CBS Kullanarak Akarsu Yönetimi İçin Havza Özelliklerinin Analizi: Gümüşhane Mikro Havzası Örneği

Year 2023, Volume: 23 Issue: 2, 144 - 155, 01.10.2023

Günay Çakır

https://doi.org/10.17475/kastorman.1368097

Cited By: 1

Abstract

Çalışmanın amacı: Mikro havzadaki akarsuların akış süreçlerinin belirlenmesinde topoğrafya ve iklim koşulları etkili olur. Günümüzde havzalarda su ve toprak koruma önlemleri için yönetim planları yapılmaktadır.
Çalışma alanı: Bu çalışma, CBS tabanlı mekansal bir yaklaşım kullanılarak Gümüşhane Yukaru Harşit mikro havzasındaki akarsuları karakterize etmek ve önceliklendirmek için gerçekleştirilmiştir.
Materyal ve yöntem: Gümüşhane mikro havzası için drenaj yoğunluğu, eğim, arazi kullanım tipleri ve akarsu sınıfı gibi temel havza özellikleri değerlendirilmiş ve yorumlanmıştır. Drenaj yoğunluğu (Dd), akış frekansı (Fs), eğim (S), arazi akışının uzunluğu (Lg) ve arazi kullanımı (Lu) için her parametre için kapsamlı bir değer hesaplanmış ve katmanlar olarak birleştirilmiştir.
Temel sonuçlar: Drenaj yoğunluğu, akarsu akış sıklığı ve mikro havzanın biçim faktörü -4 ile 26 arasındadır. Son olarak, ağırlıklı sıralamalar özetlenmiştir ve tüm mikro havzalar, risk indeksine göre olarak beş sınıfa ayrılmıştır. Risk sınıfları; çok düşük risk, düşük risk, orta risk, yüksek risk ve çok yüksek risk olarak ayrılmıştır. CBS yazılımıyla arazi kullanım türü katmanı üzerine nihai risk katmanı bindirilmiştir. Çok yüksek riskli alanlar içindeki 739 ha verimli orman alanı daha sonra risksiz alanlar olarak değiştirilmiştir.
Araştırma vurguları: Akarsuların taşıma kapasitesi, Gümüşhane mikro havzasındaki akarsuların yoğunlukları kullanılarak hesaplanmıştır. Arazi kullanım değerlerinin bulunduğu mahallerden geçen akarsuların ürettiği risk değerleri belirlenmiştir.

Keywords

Arazi Kullanım Tipi, Eğim, Drenaj Yoğunluğu, Türkiye, SAM

Analysis of Basin Characteristics for Stream Management Using GIS: A Case Study of Gumushane Micro-Watershed

Abstract

Aim of study: Topography and climatic conditions have effected in determining the processes of the streams of the micro-watershed. Nowadays, the management plans were made for water and soil protection measures in the basins.
Area of study: This study was carried outto characterize and prioritize the streams of the Gumushane upper Harşit micro-watershed using a GIS-based spatial approach.
Material and methods: Fundamental watershed characteristics including drainage density, slope, land use types, and stream class were evaluated and interpreted for the Gumushane micro-watershed. Calculatea comprehensive value for each parameter, drainage density (Dd), flow frequency (Fs), slope (S), length of land flow (Lg), and land use (Lu) was used.
Main results: The drainage density, stream flow frequency, and form factor of the microwatershed are from -4 to 26. Finally, the weighted rankings were summarized, and all micro-watersheds were categorized to five classes based on the risk index as very low risk, low risk, medium risk, high risk, and very high risk. This risk map overlaid to land use type maps in GIS where risk areas were evaluated in the finalrisk results. The 739 ha productive forest area within very high-risk areas was changed to non-risk parameters.
Highlights: The carrying capacity of streams was calculated using the stream density of streams in the Gumushane micro-watershed. The risk values produced by streams that pass through neighborhoods where land use values for preventing erosion are present.

