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Relations Between Land Use Changes and Drought in Kavar Depression (Iran)

Yıl 2018, , 397 - 406, 15.06.2018
https://doi.org/10.18016/ksudobil.343124

Öz

The multidimensional drought is primarily a meteorological
origin. But human activities are also main concern for this scenario,
especially in case of irrigation methods when agricultural crops require high
amount of water in areas with low rainfall and high temperature. Beacause of
this incresing water demand, primarily the groundwater level starts to decrease
and hence agricultural drought occures. The Kavar depression in Iran which is
the subject of this study also faces problems such as water shortage and the
wrong selection of agricultural crop production. In order to determine the
facts, the land use changes of the corresponding study area has been taken into
account from 1975 to 2017. Different version of Landsat satellite images
including Landsat 4, 5 and 8 have been processed by remote sensing techniquesto
revealing the temporal variation of the area where the crop was produced by
irrigation. However, based on the available rainfall and temperature data,
water shortage has been calculated by using Thornthwaite Method. On the other
hand, for nonparametric Mann-Kendall test correlation analyses,  evaporation data has been used along with
other climate data. In addition, water demand per hectare has also been collected
for spcific crop of Kavar depression. As a continuation of the analysis based
on the natural and artificial elements, finally the relation between the total
water demand of irrigated agriculture field and the water potential of
depression from 1975 has been found.

