Understanding how ecosystem functioning affects hydrological partitioning at the catchment scale is critically important to predict the annual water balance under climate-related land use change. Terrestrial ecosystems rely on rainfall infiltration while riparian ecosystems rely on the accumulation of surface and subsurface runoff in the riparian zone and the channel network. Some of the rainfall that infiltrates into the soils will be available for plants on the catchment's hillslopes. Some of that water may percolate down the soil profile where it can recharge a perched shallow aquifer or move even deeper to recharge bedrock aquifers. Lateral shallow subsurface flow provides a subsidy of water to plants downslope, which allows different plant species to occupy the toeslopes (Thompson et al., 2011a; Hwang et al., 2012). Perched and deep aquifers can sustain streamflow during dry periods and are thus essential for riparian and aquatic ecosystems. At the catchment scale, the persistence of flow can be analyzed by means of the flow duration curve (a plot that shows the percentage of time that discharge in a stream is likely to equal or exceed some specified value of interest).Climate has a first order control on the annual water balance (Budyko, 1974). The aridity index (ratio of average annual potential evapotranspiration, PET, to average annual rainfall, P) can predict the evaporative fraction and the runoff coefficient at climate time scales (~30 years) in many catchments. Less is known about how catchment ecosystems affect the annual water balance. Huxman et al. (2004) showed that when biomes undergo drought conditions their rainwater use efficiency (Net Primary Production/P) converges to a common maximum value. In a similar context, Troch et al. (2009) introduced the Horton index (the ratio of vaporization (i.e. evapotranspiration) to catchment wetting (the amount of water that infiltrates into the soils and does not runoff superficially) as a measure of rainwater use efficiency of the catchment's ecosystems, and showed that the Horton Index (HI) converges to a value of 1 when catchments undergo drought conditions. Subsequent research about the HI found that the index is controlled by climate (aridity index) and landscape characteristics (catchment slope and elevation) and is a useful first-order predictor for annual and interannual vegetation greenness at the catchment scale (Brooks et al., 2011; Voepel et al., 2011). 3The role of catchment water storage on vegetation response has been acknowledged in several recent ecohydrological studies (Tague, 2009; Miller et al., 2010; Thompson et al., 2011a). Evidence that water storage subsidizes plant water use through lateral hydrological connectivity (driven by topography) has been shown at the plot and the catchment scale and across different biomes (Scott et al., 2008; Thompson et al., 2011b; Hwang et al., 2012). Past research carried out in a temperate climate experimental watershed suggests a direct relationship between landscape position and storage that e...

Abstract. Streamflow simulation across the tropics is limited by the lack of data to calibrate and validate large-scale hydrological models. Here, we applied the process-based, conceptual HYPE (Hydrological Predictions for the Environment) model to quantitatively assess Costa Rica's water resources at a national scale. Data scarcity was compensated for by using adjusted global topography and remotely sensed climate products to force, calibrate, and independently evaluate the model. We used a global temperature product and bias-corrected precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) as model forcings. Daily streamflow from 13 gauges for the period 1990–2003 and monthly Moderate Resolution Imaging Spectroradiometer (MODIS) potential evapotranspiration (PET) and actual evapotranspiration (AET) for the period 2000–2014 were used to calibrate and evaluate the model applying four different model configurations (M1, M2, M3, M4). The calibration consisted of step-wise parameter constraints preserving the best parameter sets from previous simulations in an attempt to balance the variable data availability and time periods. The model configurations were independently evaluated using hydrological signatures such as the baseflow index, runoff coefficient, and aridity index, among others. Results suggested that a two-step calibration using monthly and daily streamflow (M2) was a better option than calibrating only with daily streamflow (M1), with similar mean Kling–Gupta efficiency (KGE ∼ 0.53) for daily streamflow time series, but with improvements to reproduce the flow duration curves, with a median root mean squared error (RMSE) of 0.42 for M2 and a median RMSE of 1.15 for M1. Additionally, including AET (M3 and M4) in the calibration statistically improved the simulated water balance and better matched hydrological signatures, with a mean KGE of 0.49 for KGE in M3–M4, in comparison to M1–M2 with mean KGE < 0.3. Furthermore, Kruskal–Wallis and Mann–Whitney statistical tests support a similar model performance for M3 and M4, suggesting that monthly PET-AET and daily streamflow (M3) represents an appropriate calibration sequence for regional modeling. Such a large-scale hydrological model has the potential to be used operationally across the humid tropics informing decision-making at relatively high spatial and temporal resolution.

Quantitative estimations of ecohydrological water partitioning into evaporation and transpiration remains mostly based on plot-scale investigations that use well-instrumented, small-scale experimental catchments in temperate regions. Here, we attempted to upscale and adapt the conceptual tracer-aided ecohydrology model STARRtropics to simulate water partitioning, tracer, and storage dynamics over daily time steps and a 1-km grid larger-scale (2565 km 2 ) in a sparsely instrumented tropical catchment in Costa Rica. The model was driven by bias-corrected regional climate model outputs and was simultaneously calibrated against daily discharge observations from 2 to 30 years at four discharge gauging stations and a 1-year, monthly streamwater isotope record of 46 streams. The overall model performance for the best discharge simulations ranged in KGE values from 0.4 to 0.6 and correlation coefficients for streamflow isotopes from 0.3 to 0.45. More importantly, independent modelderived transpiration estimates, point-scale residence time estimates, and measured groundwater isotopes showed reasonable model performance and simulated spatial

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