Climate change profoundly affects the global water, energy, and carbon cycle, increasing the likelihood and severity of extreme events. Better decision-support systems are essential to accurately predict and monitor environmental disasters and optimally manage water and environmental resources. A Digital Twin (DT) of the water and energy cycle over land would offer ground-breaking solutions for monitoring and simulation. Yet, it requires high-resolution (1 km, 1 hour-day) satellite Earth Observation (EO) data, fully integrated with advanced and spatially distributed modeling systems. Building a high-resolution DT over land is challenging due to: (i) the impact of human interventions on land processes through, e.g., irrigation, reservoir management, water diversion, land use and land cover changes, (ii) the need for actual high-resolution (1 km, 1 hour-day) input (e.g., precipitation, evaporation) and ancillary (e.g., soil texture, vegetation) data for characterizing the complexity of the system (for several variables, e.g., soil moisture and evaporation, ground data are scarce), and (iii) the complexity of integrating EO and modeling in a seamless, parsimonious and consistent manner for large-scale applications at high-resolution. The presentation shows the first results of the development of a DT for the water and energy cycle, as developed in the ESA DTE Hydrology project (http://hydrology.irpi.cnr.it/projects/dte-hydrology/), with applications in the Mediterranean basin for flood and landslide risk mitigation, and for water resources management (see the video (https://youtu.be/vf5wNv91nKA), the DTE Hydrology Platform (https://explorer.dte-hydro.adamplatform.eu/), and the DTE Hydrology Final Report (https://doi.org/10.5281/zenodo.8089044)).