Araştırma Makalesi
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Investigation of the effects of different plant groups on surface runoff

Yıl 2025, Cilt: 26 Sayı: 1, 191 - 201, 15.05.2025
https://doi.org/10.17474/artvinofd.1636744

Öz

Runoff is defined as the infiltration of water into the soil due to urbanisation, and it directly affects the natural water cycle, especially in urban areas and regions with intensive anthropogenic development. The present study aims to assess the impact of various vegetation groups, especially tree and shrub cover, on runoff. The 'Curve Number' method was utilised to calculate runoff amounts for Istanbul, Sariyer region, employing NDVI data for the purpose. The findings of this study demonstrate that the presence of tree cover has a beneficial effect on runoff. The study emphasises the importance of prioritising tree groups in urban areas for effective water management and the protection of existing groups.

Kaynakça

  • Alves PL, Formiga KTM (2019) Efeitos da arborização urbana na redução do escoamento pluvial superficial e no atraso do pico de vazão. Ciênc Florest, 29:193–207.
  • Alyaseri I, Zhou J (2016) Stormwater Volume Reduction in Combined Sewer Using Permeable Pavement: City of St. Louis. J Environ Eng, 142:04016002.
  • Armson D, Stringer P, Ennos AR (2013) The effect of street trees and amenity grass on urban surface water runoff in Manchester, UK. Urban For Urban Green, 12:282–286.
  • Beaugeard E, Brischoux F, Angelier F (2021) Green infrastructures and ecological corridors shape avian biodiversity in a small French city. Urban Ecosyst, 24:549–560.
  • Calvin K, Dasgupta D, Krinner G (2023) IPCC, 2023: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H Lee and J Romero (eds.)]. IPCC, Geneva, Switzerland. https://doi.org/10.59327/IPCC/AR6-9789291691647.
  • Coskun-Hepcan C, Hepcan Ş (2018) Assessing ecosystem services of Bornova’s green infrastructure, Izmir (Turkey). Fresenius Environ Bull, 27:3530–3541.
  • Dowtin AL, Cregg BC, Nowak DJ, Levia DF (2023) Towards optimized runoff reduction by urban tree cover: a review of key physical tree traits, site conditions, and management strategies. Landsc Urban Plan, 239:104849.
  • Earth Resources Observation and Science (EROS) Center (2017) Sentinel. https://doi.org/10.5066/F76W992G.
  • ESRI (2011a) ArcGIS.
  • ESRI (2011b) ArcGIS (NDVI Function).
  • European Environment Agency (2020) Urban Atlas Land Cover/Land Use 2018 (vector), Europe, 6-yearly, Jul. 2021. https://doi.org/10.2909/FB4DFFA1-6CEB-4CC0-8372-1ED354C285E6.
  • Farr TG, Rosen PA, Caro E (2007) The shuttle radar topography mission. Rev Geophys, 45:2005RG000183.
  • Fick SE, Hijmans RJ (2017) WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int J Climatol, 37:4302–4315.
  • Foti L, Barot S, Gignoux J (2021) Topsoil characteristics of forests and lawns along an urban–rural gradient in the Paris region (France). Soil Use Manag, 37:749–761.
  • Fullen MA (1991) A comparison of runoff and erosion rates on bare and grassed loamy sand soils. Soil Use Manag, 7:136–138.
  • Gorelick N, Hancher M, Dixon M (2017) Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ, 202:18–27.
  • Grey V, Livesley SJ, Fletcher TD, Szota C (2018) Tree pits to help mitigate runoff in dense urban areas. J Hydrol, 565:400–410.
  • Hao M, Gao C, Sheng D, Qing D (2019) Review of the influence of low-impact development practices on mitigation of flood and pollutants in urban areas. Desalination Water Treat, 149:323–328.
  • Hossain S, Hewa GA, Wella-Hewage S (2019) A comparison of continuous and event-based rainfall–runoff (RR) modelling using EPA-SWMM. Water, 11:611.
  • Huang M, Gallichand J, Wang Z, Goulet M (2006) A modification to the soil conservation service curve number method for steep slopes in the loess plateau of China. Hydrol Process, 20: 579-589.
  • Huang S, Tang L, Hupy JP (2021) A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. J For Res, 32:1–6.
  • Jain SK, Jain SK, Hariprasad V, Choudhry A (2011) Water balance study for a basin integrating remote sensing data and GIS. J Indian Soc Remote Sens, 39:259–270.
  • Jang S, Ji H, Choi J (2021) Investigation of correlation between surface runoff rate and stream water quality. Water Supply, 21:1495–1505.
  • Jin H, Liang R, Wang Y, Tumula P (2015) Flood-runoff in semi-arid and sub-humid regions, a case study: a simulation of Jianghe Watershed in Northern China. Water, 7:5155–5172.
