Search: onr:"swepub:oai:lup.lub.lu.se:37cdedb7-e0f9-48cd-bfdc-e32f36b0f374" >
Application of mult...
Application of multiple spatial interpolation approaches to annual rainfall data in the Wadi Cheliff basin (north Algeria)
-
- Achite, Mohammed (author)
- Hassiba Benbouali University of Chlef
-
- Tsangaratos, Paraskevas (author)
- National Technical University of Athens
-
- Pellicone, Gaetano (author)
- CNR: National Research Council of Italy
-
show more...
-
- Mohammadi, Babak (author)
- Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
-
- Caloiero, Tommaso (author)
- CNR: National Research Council of Italy
-
show less...
-
(creator_code:org_t)
- 2024
- 2024
- English.
-
In: Ain Shams Engineering Journal. - 2090-4479. ; 15:3
- Related links:
-
http://dx.doi.org/10... (free)
-
show more...
-
https://lup.lub.lu.s...
-
https://doi.org/10.1...
-
show less...
Abstract
Subject headings
Close
- This study addresses a challenging problem of predicting mean annual precipitation across arid and semi-arid areas in northern Algeria, utilizing deterministic, geostatistical (GS), and machine learning (ML) models. Through the analysis of data spanning nearly five decades and encompassing 150 monitoring stations, the result of Random Forest showed the highest training performance, with R square value (of 0.9524) and the Root Mean Square Error (of 24.98). Elevation emerges as a critical factor, enhancing prediction accuracy in mountainous and complex terrains when used as an auxiliary variable. Cluster analysis further refines our understanding of station distribution and precipitation characteristics, identifying four distinct clusters, each exhibiting unique precipitation patterns and elevation zones. This study helps for a better understanding of precipitation prediction, encouraging the integration of additional variables and the exploration of climate change impacts, thereby contributing to informed environmental management and adaptation strategies across diverse climatic and terrain scenarios.
Subject headings
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Vattenteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Water Engineering (hsv//eng)
Keyword
- Spatial interpolation
- Deterministic techniques
- Geostatistical analysis
- Machine learning
- Rainfall
Publication and Content Type
- art (subject category)
- ref (subject category)
Find in a library
To the university's database