Kaynakça

  • Abbaspour M, Javid AH, Mirbagheri SA, Ahmadi Givi F, Moghimi P 2012. Investigation of Lake Drying Attributed to Climate Change. Int. J. Environ. Sci. Techno. (9): 257–266.
  • Ahmad A 2012. Analysis of Maximum Likelihood Classification on Multispectral Data. Applied Mathematical Sciences, 6(129): 6425-6436.
  • Al Buhairi MH 2010. Analysis of Monthly, Seasonal and Annual Air Temperature Variability and Trends in Taiz City-Republic of Yemen. Journal of Environmental Protection (1): 401-409.
  • Ahmad AT, Abu Mansour A 1940. Loqat Fors (Persian Dictionary), Tehran, Majles.
  • Ardakanian R 2003. An Overwiev of Water Mannagment in Iran. Dushanbe International Fresh Water Forum, Tajikistan.
  • Avcı M 2001. Kuraklık Etkilerinin Azaltılmasında Kuraklığa Dayanıklı Bitki Çeşit Islahı ve Kurak Koşullarda Yetiştirme Teknikleri. (Orta Anadolu'da Kuraklık Şartlarında Yetiştirme Stratejileri, TEMA yayınları, Ankara: T. Vakfı içinde) 74-97.
  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held R, Jones R, Kolli RK, Kwon WK, Laprise R, Magana Rueda V, Mearns L, Menendez CG, Räisänen J, Rinke A, Sarr A, Whetton P, Arritt R, Benestad R, Beniston M, Bromwich D, Cay, D, Comis, J, de Elia R, Dethloff K 2007. Regional Climate Projections. (Climate Change 2007: The Physical Science Basis. Contribution Of Working Group I To The Fourth Assessment Report of The Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK: Ed. Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor MMB, LeRoy Miller Jr H, Chen Z).
  • Çiçek İ, Ataol M 2009. Türkiye’nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım. Coğrafi Bilimler Dergisi, 7(1): 51-64.
  • Danneberg J 2012. Changes in Runoff Time Series in Thuringia, Germany-Mann-Kendall Trend Test and Extreme Value Analysis, Advances in Geosciences, (31): 49-56.
  • Das Y 2015. Water Balance and Climatic Classification of a Tropical City Delhi India. American Journal of Water Resources, 3(5): 124-146.
  • Eimanifar A, Mohebbi F 2007. Urmia Lake (northwest Iran): a Brief Review. Saline System, (3):1–8.
  • Fazel N, Torabi Haghighi A, Kløve B 2017. Analysis of Land Use and Climate Change Impacts by Comparing River Flow Records in Headwater and Lowland Streams of Lake Urmia Basin, Iran, Global and Planetary Change, (158): 47-56.
  • Garousi V, Najafi A, Samadi A, Rasouli K, Khanaliloo B 2013. Environmental Crisis in Lake Urmia, Iran: a Systematic Review of Causes, Negative Consequences and Possible Solutions. 6th International Perspective on Water Resources and the Environment (IPWE) Izmir, Turkey.
  • Golian S, Mazdiyasni O, AghaKouchak A 2015. Trends in Meteorological and Agricultural Droughts in Iran. Theor Appl Climatol, (119): 679-688.
  • Hassanzadeh E, Zarghami M, Hassanzadeh Y 2012. Determining the Main Factors in Declining the Urmia Lake Level by Using System Dynamics Modeling. Water Resource Managment, (26):129-145.
  • Khalaf Tabrizi MH 1963. Borhan Qaate (Persian dictionary), second ed. Tehran, Rashidieh.
  • Kum G 2011. İklim Değişikliğinin Türkiye'nin Güneybatı Kıyılarında Turizm Konfor Şartlarına Etkileri. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü Basılmamış Doktora Tezi, İstanbul.
  • Longobardi A, Vllani P 2010. Trend Analysis of Annual and Seasonal Rainfall Time Series in the Mediterranean Area. International Journal of Climatology, (30): 1538-1546.
  • Madani Larijani K 2005. Iran’s Water Crisis; Inducers, challenges and Counter-Measures. ERSA 45th Congress of the European Regional Science Association, Amsterdam, Netherlands.
  • Madani K 2014. Water Management in Iran: What is Causing the Looming Crisis?. Journal of Environmental Studies Science, 4(4): 315-328.
  • Madani, K, AghaKouchak A, Mirchi A 2016. Iran’s Socio-economic Drought: Challenges of a Water-Bankrupt Nation, Iranian Studies, 49(6), 997–1016.
  • Modares, R, Sarhadi, A 2009. Rainfall Trends Analysis of Iran in the Last Half of the Twentieth Century, Journal of Geophysıcal Research, (114): 1-9.
  • Mohebbi F, Ahmadi R, Azari AM, Esmaili L, Asadpour Y 2011. On the red coloration of Urmia Lake (Northwest Iran). International Journal of Aquatic Science, (2):88–92.
  • Mondal A., Kundu S, Mukhopadhyay A 2012. Rainfall Trend Analysis by Mann-Kendall Test: A Case Study of North-Eastern Part of Cuttack District, Orissa. International Journal of Geology, Earth and Environmental Sciences, 2(1): 70-78.
  • Pamuk Mengü G, Anaç S, Özçakal E 2011. Drought Management Strategies. Ege Üniversitesi Ziraat Fakültesi Dergisi, 48(2): 175-181.
  • Raziei T, Bordi I, Pereira LS 2008. A Precipitation-Based Regionalization Forwestern Iran and Regional Drought Variability. Hydrol. Earth Syst. Sci., (12): 1309–1321.
  • Samaniego L, Schulz K 2009. Supervised Classification of Agricultural Land Cover Using a Modified k-NN Technique (MNN) and Landsat Remote Sensing Imagery. Remote Sensing, (1): 875-895.
  • Soltani, S, Saboohi, R, Yaghmaei L 2012. Rainfall and Rainy Days Trend in Iran, Climatic Change, 110( 1-2): 187-213.
  • Şen Z. 2002. İstatistik Veri İşleme Yöntemleri (Hidroloji ve Meteoroloji). Su Vakfı Yayınları, İstanbul.
  • Torabi Haghighi A, Kløve B 2017. Design of Environmental Flow Regimes to Maintain Lakes and Wetlands in Regions with High Seasonal Irrigation Demand, Ecol.Eng., (100): 120-129.
  • Türkeş M 1996. Spatial and Temporal Analysis of Annual Rainfall Variations in Turkey. International Journal of Climatology, (16): 1057-1076.
  • van der Schrier G, Jones PD, Briffa KR 2011. The Sensitivity of the PDSI to the Thornthwaite and Penman‐Monteith Parameterizations for Potential Evapotranspiration. Journal of Geophysical Research, (116): 1-16.
  • Wilhite DA, Glantz MH 1985. Understanding the Drought Phenomenon: the Role of Definitions, Water International, (10): 111–120.
  • Xu CY, Singh VP 1998. A Review on Monthly Water Balance Models for Water Resources Investigations. Water Resources Management, (12): 31-50.
  • Zeinoddini M, Bakhtiari A, Ehteshami M 2015. Long-term İmpacts from Damming and Water Level Manipulation on Flow and Salinity Regimes in Lake Urmia, Iran. Water and Environ Journal, 29(1): 71-87.

