisture Estimation: Fusing Satellite Data with Optimally-Lagged Meteorological Features},
  author = {Adrian Canovas-Rodriguez and Aurora González Vidal and Antonio F. Skarmeta},
  year = {2026},
  eprint = {2606.21475},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.21475},
}

@article{horvathmakkos2026interpretable,
  title = {Interpretable rainfall modelling reveals rapid reorganisation of Amazonian rainfall under vegetation loss},
  author = {Lilly Horvath-Makkos and Fayyaz Minhas},
  year = {2026},
  eprint = {2605.10948},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.10948},
}

@article{castro2026metbra25y,
  title = {METBRA25Y: Brazil Surface Meteorology Archive with Harmonized Variables and Quality Control},
  author = {Matheus Lima Castro and William Dantas Vichete and Leopoldo Lusquino Filho},
  year = {2026},
  eprint = {2605.08701},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.08701},
}

@article{mirhoseini2026observationguided,
  title = {Observation-Guided Neural Surrogate Learning for Scientific Simulation Emulation: A Single-Gauge Flood-Inundation Proof of Concept},
  author = {Marzieh Alireza Mirhoseini},
  year = {2026},
  eprint = {2604.25890},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.25890},
}

@article{farmani2026processaware,
  title = {Process-Aware AI for Rainfall-Runoff Modeling: A Mass-Conserving Neural Framework with Hydrological Process Constraints},
  author = {Mohammad A. Farmani and Hoshin V. Gupta and Ali Behrangi and Muhammad Jawad and Sadaf Moghisi and Guo-Yue Niu},
  year = {2026},
  eprint = {2603.25093},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.25093},
}

@article{hassan2025climate,
  title = {Climate Adaptation-Aware Flood Prediction for Coastal Cities Using Deep Learning},
  author = {Bilal Hassan and Areg Karapetyan and Aaron Chung Hin Chow and Samer Madanat},
  year = {2025},
  eprint = {2510.26017},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.26017},
}

@article{zhou2025progressive,
  title = {Progressive Scale Convolutional Network for Spatio-Temporal Downscaling of Soil Moisture: A Case Study Over the Tibetan Plateau},
  author = {Ziyu Zhou and Keyan Hu and Ling Zhang and Zhaohui Xue and Yutian Fang and Yusha Zheng},
  year = {2025},
  eprint = {2510.10244},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.10244},
}

@article{kapoor2025qdeepgr4j,
  title = {QDeepGR4J: Quantile-based ensemble of deep learning and GR4J hybrid rainfall-runoff models for extreme flow prediction with uncertainty quantification},
  author = {Arpit Kapoor and Rohitash Chandra},
  year = {2025},
  eprint = {2510.05453},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.05453},
}

@article{wang2025conuswide,
  title = {Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics},
  author = {Yuan-Heng Wang and Yang Yang and Fabio Ciulla and Hoshin V. Gupta and Charuleka Varadharajan},
  year = {2025},
  eprint = {2510.02605},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.02605},
}

@article{chen2025rainseer,
  title = {RainSeer: Fine-Grained Rainfall Reconstruction via Physics-Guided Modeling},
  author = {Lin Chen and Jun Chen and Minghui Qiu and Shuxin Zhong and Binghong Chen and Kaishun Wu},
  year = {2025},
  eprint = {2510.02414},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.02414},
}

@article{rice2025projecting,
  title = {Projecting U.S. coastal storm surge risks and impacts with deep learning},
  author = {Julian R. Rice and Karthik Balaguru and Fadia Ticona Rollano and John Wilson and Brent Daniel and David Judi and Ning Sun and L. Ruby Leung},
  year = {2025},
  eprint = {2506.13963},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.13963},
}

@article{gao2025functional,
  title = {Functional data decomposition reveals unexpectedly strong soil moisture-precipitation coupling over the Great Plains},
  author = {Yifu Gao and Runze Li and Efi Foufoula-Georgiou and Jasper A. Vrugt},
  year = {2025},
  eprint = {2506.13939},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.13939},
}

@article{mbarak2025noahmpai,
  title = {Towards NoahMP-AI: Enhancing Land Surface Model Prediction with Deep Learning},
  author = {Mahmoud Mbarak and Manmeet Singh and Naveen Sudharsan and Zong-Liang Yang},
  year = {2025},
  eprint = {2506.12919},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.12919},
}

@article{vischer2025spatially,
  title = {Spatially Resolved Meteorological and Ancillary Data in Central Europe for Rainfall Streamflow Modeling},
  author = {Marc Aurel Vischer and Noelia Otero and Jackie Ma},
  year = {2025},
  eprint = {2506.03819},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.03819},
}

@article{liu2025multitiered,
  title = {A Multi-Tiered Bayesian Network Coastal Compound Flood Analysis Framework},
  author = {Ziyue Liu and Meredith L. Carr and Norberto C. Nadal-Caraballo and Luke A. Aucoin and Madison C. Yawn and Michelle T. Bensi},
  year = {2025},
  eprint = {2505.15520},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.15520},
}

@article{masoudian2025assessing,
  title = {Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors},
  author = {Ehsan Masoudian and Ali Mirzaei and Hossein Bagheri},
  year = {2025},
  eprint = {2505.14122},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.14122},
}

@article{saranathan2025physically,
  title = {A Physically Driven Long Short Term Memory Model for Estimating Snow Water Equivalent over the Continental United States},
  author = {Arun M. Saranathan and Mahmoud Saeedimoghaddam and Brandon Smith and Deepthi Raghunandan and Grey Nearing and Craig Pelissier},
  year = {2025},
  eprint = {2504.20129},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.20129},
}

