Developing a Digital Twin Framework for Watershed Restoration Scenario Analysis:A Case Study in Mujib Basin, Jordan

Jordan’s dryland watersheds face acute water stress alongside increasing land degradation. Intense, short-duration storms cause flash runoff that accelerates soil erosion and sediment delivery to downstream infrastructure while groundwater, which is Jordan’s primary strategic water source, remains under long-term pressure. Rainwater-harvesting (RWH) interventions, including Vallerani micro catchments on damaged hillslopes, and Marab/flood-spreading and check-dam systems along ephemeral waterways, are increasingly used in restoration efforts. However, basin-scale planning is often limited by uncertainties in hydrological trade-offs and a gap between model outputs and stakeholder-ready, spatially explicit decision support.

This study develops a basin-scale hydrological Digital Twin (DT) for the Mujib Basin located in central Jordan by transforming process-based simulation findings into an interactive, scenario-driven dashboard. The DT combines a hydrological modelling core (SWAT) with harmonized in-situ and Earth Observation (EO) datasets to represent both water and land-surface responses. Physiographic inputs such as topography, soils, and land use, together with meteorological forcing derived from ERA5 reanalysis, and complemented by EO time series including Sentinel-2 vegetation indices, evapotranspiration products, and soil moisture to support the ecohydrological context.

Four intervention scenarios are represented - baseline, Vallerani, Marab, and combined - and evaluated using indicators relevant to water security, including surface runoff, sediment yield, and groundwater recharge, alongside vegetation/ET-related metrics. Outputs are produced at the sub-basin level and visualized through a web-based 3D dashboard, allowing users to visualize and compare different scenarios. The DT also enables "what-if" scenario testing by combining suitability-driven intervention placement with adjustable weather perturbations, allowing users to explore combined management and climate futures.

Beyond single-variable maps, the DT adds a decision layer for intervention targeting through a composite appropriateness framework matched with actual restoration goals: (1) Marab/check-dam suitability, which emphasizes high runoff generation, terrain controls, and proximity to channel networks; (2) infiltration-focused suitability, which highlights zones where slowing and spreading flow can increase recharge.  This study shows how digital twins can support hydrological decision-making in data-scarce dryland settings by bridging modelling outputs and implementation-oriented planning, usin Mujib Basin as a case study.