Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering
Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global...
Ausführliche Beschreibung
Autor*in: |
Akay, Anil Orhan [verfasserIn] Senturk, Esra [verfasserIn] Akgul, Mustafa [verfasserIn] Demir, Murat [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2024 |
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Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Übergeordnetes Werk: |
Enthalten in: Theoretical and applied climatology - Springer Vienna, 1948, 155(2024), 9 vom: 26. Aug., Seite 8731-8753 |
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Übergeordnetes Werk: |
volume:155 ; year:2024 ; number:9 ; day:26 ; month:08 ; pages:8731-8753 |
Links: |
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DOI / URN: |
10.1007/s00704-024-05156-6 |
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Katalog-ID: |
SPR057380589 |
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520 | |a Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. | ||
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10.1007/s00704-024-05156-6 doi (DE-627)SPR057380589 (SPR)s00704-024-05156-6-e DE-627 ger DE-627 rakwb eng 550 VZ 38.82 bkl Akay, Anil Orhan verfasserin aut Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. Senturk, Esra verfasserin aut Akgul, Mustafa verfasserin aut Demir, Murat verfasserin aut Enthalten in Theoretical and applied climatology Springer Vienna, 1948 155(2024), 9 vom: 26. Aug., Seite 8731-8753 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:155 year:2024 number:9 day:26 month:08 pages:8731-8753 https://dx.doi.org/10.1007/s00704-024-05156-6 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 VZ AR 155 2024 9 26 08 8731-8753 |
spelling |
10.1007/s00704-024-05156-6 doi (DE-627)SPR057380589 (SPR)s00704-024-05156-6-e DE-627 ger DE-627 rakwb eng 550 VZ 38.82 bkl Akay, Anil Orhan verfasserin aut Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. Senturk, Esra verfasserin aut Akgul, Mustafa verfasserin aut Demir, Murat verfasserin aut Enthalten in Theoretical and applied climatology Springer Vienna, 1948 155(2024), 9 vom: 26. Aug., Seite 8731-8753 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:155 year:2024 number:9 day:26 month:08 pages:8731-8753 https://dx.doi.org/10.1007/s00704-024-05156-6 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 VZ AR 155 2024 9 26 08 8731-8753 |
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10.1007/s00704-024-05156-6 doi (DE-627)SPR057380589 (SPR)s00704-024-05156-6-e DE-627 ger DE-627 rakwb eng 550 VZ 38.82 bkl Akay, Anil Orhan verfasserin aut Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. Senturk, Esra verfasserin aut Akgul, Mustafa verfasserin aut Demir, Murat verfasserin aut Enthalten in Theoretical and applied climatology Springer Vienna, 1948 155(2024), 9 vom: 26. Aug., Seite 8731-8753 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:155 year:2024 number:9 day:26 month:08 pages:8731-8753 https://dx.doi.org/10.1007/s00704-024-05156-6 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 VZ AR 155 2024 9 26 08 8731-8753 |
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10.1007/s00704-024-05156-6 doi (DE-627)SPR057380589 (SPR)s00704-024-05156-6-e DE-627 ger DE-627 rakwb eng 550 VZ 38.82 bkl Akay, Anil Orhan verfasserin aut Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. Senturk, Esra verfasserin aut Akgul, Mustafa verfasserin aut Demir, Murat verfasserin aut Enthalten in Theoretical and applied climatology Springer Vienna, 1948 155(2024), 9 vom: 26. Aug., Seite 8731-8753 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:155 year:2024 number:9 day:26 month:08 pages:8731-8753 https://dx.doi.org/10.1007/s00704-024-05156-6 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 VZ AR 155 2024 9 26 08 8731-8753 |
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10.1007/s00704-024-05156-6 doi (DE-627)SPR057380589 (SPR)s00704-024-05156-6-e DE-627 ger DE-627 rakwb eng 550 VZ 38.82 bkl Akay, Anil Orhan verfasserin aut Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. Senturk, Esra verfasserin aut Akgul, Mustafa verfasserin aut Demir, Murat verfasserin aut Enthalten in Theoretical and applied climatology Springer Vienna, 1948 155(2024), 9 vom: 26. Aug., Seite 8731-8753 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:155 year:2024 number:9 day:26 month:08 pages:8731-8753 https://dx.doi.org/10.1007/s00704-024-05156-6 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 VZ AR 155 2024 9 26 08 8731-8753 |
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Akay, Anil Orhan @@aut@@ Senturk, Esra @@aut@@ Akgul, Mustafa @@aut@@ Demir, Murat @@aut@@ |
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Akay, Anil Orhan |
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Akay, Anil Orhan ddc 550 bkl 38.82 Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering |
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Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering |
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Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering |
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temporal and spatial variation of sediment risk in turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing entropy-based waspas and fuzzy clustering |
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Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering |
abstract |
Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstractGer |
Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstract_unstemmed |
Abstract The sustainable management of forestry activities, together with changes in vegetation due to deforestation or degradation, contributes to sediment risk and increases the risk of surface runoff. Changes in meteorological criteria, such as precipitation and temperature, as a result of global climate change are also significant factors affecting sediment risk. In this study, sediment risk was predicted spatially and temporally for 65 provinces in Turkey using criteria related to average forest road construction rates and average wood harvesting rates for the period between 2017 and 2021, as well as climate change models (GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR) and their scenarios (RCP 4.5 and RCP 8.5) for five-year periods between 2022 and 2096. In addition, changes in sediment risk in the short and long terms—that is, trends—were determined in spatially and temporally. Entropy-based WASPAS and fuzzy clustering analysis were used together to determine sediment risk in this context. The results show that, in terms of sediment risk, criteria related to forestry activities had a higher weight than criteria related to climate change when looking at the overall criterion weights. In addition, it was generally observed that the contribution of the average precipitation criterion to sediment risk increased in weight over five-year periods in the context of climate change models and scenarios. Regarding climate change models and scenarios, it was found that provinces consistently in the highest risk category (R1) over five-year periods were mainly located in the Black Sea and Marmara regions. In addition, provinces showing an increase or decrease in sediment risk trends between two consecutive five-year periods were mostly found in the Black Sea and Mediterranean regions. When evaluating the 15-year time intervals, differences in sediment risk trends were found between the geographical regions. In conclusion, the study results indicate that, regionally, Turkey’s northern regions, especially the Black Sea and Marmara regions, as well as the southern Mediterranean and western Aegean regions, will become increasingly vulnerable to sediment risk over time owing to the impact of climate change. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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container_issue |
9 |
title_short |
Temporal and spatial variation of sediment risk in Turkey: the role of forestry activities and climate change scenarios (2022–2096) utilizing Entropy-based WASPAS and fuzzy clustering |
url |
https://dx.doi.org/10.1007/s00704-024-05156-6 |
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Senturk, Esra Akgul, Mustafa Demir, Murat |
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Senturk, Esra Akgul, Mustafa Demir, Murat |
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10.1007/s00704-024-05156-6 |
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2024-09-20T05:13:52.221Z |
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|
score |
7.4000015 |