[1] An accurate description of plant ecology requires an understanding of the interplay between precipitation, infiltration, and evapotranspiration. A simple model for soil moisture dynamics, which does not resolve spatial variations in saturation, facilitates analytical expressions of soil and plant behavior as functions of climate, soil, and vegetation characteristics. Proper application of such a model requires knowledge of the conditions under which the underlying simplifications are appropriate. To address this issue, we compare predictions of evapotranspiration and root zone saturation over a growing season from a simple bucket-filling model to those from a more complex, vertically resolved model. Dimensionless groups of key parameters measure the quality of the match between the models. For a climate, soil, and woody plant characteristic of an African savanna the predictions of the two models are quite similar if the plant can extract water from locally wet regions to make up for roots in dry portions of the soil column; if not, the match is poor.

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[1] The depth of the active root zone identifies the portion of the subsurface that exchanges soil water with the atmosphere. The depth of this zone is determined by a number of factors, and this work focuses on the drivers related to water and climate. An analytical expression for a water-optimal root depth is developed by equating the marginal carbon cost and benefit of deeper roots. Soil-moisture dynamics are driven by stochastic rainfall, and the predicted root depth is a function climate, soil, and vegetation characteristics. Consistent with results from the field, deep roots coincide with environments for which precipitation and potential evapotranspiration are approximately equal. For water-limited ecosystems, increases in the wetness of the climate produce deeper roots, and root depth is more sensitive to changes in the depth of rain events than to their frequency. In wet environments, the opposite is true; root depth generally decreases with increasing wetness and shows greater sensitivity to changes in rainfall frequency than intensity.

[1] The lower Colorado River (LCR) near Austin, Texas is heavily regulated for hydropower generation. Daily water releases from a dam located 23 km upstream of our study site in the LCR caused the stage to fluctuate by more than 1.5 m about a mean depth of 1.3 m. As a result, the river switches from gaining to losing over a dam storage-release cycle, driving exchange between river water and groundwater. We assessed the hydrologic impacts of this by simultaneous temperature and head monitoring across a bed-to-bank transect. River-groundwater exchange flux is largest close to the bank and decreases away from the bank. Correspondingly, both the depth of the hyporheic zone and the exchange time are largest close to the bank. Adjacent to the bank, the streambed head response is hysteretic, with the hysteresis disappearing with distance from the bank, indicating that transient bank storage affects the magnitude and direction of vertical exchange close to the bank. Pronounced changes in streambed temperature are observed down to a meter. When the river stage is high, which coincides with when the river is coldest, downward advection of heat from a previous cycles' warm-water pulse warms the streambed. When the river is at its lowest stage but warmest temperature, upwelling groundwater cools the streambed. Future research should consider and focus on a more thorough understanding of the impacts of dam regulation on the hydrologic, thermal, biogeochemical, and ecologic dynamics of rivers and their hyporheic and riparian zones.

Ecosystem characteristics and processes provide significant value to human health and wellbeing, and there is growing interest in quantifying those values. Of particular interest are water-related ecosystem services and the incorporation of their value into local and regional decision making. This presents multiple challenges and opportunities to the hydrologic-modeling community. To motivate advances in water-resources research, we first present three common decision contexts that draw upon an ecosystemservice framework: scenario analysis, payments for watershed services, and spatial planning. Within these contexts, we highlight the particular challenges to hydrologic modeling, and then present a set of opportunities that arise from ecosystem-service decisions. The paper concludes with a set of recommendations regarding how we can prioritize our work to support decisions based on ecosystem-service valuation.