  • Kim CG, Kim NW (2004) Assessment of forest vegetation effect on water balance in a watershed. Journal of Korea Water Resources Association, 37(9), 737–744.
  • Kim HW, Kim J-H, Li W (2017) Exploring the impact of green space health on runoff reduction using NDVI. Urban For Urban Green, 28:81–87.
  • Kuehler E, Hathaway J, Tirpak A (2017) Quantifying the benefits of urban forest systems as a component of the green infrastructure stormwater treatment network. Ecohydrology, 10: e1813.
  • Li J, Li Y, Li Y (2016) SWMM-based evaluation of the effect of rain gardens on urbanized areas. Environ Earth Sci, 75:17.
  • Li F, Chen J, Engel BA (2020a) Assessing the effectiveness and cost efficiency of green infrastructure practices on surface runoff reduction at an urban watershed in China. Water, 13:24.
  • Li L, Van Eetvelde V, Cheng X, Uyttenhove P (2020b) Assessing stormwater runoff reduction capacity of existing green infrastructure in the city of Ghent. Int J Sustain Dev World Ecol, 27:749–761.
  • Liu W, Chen W, Peng C (2014) Assessing the effectiveness of green infrastructures on urban flooding reduction: a community scale study. Ecol Model, 291:6–14.
  • Maragno D, Gaglio M, Robbi M (2018) Fine-scale analysis of urban flooding reduction from green infrastructure: an ecosystem services approach for the management of water flows. Ecol Model, 386:1–10.
  • Ozturk D, Batuk F, Bektas S (2011) Determination of Land Use/Cover and Topographical/Morphological Features of River Watershed for Water Resources Management Using Remote Sensing and GIS.
  • Patton D, Smith D, Muche ME (2022) Catchment scale runoff time-series generation and validation using statistical models for the Continental United States. Environ Model Softw, 149:105321.
  • Rahman MA, Pawijit Y, Xu C (2023) A comparative analysis of urban forests for storm-water management. Sci Rep, 13:1451.
  • Ramke H-G (2018) Collection of surface runoff and drainage of landfill top cover systems, in: solid waste landfilling. Elsevier, 373–416.
  • Republic of Türkiye Ministry of Agriculture and Forestry (2013) Soil Maps.
  • Schärer LA, Busklein JO, Sivertsen E, Muthanna TM (2020) Limitations in using runoff coefficients for green and gray roof design. Hydrol Res, 51:339–350.
  • Shao Z, Fu H, Li D (2019) Remote sensing monitoring of multi-scale watersheds impermeability for urban hydrological evaluation. Remote Sens Environ, 232:111338.
  • Turkish State Meteorological Service (2021) Istanbul Precipitation Dataset.
  • URL-1 http://www.Sariyer.gov.tr/belgrad-ormani. Date of Access: 07.02.2025.
  • URL-2 https://www.eyupsultan.bel.tr/tr/main/pages/belgrad-ormanlari/1791. Date of Access: 07.02.2025.
  • US Environment Protection Agency (EPA) (2024) Storm Water Management Model (SWMM).
  • USDA NRCS (2004) Hydrologic Soil-Cover Complexes, in: National Engineering Handbook. p Part 630.
  • USDA NRCS (1986) Urban Hydrology for Small Watersheds (TR-55).
  • Verma S, Verma RK, Mishra SK (2017) A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation. Hydrol Sci J., 62:1891–1930.
  • Woznicki SA, Hondula KL, Jarnagin ST (2018) Effectiveness of landscape‐based green infrastructure for stormwater management in suburban catchments. Hydrol Process, 32:2346–2361.
  • Wu X, Chang Q, Kazama S (2024) Integrated assessment of the runoff and heat mitigation effects of vegetation in an urban residential area. Sustainability, 16:5201.
  • Xiao Y, Zhang T, Liang D, Chen JM (2016) Experimental study of water and dissolved pollutant runoffs on impervious surfaces. J Hydrodyn, 28:162–165.
  • Xue H, Liu J, Dong G (2022) Runoff estimation in the upper reaches of the heihe river using an lSTM model with remote sensing data. Remote Sens, 14:2488.
  • Yan Z (2024) Establishment of urban green corridor network based on neural network and landscape ecological security. J Comput Sci, 79:102315.
  • Yang B, Lee DK (2021) Planning strategy for the reduction of runoff using urban green space. Sustainability, 13:2238.
  • Young CB, McEnroe BM, Rome AC (2009) Empirical determination of rational method runoff coefficients. j Hydrol Eng, 14:1283–1289.
  • Zhang C, Wang J, Liu J (2023) Performance assessment for the integrated green-gray-blue infrastructure under extreme rainfall scenarios. Front Ecol Evol, 11:1242492.
  • Zhang Z, Meerow S, Newell JP, Lindquist M (2019) Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design. Urban For Urban Green, 38:305–317.
  • Zhao Q, Qu Y (2024) The retrieval of ground ndvi (normalized difference vegetation index) data consistent with remote-sensing observations. Remote Sens, 16:1212.

