Explanations for distinct adjacent ecosystems that extend across hilly landscapes typically point to differences in climate or land use. Here we document—within a similar climate—how contrasting regional plant communities correlate with distinct underlying lithology and reveal how differences in water storage capacity in the critical zone (CZ) explain this relationship. We present observations of subsurface CZ structure and groundwater dynamics from deep boreholes and quantify catchment‐wide dynamic water storage in two Franciscan rock types of the Northern California Coast Ranges. Our field sites have a Mediterranean climate, where rains are out of phase with solar energy, amplifying the importance of subsurface water storage for periods of peak ecosystem productivity in the dry season. In the deeply weathered (~30 m at ridge) Coastal Belt argillite and sandstone, ample, seasonally replenished rock moisture supports an evergreen forest and groundwater drainage sustains baseflow throughout the summer. In the Central Belt argillite‐matrix mélange, a thin CZ (~3 m at ridge) limits total dynamic water storage capacity (100–200 mm) and rapidly sheds winter rainfall via shallow storm and saturation overland flow, resulting in low plant‐available water (inferred from predawn tree water potential) and negligible groundwater storage that can drain to streams in summer. This storage limitation mechanism explains the presence of an oak savanna‐woodland bounded by seasonally ephemeral streams, despite >1,800 mm of average precipitation. Through hydrologic monitoring and subsurface characterization, we reveal a mechanism by which differences in rock type result in distinct regionally extensive plant communities under a similar climate.

The relationship between seasonal catchment water storage and discharge is typically nonunique due to water storage that is not directly hydraulically connected to streams. Hydraulically disconnected water volumes are often ecologically and hydrologically important but cannot be explicitly estimated using current storage–discharge techniques. Here, we propose that discharge is explicitly sensitive to changes in only some fraction of seasonally dynamic storage that we call “direct storage,” whereas the remaining storage (“indirect storage”) varies without directly influencing discharge. We use a coupled mass balance and storage–discharge function approach to partition seasonally dynamic storage between these 2 pools in the Northern California Coast Ranges. We find that indirect storage constitutes the vast majority of dynamic catchment storage, even at the wettest times of the year. Indirect storage exhibits lower variability over the course of the wet season (and in successive winter periods) than does direct storage. Predicted indirect storage volumes and dynamics match field observations. Comparison of 2 neighbouring field sites reveals that indirect storage volumes can occur as unsaturated storage held under tension in soils and weathered bedrock and as near‐surface saturated storage that remains on hillslopes (and is eventually evapotranspired). Indirect storage volumes (including moisture in the weathered bedrock) may support plant transpiration, and our method indicates that this important water source could be quantified from precipitation and stream discharge records.

Flow duration curves (FDC) display streamflow values against their relative exceedance time.They provide critical information for watershed management by representing the variation in the availability and reliability of surface water to supply ecosystem services and satisfy anthropogenic needs. FDCs are particularly revealing in seasonally dry climates, where surface water supplies are highly variable. While useful, the empirical computation of FDCs is data intensive and challenging in sparsely gauged regions, meaning that there is a need for robust, predictive models to evaluate FDCs with simple parameterization. Here, we derive a process-based analytical expression for FDCs in seasonally dry climates. During the wet season, streamflow is modeled as a stochastic variable driven by rainfall, following the stochastic analytical model of Botter et al. (2007a). During the dry season, streamflow is modeled as a deterministic recession with a stochastic initial condition that accounts for the carryover of catchment storage across seasons. The resulting FDC model is applied to 38 catchments in Nepal, coastal California, and Western Australia, where FDCs are successfully modeled using five physically meaningful parameters with minimal calibration. A Monte Carlo analysis revealed that the model is robust to deviations from its assumptions of Poissonian rainfall, exponentially distributed response times and constant seasonal timing. The approach successfully models period-of-record FDCs and allows interannual and intra-annual sources of variations in dry season streamflow to be separated. The resulting median annual FDCs and confidence intervals allow the simulation of the consequences of interannual flow variations for infrastructure projects. We present an example using run-of-river hydropower in Nepal as a case study.