Flood damage depends on location and adaptation of human presence and activity to inherent variability of river flow. Reduced predictability of river flow is a common sign of degrading watersheds associated with increased flooding risk and reduced dry-season flows. The dimensionless FlowPer parameter (Fp), representing predictability, is key to a parsimonious recursive model of river flow, Qt = FpQt-1 + (1-Fp)(Pt-Etx), with Q, P and E expressed in mm d-1. Fp varies between 0 and 1, and can be derived from a time-series of measured (or modeled) river flow data. The spatially averaged precipitation term Pt and preceding cumulative evapotranspiration since previous rain Etx are treated as constrained but unknown, stochastic variables. A decrease in Fp from 0.9 to 0.8 means peak flow doubling from 10 to 20% of peak rainfall (minus its accompanying Etx) and, in a numerical example, an increase in expected flood duration by 3 days. We compared Fp estimates from four meso-scale watersheds in Indonesia and Thailand, with varying climate, geology and land cover history, at a decadal time scale. Wet-season (3-monthly) Fp values are lower than dry-season values in climates with pronounced seasonality. A wet-season Fp value above 0.7 was achievable in forest-agroforestry mosaic case studies. Interannual variability in Fp is large relative to effects of land cover change; multiple years of paired-plot data are needed to reject no-change null-hypotheses. While empirical evidence at scale is understandably scarce, Fp trends over time serve as a holistic scale-dependent performance indicator of degrading/recovering watershed health.