Thesis (Ph.D. - Hydrology and Water Resources)--University of Arizona. / Includes bibliographical references (leaves 123-128).

The spatial distribution of snowpack in relation to snow water equivalent (SWE) and covered extent is highly variable in time both seasonally and interannually. In order to assess basin water resources, SWE must be distributed to areal estimates. This spatially distributed SWE connects the point scale to the larger scale of the basin (i.e. macro-scale), requiring a combination approach of statistical interpolation techniques and snowpack extent constraint from remote sensing. This research connects those multiple spatial scales and applies the combined remote sensing and ground-based SWE products in a hydrologic model setting to aid in improving streamflow forecasting in the mountainous terrain of snowmelt-dominated basins, a current modeling gap. Four specific advancements were achieved: 1) a comprehensive assessment of spatial distribution techniques in interpolating point snow water equivalent (SWE) measurements at snow telemetry (SNOTEL) stations to the macro-scale was made and an optimal technique for distributing SWE on this scale was obtained; 2) differences between two major data sources of SWE (SNOTEL and snowcourse) were quantified for both point-scale variability and interpolated macro-scale variability to determine spatial and temporal differences in data sources for dry, average and wet years to better inform water resources management applications; 3) basin-scale estimates of ground-based SWE and snow covered area (SCA) from remote sensing were evaluated relative to equivalent fields calculated by a hydrologic model and the effect of assimilating the remote sensing products into the model were investigated; and 4) in the context of (3), improvements were made in macro-scale SCA estimates through both a canopy correction and a low pass statistical filter in an effort to correct for the relatively low resolution of remotely sensed estimates.

This thesis describes the comparison of time-lapse field observations of suncups on alpine snow with numerical simulations. The simulations consist of solutions to a nonlinear partial differential equation which exhibits spontaneous pattern formation from a low amplitude, random initial surface. Both the field observations and the numerical solutions are found to saturate at a characteristic height and fluctuate chaotically with time. The timescale of these fluctuations is found to be instrumental in determining the full set of parameters for the numerical model such that it mimics the nonlinear dynamics of suncups. These parameters in turn are related to the change in albedo of the snow surface caused by the presence of suncups. This suggests the more general importance of dynamical behaviour in gaining an understanding of pattern formation phenomena.

This thesis describes the comparison of time-lapse field observations of suncups on alpine snow with numerical simulations. The simulations consist of solutions to a nonlinear partial differential equation which exhibits spontaneous pattern formation from a low amplitude, random initial surface. Both the field observations and the numerical solutions are found to saturate at a characteristic height and fluctuate chaotically with time. The timescale of these fluctuations is found to be instrumental in determining the full set of parameters for the numerical model such that it mimics the nonlinear dynamics of suncups. These parameters in turn are related to the change in albedo of the snow surface caused by the presence of suncups. This suggests the more general importance of dynamical behaviour in gaining an understanding of pattern formation phenomena.

This thesis describes the comparison of time-lapse field observations of suncups on alpine snow with numerical simulations. The simulations consist of solutions to a nonlinear partial differential equation which exhibits spontaneous pattern formation from a low amplitude, random initial surface. Both the field observations and the numerical solutions are found to saturate at a characteristic height and fluctuate chaotically with time. The timescale of these fluctuations is found to be instrumental in determining the full set of parameters for the numerical model such that it mimics the nonlinear dynamics of suncups. These parameters in turn are related to the change in albedo of the snow surface caused by the presence of suncups. This suggests the more general importance of dynamical behaviour in gaining an understanding of pattern formation phenomena. / Science, Faculty of / Physics and Astronomy, Department of / Graduate

We used demographic methods to address one of the main challenges facing ecological science: forecasting the effect of climate change on plant communities. Ecological forecasts will be crucial to inform long-term planning in wildland management and demographic methods are ideal to quantify changes in plant abundance. We carried out our research in the sagebrush steppe, one of the most extensive plant ecosystems of Western North America. Our research intended to inform ecological forecasts on an exotic invader, cheatgrass (Bromus tectorum). Moreover, we investigated the general question asking: to what degree competition among plants influences the outcome of ecological forecasts on the effect of climate change? We carried out two field experiments to test the hypothesis that warming will increase cheatgrass abundance in the sagebrush steppe. This hypothesis was strongly supported by both experiments. Warming increased cheatgrass abundance regardless of elevation, neighboring vegetation or cheatgrass genotype. Moreover, we found cheatgrass was hindered by snow cover. Therefore, warming increases cheatgrass growth directly by increasing temperature, and indirectly by decreasing or removing snow cover. In our last experiment, we tested whether forecasts of climate change effects on rare species can ignore competition from neighbors. This should occur because rare species should have little niche overlap with other species. The lower the niche overlap, the less competition with other species. To test this hypothesis, we used a long-term data set from an Idaho sagebrush steppe. We built population models that reproduced the dynamics of the system by simulating climate and competition. Model simulations supported our hypothesis: rare species have little niche overlap and little competitive interactions with neighbor species.

