Estimation models for precipitation in mountainous regions: the use of GIS and multivariate analysis
2003
Marquinez, J. | Lastra, J. | García, P.
Using multiple linear regression and Geographic Information System techniques, we modelled the spatial distribution of mean monthly precipitation for the seasonal and annual periods in a mountainous region of 10,590 km2, located in the central area of the Cantabrian Coast, Spain. We used precipitation data measured at 117 stations for the period 1966-1990, using 84 stations for function development and reserving 33 for validation tests. The best model developed used five topographic descriptors as independent variables: elevation, distance from the coastline, distance from the west, and a measurement of elevation and slope means into homogeneous areas. These topographic variables were calculated as raster models with 200 m resolution. The model accounted for most of the spatial variability in mean precipitation, with an adjusted R2 between 0.58 and 0.67. The standard error was approximately 10% and the mean absolute error ranged from 8.1 to 26.1 mm, which represented 13-19% of observed precipitation. Regression enabled us to estimate precipitation in areas where there are no nearby stations and where topography has a major influence on the precipitation.
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