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001-es BibID:BIBFORM106135
035-os BibID:(cikkazonosító)45 (WOS)000904136700001 (Scopus)85145169018
Első szerző:Abdo, Hazem Ghassan
Cím:Spatial implementation of frequency ratio, statistical index and index of entropy models for landslide susceptibility mapping in Al-Balouta river basin, Tartous Governorate, Syria / Hazem Ghassan Abdo1, Hussein Almohamad, Ahmed Abdullah Al Dughairi, Sk Ajim Ali, Farhana Parvin, Ahmed Elbeltagi, Romulus Costache, Safwan Mohammed, Motrih Al-Mutiry, Karam Alsafadi
Megjegyzések:Landslide vulnerability prediction maps are among the most important tools for managing natural hazards associated with slope stability in river basins that affect ecosystems, properties, infrastructure and society. Landslide events are among the most hazardous patterns of slope instability in the coastal mountains of Syria. Thus, the main goals of this research are to evaluate the performance of three different statistical outputs: Frequency Ratio (FR), Statistical Index (SI) and Index of Entropy (IoE) and therefore map landslide susceptibility in the coastal region of Syria. To this end, we identified a total of 446 locations of landslide events, based on the preliminary inventory map derived from fieldwork and high-resolution imagery surveys. In this regard, 13 geo-environmental factors that have a high influence on landslides were selected for landslide susceptibility mapping. The results indicated that the FR method outperformed the SI and IoE models with a high AUC of 0.824 and better adaptability, followed by the SI with 0.791. According to the SCAI values, although the FR model achieved the best reliability, the other two models also showed good capability in determining landslide susceptibility. The result of FR-based modelling showed that 18.51 and 19.98% of the study area fall under the high and very high landslide susceptible categories, respectively. In the map generated by the SI method, about 36% of the study area is classified as having high or very high landslide sensitivity. In the IoE method, whereas 14.18 and 25.62% of the study area were classified as ?very high susceptible" and ?high susceptible," respectively. The relative importance analysis demonstrated that the slope aspects, lithology and proximity to roads effectively motivated the acceleration of slope material instability and were the most influential in both the FR and SI models. On the other hand, the IoE model indicated that the proximity to faults and roads, along with the lithology factor, were important influences in the formation of landslide events. As a result, the statistical bivariate models-based landslide mapping provided a reliable and systematic approach to guide the long-term strategic planning procedures in the study area.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Frequency ratio
Statistical index
Index of entropy
Coastal mountain area
Megjelenés:Geoscience Letters. - 9 : 1 (2022), p.1-24. -
További szerzők:Almohamad, Hussein Al Dughairi, Ahmed Abdullah Ali, Sk Ajim Parvin, Farhana Elbeltagi, Ahmed Costache, Romulus Mohammed Safwan (1985-) (agrármérnök) Al-Mutiry, Motrih Alsafadi, Karam
Pályázati támogatás:TKP2021-NKTA-32
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001-es BibID:BIBFORM110952
035-os BibID:(Scopus)85152927438 (WoS)000985353900001 (cikkazonosító)20
Első szerző:Alsafadi, Karam
Cím:Modeling the impacts of projected climate change on wheat crop suitability in semi-arid regions using the AHP-based weighted climatic suitability index and CMIP6 / Karam Alsafadi, Shuoben Bi, Hazem Ghassan Abdo, Hussein Almohamad, Basma Alatrach, Amit Kumar Srivastava, Motrih Al?Mutiry, Santanu Kumar Bal, M. A. Sarath Chandran, Safwan Mohammed
Megjegyzések:Due to rapid population growth and the limitation of land resources, the sustainability of agricultural ecosystems has attracted more attention all over the world. Human activities will alter the components of the atmosphere and lead to climate change, which consequently afects crop production badly. In this context, wheat is considered an important crop and ranks as one of the top strategic crops globally. The main objective of this research is to develop a new approach (a weighted climatic suitability index) for evaluating the climate suitability for wheat production. The specifc objectives are to project the impact of future climate change on wheat suitability using three models based on WCSI and CMIP6-based projections and to identify the most vulnerable area to climate change and productivity reduction. The climatic criteria for wheat production were selected and classifed into eight indicators based on the Sys` scheme and the FAO framework, and then the weighted overlay approach was used in conjunction with the analytic hierarchy process. To confrm the reliability of the integrated WCSI, we determined the nonlinear curve ftting of integrated WCSI-induced wheat yields by the exponential growth equation. Finally, the CMIP6-GCMs projected from three shared socioeconomic pathways were used for WCSI mapping and predicting wheat yields in the short and long term (Southern Syria was selected as a case study). The results show that the nonlinear correlation between wheat yields and the integrated WCSI was 0.78 (R2=0.61) confrming the integrated WCSI`s reliability in refecting yield variation caused by climate suitability. The results indicated that WCSI for wheat will be lower over the study area during 2080-2100 compared to the current climate. During 2080-2100, the wheat yield is projected to decrease by 0.2-0.8 t. ha?1 in the western parts of the study area. The fndings of this study could be used to plan and develop adaptation strategies for sustainable wheat production in the face of projected climate change. The results of the study will also help in the strategic planning of wheat production in Syria under the projected climate. The results of this research are limited to small areas as a case study, although they are not relevant to similar regions worldwide. However, the study employs novel analytical methods that can be used broadly.
Tárgyszavak:Agrártudományok Állatorvosi tudományok idegen nyelvű folyóiratközlemény külföldi lapban
Climate change
Yield forecasting
Agro-climatic indices
Agricultural sustainability
Megjelenés:Geoscience Letters. - 10 : 20 (2023), p. 1-21. -
További szerzők:Bi, Shuoben Abdo, Hazem Ghassan Almohamad, Hussein Alatrach, Basma Srivastava, Amit Kumar Al-Mutiry, Motrih Bal, Santanu Kumar Chandran, M. A. Sarath Mohammed Safwan (1985-) (agrármérnök)
Internet cím:Szerző által megadott URL
Intézményi repozitóriumban (DEA) tárolt változat
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