ASU Scholarship Showcase

Potential climate change impacts on summer precipitation and subsequent hydrologic responses in the southwestern U.S. are poorly constrained at present due to a lack of studies accounting for high resolution processes. In this investigation, we apply a distributed hydrologic model to the Beaver Creek watershed of central Arizona to explore its utility for climate change assessments. Manual model calibration and model validation were performed using radar-based precipitation data during three summers and compared to two alternative meteorological products to illustrate the sensitivity of the streamflow response. Using the calibrated and validated model, we investigated the watershed response during historical (1990–2000) and future (2031–2040) summer projections derived from a single realization of a mesoscale model forced with boundary conditions from a general circulation model under a high emissions scenario. Results indicate spatially-averaged changes across the two projections: an increase in air temperature of 1.2 °C, a 2.4-fold increase in precipitation amount and a 3-fold increase in variability, and a 3.1-fold increase in streamflow amount and a 5.1-fold increase in variability. Nevertheless, relatively minor changes were obtained in spatially-averaged evapotranspiration. To explain this, we used the simulated hydroclimatological mechanisms to identify that higher precipitation limits radiation through cloud cover leading to lower evapotranspiration in regions with orographic effects. This challenges conventional wisdom on evapotranspiration trends and suggest that a more nuanced approach is needed to communicate hydrologic vulnerability to stakeholders and decision-makers in this semiarid region.

Although previous research has studied power in mediation models, the extent to which the inclusion of a mediator will increase power has not been investigated. To address this deficit, in a first study we compared the analytical power values of the mediated effect and the total effect in a single-mediator model, to identify the situations in which the inclusion of one mediator increased statistical power. The results from this first study indicated that including a mediator increased statistical power in small samples with large coefficients and in large samples with small coefficients, and when coefficients were nonzero and equal across models. Next, we identified conditions under which power was greater for the test of the total mediated effect than for the test of the total effect in the parallel two-mediator model. These results indicated that including two mediators increased power in small samples with large coefficients and in large samples with small coefficients, the same pattern of results that had been found in the first study. Finally, we assessed the analytical power for a sequential (three-path) two-mediator model and compared the power to detect the three-path mediated effect to the power to detect both the test of the total effect and the test of the mediated effect for the single-mediator model. The results indicated that the three-path mediated effect had more power than the mediated effect from the single-mediator model and the test of the total effect. Practical implications of these results for researchers are then discussed.

Porous carbon nanospheres prepared using spray pyrolysis were evaluated as adsorbents for removal of arsenate and selenate in de-ionized (DI), canal, and well waters. The carbon nanospheres displayed good binding to both metals in DI water and outperformed commercial activated carbons for arsenate removal in pH > 8, likely due to the presence of basic surface functional groups, high surface-to-volume ratio, and suitable micropores formed during the synthesis.