@article{gorooh2025enhancing,
  title = {Enhancing Deterministic Freezing Level Predictions in the Northern Sierra Nevada Through Deep Neural Networks},
  author = {Vesta Afzali Gorooh and Agniv Sengupta and Shawn Roj and Rachel Weihs and Brian Kawzenuk and Luca Delle Monache and F. Martin Ralph},
  year = {2025},
  eprint = {2504.11560},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.11560},
}

@article{dhankhar2025spatiotemporal,
  title = {A Spatiotemporal Radar-Based Precipitation Model for Water Level Prediction and Flood Forecasting},
  author = {Sakshi Dhankhar and Stefan Wittek and Hamidreza Eivazi and Andreas Rausch},
  year = {2025},
  eprint = {2503.19943},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.19943},
}

@article{jamaat2025update,
  title = {Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models},
  author = {Amirmoez Jamaat and Yalan Song and Farshid Rahmani and Jiangtao Liu and Kathryn Lawson and Chaopeng Shen},
  year = {2025},
  eprint = {2502.16444},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.16444},
}

@article{tazi2025refined,
  title = {Refined climatologies of future precipitation over High Mountain Asia using probabilistic ensemble learning},
  author = {Kenza Tazi and Sun Woo P. Kim and Marc Girona-Mata and Richard E. Turner},
  year = {2025},
  eprint = {2501.15690},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.15690},
}

@article{wang2025deep,
  title = {A Deep State Space Model for Rainfall-Runoff Simulations},
  author = {Yihan Wang and Lujun Zhang and Annan Yu and N. Benjamin Erichson and Tiantian Yang},
  year = {2025},
  eprint = {2501.14980},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.14980},
}

@article{xia2025aidriven,
  title = {AI-Driven Reinvention of Hydrological Modeling for Accurate Predictions and Interpretation to Transform Earth System Modeling},
  author = {Cuihui Xia and Lei Yue and Deliang Chen and Yuyang Li and Hongqiang Yang and Ancheng Xue and Zhiqiang Li and Qing He and Guoqing Zhang and Dambaru Ballab Kattel and Lei Lei and Ming Zhou},
  year = {2025},
  eprint = {2501.04733},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.04733},
}

@article{salcedo2024graph,
  title = {Graph Learning-based Regional Heavy Rainfall Prediction Using Low-Cost Rain Gauges},
  author = {Edwin Salcedo},
  year = {2024},
  eprint = {2412.16842},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.16842},
}

@article{charbonneau2024physicsconstrained,
  title = {A Physics-Constrained Neural Differential Equation Framework for Data-Driven Snowpack Simulation},
  author = {Andrew Charbonneau and Katherine Deck and Tapio Schneider},
  year = {2024},
  eprint = {2412.06819},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.06819},
}

@article{wang2024machine,
  title = {Using Machine Learning to Discover Parsimonious and Physically-Interpretable Representations of Catchment-Scale Rainfall-Runoff Dynamics},
  author = {Yuan-Heng Wang and Hoshin V. Gupta},
  year = {2024},
  eprint = {2412.04845},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.04845},
}

@article{mirhoseini2024learning,
  title = {Learning Surrogate Rainfall-driven Inundation Models with Few Data},
  author = {Marzieh Alireza Mirhoseini},
  year = {2024},
  eprint = {2411.19323},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.19323},
}

@article{chun2024unravelling,
  title = {Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures},
  author = {Kwok P Chun and Thanti Octavianti and Georgia Papacharalampous and Hristos Tyralis and Samuel J. Sutanto and Pavel Terskii and Paola Mazzoglio and Dario Treppiedi and Juan Rivera and Nilay Dogulu and Adeyemi Olusola and Bastien Dieppois and Moctar Dembélé and Simon Moulds and Cheng Li and Luis Alejandro Morales-Marin and Neil Macdonald and Toundji Olivier Amoussou and Roland Yonaba and Salomon Obahoundje and Nicolas Massei and David M. Hannah and Sivarama Krishna Reddy Chidepudi and Byman Hamududu},
  year = {2024},
  eprint = {2409.19003},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.19003},
}

@article{huang2024highresolution,
  title = {High-Resolution Flood Probability Mapping Using Generative Machine Learning with Large-Scale Synthetic Precipitation and Inundation Data},
  author = {Lipai Huang and Federico Antolini and Ali Mostafavi and Russell Blessing and Matthew Garcia and Samuel D. Brody},
  year = {2024},
  eprint = {2409.13936},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.13936},
}

@article{salis2024time,
  title = {Time Distributed Deep Learning Models for Purely Exogenous Forecasting: Application to Water Table Depth Prediction using Weather Image Time Series},
  author = {Matteo Salis and Abdourrahmane M. Atto and Stefano Ferraris and Rosa Meo},
  year = {2024},
  eprint = {2409.13284},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.13284},
}

@article{wang2024cascanglong,
  title = {CAS-Canglong: A skillful 3D Transformer model for sub-seasonal to seasonal global sea surface temperature prediction},
  author = {Longhao Wang and Xuanze Zhang and L. Ruby Leung and Francis H. S. Chiew and Amir AghaKouchak and Kairan Ying and Yongqiang Zhang},
  year = {2024},
  eprint = {2409.05369},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.05369},
}

@article{shi2024evapotranspiration,
  title = {Evapotranspiration trends over the last 300 years reconstructed from historical weather station observations via machine learning},
  author = {Haiyang Shi},
  year = {2024},
  eprint = {2407.16265},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.16265},
}

@article{chandra2024ensemble,
  title = {Ensemble quantile-based deep learning framework for streamflow and flood prediction in Australian catchments},
  author = {Rohitash Chandra and Arpit Kapoor and Siddharth Khedkar and Jim Ng and R. Willem Vervoort},
  year = {2024},
  eprint = {2407.15882},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.15882},
}