Kavar Depresyonu’nda (İran) Arazi Kullanımındaki Değişimler ile Kuraklık Arasındaki İlişkiler

Yıl 2018, , 397 - 406, 15.06.2018
https://doi.org/10.18016/ksudobil.343124

Öz

Çok boyutlu olan kuraklık her ne kadar temelde meteorolojik
kökenli ise de insan faaliyetlerinin de önemli ölçüde etkilediği bir olaydır.
Özellikle yüksek miktarda su isteyen bitkilerin düşük yağış ve yüksek sıcaklık
değerlerinin olduğu alanlarda sulama yöntemiyle üretime başlanması, öncelikle
yer altı suyu seviyesini düşürmekte ardından tarımsal kuraklığa neden
olmaktadır. Çalışmaya konu olan Kavar depresyonu (İran) hatalı ürün seçimi ve
su noksanlığı nedeniyle günümüzde benzer sorunlarla karşı karşıyadır. Bunu
belirlemek amacıyla öncelikle çalışma sahasının 1975-2017 yılları arasındaki
arazi kullanımındaki değişimleri ele alınmıştır. Landsat uydu görüntülerinden
elde edilen veriler işlenerek çalışma sahasında sulama ile üretimi gerçekleşen
alanların zamansal değişimi ortaya konulmuştur. Öte yandan yörenin yağış,
sıcaklık, buharlaşma ve su noksanlığı da belirlenmiştir. Ayrıca bölgede
ürünlerin hektar başına su kullanım değerlerine de ulaşılmıştır. Böylece arazi
kullanımındaki değişimlerin yanında depresyonun iklim elemanlarındaki
değişimler de ortaya konulmuştur. Sonuçta 1975’ten günümüze hızla artan sulu
tarım alanlarının toplam su istekleri ile depresyonun mevcut su potansiyeli
arasındaki ilişki ele alınmış ve bu bağlamda 
çeşitli çıkarımlarda bulunularak geleceğe yönelik tahminler ve çözüm
önerilerinde bulunulmuştur. Çalışmada Landsat 4, 5 ve 8 verileri uzaktan
algılama teknikleriyle işlenirken, iklim verileri için nonparamedik
Mann-Kendall test korelasyonu ve Thornthwaite Metodu kullanılmıştır.

