[1] We investigate the observed positive trends in annual runoff in several basins in central Nebraska using the Budyko hypothesis as a diagnostic tool. In basins where runoff is dominated by base flow we found that the estimated annual evapotranspiration (ET a ) to precipitation (P) ratio (ET a /P) from data is negatively related to the aridity index (ET p /P, where ET p is potential annual evapotranspiration). This observation is inconsistent with the Budyko hypothesis. We hypothesized that the observed negative trend results from significant interannual changes in basin water storage. This hypothesis is tested using data from groundwater monitoring wells in the Sand Hills region of Nebraska. Plots of the yearly changes in groundwater storage versus the annual aridity index revealed the mean annual aridity index as a critical climatological variable that controls basin storage gain-loss dynamics. For the same absolute deviation from the mean climate, we found that a wetter year leads to a larger gain in groundwater storage than the net loss in a drier year. We argue that this storage gain-loss behavior builds a climate memory in the hydrologic system, causing persistence and statistically significant trends in annual runoff. A parsimonious model was developed that couples the Budyko hypothesis with a linear reservoir equation for base flow and was used to examine the possible causes of observed positive trends of annual runoff. We found that subtle, statistically insignificant, increases in annual P have led to positive and statistically insignificant trends in annual ET a and P À ET a . Annual runoff, on the other hand, was predicted to have high persistence and statistical significance, consistent with observations. Further model sensitivity analyses showed that increasing the size of the groundwater reservoir is associated with increased long-term (multidecadal) persistence in annual runoff and translates high-frequency, high-amplitude variation in climate to low-frequency, low-amplitude runoff response. Our results underscore the importance of evaluating apparent trends in any system variable in a complete water budget context.

In this study, we developed the urban ecohydrology model (UEM) to investigate the role of bioretention on watershed water balance, runoff production, and streamflow variability. UEM partitions the land surface into pervious, impervious, and bioretention cell fractions. Soil moisture and vegetation dynamics are simulated in pervious areas and bioretention cells using a lumped ecohydrological approach.Bioretention cells receive runoff from a fraction of impervious areas. The model is calibrated in an urban headwater catchment near Seattle, WA, USA, using hourly weather data and streamflow observations for 3 years. The calibrated model is first used to investigate the relationship between streamflow variability and bioretention cell size that receives runoff from different values of impervious area in the watershed. Streamflow variability is quantified by 2 indices, high pulse count (HPC), which quantifies the number of flow high pulses in a water year above a threshold, and high pulse range (HPR), which defines the time over which the pulses occurred. Low values of these indices are associated with improved stream health. The effectiveness of the modelled bioretention facilities are measured by their influence on reducing HPC and HPR and on flow duration curves in comparison with modelled fully forested conditions. We used UEM to examine the effectiveness of bioretention cells under rainfall regimes that are wetter and drier than the study area in an effort to understand linkages between the degree of urbanization, climate, and design bioretention cell size to improve inferred stream health conditions. In all model simulations, limits to the reduction of HPC and HPR indicators were reached as the size of bioretention cells grew. Bioretention was more effective as the rainfall regime gets drier. Results may guide bioretention design practices and future studies to explore climate change impacts on bioretention design and management.