69 citations as recorded by crossref.

1. Evaluating the accuracy of the global precipitation products: a time-series analysis in Poland R. Sarli et al. https://doi.org/10.1007/s00382-025-07636-5
2. Advancing hydrological prediction in South Africa with differentiable multi-source meteorological data fusion Y. Hu et al. https://doi.org/10.1016/j.ejrh.2026.103238
3. How GPM IMERG and GSMaP advance hydrological applications: A global perspective Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2025.133514
4. High-Accuracy Precipitation Fusion via a Two-Stage Machine Learning Approach for Enhanced Drought Monitoring in China’s Drylands W. Wang et al. https://doi.org/10.3390/rs18081194
5. Links between Western Mediterranean Oscillation and Mediterranean Moisture Paths: Implications for European Rainfall J. Ernst et al. https://doi.org/10.1007/s41748-025-00980-w
6. Evaluation of globally gridded precipitation data and satellite-based terrestrial water storage products using hydrological drought recovery time Ç. Çakan et al. https://doi.org/10.5194/hess-29-3359-2025
7. Season-land-use heterogeneity Bayesian Three-Cornered Hat (SLH-BTCH) for precipitation fusion in ungauged and sparsely gauged regions Q. Yu et al. https://doi.org/10.1016/j.ejrh.2026.103110
8. Comparative Assessment of Remote Sensing Precipitation Products for Runoff Estimation in Indian Watersheds D. Roy et al. https://doi.org/10.1061/JHYEFF.HEENG-6847
9. Enhancing discharge estimation in Pancarglagas watershed using NRECA with genetic algorithm optimization U. Andawayanti et al. https://doi.org/10.1088/1755-1315/1593/1/012002
10. Warming and Drying Intensification Across Iran’s River Basins (1950–2040): Historical Trends and LightGBM-Based Projections I. Rousta et al. https://doi.org/10.3390/atmos17050446
11. Future water resources and droughts in the Atlas Mountains of Morocco under a high-emission climate scenario O. Lahnik et al. https://doi.org/10.1016/j.ejrh.2025.102371
12. Augmenting precipitation datasets: A comparative study of topographic-based corrections and collocation techniques considering orographic effects M. Besharatifar et al. https://doi.org/10.1016/j.atmosres.2025.108317
13. Climate drives observational changes in hydrological extremes across most global regions N. Wang et al. https://doi.org/10.1016/j.xinn.2025.101171
14. Bayesian Model Averaging Method for Merging Multiple Precipitation Products over the Arid Region of Northwest China Y. Yang et al. https://doi.org/10.3390/atmos17010094
15. Comparison of high-resolution climate reanalysis datasets for hydro-climatic impact studies R. Wood et al. https://doi.org/10.5194/hess-29-4153-2025
16. From unreliable observations to reliable forecasts: Enhancing Jakarta flood prediction using HEC-HMS-assisted LSTM modeling H. Kardhana et al. https://doi.org/10.1016/j.envc.2026.101464
17. A rain-gauge fusion framework using Box–Cox transformation and LETKF to improve reanalysis precipitation estimates over China X. Liu et al. https://doi.org/10.1016/j.aosl.2026.100895
18. Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model P. Kalura et al. https://doi.org/10.1002/hyp.15275
19. Archetypal flow regime change classes and their associations with anthropogenic drivers of global streamflow alterations V. Virkki et al. https://doi.org/10.1088/2515-7620/ad9439
20. Machine-learning-based estimates of global natural vegetated wetland methane emissions (2000–2025) M. Li et al. https://doi.org/10.5194/essd-18-3507-2026
21. Refining precipitation estimates: CHIRPS v3.0 improvements in Caribbean Colombian L. Díaz-Chávez et al. https://doi.org/10.1016/j.htopen.2026.100063
22. Divergent seasonal contributions to global greening and record-high greenness in 2024 J. Zhao et al. https://doi.org/10.1007/s11430-025-1968-7
23. Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions J. Janzing et al. https://doi.org/10.5194/hess-29-7041-2025
24. Emerging technologies to multiscale drought risk assesment and modeling in the era of Big Earth Data and GeoAI A. Fentie & D. Mengistu https://doi.org/10.1007/s43621-026-03879-2