Keywords

Land Use Types, Slope, Drainage Density, Türkiye, DEM

References

• Barnett, T. P., Pierce, D. W., Hidalgo, H. G., Bonfils, C., Santer, B. D. et al. (2008). Human-induced changes in the hydrology of the western United States. Science, 319(5866), 1080-1083.
• Berghuijs, W. R., Woods, R. A. & Hrachowitz, M. A, (2014). Precipitation shift from snow towards rain leads to a decrease in stream fow. Nature Climate Change. 4, 583-586.
• Brown, G. McAlpine, C., Rhodes, J., Lunney, D. Goldinggy, R., et al. (2019). Integration of social spatial data to assess conservation opportunities and priorities. Biological Conservation. 236: 452-463.
• Chaplin-Kramer, R., Neugarten, R. A., Sharp, R. P.M., Collins, P., Polasky, S., et al. (2023). Mapping the planet’s critical natural assets. Nature Ecology & Evolution. 7:51-61. https://doi.org/10.1038/s41559-022-01934-5.
• Cox, R. T. (1994). Analysis of drainage-basin symmetry as a rapid technique to identify areas of possible Quaternary tilt-block tectonics: an example from the Mississippi Embayment. Geological society of america bulletin, 106(5), 571-581.
• Çakır, G, Kaya, L. G., Yücedağ, C. & Bayram, S. (2019). Determination of the Effects of Alucra Forest Planning Unit’s Population Dynamics on Land Use Canges. Kastamonu University Journal of Forestry Faculty. 19 (1), 35-46.
• Çakir, G., Ün, C., Baskent, E. Z., Köse, S., Sivrikaya, F. & Keleş, S. (2008). Evaluating Urbanization, Fragmentation And Land Use/Land Cover Change Pattern In Istanbul City, Turkey From 1971 to 2002, Land Degradation and Development. 19 (6), 663-675. https://doi.org/10.1002/ldr.859.
• Çakır, G., Köse, S. & Başkent, E. Z. (2010). Orman Amenajman Planında Yol, Dere Yatağı ve Enerji Nakil Hatlarının Polygon Olarak Gösterilmesi ve Oluşturduğu Sonuçlar. Kastamonu University Journal of Forestry Faculty. 10 (1), 12-19.
• Eroğlu, H., Çakır, G., Sivrikaya, F. & Akay, A. E. (2010). Using High Resolution Images And Elevation Data In Classifying Erosion Risks Of Bare Soil Areas In The Hatilla Valley Natural Protected Area, Turkey. Stochastic Environmental Research and Risk Assessment. 24 (5), 699-704. https://doi.org/10.1007/s00477-009-0356-5.
• Grohmann, C. H., Riccomini, C. & Alves, F. M. (2007). SRTM-Based Morphotectonic Analysis of the Poços de Caldas Alkaline Massif, Southeastern Brazil. Computers & Geosciences. 33, 10-19. http://dx.doi.org/10.1016/j.cageo.2006.05.002.
• Horton, R. E. (1945). Erosion Development of Streams and Their Drainage Basins: Hydrophysical Approach to Quantitative Morphology. Bulletin of the Geological Society of America, 56, 275-370. http://dx.doi.org/10.1130/0016-7606.
• Jaiswal, R.K., Thomas, T., Galkate, R.V., Ghosh, N.C. & Singh, S. (2014). Watershed prioritization using Saaty’s AHP based decision support for soil conservation measures. Water Resource & Management. 28, 475-494. https://doi.org/10.1007/s11269-013-0494-x.
• Javed, A. & Yousuf Khanday, M. (2009). Ahmed Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques. Journal of Indian Society and Remote Sensing. 37, 261-274.
• Jha, M. K., Chowdhury, A., Chowdary, V. M. & Peiffer, S. (2007). Groundwater Management and Development by Integrated RS and GIS: Prospects and Constraints. Water Resource Management. 21, 427-467. http://dx.doi.org/10.1007/s11269-006-9024-4.
• Kale, V.S., Sengupta, S., Achyuthan, H. & Jaiswal, M. K. (2014). Tectonic controls upon Kaveri River drainage, cratonic Peninsular India: inferences from longitudinal profiles, morphotectonic indices, hanging valleys and fluvial records. Geomorphology. 227, 153-165.
• Karami H, Anaraki M.V., Farzin S, Mirjalili, S. (2021). Flow Direction Algorithm (FDA): A Novel Optimization Approach for Solving Optimization Problems, Computers & Industrial Engineering, 156, 107224.
• Keleş, S., Durusoy, İ. & Çakır, G. (2017). Analysis Of The Changes In Forest Ecosystem Functions, Structure And Composition In The Black Sea Region Of Turkey, Journal of Forestry Research. 28 (2), 329-342. https://doi.org/10.1007/s11676-016-0322-2.
• Mark, D. M. (1984). Automatic Detection of Drainage Networks from Digital Elevation Models. Cartographica. 21, 168-178. http://dx.doi.org/10.3138/10LM-4435-6310-251R.