Farklı bitki gruplarının yüzeysel akış üzerindeki etkilerinin incelenmesi

Yıl 2025, Cilt: 26 Sayı: 1, 191 - 201, 15.05.2025
https://doi.org/10.17474/artvinofd.1636744

Öz

Kentleşmeye bağlı olarak suyun toprağa sızması olarak tanımlanan yüzeysel akış, özellikle kentsel alanlarda ve antropojenik gelişimin yoğun olduğu bölgelerde doğal su döngüsünü doğrudan etkilemektedir. Bu çalışma, çeşitli bitki gruplarının, özellikle de ağaç ve çalı örtüsünün yüzeysel akış üzerindeki etkisini değerlendirmeyi amaçlamaktadır. İstanbul, Sarıyer ilçesi için yüzeysel akış miktarlarını hesaplamak amacıyla 'Eğri Numarası' yöntemi kullanılmış ve bu amaçla NDVI verileri kullanılmıştır. Bu çalışmanın bulguları, ağaç örtüsünün varlığının yüzeysel akış üzerinde faydalı bir etkiye sahip olduğunu göstermektedir. Çalışma, etkin su yönetimi için kentsel alanlarda ağaç gruplarına öncelik verilmesinin ve mevcut grupların korunmasının önemini vurgulamaktadır.

