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Mapping the spatial variability of rainfall from a physiographic-based multilinear regression: model development and application to the Southwestern Iberian Peninsula

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URI: http://hdl.handle.net/10498/34861

DOI: https://doi.org/10.1007/s10661-022-10312-4

ISSN: 0167-6369

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Author/s
Ruiz Ortiz, VerónicaAuthority UCA; Isidoro, Jorge M.G.P.; Fernandez, Helena Maria; Granja Martins, Fernando M.; García López, SantiagoAuthority UCA
Date
2022
Department
Ciencias de la Tierra; Ingeniería Industrial e Ingeniería Civil
Source
Environmental Monitoring and Assessment, Vol. 194, Núm. 10, 2022
Abstract
A physiographic-based multilinear regression model supported by GIS was developed to estimate spatial rainfall variability in the Southwest Iberian Peninsula. The area study includes a wide diversity of landscape features and comprises four Portuguese regions and one Spanish province (totalizing 28,860 km2). The region suffers a very strong Mediterranean influence, with a major cleavage between winter and summer seasons. Thus, the analysis was carried out separately for the wet (October to March) and dry (April to September) semesters. From an initial set of 10 explanatory physiographic variables, five were selected to be used in the multilinear regression, as they allowed generating models by map algebra that fitted well with the last 40 years of monthly rainfall data records. These records were obtained from 163 weather stations, filtered from an initial set of 230 (142 stations in Portugal and 88 in Spain). The correlation between the physiographic-based multilinear regression model and a model obtained by interpolation from rainfall historical data showed to be good or very good in approximately 75% of the area under study. Results show that physiographic-based models can be effectively used to estimate rainfall where there is a lack of rain gauges, or to densify spatial resolution of rainfall between rain gauges.
Subjects
Rainfall; Physiography; Multilinear regression; Interpolation; Map algebra; Iberian Peninsula
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  • Articulos Científicos CC. Tierra [261]
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

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