NARA Discovery
Article Details
← Back to Search Results
Journal Article

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

B. Faybishenko; B. Arora; D. Dwivedi; E. Brodie
Stochastic Environmental Research and Risk Assessment · Vol. 37, Issue 4 · pp. 1303-1319 · 2023

Abstract

Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

Bibliographic Information

JournalStochastic Environmental Research and Risk Assessment
PublisherSpringer
Publication Date2023-04-01
Publication Year2023
Volume37
Issue4
Pages1303-1319
Document TypeJournal Article
Print ISSN1436-3240
eISSN1436-3259
DOI10.1007/s00477-022-02327-7

Access Information

NARA Access Coverage1987-01-01~Current
Journal Homepagehttps://www.springer.com/journal/477
Publisher PageOpen Publisher Page
Full-text access depends on NARA's subscribed coverage and institutional access.