A 3D terrain-aware Framework for Rain Gauge Network Optimization

Rain-gauge network optimisation in complex terrain should consider more than station density or planar spacing. It should also assess whether the existing gauges adequately sample the elevation ranges and terrain settings that influence spatial rainfall variability. This study proposes a terrain-aware Composite Gap Coverage (COMP) strategy for augmenting an operational rain gauge network in the Wupper River catchment, western Germany. COMP translates residual terrain representativeness gaps into an interpretable station selection problem by combining Digital Elevation Model (DEM) derived elevation mismatch, horizontal spacing, and terrain complexity in a Composite Terrain Gap Score (CTGS). Candidate locations are selected through a greedy coverage procedure that prioritises areas where the current network remains structurally under-representative. The framework is designed as a planning support tool rather than as a claim of unique optimal station placement. In the full domain application, COMP identified five terrain-aware priority zones that improved model-based interpolation uncertainty, spatial coverage, elevation distribution representativeness, and terrain weighted coverage relative to the 17 gauge baseline network. A weight sensitivity analysis showed that exact grid cell rankings depend on CTGS weights, so the recommendations are interpreted as planning level priority zones rather than fixed installation coordinates. A core domain proxy validation was then performed using four additional gauges. These proxy gauges reproduced 96.1% of the ideal geometric variance reduction and produced moderate monthly prediction error reductions of about 7–8%. The results show that COMP provides a transparent and interpretable way to identify terrain related monitoring gaps in operational rain gauge networks.