Kaynakça

  • Alves PL, Formiga KTM (2019) Efeitos da arborização urbana na redução do escoamento pluvial superficial e no atraso do pico de vazão. Ciênc Florest, 29:193–207.
  • Alyaseri I, Zhou J (2016) Stormwater Volume Reduction in Combined Sewer Using Permeable Pavement: City of St. Louis. J Environ Eng, 142:04016002.
  • Armson D, Stringer P, Ennos AR (2013) The effect of street trees and amenity grass on urban surface water runoff in Manchester, UK. Urban For Urban Green, 12:282–286.
  • Beaugeard E, Brischoux F, Angelier F (2021) Green infrastructures and ecological corridors shape avian biodiversity in a small French city. Urban Ecosyst, 24:549–560.
  • Calvin K, Dasgupta D, Krinner G (2023) IPCC, 2023: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H Lee and J Romero (eds.)]. IPCC, Geneva, Switzerland. https://doi.org/10.59327/IPCC/AR6-9789291691647.
  • Coskun-Hepcan C, Hepcan Ş (2018) Assessing ecosystem services of Bornova’s green infrastructure, Izmir (Turkey). Fresenius Environ Bull, 27:3530–3541.
  • Dowtin AL, Cregg BC, Nowak DJ, Levia DF (2023) Towards optimized runoff reduction by urban tree cover: a review of key physical tree traits, site conditions, and management strategies. Landsc Urban Plan, 239:104849.
  • Earth Resources Observation and Science (EROS) Center (2017) Sentinel. https://doi.org/10.5066/F76W992G.
  • ESRI (2011a) ArcGIS.
  • ESRI (2011b) ArcGIS (NDVI Function).
  • European Environment Agency (2020) Urban Atlas Land Cover/Land Use 2018 (vector), Europe, 6-yearly, Jul. 2021. https://doi.org/10.2909/FB4DFFA1-6CEB-4CC0-8372-1ED354C285E6.
  • Farr TG, Rosen PA, Caro E (2007) The shuttle radar topography mission. Rev Geophys, 45:2005RG000183.
  • Fick SE, Hijmans RJ (2017) WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int J Climatol, 37:4302–4315.
  • Foti L, Barot S, Gignoux J (2021) Topsoil characteristics of forests and lawns along an urban–rural gradient in the Paris region (France). Soil Use Manag, 37:749–761.
  • Fullen MA (1991) A comparison of runoff and erosion rates on bare and grassed loamy sand soils. Soil Use Manag, 7:136–138.
  • Gorelick N, Hancher M, Dixon M (2017) Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ, 202:18–27.
  • Grey V, Livesley SJ, Fletcher TD, Szota C (2018) Tree pits to help mitigate runoff in dense urban areas. J Hydrol, 565:400–410.
  • Hao M, Gao C, Sheng D, Qing D (2019) Review of the influence of low-impact development practices on mitigation of flood and pollutants in urban areas. Desalination Water Treat, 149:323–328.
  • Hossain S, Hewa GA, Wella-Hewage S (2019) A comparison of continuous and event-based rainfall–runoff (RR) modelling using EPA-SWMM. Water, 11:611.
  • Huang M, Gallichand J, Wang Z, Goulet M (2006) A modification to the soil conservation service curve number method for steep slopes in the loess plateau of China. Hydrol Process, 20: 579-589.
  • Huang S, Tang L, Hupy JP (2021) A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. J For Res, 32:1–6.
  • Jain SK, Jain SK, Hariprasad V, Choudhry A (2011) Water balance study for a basin integrating remote sensing data and GIS. J Indian Soc Remote Sens, 39:259–270.
  • Jang S, Ji H, Choi J (2021) Investigation of correlation between surface runoff rate and stream water quality. Water Supply, 21:1495–1505.
  • Jin H, Liang R, Wang Y, Tumula P (2015) Flood-runoff in semi-arid and sub-humid regions, a case study: a simulation of Jianghe Watershed in Northern China. Water, 7:5155–5172.
  • Kim CG, Kim NW (2004) Assessment of forest vegetation effect on water balance in a watershed. Journal of Korea Water Resources Association, 37(9), 737–744.
  • Kim HW, Kim J-H, Li W (2017) Exploring the impact of green space health on runoff reduction using NDVI. Urban For Urban Green, 28:81–87.
  • Kuehler E, Hathaway J, Tirpak A (2017) Quantifying the benefits of urban forest systems as a component of the green infrastructure stormwater treatment network. Ecohydrology, 10: e1813.
  • Li J, Li Y, Li Y (2016) SWMM-based evaluation of the effect of rain gardens on urbanized areas. Environ Earth Sci, 75:17.
  • Li F, Chen J, Engel BA (2020a) Assessing the effectiveness and cost efficiency of green infrastructure practices on surface runoff reduction at an urban watershed in China. Water, 13:24.
  • Li L, Van Eetvelde V, Cheng X, Uyttenhove P (2020b) Assessing stormwater runoff reduction capacity of existing green infrastructure in the city of Ghent. Int J Sustain Dev World Ecol, 27:749–761.
  • Liu W, Chen W, Peng C (2014) Assessing the effectiveness of green infrastructures on urban flooding reduction: a community scale study. Ecol Model, 291:6–14.
  • Maragno D, Gaglio M, Robbi M (2018) Fine-scale analysis of urban flooding reduction from green infrastructure: an ecosystem services approach for the management of water flows. Ecol Model, 386:1–10.
  • Ozturk D, Batuk F, Bektas S (2011) Determination of Land Use/Cover and Topographical/Morphological Features of River Watershed for Water Resources Management Using Remote Sensing and GIS.
  • Patton D, Smith D, Muche ME (2022) Catchment scale runoff time-series generation and validation using statistical models for the Continental United States. Environ Model Softw, 149:105321.
  • Rahman MA, Pawijit Y, Xu C (2023) A comparative analysis of urban forests for storm-water management. Sci Rep, 13:1451.
  • Ramke H-G (2018) Collection of surface runoff and drainage of landfill top cover systems, in: solid waste landfilling. Elsevier, 373–416.
  • Republic of Türkiye Ministry of Agriculture and Forestry (2013) Soil Maps.
  • Schärer LA, Busklein JO, Sivertsen E, Muthanna TM (2020) Limitations in using runoff coefficients for green and gray roof design. Hydrol Res, 51:339–350.
  • Shao Z, Fu H, Li D (2019) Remote sensing monitoring of multi-scale watersheds impermeability for urban hydrological evaluation. Remote Sens Environ, 232:111338.
  • Turkish State Meteorological Service (2021) Istanbul Precipitation Dataset.
  • URL-1 http://www.Sariyer.gov.tr/belgrad-ormani. Date of Access: 07.02.2025.
  • URL-2 https://www.eyupsultan.bel.tr/tr/main/pages/belgrad-ormanlari/1791. Date of Access: 07.02.2025.
  • US Environment Protection Agency (EPA) (2024) Storm Water Management Model (SWMM).
  • USDA NRCS (2004) Hydrologic Soil-Cover Complexes, in: National Engineering Handbook. p Part 630.
  • USDA NRCS (1986) Urban Hydrology for Small Watersheds (TR-55).
  • Verma S, Verma RK, Mishra SK (2017) A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation. Hydrol Sci J., 62:1891–1930.
  • Woznicki SA, Hondula KL, Jarnagin ST (2018) Effectiveness of landscape‐based green infrastructure for stormwater management in suburban catchments. Hydrol Process, 32:2346–2361.
  • Wu X, Chang Q, Kazama S (2024) Integrated assessment of the runoff and heat mitigation effects of vegetation in an urban residential area. Sustainability, 16:5201.
  • Xiao Y, Zhang T, Liang D, Chen JM (2016) Experimental study of water and dissolved pollutant runoffs on impervious surfaces. J Hydrodyn, 28:162–165.
  • Xue H, Liu J, Dong G (2022) Runoff estimation in the upper reaches of the heihe river using an lSTM model with remote sensing data. Remote Sens, 14:2488.
  • Yan Z (2024) Establishment of urban green corridor network based on neural network and landscape ecological security. J Comput Sci, 79:102315.
  • Yang B, Lee DK (2021) Planning strategy for the reduction of runoff using urban green space. Sustainability, 13:2238.
  • Young CB, McEnroe BM, Rome AC (2009) Empirical determination of rational method runoff coefficients. j Hydrol Eng, 14:1283–1289.
  • Zhang C, Wang J, Liu J (2023) Performance assessment for the integrated green-gray-blue infrastructure under extreme rainfall scenarios. Front Ecol Evol, 11:1242492.
  • Zhang Z, Meerow S, Newell JP, Lindquist M (2019) Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design. Urban For Urban Green, 38:305–317.
  • Zhao Q, Qu Y (2024) The retrieval of ground ndvi (normalized difference vegetation index) data consistent with remote-sensing observations. Remote Sens, 16:1212.
Toplam 56 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yeşil Yapılar ve Çevreler
Bölüm Araştırma Makalesi
Yazarlar

