What problem does it solve? Running Deltares' wflow distributed hydrological model correctly requires deep operational knowledge: Julia environment setup, TOML v1.0 configuration, NetCDF forcing in exact units, cycle-free flow networks, and sediment parameterization. This Skill packages that expertise so an AI agent can build, run, validate, and couple wflow_sbm and wflow_sediment models without silent scientific errors. ## Core Features & Use Cases - End-to-end pipeline: 24 tools across 10 stages covering configuration, HydroMT model building, CMFD/MSWX forcing conversion, PET calculation, TOML generation, Julia execution, discharge extraction, and sediment analysis. - Diagnostic recovery: 39 diagnostic triplets map symptoms (e.g., LDD cycles, Kelvin-vs-Celsius forcing, double-counted routing with CaMa-Flood) to validated remedies. - Coupling and validation: Export unrouted runoff to CaMa-Flood, recharge to MODFLOW, compare discharge against VIC with NSE/KGE metrics, and derive USLE K/C factors from HWSD and AVHRR data. - Use Case: Ask the agent to simulate discharge for the Bengbu basin (2003-2005) with CMFD forcing; it builds staticmaps.nc, converts forcing, generates the v1.0 TOML, runs Wflow.jl in 14 seconds, and validates the hydrograph. ## Quick Start Run preflight_check.py in this KI directory, then ask the agent to build and run a wflow_sbm simulation for your basin by providing the outlet coordinates, period, and forcing dataset.