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Material for 'Statistical-Topographical Mapping of Rainfall Over Mountainous Terrain Using Beta Scaling'
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| Type: | Resource | |
| Storage: | The size of this resource is 1.9 GB | |
| Created: | Apr 07, 2023 at 4 p.m. | |
| Last updated: | Apr 25, 2023 at 12:32 p.m. (Metadata update) | |
| Published date: | Apr 25, 2023 at 12:32 p.m. | |
| DOI: | 10.4211/hs.fa0007d553ae4c8682dd9c464e91913d | |
| Citation: | See how to cite this resource | |
| Content types: | Single File Content Geographic Feature Content Multidimensional Content Geographic Raster Content |
| Sharing Status: | Published |
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| Views: | 701 |
| Downloads: | 28 |
| +1 Votes: | 1 other +1 this |
| Comments: | No comments (yet) |
Abstract
This resource belongs to the manuscript "Statistical-Topographical Mapping of Rainfall Over Mountainous Terrain Using Beta Scaling". It collects the R code and the data needed to reproduce the analyses and generate the figures.
We present a robust approach for quantitative precipitation estimation (QPE) for water resources management in mountainous catchments, where rainfall sums and variability are correlated with orographic elevation, but density of rain gauges does not allow for advanced geostatistical interpolation of rainfall fields.
Key of the method is modelling rainfall at unobserved locations by their elevation-dependent expected daily mean, and a daily fluctuation which is determined by spatial interpolation of the residuals of neighbouring rain gauges, which are scaled according to the elevation difference. The scaling factor is defined as the ratio of covariance and variance, in analogy to the "beta" used in economics.
The approach is illustrated for the Chirilu catchments (Chillón, Rímac, Lurín) in the Andes near Lima, Peru. The results are compared to conventional IDW interpolation and a merged national rainfall product. The method results in QPE that are better matching with observed discharges. The β-IDW approach thus provides a robust and flexible means to estimate rainfall input to mesoscale mountainous catchments.
Subject Keywords
Coverage
Spatial
Temporal
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Content
README.md
betaIDW
Material for the paper of Wienhoefer, Alcamo, Bondy & Zehe, submitted to Water Resources Research
(c) 2023 Jan Wienhoefer
Usage
The analyses were done using the R programming environment.
Copy the files and subdirectories into a working directory on your computer.
Folder structure
/data/
/figs/
/R/
/R/functions
/runs
Open and run the script "main.r" at the root level of the resource. In default form, the analyses and figures are reproduced using existing data from the folder "/runs". To reproduce the calculations, set "make.calculations = TRUE" before executing the respective part from the main script. Warning: This can take several hours.
Further comments are in the scripts.
Data Services
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| Federal Ministry of Education and Research of Germany | TRUST | 02WGR1426A-G |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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