Publications
Generative deep learning for probabilistic streamflow forecasting: conditional variational auto-encoder. Journal of Hydrology, 629, 130498. Retrieved from
. (2024). A quantile-based encoder-decoder framework for multi-step ahead runoff forecasting. Journal of Hydrology, 619, 129269. Retrieved from
. (2023). Bayesian extreme learning machines for hydrological prediction uncertainty. Journal of Hydrology, 626, 130138. Retrieved from
. (2023). Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions. Pedosphere. Retrieved from
. (2022). Investigating the impact of input variable selection on daily solar radiation prediction accuracy using data-driven models: a case study in northern Iran. Stochastic Environmental Research and Risk Assessment, 36(1), 225-249. Retrieved from
. (2022). A stochastic conceptual-data-driven approach for improved hydrological simulations. Environmental Modelling & Software, 149, 105326. Retrieved from
. (2022). Improving hydrological forecasts through temporal hierarchal reconciliation. EGU General Assembly 2021. Retrieved from
. (2021). Learning from one’s errors: A data-driven approach for mimicking an ensemble of hydrological model residuals. EGU General Assembly 2021. Retrieved from
. (2021). Improving Deep Learning hydrological time series modeling using Gaussian Filter preprocessing. EGU General Assembly 2021. Retrieved from
. (2021). Probabilistic urban water demand forecasting using wavelet-based machine learning models. Journal of Hydrology, 126358. Retrieved from
. (2021). A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations. Environmental Modelling & Software, 105094. Retrieved from
. (2021). Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models. Journal of Hydrology, 598, 126370. Retrieved from
. (2021). A maximal overlap discrete wavelet packet transform integrated approach for rainfall forecasting–A case study in the Awash River Basin. Environmental Modelling & Software, 105119. Retrieved from
. (2021). A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes. Environmental Modelling & Software, 130, 104718.
. (2020). Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms. Advances in Water Resources, 141, 103595.
. (2020). Data assimilation for streamflow forecasting using extreme learning machines. Water Resources Research, 56, e2019WR026226.
. (2020). Using a boundary-corrected wavelet transform coupled with machine learning and hybrid deep learning approaches for multi-step water level forecasting in Lakes Michigan and Ontario. EGU General Assembly Conference Abstracts, 4233. Retrieved from
. (2020). Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones. Journal of Hydrology, 591, 125509. Retrieved from
. (2020). On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction. Agricultural and Forest Meteorology, 278, 107647. Elsevier.
. (2019). Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting. Agricultural Water Management, 219, 72–85. Elsevier.
. (2019).