Application of snow distribution models within the laguna Negra basin, Chile
| dc.contributor.author | Cadle, Brad J. | |
| dc.contributor.author | Bales, Roger C. | |
| dc.date.accessioned | 2016-07-07T23:49:57Z | |
| dc.date.available | 2016-07-07T23:49:57Z | |
| dc.date.issued | 1997-08 | |
| dc.identifier.uri | http://hdl.handle.net/10150/615753 | |
| dc.description.abstract | Spectral linear unmixing and binary regression trees were used to estimate the distribution of snow within the Laguna Negra basin in Chile. Spectral linear unmixing was performed for multi-band Landsat 5 images for the determination of sub-pixel snow fractions. We were interested in determining the number of bands needed for an adequate distribution of SCA. Results showed that for winter scenes (scenes with greater than 90% snow cover and portions of the basin covered by shadows) linear spectral unmixing can be used to model SCA using at least four bands with a rock, a snow and a shaded snow endmember, but that five bands, using two rock endmembers, a snow and a shaded rock endmember, are needed for the fall scenes (scenes with less than 10% snow cover and portions of the basin covered by shadows). The spring scenes (scenes with 50 percent and higher snow cover and no shadows) showed plausible results with three bands, but the need for a second rock endmember in the fall scenes suggest 4 bands may give a more accurate result. A binary regression tree model was used to determine distributed SWE at peak accumulation in the Echaurren basin, a sub basin of Laguna Negra. Regression trees grown from field snow survey data did an excellent job at explaining the variation of SWE in two of the three surveys examined when resubstitution was used to evaluate the model, but did a poor job in all cases when cross validation was used. However, cross validation may over estimate the errors associated with the model. Basin-wide SWE maps resulting from the application of the regression trees formed plausible structures. Normalized snow distribution was sufficiently different between years such that a "typical" SWE map could not be developed. Nonetheless, there were identifiable patterns that did occur in the SWE distributions from different years that gave insight into the factors affecting SWE in the basin. Such factors include a strong dependance on radiation in the lower portion of Echaurren for two of the years, and the presence of heavy SWE regions near cliffs. Insights such as these provided useful information on how the type of data and method of collection might be improved. The large SWE values near cliffs, for instance, suggest that use of an avalanche map might improve the modeled SWE distribution. The dependance of SWE on radiation in the lower basin suggest the SWE data should be obtained over the entire range of radiation values in the lower basin. | |
| dc.description.sponsorship | I wish to thank Dr. Don Davis for the help he gave me in the use of statistics in analyzing the results of the regression tree based SWE models. He also gave me plenty of ideas on alternative ways of using the model. I only wish I had time to try them all. Second, I wish to thank Dr. Kelly Elder for his advise on the use of his regression tree based SWE models on the Echaurren basin data sets. He provided good input even while recuperating from knee surgery. Third, Walter Rosenthal for the immense time spent on explaining to me the nuances of linear spectral unmixing of Landsat 5 images. I must have spent a sum total of several hours on the phone and many more by e-mail prodding him for information on the method. Fourth, Robert Harrington for essential information on the site conditions at Echaurren and Laguna Negra. His personal experience in the field was a necessary component to interpreting many of the results I got from the models. I also appreciate the guidance he gave me in the use of Grass 4.1 when I began working for Roger. Fifth, Ray Brice for his help with Shell and Awk programming. Also for the bike he sold me for $20. I never did get around to using it, however. Sixth, Justin Rohrbough for his excellent job at proof reading large portions of my thesis. I wish my grammar was as good as his. Of course, I can't forget the immense support of my wife, Fatima, while I was working on finishing my thesis. She was a constant source of encouragement for me. I also wish to thank my parents for their moral and financial support of my education throughout my college years both as an undergraduate and graduate student. Also for their time and caring while raising me. | en |
| dc.language.iso | en_US | en |
| dc.publisher | Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ) | en |
| dc.relation.ispartofseries | Technical Reports on Hydrology and Water Resources, No. 97-090 | en |
| dc.rights | Copyright © Arizona Board of Regents | en |
| dc.source | Provided by the Department of Hydrology and Water Resources. | en |
| dc.title | Application of snow distribution models within the laguna Negra basin, Chile | en_US |
| dc.type | text | en |
| dc.type | Technical Report | en |
| dc.contributor.department | Department of Hydrology & Water Resources, The University of Arizona | en |
| dc.description.collectioninformation | This title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu. | en |
| refterms.dateFOA | 2018-06-11T21:34:38Z | |
| html.description.abstract | Spectral linear unmixing and binary regression trees were used to estimate the distribution of snow within the Laguna Negra basin in Chile. Spectral linear unmixing was performed for multi-band Landsat 5 images for the determination of sub-pixel snow fractions. We were interested in determining the number of bands needed for an adequate distribution of SCA. Results showed that for winter scenes (scenes with greater than 90% snow cover and portions of the basin covered by shadows) linear spectral unmixing can be used to model SCA using at least four bands with a rock, a snow and a shaded snow endmember, but that five bands, using two rock endmembers, a snow and a shaded rock endmember, are needed for the fall scenes (scenes with less than 10% snow cover and portions of the basin covered by shadows). The spring scenes (scenes with 50 percent and higher snow cover and no shadows) showed plausible results with three bands, but the need for a second rock endmember in the fall scenes suggest 4 bands may give a more accurate result. A binary regression tree model was used to determine distributed SWE at peak accumulation in the Echaurren basin, a sub basin of Laguna Negra. Regression trees grown from field snow survey data did an excellent job at explaining the variation of SWE in two of the three surveys examined when resubstitution was used to evaluate the model, but did a poor job in all cases when cross validation was used. However, cross validation may over estimate the errors associated with the model. Basin-wide SWE maps resulting from the application of the regression trees formed plausible structures. Normalized snow distribution was sufficiently different between years such that a "typical" SWE map could not be developed. Nonetheless, there were identifiable patterns that did occur in the SWE distributions from different years that gave insight into the factors affecting SWE in the basin. Such factors include a strong dependance on radiation in the lower portion of Echaurren for two of the years, and the presence of heavy SWE regions near cliffs. Insights such as these provided useful information on how the type of data and method of collection might be improved. The large SWE values near cliffs, for instance, suggest that use of an avalanche map might improve the modeled SWE distribution. The dependance of SWE on radiation in the lower basin suggest the SWE data should be obtained over the entire range of radiation values in the lower basin. |