25. Coupled RUSLE-SWPT morphometric characterization of soil erosion under land use change and climate projections in the Upper OMO Gibe Basin M. Shomre et al. https://doi.org/10.1007/s44378-026-00264-3
26. Assessing the role of precipitation inputs and overbank flow in hydrological modeling: a case study of the Irrawaddy River Basin in Myanmar using WRF-Hydro Q. Sun et al. https://doi.org/10.3389/fclim.2025.1644481
27. Spatiotemporal evaluation of precipitation and streamflow trends in the Upper Awash River Basin using multisource data (1990–2023) N. Bihon et al. https://doi.org/10.2166/aqua.2025.047
28. Warming accelerates global drought severity S. Gebrechorkos et al. https://doi.org/10.1038/s41586-025-09047-2
29. What is our pick? Assessment of satellite and reanalysis precipitation datasets over Italy B. Moccia et al. https://doi.org/10.1016/j.ejrh.2025.102487
30. Machine learning gap-filling of hydrometeorological time series in south-central Chile: Streamflow, temperature and precipitation P. Sandoval-Quilodrán et al. https://doi.org/10.1016/j.ejrh.2026.103659
31. Comprehensive Global Assessment of 24 Gridded Precipitation Datasets Across 18 428 Catchments Using Hydrological Modeling A. Abbas et al. https://doi.org/10.5194/hess-30-3399-2026
32. Coherent changes in global high and low flows Q. Huang et al. https://doi.org/10.1016/j.hydroa.2025.100212
33. Evaluating Satellite and Reanalysis Rainfall Estimates for Climate Services in Agriculture: A Comprehensive Methodology D. Parsons et al. https://doi.org/10.1002/met.70170
34. Multiscale drought dataset for the Greater Antilles: a resource for environmental and adaptation studies M. Stojanovic et al. https://doi.org/10.1038/s41597-025-05992-9
35. Assessment of Simulated Meteorological Data Applicability for Hydrological Modelling in Low Land River Catchments S. Nazarenko et al. https://doi.org/10.3390/w18040454
36. Quantifying the Contribution of Global Precipitation Product Uncertainty to Ensemble Discharge Simulations and Projections: A Case Study in the Liujiang Catchment, Southwest China Y. Chang et al. https://doi.org/10.3390/atmos16111260
37. Research on Multi-Source Precipitation Fusion Based on Classification and Regression Machine Learning Methods—A Case Study of the Min River Basin in the Eastern Source of the Qinghai–Tibet Plateau S. Liu et al. https://doi.org/10.3390/rs17243982
38. Evaluation of ten satellite-based and reanalysis precipitation datasets on a daily basis for Czechia (2001–2021) D. Paluba et al. https://doi.org/10.1080/20964471.2025.2592444
39. Multi-criteria framework for evaluating gridded precipitation climate products in the Sahel region W. Muhammad et al. https://doi.org/10.1016/j.ejrh.2026.103240
40. State-of-the-art hydrological datasets exhibit low water balance consistency globally H. Huang et al. https://doi.org/10.5194/essd-18-3109-2026
41. Understanding meteorological, runoff, and agricultural drought propagation and their influencing factors in an ensemble of multiple datasets Y. Liu et al. https://doi.org/10.5194/hess-30-2775-2026
42. Development of intensity-duration-frequency curves using machine learning and satellite-derived precipitation data E. Dargham & C. Andraos https://doi.org/10.3389/frwa.2026.1727182
43. Evaluating the role of observational uncertainty in climate impact assessments: Temperature-driven yellow fever risk in South America S. Jahn et al. https://doi.org/10.1371/journal.pclm.0000601
44. Identifying Optimal Reanalysis and Remote Sensing Data Combinations for Multi-Scale SPEI-Based Drought Assessment in Zhejiang Province, China S. Pan et al. https://doi.org/10.3390/atmos16091078
45. An effective gauge-satellite fusion approach for daily precipitation bias correction based on multi-dimensional precipitation feature space (BCFS) G. Shen et al. https://doi.org/10.1016/j.atmosres.2025.108624
46. Lagrangian Tropical Cyclone Precipitation Estimates and Moisture Sources (LagTCPMoS) Dataset A. Pérez-Alarcón et al. https://doi.org/10.1038/s41597-025-05490-y
47. Multi-step ahead streamflow forecasting method using Embedding Multi-Layer Perceptron Y. Li & S. Yang https://doi.org/10.1016/j.ejrh.2026.103349
