Improving flood forecasting using time-distributed CNN-LSTM model: a time-distributed spatiotemporal method

This publication has 58 references indexed in Scilit:

• Data-driven and knowledge-guided denoising diffusion model for flood forecasting
  Expert Systems with Applications, 2023
• Comparative evaluation of LSTM, CNN, and ConvLSTM for hourly short-term streamflow forecasting using deep learning approaches
  Ecological Informatics, 2023
• Avg-topk: A new pooling method for convolutional neural networks
  Expert Systems with Applications, 2023
• Wadi Flash Floods
  2022
• Monthly Streamflow Forecasting Using Convolutional Neural Network
  Water Resources Management, 2021
• Hydrologic Performance Simulation of Green Infrastructures: Why Data-Driven Modelling Can Be Useful?
  2018
• River flow modelling: comparison of performance and evaluation of uncertainty using data-driven models and conceptual hydrological model
  Stochastic Environmental Research and Risk Assessment, 2018
• Operational River Discharge Forecasting with Support Vector Regression Technique Applied to Alpine Catchments: Results, Advantages, Limits and Lesson Learned
  Water Resources Management, 2017
• Streamflow Forecasting and Estimation Using Least Square Support Vector Regression and Adaptive Neuro-Fuzzy Embedded Fuzzy c-means Clustering
  Water Resources Management, 2015
• Using observations and a distributed hydrologic model to explore runoff thresholds linked with mesquite encroachment in the Sonoran Desert
  Water Resources Research, 2014