Thesis (Ph. D. - Watershed Management)--University of Arizona. / Includes bibliographical references.

Thesis (M.S.)--Montana State University--Bozeman, 2004. / Typescript. Chairperson, Graduate Committee: Edward E. Adams. Includes bibliographical references (leaves 176-181).

No description available.

Thesis (M.S.)--Oregon State University, 2006. / Printout. Includes bibliographical references. Also available on the World Wide Web.

Inventory-prediction equations describing snowpack water content as functions of readily available or easily obtained inventory variables were developed for use in the ponderosa pine type in Arizona. Although empirical in nature, these equations include parameters assumed to index interception of precipitation inputs, obstruction of direct beam solar radiation, and re-radiation from trees onto the snowpack. Primary consideration was given to forest cover variables in synthesizing the inventory-prediction equations I because currently proposed water improvement programs designed to increase water yield derived from snow consist essentially of vegetative manipulations. Additional independent variables evaluated include potential direct beam solar radiation, elevation, soil, and precipitation inputs. All of the inventory-prediction equations describing a particular snowpack condition were not statistically equivalent in terms of the standard error of estimate or the coefficient of determination. Equations including basal area, bole area I volume, and height-index as expressions of forest cover density were generally better than equations with point density, sum of diameters, and number of trees. Inventory-prediction equations developed to describe snowpack dynamics throughout the accumulation period showed similar statistical form, except as possibly attributable to different precipitation inputs. Equations for characterizing residual snowpacks during spring runoff were statistically weak, possibly because factors other than those considered in this study control the runoff process. The inventory-prediction equations were developed to estimate the mean snowpack water content on a basin, and to describe the trade-off , or the rate of exchange, between snowpack water content and forest-site variables on a decision-making unit. The equations do not necessarily predict changes in recoverable water yield resulting from the implementation of a land management system, however. Nonbiotic characteristics of the land, L e., topographic features, geologic formations, and soil . properties, could conceivably control water yield to the extent that changes predicted by the inventory-prediction equations could be masked. Because of limitations in predicting potential changes in recoverable water yield, it was assumed that a land management system that maximizes snowpack water content on site would also provide the maximum potential for increasing recoverable water yield derived from snow. Management guidelines designed to allow snowpack water content to be maximized on site can be formulated within the framework of the inventory-prediction equations, multiple use management constraints, and forest-based product benefits and costs. Management guidelines indicate that the greatest gain in snowpack water content on site would be realized on decision-making units where the greatest reduction in forest cover density could be prescribed. However, a timber production constraint may limit the array of management possibilities. This constraint was defined as 35 to 40 square feet of basal area or 1,050 to 1,175 cubic feet of volume per acre, depending upon the existing growth percent and the intermingling of tree volumes and size classes. The potential increase in snowpack water content on site will be determined by the magnitude of the reduction in forest cover density and how close management re-direction can approach the timber production constraint. The proportion of the snowpack water content on site converted to recoverable water yield is dependent upon the runoff efficiency.

No description available.

The objective of this research is to map snow cover in the Quebec area using passive microwave and other remote sensing data. The areal snow extent and snow water equivalent are determined and a twelve year snow water equivalent map is produced for the purpose of analyzing interannual snow variability. / The presence of vegetation cover will affect the data obtained with passive systems. For heavily vegetated areas such as Quebec, the vegetation effect should be predetermined and classified to reduce the error on snow water equivalence calculation. / In dry snow conditions, forest coverage and snow density are the two major error parameters in passive microwave snow mapping. The error on snow water equivalence estimation is directly proportional to the error in estimated snow density and forest coverage. For Quebec, ignoring the fraction of the forest cover may cause up to 49% snow depth or water equivalence underestimation. / The ground measured snow depth and snow density data are necessary for calibrating satellite derived snow depth and mean snow density within forest covered regions.

No description available.

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 possibility of using imagery from the earth resources technology satellites (ERTS) to monitor changes in areal snow cover in east-central Arizona is examined. Four methods were used in the interpretation of areal snow cover from the ERTS imagery, the densitometer, dot grid, squares grid and projection-planimeter methods providing results of 69, 71, 72 and 74 percent of areal cover respectively. No one method for interpretation of ERTS imagery should be ruled unusable, but any use made of ERTS imagery is dependent upon turn-around time for obtaining the imagery, as snow cover information which cannot be obtained within 24 hours is limited in practical application.