Kaynakça

  • Abbaspour M, Javid AH, Mirbagheri SA, Ahmadi Givi F, Moghimi P 2012. Investigation of Lake Drying Attributed to Climate Change. Int. J. Environ. Sci. Techno. (9): 257–266.
  • Ahmad A 2012. Analysis of Maximum Likelihood Classification on Multispectral Data. Applied Mathematical Sciences, 6(129): 6425-6436.
  • Al Buhairi MH 2010. Analysis of Monthly, Seasonal and Annual Air Temperature Variability and Trends in Taiz City-Republic of Yemen. Journal of Environmental Protection (1): 401-409.
  • Ahmad AT, Abu Mansour A 1940. Loqat Fors (Persian Dictionary), Tehran, Majles.
  • Ardakanian R 2003. An Overwiev of Water Mannagment in Iran. Dushanbe International Fresh Water Forum, Tajikistan.
  • Avcı M 2001. Kuraklık Etkilerinin Azaltılmasında Kuraklığa Dayanıklı Bitki Çeşit Islahı ve Kurak Koşullarda Yetiştirme Teknikleri. (Orta Anadolu'da Kuraklık Şartlarında Yetiştirme Stratejileri, TEMA yayınları, Ankara: T. Vakfı içinde) 74-97.
  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held R, Jones R, Kolli RK, Kwon WK, Laprise R, Magana Rueda V, Mearns L, Menendez CG, Räisänen J, Rinke A, Sarr A, Whetton P, Arritt R, Benestad R, Beniston M, Bromwich D, Cay, D, Comis, J, de Elia R, Dethloff K 2007. Regional Climate Projections. (Climate Change 2007: The Physical Science Basis. Contribution Of Working Group I To The Fourth Assessment Report of The Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK: Ed. Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor MMB, LeRoy Miller Jr H, Chen Z).
  • Çiçek İ, Ataol M 2009. Türkiye’nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım. Coğrafi Bilimler Dergisi, 7(1): 51-64.
  • Danneberg J 2012. Changes in Runoff Time Series in Thuringia, Germany-Mann-Kendall Trend Test and Extreme Value Analysis, Advances in Geosciences, (31): 49-56.
  • Das Y 2015. Water Balance and Climatic Classification of a Tropical City Delhi India. American Journal of Water Resources, 3(5): 124-146.
  • Eimanifar A, Mohebbi F 2007. Urmia Lake (northwest Iran): a Brief Review. Saline System, (3):1–8.
  • Fazel N, Torabi Haghighi A, Kløve B 2017. Analysis of Land Use and Climate Change Impacts by Comparing River Flow Records in Headwater and Lowland Streams of Lake Urmia Basin, Iran, Global and Planetary Change, (158): 47-56.
  • Garousi V, Najafi A, Samadi A, Rasouli K, Khanaliloo B 2013. Environmental Crisis in Lake Urmia, Iran: a Systematic Review of Causes, Negative Consequences and Possible Solutions. 6th International Perspective on Water Resources and the Environment (IPWE) Izmir, Turkey.
  • Golian S, Mazdiyasni O, AghaKouchak A 2015. Trends in Meteorological and Agricultural Droughts in Iran. Theor Appl Climatol, (119): 679-688.
  • Hassanzadeh E, Zarghami M, Hassanzadeh Y 2012. Determining the Main Factors in Declining the Urmia Lake Level by Using System Dynamics Modeling. Water Resource Managment, (26):129-145.
  • Khalaf Tabrizi MH 1963. Borhan Qaate (Persian dictionary), second ed. Tehran, Rashidieh.
  • Kum G 2011. İklim Değişikliğinin Türkiye'nin Güneybatı Kıyılarında Turizm Konfor Şartlarına Etkileri. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü Basılmamış Doktora Tezi, İstanbul.
  • Longobardi A, Vllani P 2010. Trend Analysis of Annual and Seasonal Rainfall Time Series in the Mediterranean Area. International Journal of Climatology, (30): 1538-1546.