The representation of high-latitude surface processes and quantifying surface-climate feedbacks are some of the most serious shortcomings of present day Arctic land surface modelling. The energy balance of seasonally snow-covered sparse deciduous forests at high latitudes is poorly understood and inaccurately represented within hydrological and climate models. Snow cover plays an important role in wintertime fluxes of energy, water and carbon, controlling the length of the active growing season and hence the overall carbon balance of Arctic ecosystems. Snow cover is non-uniform and spatially variable, as wind redistributes snow from areas of exposed open tundra to sheltered areas within the forest, where a deeper snowpack develops. Low solar zenith angles, coupled with sparse deciduous leafless trees, cast shadows across the snow surface. The spatial distribution of canopy gaps determines the timing of direct radiation which penetrates down through the canopy to the snow surface. The forest canopy also excludes incoming longwave radiation and yet also emits longwave radiation to the snow surface. Consequently the forest canopy plays a key role in the radiation balance of sparse forests. To improve our knowledge of these complex processes, meteorological and field observations were taken in an area of highly heterogeneous birch Betula pubescens ssp. czerepanovii forest in Abisko, Sweden during the spring of 2008 and 2009. Detailed measurements of short and longwave radiation above and below the canopy, hemispherical photographs, tree temperatures and snow surveys were conducted to quantify the radiation balance of the sparse deciduous forest. An array of below canopy pyranometers found the mean canopy transmissivity to be 74 % in 2008 and 76 % in 2009. Hemispherical photographs taken at the pyranometer locations analysed with Gap Light Analyzer (GLA) showed reasonable agreement with a mean canopy transmissivity of 75 % in 2008 and 74 % in 2009. The canopy transmissivity was found to be independent of the diffuse fraction of radiation as the canopy is very sparse. A series of survey grids and transects were established to scale up from the below canopy pyranometers to the landscape scale. Hemispherical photographs analysed with GLA showed the sparse forest canopy had a mean transmissivity of 78 % and a mean LAI of 0.25, whereas the open tundra had a mean transmissivity of 97 % and a mean LAI of < 0.01. Snow surveys showed the sparse forest snow depth to vary between 0.34 and 0.55 m, whereas the snow depth in the open tundra varied between 0.12 and 0.18 m. Observations of canopy temperatures showed a strong influence of incident shortwave radiation warming the tree branches to temperatures up to 15 °C warmer than ambient air temperature on the south facing sides of the trees, and up to 6 °C on the north facing sides of the trees. To reproduce the observed radiation balance, two canopy models (Homogenous and Clumped) were developed. The Homogeneous canopy model assumes a single tree tile with a uniform sparse canopy. The Clumped canopy model assumes a tree and a grass tile, where the tree tile is permanently in shade from the canopy and the grass tile receives all the incoming radiation. These canopy models identified the need for a parameter that accounts for the spatial and temporal variation of the shaded gaps within the sparse forest. JULES (Joint UK Land Environment Simulator) is the community land surface model used in the UK Hadley Centre GCM suite. Modifications of the land-surface interactions were included in JULES to represent the shaded gaps within the sparse deciduous forest. New parameterisations were developed for the time-varying sunlit fractions of the gap (flit), the sky-view fraction (fv), and the longwave radiation emitted from the canopy (LWtree). These model developments were informed by field observations of the forest canopy and evaluated against the below canopy short and longwave radiation observed data sets. The JULES Shaded gap model output showed a strong positive relationship with the observations of below canopy shortwave and longwave radiation. The JULES Shaded gap model improves the ratio of observed to modelled short and longwave radiation on sunny days compared to the JULES model. The JULES Shaded gap model reduces the time to snow melt by 2 to 4 days compared to the JULES model, making the model output more aligned with in-situ observational data. This shortening of the modelled snow-season directly impacts on the simulated carbon and water balance regionally and has wider relevance at the pan-Arctic scale. When JULES Shaded Gap was evaluated on the global scale, it improved the modelled snowmass across large areas of sparse forest in northern Canada, Scandinavia and Northern Russia with respect to GlobSnow. The performance of the land surface-snow-vegetation interactions of JULES was improved by using the Shaded gap to model the radiation balance of sparse forests in climate-sensitive Arctic regions. Furthermore these observational data can be used to develop and evaluate high latitude land-surface processes and biogeochemical feedbacks in other earth system models.

From the Proceedings of the 1975 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 11-12, 1975, Tempe, Arizona / The quantification of snowpacks in relation to inventory-prediction may be useful in the development of water yield improvement practices involving vegetation management in the mixed conifer forests in Arizona. While mixed conifer forests are relatively limited in extent in Arizona, the potential for water yield improvement by manipulation of snow storage through vegetation management may be high. Sample points on the north fork of Thomas Creek showed high initial snow storage followed by slow melt in association with low forest densities, low potential insolation values, and high elevation. Sample points exhibiting these conditions also possessed maximum storage-duration index values. Low initial snow storage followed by rapid melt was associated with high forest densities, high potential insolation values, and low elevations