Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco

Here, we investigate the precipitation regionalization and the spatial variability of rainfall extremes, using a 47-year long station-based dataset from western central Morocco, a region with marked topographic and climatic variations. The principal component analysis revealed three homogeneous rain...

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Autores principales:	Abdelhafid El Alaoui El Fels, Mohamed El Mehdi Saidi, Assma Bouiji, Mounia Benrhanem
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	artificial neural networks morocco precipitation extremes principal components analysis rainfall regionalization rainfall variability Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/1da44d2e334c4a4e810f7f90b6346584
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spelling	oai:doaj.org-article:1da44d2e334c4a4e810f7f90b63465842021-11-05T18:52:14ZRainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco2040-22442408-935410.2166/wcc.2020.217https://doaj.org/article/1da44d2e334c4a4e810f7f90b63465842021-06-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/4/1107https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354Here, we investigate the precipitation regionalization and the spatial variability of rainfall extremes, using a 47-year long station-based dataset from western central Morocco, a region with marked topographic and climatic variations. The principal component analysis revealed three homogeneous rainfall regimes, consistent with topographic features: the coastal area receives heavy rainfall during autumns and winters, whereas the inner lowlands, in the middle of the study area, are characterized by an overall rainfall deficit regardless of their high water demand for irrigation, and the highest rainfall amounts take place in the mid-mountain area, including the summer seasons. Furthermore, the frequency analysis of daily rainfall extremes revealed high ten-year precipitation amounts in the coastal region (about 88 mm) and exceptional daily precipitation for longer return periods (182 mm for a 100-year period). Using artificial neural networks, the spatialization of these extreme precipitation events shows that they increase from the plain to the Atlas mountains and especially from the plain to the Atlantic Ocean. The spatial distribution of extreme precipitation highlights the areas where stormwater management needs to be improved, such as efficient stormwater drainage, and where floods are more likely to take place in the future.Abdelhafid El Alaoui El FelsMohamed El Mehdi SaidiAssma BouijiMounia BenrhanemIWA Publishingarticleartificial neural networksmoroccoprecipitation extremesprincipal components analysisrainfall regionalizationrainfall variabilityEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 4, Pp 1107-1122 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial neural networks morocco precipitation extremes principal components analysis rainfall regionalization rainfall variability Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
spellingShingle	artificial neural networks morocco precipitation extremes principal components analysis rainfall regionalization rainfall variability Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Abdelhafid El Alaoui El Fels Mohamed El Mehdi Saidi Assma Bouiji Mounia Benrhanem Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
description	Here, we investigate the precipitation regionalization and the spatial variability of rainfall extremes, using a 47-year long station-based dataset from western central Morocco, a region with marked topographic and climatic variations. The principal component analysis revealed three homogeneous rainfall regimes, consistent with topographic features: the coastal area receives heavy rainfall during autumns and winters, whereas the inner lowlands, in the middle of the study area, are characterized by an overall rainfall deficit regardless of their high water demand for irrigation, and the highest rainfall amounts take place in the mid-mountain area, including the summer seasons. Furthermore, the frequency analysis of daily rainfall extremes revealed high ten-year precipitation amounts in the coastal region (about 88 mm) and exceptional daily precipitation for longer return periods (182 mm for a 100-year period). Using artificial neural networks, the spatialization of these extreme precipitation events shows that they increase from the plain to the Atlas mountains and especially from the plain to the Atlantic Ocean. The spatial distribution of extreme precipitation highlights the areas where stormwater management needs to be improved, such as efficient stormwater drainage, and where floods are more likely to take place in the future.
format	article
author	Abdelhafid El Alaoui El Fels Mohamed El Mehdi Saidi Assma Bouiji Mounia Benrhanem
author_facet	Abdelhafid El Alaoui El Fels Mohamed El Mehdi Saidi Assma Bouiji Mounia Benrhanem
author_sort	Abdelhafid El Alaoui El Fels
title	Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
title_short	Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
title_full	Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
title_fullStr	Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
title_full_unstemmed	Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
title_sort	rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central morocco
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/1da44d2e334c4a4e810f7f90b6346584
work_keys_str_mv	AT abdelhafidelalaouielfels rainfallregionalizationandvariabilityofextremeprecipitationusingartificialneuralnetworksacasestudyfromwesterncentralmorocco AT mohamedelmehdisaidi rainfallregionalizationandvariabilityofextremeprecipitationusingartificialneuralnetworksacasestudyfromwesterncentralmorocco AT assmabouiji rainfallregionalizationandvariabilityofextremeprecipitationusingartificialneuralnetworksacasestudyfromwesterncentralmorocco AT mouniabenrhanem rainfallregionalizationandvariabilityofextremeprecipitationusingartificialneuralnetworksacasestudyfromwesterncentralmorocco
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Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco

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