and-atmosphere interactions are an important component of climate, especially in semi-arid regions such as the Southern Great Plains. Interactions between soil moisture and vegetation modulate land-atmosphere coupling and thus represent a crucial, but not well understood climate factor. This study examines soil moisture-vegetation health interactions using both in situ observations and land surface model simulations. For the observational study, soil moisture is taken from 20 in situ Oklahoma Mesonet soil moisture observation sites, and vegetation health is represented by MODIS-derived normalized difference vegetation index (NDVI). For the modeling study, the variable infiltration capacity (VIC) hydrologic model is employed with two different vegetation parameterizations. The first is the model default vegetation parameter which is interannually-invariant leaf area index (LAI). This parameter is referred to as the control parameter. The second is MODIS-derived LAI, which captures interannual differences in vegetation health. Soil moisture simulations from both vegetation parameterizations are compared and the VIC-simulated soil moisture’s sensitivity to the vegetation parameters is also examined. Correlation results from the observation study suggest that soil moisture-vegetation interactions in Oklahoma are inconsistent, varying both in space and time. The modeling results show that using a vegetation parameterization that does not capture interannual vegetation health variability could potentially result in dry or wet biased soil moisture simulations.

Thesis (Ph. D.)--University of Melbourne, 1987. / Typescript (photocopy). Includes bibliographical references (leaves [10-16] (2nd group)).

Thesis (M.Sc.)--University of Melbourne, Dept. of Science, 1974. / Typescript (roneo copy). Includes bibliographical references (leaves 104-105).

Thesis (M.Sc.)--University of Melbourne, 1992. / Typescript (photocopy). Bibliography: leaves 110-115.

Thesis (Ph.D.)--University of Melbourne, Dept. of Zoology, 2009. / Typescript. Includes bibliographical references (p. 108-119)

Water managers for the City of Phoenix face the need to make informed policy decisions regarding long-term impacts of climate change on the Salt-Verde River basin. To provide a scientifically informed basis for this, we estimate the evolution of important components of the basin-scale water balance through the end of the 21st century. Bias-corrected and spatially downscaled climate projections from the Phase-3 Coupled Model Intercomparison Project of the World Climate Research Programme were used to drive a spatially distributed variable infiltration capacity model of the hydrologic processes in the Salt-Verde basin. From the many Global Climate Model's participating in the IPCC fourth assessment, we selected a five-model ensemble, including three that best reproduce the historical climatology for our study region, plus two others to represent wetter and drier than model average conditions; the latter two were requested by City of Phoenix water managers to more fully represent the full range of GCM prediction uncertainty. For each GCM, data for three emission scenarios (A1B, A2, B1) was used to drive the hydrologic model into the future. The model projections indicate a statistically significant 25% decrease in streamflow by the end of the 21st century. Contrary to previous assessments, this is not caused primarily by changes in the P/E ratio, but is found to result mainly from decreased winter precipitation accompanied by significant (temperature driven) reductions in storage of snow. The results show clearly the manner in which water management in central Arizona is likely to be impacted by changes in regional climate.

Groundwater is a major source of water in the western US. However, there are limited recharge estimates in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01% to 15% for Mosaic, 3.2% to 42% for Noah, and 6.7% to 31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge in data limited regions.

Abstract not available

Thesis (M. Med.)--University of Melbourne, 1996. / Typescript (photocopy). Includes bibliographical references.

Thesis (Ph.D.)--University of Melbourne, Dept. of History, 1999. / Author's name on cover: C. Day. Typescript (photocopy). Includes bibliographical references (leaves 409-418).