identification of variations in the climatic conditions of the lerma-chapala-santiago watershed by comparative analysis of time series

Clicks: 128
ID: 174883
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #133 of 174 articles by views in The Journal of biological chemistry

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 174 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
The current study presents a method for automating the Köppen–Garcia climate classification using a GIS module. This method was then applied in a case study of the Lerma-Chapala-Santiago watershed to compare time series data on climate from 1960 to 1989, 1981 to 2010, and 1960 to 2010. The kappa statistic indicated that the climate classifications of the generated model had a perfect degree of agreement with those of a prior nonautomated study. The climate data from the period 1960 to 2010 were used to create a climate map for the watershed. Overall, the dominant climates were dry, semiarid, temperate, and semiwarm temperate with a summer rainfall pattern. A comparative analysis of climate behavior between 1960 and 1989 and between 1981 and 2010 showed changes in temperature and extreme temperatures over 13.6% and 9.9%, respectively, of the watershed; the presence or absence of mid-summer drought also changed over 0.8% of the watershed. The module developed herein can be used to classify climates across all of Mexico, and data of varying spatial resolution and coverage can be inputted to the module. Finally, this module can be used to automate the creation of climate maps or to update climate maps at diverse spatial-temporal scales.
Reference Key
manzano-sols2018advancesidentification Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Luis Ricardo Manzano-Solís;Miguel A. Gómez-Albores;Carlos Díaz-Delgado;Carlos Alberto Mastachi-Loza;Raymundo Ordoñez-Sierra;Khalidou M. Bâ;Roberto Franco-Plata
Journal The Journal of biological chemistry
Year 2018
DOI
10.1155/2018/1098942
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.