An investigation into modeling snow cover elements at Crater Lake National Park and surrounding environs as an improved "ground truth" method for satellite snow observations Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/b2773z110

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  • Streamflow forecasts are essential to the optimal operation of hydroelectric and irrigation reservoirs in the Pacific Northwest. Satellite snow cover observations would aid in these streamflow forecasts by providing snow cover data at regular time intervals. Unfortunately, satellite capability to remotely sense mountain snow cover conditions is indeterminate due to lack of "ground truth." This study focuses on the development of a mountain snow cover model capable of generating snow cover data at a scale useful as "ground truth" for operational satellite snow cover observations. The study area used to develop the snow cover model was Crater Lake National Park and its surrounding environs. Both the physiography (topography and vegetation) and snow climate of the study area were analyzed and found to be quite dynamic. In order to take into account the affects of the dynamic snow climate and physiography upon snow cover conditions, multiple regression analysis was used to create the Crater Lake Snow Model. Forty-five snow core sites were located within the study area. Snow depth and snow water equivalent values were recorded at each site. Eighteen sites located within Crater Lake National Park were sampled on a weekly basis for the 1977-1978 snow year. An additional 16 sites were sampled at high elevations in the Park on a weekly basis from April through June, 1978. The remaining 11 sites comprised the historical snow core data set collected by Soil Conservation Service (S.C.S.) on a monthly basis, January through June, 1948 through 1978. These data sets were statistically reduced using the quasi-constant ratio theory to synthesize values for missing data to temporally unify the data sets. Also the physiographic elements of slope, aspect, elevation, percentage of forest canopy cover, and regional aspect were recorded for each snow core site. The physiographic elements (independent variables) were regressed against the snow core data (dependent variables) to produce snow model equations. Three different Temporal-Spatial Situations (T.S.S. 1, 2, 3) of data were entered into regression analysis. T.S.S. 1 and 2 models were generated from the 11 S.C.S. snow core sites, T.S.S. 1 from 1978 data and T.S.S. 2 for 1948 -1978 data. The T.S.S. 3 model was generated from the 45 snow core site data for 1978. Using the theory of the quasiconstant ratio it was possible to combine the T.S.S. 1, 2, and 3 sets of regression equations to produce a T.S.S. 4 snow model ( a model based upon the 45 sites for the 1948-1978 snow seasons). Subsequently the T.S.S. 1 and 2 snow models were utilized with this derived T.S.S. 4 snow model to produce T.S.S. 3 snow cover models for any month of any year for the 1948 through 1978 period. Validity testing of the model indicates that it has an average error of ± 15.7" for modeled snow depth values and ± 8.2" for modeled snow water equivalent values. The Crater Lake Snow Model has a combined spatial, annual, and long term resolution unequaled in previous snow cover models. The Model's combined high resolving properties give it capabilities of generating mountain snow cover "ground truth." Current studies are being conducted to couple dynamic snow meteorology and LANDSAT digital data to the Model to increase its accuracy and reduce its dependency on snow core data. Also, output of the Model can be used for studies on snow cover affect upon wildlife movement and survival and the determination of source regions of relative runoff from snow melt.
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