69 citations as recorded by crossref.

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28. Mapping the groundwater memory across Ireland: A step towards a groundwater drought susceptibility assessment P. Schuler et al. 10.1016/j.jhydrol.2022.128277
29. Spatial prediction of groundwater levels using machine learning and geostatistical models: a case study of coastal faulted aquifer systems in southeastern Tunisia H. Chihi & I. Ben Cheikh Larbi 10.1007/s10040-023-02686-7
30. A Data-Driven Method for the Temporal Estimation of Soil Water Potential and Its Application for Shallow Landslides Prediction M. Bordoni et al. 10.3390/w13091208
31. Exploring the spatiotemporal water quality variations and their influencing factors in a large floodplain lake in China B. Li et al. 10.1016/j.ecolind.2020.106454
32. Estimation of Daily Water Table Level with Bimonthly Measurements in Restored Ombrotrophic Peatland S. Gutierrez Pacheco et al. 10.3390/su13105474
33. Evaluation of shallow groundwater dynamics after water supplement in North China Plain based on attention-GRU model T. Nan et al. 10.1016/j.jhydrol.2023.130085
34. Groundwater level estimation in northern region of Bangladesh using hybrid locally weighted linear regression and Gaussian process regression modeling A. Elbeltagi et al. 10.1007/s00704-022-04037-0
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37. Assessing impacts of land use/land cover patterns to shallow groundwater nitrate pollution in an agricultural-dominant area in northwest China using random forest F. Su et al. 10.1007/s12665-024-11856-z
38. A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin) H. Henriksen et al. 10.3390/w15010025
39. Application of Hybrid Prediction Methods in Spatial Assessment of Inland Excess Water Hazard A. Laborczi et al. 10.3390/ijgi9040268
40. Comparing alternative conceptual models for tile drains and soil heterogeneity for the simulation of tile drainage in agricultural catchments V. Boico et al. 10.1016/j.jhydrol.2022.128120
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42. High Resolution Water Table Modeling of the Shallow Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model J. Koch et al. 10.3389/frwa.2021.701726
43. Machine Learning-Based Reconstruction and Prediction of Groundwater Time Series in the Allertal, Germany T. Tran et al. 10.3390/w17030433
44. Prediction of Groundwater Level Variations in a Changing Climate: A Danish Case Study R. Gonzalez & J. Arsanjani 10.3390/ijgi10110792
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46. Simulation of regional groundwater levels in arid regions using interpretable machine learning models Q. Liu et al. 10.1016/j.scitotenv.2022.154902
47. Deciphering the impact of cascade reservoirs on nitrogen transport and nitrate transformation: Insights from multiple isotope analysis and machine learning Y. Bao et al. 10.1016/j.watres.2024.122638
48. A robust objective function for calibration of groundwater models in light of deficiencies of model structure and observations R. Schneider et al. 10.1016/j.jhydrol.2022.128339
49. A high-resolution map of diffuse groundwater recharge rates for Australia S. Lee et al. 10.5194/hess-28-1771-2024
50. Hydrological process knowledge in catchment modelling – Lessons and perspectives from 60 years development J. Refsgaard et al. 10.1002/hyp.14463
51. The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting S. Hauswirth et al. 10.5194/hess-27-501-2023
52. Comparative analysis of kernel-based versus ANN and deep learning methods in monthly reference evapotranspiration estimation M. Sattari et al. 10.5194/hess-25-603-2021
53. A critical review on groundwater level depletion monitoring based on GIS and data-driven models: Global perspectives and future challenges M. Monir et al. 10.1016/j.hydres.2024.05.001
54. Development of MCS based-ensemble models using CEEMDAN decomposition and machine intelligence S. Garai & R. Paul 10.1016/j.iswa.2023.200202
55. Employing machine learning to quantify long-term climatological and regulatory impacts on groundwater availability in intensively irrigated regions S. Nozari et al. 10.1016/j.jhydrol.2022.128511
56. Spatial Analysis and Risk Assessment Model Research of Arthritis Based on Risk Factors: China, 2011, 2013 and 2015 Z. Ren et al. 10.1109/ACCESS.2020.3037912
57. Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm S. Samantaray et al. 10.1016/j.clwat.2024.100003
58. Satellite-derived shallow water depths estimation using remote sensing and artificial intelligence models, a case study: Darbandikhan Lake Upper, Kurdistan Region, Iraq A. Othman et al. 10.1016/j.rsase.2024.101432
59. Altimetry‐Derived Gravity Gradients Using Spectral Method and Their Performance in Bathymetry Inversion Using Back‐Propagation Neural Network X. Wan et al. 10.1029/2022JB025785
60. Machine learning for predicting shallow groundwater levels in urban areas A. LaBianca et al. 10.1016/j.jhydrol.2024.130902
61. A Machine Learning Approach to Predict Groundwater Levels in California Reveals Ecosystems at Risk M. Rohde et al. 10.3389/feart.2021.784499
62. Using random forests to explore the feasibility of groundwater knowledge transfer between the contiguous US and Denmark Y. Ma et al. 10.1088/2515-7620/ad9b08
63. Downscaling a national hydrological model to subgrid scale S. Noorduijn et al. 10.1016/j.jhydrol.2021.126796
64. Basin-wide tracking of nitrate cycling in Yangtze River through dual isotope and machine learning F. Xie et al. 10.1016/j.scitotenv.2023.169656
65. Performance comparison of physics-based and machine learning assisted multi-fidelity methods for the management of coastal aquifer systems G. Kopsiaftis et al. 10.3389/frwa.2023.1195029
66. An improved support vector machine model for groundwater level prediction: a case study S. Sahoo & D. Satapathy 10.1007/s12145-024-01647-2
67. Assessing automated gap imputation of regional scale groundwater level data sets with typical gap patterns J. Bikše et al. 10.1016/j.jhydrol.2023.129424
68. Estimation of groundwater age distributions from hydrochemistry: comparison of two metamodelling algorithms in the Heretaunga Plains aquifer system, New Zealand C. Tschritter et al. 10.5194/hess-27-4295-2023
69. Prediction of groundwater level using the hybrid model combining wavelet transform and machine learning algorithms A. Wei et al. 10.1007/s12145-022-00853-0