Merve Eminel Kutay 0000-0001-6422-0174

Mert Ekşi 0000-0001-6373-9257

Gönderilme Tarihi 10 Şubat 2025
Kabul Tarihi 9 Mayıs 2025
Yayımlanma Tarihi 15 Mayıs 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 26 Sayı: 1

Kaynak Göster

APA Eminel Kutay, M., & Ekşi, M. (2025). Investigation of the effects of different plant groups on surface runoff. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, 26(1), 191-201. https://doi.org/10.17474/artvinofd.1636744
AMA Eminel Kutay M, Ekşi M. Investigation of the effects of different plant groups on surface runoff. AÇÜOFD. Mayıs 2025;26(1):191-201. doi:10.17474/artvinofd.1636744
Chicago Eminel Kutay, Merve, ve Mert Ekşi. “Investigation of the effects of different plant groups on surface runoff”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 26, sy. 1 (Mayıs 2025): 191-201. https://doi.org/10.17474/artvinofd.1636744.
EndNote Eminel Kutay M, Ekşi M (01 Mayıs 2025) Investigation of the effects of different plant groups on surface runoff. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 26 1 191–201.
IEEE M. Eminel Kutay ve M. Ekşi, “Investigation of the effects of different plant groups on surface runoff”, AÇÜOFD, c. 26, sy. 1, ss. 191–201, 2025, doi: 10.17474/artvinofd.1636744.
ISNAD Eminel Kutay, Merve - Ekşi, Mert. “Investigation of the effects of different plant groups on surface runoff”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 26/1 (Mayıs2025), 191-201. https://doi.org/10.17474/artvinofd.1636744.
JAMA Eminel Kutay M, Ekşi M. Investigation of the effects of different plant groups on surface runoff. AÇÜOFD. 2025;26:191–201.
MLA Eminel Kutay, Merve ve Mert Ekşi. “Investigation of the effects of different plant groups on surface runoff”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, c. 26, sy. 1, 2025, ss. 191-0, doi:10.17474/artvinofd.1636744.
Vancouver Eminel Kutay M, Ekşi M. Investigation of the effects of different plant groups on surface runoff. AÇÜOFD. 2025;26(1):191-20.
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