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Modellering av volym samt max- och medeldjup i svenska sjöar: en statistisk analys med hjälp av geografiska informationssystem
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Institutionen för vatten och miljö, SLU.
2017 (Swedish)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesisAlternative title
Modeling volume, max- and mean-depth in Swedish lakes : a statistical analysis with geographical information systems (English)
Abstract [en]

Lake volume and lake depth are important variables that defines a lake and its ecosystem. Sweden has around 100 000 lakes, but only around 8000 lakes has measured data for volume, max- and mean-depth. To collect data for the rest of the lakes is presently too time consuming and expensive, therefore a predictive method is needed. Previous studies by Sobek et al. (2011) have found a model predicting lake volume from map-derived parameters with high degrees of explanation for mean volume of 15 lakes or more. However, the predictions for one individual lake, as well as max- and mean-depth, were not accurate enough. The purpose with this study was to derive better models based on new map material with higher resolution. Variables used was derived using GIS-based calculations and then analyzed with multivariate statistical analysis with PCA, PLS-regression and multiple linear regression. A model predicting lake volume for one individual lake with better accuracy than previous studies was found. The variables best explaining the variations in lake volume was lake area and the median slope of an individual zone around each lake (R2=0.87, p<0.00001). Also, the model predicting max-depth from lake area, median slope of an individual zone around each lake and height differences in the closest area surrounding each lake, had higher degrees of explanation than in previous studies (R2=0.42). The mean-depth had no significant correlation with map-derived parameters, but showed strong correlation with max-depth.

Reference

Sobek, S., Nisell, J. & Fölster J. (2011). Predicting the volume and depths of lakes from map-derived parameters. Inland Waters, vol. 1, ss. 177-184.

Place, publisher, year, edition, pages
2017. , p. 88
Series
UPTEC W, ISSN 1401-5765 ; 17023
Keywords [en]
Lake depth, lake volume, PCA, PLS-regression, GIS, multivariate analysis, multiple linear regression, SIMCA, Python.
Keywords [sv]
Maxdjup, sjövolym, medeldjup, PCA, PLS-regression, GIS, multivariat analys, mulitpel linjär regression, SIMCA, Python.
National Category
Engineering and Technology Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:uu:diva-325822OAI: oai:DiVA.org:uu-325822DiVA, id: diva2:1116949
Educational program
Master Programme in Environmental and Water Engineering
Supervisors
Examiners
Available from: 2017-06-28 Created: 2017-06-28 Last updated: 2017-06-28Bibliographically approved

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