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001-es BibID:	BIBFORM117608
035-os BibID:	(WoS)001135261800001 (Scopus)85181237372
Első szerző:	De Oliveira-Júnior, José Francisco
Cím:	Impact of the El Niño on Fire Dynamics on the African Continent / José Francisco de Oliveira-Júnior, David Mendes, Szilard Szabo, Sudhir Kumar Singh, Punyawi Jamjareegulgarn, Kelvy Rosalvo Alencar Cardoso, Laszlo Bertalan, Marcos Vinicius da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Jhon Lennon Bezerra da Silva, Gustavo Bastos Lyra, Marcel Carvalho Abreu, Washington Luiz Félix Correia Filho, Amaury de Sousa, Dimas de Barros Santiago, Iwldson Guilherme da Silva Santos, Vafaeva Khristina Maksudovna
Dátum:	2024
ISSN:	2509-9426 2509-9434
Megjegyzések:	Several studies investigated the occurrence of fires in Africa with numerical modeling or applied statistics; however, only a few studies focused on the influence of El Nino on the fire risk using a coupled model. The study aimed to assess the influence of El Nino on wildfire dynamics in Africa using the SPEEDY-HYCOM model. El Nino events in the Eastern Tropical Pacific were classified via sea surface temperature (SST) anomaly based on a predefined climatology between 1961 and 2020 for the entire time series of SST, obtaining linear anomalies. The time series of the SST anomalies was created for the region between 5 degrees N and 5 degrees S and 110 degrees W and 170 degrees W. The events were defined in three consecutive 3-month periods as weak, moderate, and strong El Nino conditions. The Meteorological Fire Danger Index (MFDI) was applied to detect fire hazards. The MFDI simulated by the SPEEDY-HYCOM model for three El Nino categories across different lagged months revealed relevant distinctions among the categories. In the case of 'Weak', the maximum variability of fire risk observed at time lags (0, -3, -6, and -9 months) was primarily in Congo, Gabon, and Madagascar. The 'Moderate' pattern had similar characteristics to 'Weak' except for the lag-6 months and its occurrence in the equatorial zone of Africa. 'Strong' showed a remarkable impact in East Africa, resulting in high fire risk, regardless of time lags. Precipitation and evaporation simulations (SPEEDY-HYCOM) indicated that El Nino categories in Africa need particular attention in the central, southern, and southeastern regions emphasizing the significance of lag-0 and lag-6 (evaporation) as well as lag-0, lag-6, and lag-9 (precipitation). The SPEEDY-HYCOM coupled model in conjunction with the MFDI was efficient in assessing climate variabilities in Africa during El Nino events. This model allows the analysis and prediction of wildfire risks based on El Nino events, providing crucial information for wildfire management and prevention. Its simulations uncover significant variations in risks among different El Nino categories and lagged months, contributing to the understanding and mitigation of this environmental challenge.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk fire risk coupled modelling El Nino categories SPEEDY-HYCOM model
Megjelenés:	Earth Systems and Environment. - [Epub ahead of print] (2024). -
További szerzők:	Mendes, David Szabó Szilárd (1974-) (geográfus) Singh, Sudhir Kumar (1970-) (geográfus) Jamjareegulgarn, Punyawi Cardoso, Kelvy Rosalvo Alencar Bertalan László (1989-) (geográfus) Da Silva, Marcos Vinicius Da Rosa Ferraz Jardim, Alexandre Manicoba Da Silva, Jhon Lennon Bezerra Lyra, Gustavo Bastos Abreu, Marcel Carvalho Filho, Washington Luiz Félix Correia De Sousa, Amaury De Barros Santiago, Dimas Da Silva Santos, Iwldson Guilherme Maksudovna, Vafaeva Khristina
Pályázati támogatás:	K138079 Egyéb RRF2.3.121202200008 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM102406
035-os BibID:	(WoS)000794114200001 (Scopus)85129824995
Első szerző:	Ebhuoma Osadolor
Cím:	Soil Erosion Vulnerability Mapping in Selected Rural Communities of uThukela Catchment, South Africa, Using the Analytic Hierarchy Process / Osadolor Ebhuoma, Michael Gebreslasie, Njoya Silas Ngetar, Kwanele Phinzi, Shwarnali Bhattacharjee
Dátum:	2022
ISSN:	2509-9426 2509-9434
Megjegyzések:	Soil erosion remains one of the main causes of land degradation, affecting many countries across the globe including South Africa. In rural communities with much reliance on agriculture, soil erosion is an important threat to food security. Therefore, mapping erosion-prone areas is an essential step towards adopting appropriate erosion mitigation and soil conservation measures. The objectives of this study were to (i) assess and model soil erosion vulnerability based on the Analytic Hierarchy Process (AHP) approach in Hoffenthal and KwaMaye communities within the uThukela Catchment, South Africa; and (ii) identify the relevant sustainable interventions and remedial strategies to combat soil erosion in the study area. The AHP was employed to map soil erosion vulnerability and derive the percentage weights of geo-environmental parameters contributing to soil erosion: rainfall, slope, drainage density, soil type, vegetation cover, and land use/land cover. The AHP model showed that slope, vegetation cover, and rainfall had the most considerable influence on soil erosion with factor weights of 29, 23, and 18%, respectively, in the study area. Further, this study revealed that high-risk soil erosion areas occupy 21% of the total study area, while very high-risk areas are about 14%, and the east and central areas are most vulnerable to soil erosion. Validation of the AHP model (overall accuracy = 85%; kappa coefficient = 0.70) results suggests that the predictive capacity of the model was satisfactory. Therefore, the developed soil erosion vulnerability model can serve as an important planning tool to prioritize areas for soil conservation and erosion management approaches like sustainable agriculture and bioengineering interventions.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Earth Systems and Environment. - 6 (2022), p. 851-864. -
További szerzők:	Gebreslasie, Michael Ngetar Njoya Silas Phinzi, Kwanele (1989-) Bhattacharjee, Shwarnali
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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