48. Enhancing water management in data-scarce watersheds using satellite and reanalysis precipitation: a combined SWAT+ and SMOGN machine learning approach M. Almeida et al. https://doi.org/10.1016/j.jhydrol.2026.135895
49. 全球植被绿度变化的季节差异及2024年异常升高机制 静. 赵 et al. https://doi.org/10.1360/N072025-0434
50. Spatiotemporal Analysis of Temperature and Precipitation in Syria O. Alsenjar & H. Aksu https://doi.org/10.1007/s00024-026-03948-7
51. Sensitivity of lumped and semi-distributed hydrological models to 20 gridded precipitation products in a transboundary basin P. Pacheco M. et al. https://doi.org/10.1016/j.jhydrol.2025.133462
52. Global spatio-temporal ERA5 precipitation downscaling to km and sub-hourly scale using generative AI L. Glawion et al. https://doi.org/10.1038/s41612-025-01103-y
53. Performance evaluation of MSWEP, CHIRPS, and ERA5 global gridded precipitation products against ground observations in the Gaza Strip H. Al-Najjar et al. https://doi.org/10.1007/s41207-026-01066-3
54. Assessing the Hydrological Utility of Multiple Satellite Precipitation Products in the Yellow River Source Region with Error Propagation Analysis C. Meng et al. https://doi.org/10.3390/rs18040537
55. Evaluating the spatiotemporal skill of bias-corrected NMME forecasts against climatological forecasts for seasonal precipitation in China B. Yu et al. https://doi.org/10.1038/s41598-026-39636-8
56. Integrating SMART principles in flood early warning system design in the Himalayas S. Dixit et al. https://doi.org/10.5194/nhess-26-1251-2026
57. Long-term spatiotemporal dynamics of global monthly rainfall erosivity derived from daily precipitation data and machine learning (1981–2020) B. Chen et al. https://doi.org/10.1016/j.iswcr.2026.100679
58. A new tool for correcting the spatial and temporal pattern of global precipitation products across mountainous terrain: precipitation and hydrological analysis S. Azimi et al. https://doi.org/10.1016/j.jhydrol.2025.133530
59. A novel cascaded neural network architecture integrating nonlinear autoregressive models with exogenous inputs (NARX) and LSTM for precipitation error correction M. Besharatifar et al. https://doi.org/10.1016/j.pce.2026.104479
60. Evaluating the Performance of Multiple Precipitation Datasets over the Transboundary Ili River Basin Between China and Kazakhstan B. Duisebek et al. https://doi.org/10.3390/su17167418
61. Hydroclimatic Change Detection Based on Observations and Bias-Corrected CMIP6 Projections Under SSP Scenarios P. Spor et al. https://doi.org/10.3390/su18084014
62. Comprehensive evaluations of gridded precipitation datasets across diverse climate zones of Brazos River Basin, Texas, USA T. Tarkegn et al. https://doi.org/10.1016/j.rsase.2026.101947
63. High-resolution precipitation downscaling in mainland Southeast Asia: A novel integration of BMA and U-Net CNN T. Amnuaylojaroen https://doi.org/10.1016/j.envsoft.2025.106682
64. Filling Data Gaps: Comparing Regression-based Models and Machine Learning Methods for Rainfall Time Series Reconstruction A. de Oliveira Pinheiro et al. https://doi.org/10.1007/s41748-026-01317-x
65. Effects of meteorological reconstruction on hydrological and deep learning streamflow models in Lanyang Watershed, Taiwan N. Tran & Y. Su https://doi.org/10.1016/j.ejrh.2026.103673
66. Landslide Mapping and Susceptibility Assessment in the Middle and Lower Reaches of the Nujiang River (2017–2025) Using Satellite Embedding and Multidimensional Environmental Factors W. Liu et al. https://doi.org/10.3390/rs18111854
67. Evaluation of national and international gridded meteorological products for rainfall-runoff modelling in Northern Italy G. Sarigil et al. https://doi.org/10.1016/j.ejrh.2024.102031
68. An Atlantic influence on evapotranspiration in the Orinoco and Amazon basins N. Duque-Gardeazabal et al. https://doi.org/10.5194/hess-29-3277-2025
69. Assessment of Remote Sensing Precipitation Products for Improved Drought Monitoring in Southern Tanzania V. Ogembo et al. https://doi.org/10.3390/cli14020036