  • Madani Larijani K 2005. Iran’s Water Crisis; Inducers, challenges and Counter-Measures. ERSA 45th Congress of the European Regional Science Association, Amsterdam, Netherlands.
  • Madani K 2014. Water Management in Iran: What is Causing the Looming Crisis?. Journal of Environmental Studies Science, 4(4): 315-328.
  • Madani, K, AghaKouchak A, Mirchi A 2016. Iran’s Socio-economic Drought: Challenges of a Water-Bankrupt Nation, Iranian Studies, 49(6), 997–1016.
  • Modares, R, Sarhadi, A 2009. Rainfall Trends Analysis of Iran in the Last Half of the Twentieth Century, Journal of Geophysıcal Research, (114): 1-9.
  • Mohebbi F, Ahmadi R, Azari AM, Esmaili L, Asadpour Y 2011. On the red coloration of Urmia Lake (Northwest Iran). International Journal of Aquatic Science, (2):88–92.
  • Mondal A., Kundu S, Mukhopadhyay A 2012. Rainfall Trend Analysis by Mann-Kendall Test: A Case Study of North-Eastern Part of Cuttack District, Orissa. International Journal of Geology, Earth and Environmental Sciences, 2(1): 70-78.
  • Pamuk Mengü G, Anaç S, Özçakal E 2011. Drought Management Strategies. Ege Üniversitesi Ziraat Fakültesi Dergisi, 48(2): 175-181.
  • Raziei T, Bordi I, Pereira LS 2008. A Precipitation-Based Regionalization Forwestern Iran and Regional Drought Variability. Hydrol. Earth Syst. Sci., (12): 1309–1321.
  • Samaniego L, Schulz K 2009. Supervised Classification of Agricultural Land Cover Using a Modified k-NN Technique (MNN) and Landsat Remote Sensing Imagery. Remote Sensing, (1): 875-895.
  • Soltani, S, Saboohi, R, Yaghmaei L 2012. Rainfall and Rainy Days Trend in Iran, Climatic Change, 110( 1-2): 187-213.
  • Şen Z. 2002. İstatistik Veri İşleme Yöntemleri (Hidroloji ve Meteoroloji). Su Vakfı Yayınları, İstanbul.
  • Torabi Haghighi A, Kløve B 2017. Design of Environmental Flow Regimes to Maintain Lakes and Wetlands in Regions with High Seasonal Irrigation Demand, Ecol.Eng., (100): 120-129.
  • Türkeş M 1996. Spatial and Temporal Analysis of Annual Rainfall Variations in Turkey. International Journal of Climatology, (16): 1057-1076.
  • van der Schrier G, Jones PD, Briffa KR 2011. The Sensitivity of the PDSI to the Thornthwaite and Penman‐Monteith Parameterizations for Potential Evapotranspiration. Journal of Geophysical Research, (116): 1-16.
  • Wilhite DA, Glantz MH 1985. Understanding the Drought Phenomenon: the Role of Definitions, Water International, (10): 111–120.
  • Xu CY, Singh VP 1998. A Review on Monthly Water Balance Models for Water Resources Investigations. Water Resources Management, (12): 31-50.
  • Zeinoddini M, Bakhtiari A, Ehteshami M 2015. Long-term İmpacts from Damming and Water Level Manipulation on Flow and Salinity Regimes in Lake Urmia, Iran. Water and Environ Journal, 29(1): 71-87.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm ARAŞTIRMA MAKALESİ (Research Article)
Yazarlar

Ali Torabi Haghıghı 0000-0002-5157-0156

Mehmet Emin Sönmez 0000-0003-2940-3308

Nasim Fazel 0000-0002-3922-0524

Bjorn Klove 0000-0002-2353-1440

Yayımlanma Tarihi 15 Haziran 2018
Gönderilme Tarihi 12 Ekim 2017
Kabul Tarihi 5 Aralık 2017
Yayımlandığı Sayı Yıl 2018

Kaynak Göster

APA Haghıghı, A. T., Sönmez, M. E., Fazel, N., Klove, B. (2018). Kavar Depresyonu’nda (İran) Arazi Kullanımındaki Değişimler ile Kuraklık Arasındaki İlişkiler. Kahramanmaraş Sütçü İmam Üniversitesi Tarım Ve Doğa Dergisi, 21(3), 397-406. https://doi.org/10.18016/ksudobil.343124

21082



2022-JIF = 0.500

2022-JCI = 0.170

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