• Milly, P. C. D., Dunne, K. A. &Vecchia, A. V. (2005). Global pattern of trends in stream flow and water availability in a changing climate. Nature. 438, 347-350.
• Nagaraju, M.S.S., Obi Reddy GP, Maji AK, Srivastava R, Raja P, Barthwal AK. (2011). Soil loss mapping for sustainable development and management of land resources in Warora Tehsil of Chandrapur district of Maharashtra: an integrated approach using remote sensing and GIS. Journal of Indian Society and Remote Sensing. 39 (1), 51–61.
• Panhalkar, S. S. (2014). Hydrological Modelling Using SWAT Model and Geoinformatic Techniques. The Egyptian Journal of Remote Sensing and Space Science. 17, 197-207. http://dx.doi.org/10.1016/j.ejrs.2014.03.001.
• Pidwirny, M. (2006). "Stream Morphometry". Fundamentals of Physical Geography, 2nd Edition. Date Viewed. http://www.physicalgeography.net/fundamentals/10ab.html).
• Randhir, T. O., O'Connor, R., Penner, P.R. & Goodwin, D.W. (2001). A watershed based land prioritization model for water supply protection. Forest Ecology and Management. 143, 47-56.
• Rao, K. N., Narendra, K. & Latha, P. S. (2010). An integrated study of geospatial information technologies for surface runoff estimation in an agricultural watershed, India. Journal of Indian Society and Remote Sensing. 38, 255-267.
• Samuwai, J. & Hills, J. M. (2018). Assessing climate finance readiness in the Asia-Pacific Region. Sustainability. 10: 4, 1192. https://doi.org/10.3390/su10041192.
• Sarita, G., Sharma, S.K. & Tignath, S. (2015). Development of a geomorphological erosion index for Shakkar watershed. Journal of Geological Society of India. 86, 361–370.
• Sarukhan, J and Whyte, A., (Ed.). (2005). Ecosystems and Human Well-Being: Systhesis. Current State and Trends: Synthesis. ISBN 1-59726-040-1. 137 pp. Island Press, Washington, D.C.
• Shi, Z. H., Cai, C. F., Ding, S.W., Wang, T.W. & Chow, T.L. (2004). Soil conservation planning at the small watershed level using RUSLE with GIS: a case study in the three gorge area of China. Catena. 55, 33-48.
• Shinde, V., Sharma, A., Tiwari, K.N. & Singh, M. (2011). Quantitative determination of soil erosion and prioritization of micro watersheds using remote sensing and GIS. Journal of Indian Society and Remote Sensing. 39 (2): 181–192.
• Schulte, L.A., Dale, B.E., Bozzetto, S., Liebman, M., Souza, G.M., et al. (2022). Meeting global challenges with regenerative agriculture producing food and energy. Nature Sustainability. 5, 384-388. https://doi.org/10.1038/s41893-021-00827.
• Strahler, A.N. (1957). Quantitative analysis of watershed geomorphology. Transactions of the American Geophysical Union. 38, 913-920.
• Singh, P., Thakur, J.K. & Singh, U.C. (2013). Morphometric Analysis of Morar River Basin, Madhya Pradesh, India, Using Remote Sensing and GIS Techniques. Environmental Earth Sciences. 68, 1967-1977 .http://dx.doi.org/10.1007/s12665-012-1884-8.
• Singh, N.K. & Basu, N.B. (2022). The human factor in seasonal stream flows across natural and managed watersheds of North America. Nature Sustainability 5, 397-405. https://doi.org/10.1038/s41893-022-00848-1.
• Tarboton, D.G. (1997). A New Method for the Determination of Flow Directions and Contributing Areas in Grid Digital Elevation Models. Water Resources Research. 33, 309-319. http://dx.doi.org/10.1029/96WR03137.
• Vijith, H., Prasannakumar, V., Sharath Mohan, M.A., Ninu Krishnan, M.V. & Pratheesh, P. (2017). River and basin morphometric indexes to detect tectonic activity: a case study of selected river basins in the South Indian Granulite Terrain (SIGT). Physical Geography. 38, 1-19. https://doi.org/10.1080/02723646.2017.1283478.
• Vörösmarty, C. J., Green, P., Salisbury, J. & Lammers, R. B. (2000). Global water resources: vulnerability from climate change and population growth. Science. 289, 284-288.
• Zeybek, H. İ & Eraslan S. (2018), Analysis of Flood Hazard in Gümüşhane Province Using Geographic Information Systems (GIS) And Analytic Hierarchy Process (AHP), 1st International Disaster Management Congress (IDMC2018), 336-354.