14 citations as recorded by crossref.

1. Integrating climate resilience and digital twin technologies in housing: A comparative analysis and sustainable design proposal for Jordan and South Africa A. Shehadeh et al.
2. A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin) H. Henriksen et al.
3. CAMELS-DK: hydrometeorological time series and landscape attributes for 3330 Danish catchments with streamflow observations from 304 gauged stations J. Liu et al.
4. Leveraging digital twins for community-driven sustainable WEFE nexus management A. Shehadeh et al.
5. A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks J. Liu et al.
6. Modelling of shallow groundwater levels and interaction with drainage system and streams under the impact of climate change S. Thorndahl & R. Nielsen
7. Modeling groundwater in a changing climate: A review of advanced machine learning solutions N. Chahboune et al.
8. Combined water table and temperature dynamics control CO2 emission estimates from drained peatlands under rewetting and climate change scenarios T. Denager et al.
9. Impact of urban geology on model simulations of shallow groundwater levels and flow paths A. LaBianca et al.
10. Machine learning-based spatial downscaling and bias-correction framework for high-resolution temperature forecasting X. Meng et al.
11. Enhancing Urban Sustainability and Resilience: Employing Digital Twin Technologies for Integrated WEFE Nexus Management to Achieve SDGs A. Shehadeh et al.
12. Using random forests to explore the feasibility of groundwater knowledge transfer between the contiguous US and Denmark Y. Ma et al.
13. Harnessing machine learning for assessing climate change influences on groundwater resources: A comprehensive review A. Bamal et al.
14. High-Resolution Precipitation Modeling in Complex Terrains Using Hybrid Interpolation Techniques: Incorporating Physiographic and MODIS Cloud Cover Influences K. Alsafadi et al.