150 citations as recorded by crossref.

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44. Inferring catchment flow path responses using a data-driven model: an exploratory study based on a generalized additive model D. Kundu et al. 10.1080/02626667.2017.1357887
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46. Predicting standard penetration test N-value from cone penetration test data using artificial neural networks B. Tarawneh 10.1016/j.gsf.2016.02.003
47. Reviews and Syntheses: Promoting the Advancement of Hillslope Hydrology and Stability in Taiwan from the Perspective of Critical Zone Science Y. Yang et al. 10.3390/w15061234
48. Analytical and predictive assessment of rounding effects on rock slope stability under block toppling using adaptive moment estimation optimization N. Chaudhary et al. 10.1007/s40808-025-02545-2
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51. Multi-objective optimization of typhoon inundation forecast models with cross-site structures for a water-level gauging network by integrating ARMAX with a genetic algorithm H. Ouyang 10.5194/nhess-16-1897-2016
52. A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation E. Tapoglou et al. 10.1016/j.jhydrol.2014.10.040
53. Evaluation of short-term streamflow prediction methods in Urban river basins X. Huang et al. 10.1016/j.pce.2021.103027
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56. Analyzing drought characteristics using copula-based genetic algorithm method H. Kiafar et al. 10.1007/s12517-020-05703-1
57. Multi-time-step ahead daily global solar radiation forecasting: performance evaluation of wavelet-based artificial neural network model S. Sharifi et al. 10.1007/s00703-022-00882-w
58. Incorporating basic hydrological concepts into genetic programming for rainfall-runoff forecasting V. Havlíček et al. 10.1007/s00607-013-0298-0
59. How Well Can Machine Learning Models Perform without Hydrologists? Application of Rational Feature Selection to Improve Hydrological Forecasting V. Moreido et al. 10.3390/w13121696
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64. Data-driven techniques for modelling the gross primary production of the páramo vegetation using climate data: Application in the Ecuadorian Andean region V. Minaya et al. 10.1016/j.ecoinf.2016.12.002
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68. Monthly Rainfall-Runoff Modeling at Watershed Scale: A Comparative Study of Data-Driven and Theory-Driven Approaches W. Chang & X. Chen 10.3390/w10091116
69. Combined TBATS and SVM model of minimum and maximum air temperatures applied to wheat yield prediction at different locations in Europe M. Gos et al. 10.1016/j.agrformet.2019.107827
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79. The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models M. Demirel et al. 10.5194/hess-19-275-2015
80. A review of artificial intelligence applications in shallow foundations M. Shahin 10.1179/1939787914Y.0000000058
81. Quantifying the Uncertainties in Data-Driven Models for Reservoir Inflow Prediction X. Zhang et al. 10.1007/s11269-020-02514-7
82. Estimation of ANN prediction bounds for the suspended sediment load modeling V. Nourani et al. 10.1088/1755-1315/491/1/012001
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86. Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling C. Meng et al. 10.3390/w8090407
87. A Hybrid Method for the Run-Of-The-River Hydroelectric Power Plant Energy Forecast: HYPE Hydrological Model and Neural Network E. Ogliari et al. 10.3390/forecast2040022
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91. Assessing the effects of climate change on monthly precipitation: Proposing of a downscaling strategy through a case study in Turkey U. Okkan 10.1007/s12205-014-0052-y
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