Analysis of Snow Water Equivalent Annual Maxima in the Upper Connecticut River Basin Using a Max Stable Spatial Process Model
Abstract
Recent advances from the science of spatial extremes and model regularization were applied to develop areal-based extremes of snow water equivalent (SWE) data for the upper Connecticut River Basin. Development of areal-based SWE exceedance probability estimates are of relevance for cool season probabilistic flood hazard analyses (PFHA). The approach profiled in this case study is applicable for other hydrometeorological variables of relevance to PFHA. The methodology conforms with Extreme Value Theory (EVT) for the analysis of spatial extremes; hence, there is a firm theoretical basis for extrapolation. Trend surface development is guided by EVT theory and recent advances for regularizing general linear models. R, a free software environment for statistical computing and graphics, and QGIS, a free and open-source geographic information system, were the primary tools used for product development and delivery. The following R software packages were primarily used during project execution: evd, Glmnet, maps, raster, rgdal, SDMTools, sp, and SpatialExtremes. R software packages exist in the public domain and support PFHA analyses of varying complexities. Their application herein is not an endorsement or recommendation. It is recommended that one would need to evaluate any particular R software package regarding its suitability for use for any specific application.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 30, 2020
- Accession Number
- AD1097406
Entities
People
- Brian Skahill
- Joseph Kanney
- Meredith Carr