Volume 23, Issue 68 (3-2023)
jgs 2023, 23(68): 243-257 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Ebadi Nehari Z, Erfanian M, Kazempour Choursi S. (2023). A new method for evaluation and comprehensive drought Monitoring in the Urmia Lake Basin using a Synthesized Drought Index (SDI). jgs. 23(68), : 14 doi:10.52547/jgs.23.68.243
URL: http://jgs.khu.ac.ir/article-1-3290-en.html
URL: http://jgs.khu.ac.ir/article-1-3290-en.html
1- Masters Degree in Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran, Faculty of Natural Resources
2- Associate Professor, Watershed Management Engineering, Faculty of Natural Resources, Urmia University, Urmia, Iran, Faculty of Natural Resources ,m.erfanian@urmia.ac.ir
3- Watershed Science and Engineering Student, Faculty of Natural Resources, Urmia University, Urmia, Iran, Faculty of Natural Resources
2- Associate Professor, Watershed Management Engineering, Faculty of Natural Resources, Urmia University, Urmia, Iran, Faculty of Natural Resources ,
3- Watershed Science and Engineering Student, Faculty of Natural Resources, Urmia University, Urmia, Iran, Faculty of Natural Resources
Abstract: (7775 Views)
Drought is a complex phenomenon caused by the breaking of water balance and it has always an impact on agricultural, ecological and socio-economic spheres. Although the drought indices deriving from remote sensing data have been used to monitor meteorological or agricultural drought, there are no indices that can suitably reflect the comprehensive information of drought from meteorological to agricultural aspects. In this study, the synthesized drought index (SDI) as a synthesized index from the vegetation condition index (VCI), temperature condition index (TCI) and precipitation condition index (PCI) were used for comprehensive drought monitoring in the Urmia Lake Basin (ULB) based on the Principal Component Analysis (PCA). For this purpose, MOD13A3, MOD11A2 and TRMM 3B43 data series were downloaded y for the period of 2001–2012. After initial processing, drought indicators were calculated using LST NDVI and TRMM data, and monthly drought severity maps were prepared. In order to validate SDI index, the Correlation relationship between SDI and SPI indices was obtained in the 3 month period during the growing season. As well as, SDI correlation relationships were investigated with wheat and barley crop yields. The results indicate that drought occurred in 2008 and 2001 in the ULB. The results of validation show that there is a correlation of 80% between the two SDI and SPI indicators. Also, the results of this study showed that the SDI index, as a comprehensive index of drought monitoring, reflects the effects of drought on agriculture.
Article number: 14
Type of Study: Research |
Subject:
climatology
References
1. پیشنماز احمدی، مجید، هوشمند، علی و زمانی، فهمیمه، (1396)، پایش خشکسالی شمال غرب کشور با استفاده از داده¬های MODIS و TRMM. بیست و چهارمین همایش ملی ژئوماتیک، اردیبهشت 1396.
2. درویشی خاتونی، جواد، صالحی پور میلانی، علیرضا و محمدي، علی، (1393)، گزارش لیمنولوژي و پالئولیمنولوژي دریاچه ارومیه اقلیم، زمین شناسی، هیدرولوژي و سنجش از راه دور. معاونت زمین¬شناسی مدیریت زمین شناسی دریایی گروه رسوب شناسی، 95 ص.
3. زمانیان، محمدتقی، بهیار، محمدباقر، کریمی حسینی، آزاده و وظیفه دوست، مجید، (1391)، پایش و تحلیل خشکسالی کشاورزی با استفاده از تولیدات ماهواره¬ای سنجنده NOAA-AVHRR، نشریه پژوهش¬های اقلیم شناسی، 3(9): 54-43.
4. رضایی¬مقدم، محمدحسین، ولیزاده¬کامران، خلیل، رستم¬زاده، هاشم و رضایی، علی، (1391)، ارزیابی کارایی داده-های سنجنده¬ MODIS در برآورد خشکسالی (مطالعه¬ی موردی: حوضه¬ی آبریز دریاچه ارومیه)، مجله جغرافیا و پایداری محیط، (5): 52-37.
5. موذن¬زاده، روزیه، ارشد، صالح، قهرمان، بیژن و داوری، کامران، (1391)، پایش خشکسالی در کشت¬های غیرآبی با استفاده از تکنیک سنجش از دور، مدیریت آب و آبیاری، 2(2):52-39.
6. Bhuiyan, C. (2008). Desert Vegetarian during Droughts: Response and Sensitivity, the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(8): 907-912.
7. Chaves, M.M, Pereira, J.S, Maroco, J, Rodrigues, M.L, Ricardo, C.P.P, Osório, M.L, Carvalho, I, Faria, T, Pinheiro, C. (2002). How Plants Cope with Water Stress in the Field? Photosynthesis and Growth, Annals of botany, 89(7): 907-916. [DOI:10.1093/aob/mcf105] [PMID] []
8. Elhag, K, Zhang, W. (2018). Monitoring and Assessment of Drought Focused on Its Impact on Sorghum Yield over Sudan by Using Meteorological Drought Indices for the Period 2001-2011, Remote Sensing, 10(8), 1231. [DOI:10.3390/rs10081231]
9. Heim, R.R. (2002). A Review of Twentieth-Century Drought Indices Used in the United States, Bulletin of the American Meteorological Society, 83(8): 1149-1166. [DOI:10.1175/1520-0477-83.8.1149]
10. Du, L, Tian, Q, Yu, T, Meng, Q, Jancso, T, Udvardy, P, Huang, Y. (2012). A Comprehensive Drought Monitoring Method Integrating MODIS and TRMM Data, International Journal of Applied Earth Observation and Geoinformation, 23: 245-253. [DOI:10.1016/j.jag.2012.09.010]
11. Keyantash, J, Dracup, J. A. (2002). The Quantification of Drought: An Evaluation of Drought Indices, Bulletin of the American Meteorological Society, 83(8): 1167-1180. [DOI:10.1175/1520-0477-83.8.1167]
12. Kim, Y, Lee, S. B, Yun, H, Kim, J, Park, Y. (2017). A Drought Analysis Method Based on Modis Satellite Imagery and AWS Data. In Geoscience and Remote Sensing Symposium (IGARSS), 2017 IEEE International (pp. 4862-4865). IEEE [DOI:10.1109/IGARSS.2017.8128092]
13. Kogan, F.N, (1995). Application of Vegetation Index and Brightness Temperature for Drought Detection, Advances in Space Research, 15(11): 91-100. [DOI:10.1016/0273-1177(95)00079-T]
14. Mastrangelo, A.M, Mazzucotelli, E, Guerra, D, De Vita, P, Cattivelli, L. (2012). Improvement of Drought Resistance in Crops: From Conventional Breeding to Genomic Selection, Crop Stress and Its Management: Perspectives and Strategies. Springer, 225-259. [DOI:10.1007/978-94-007-2220-0_7]
15. Rhee, J., Im, J., Carbone, G.J. (2010). Monitoring agricultural drought for arid and humid regions using multisensor remote sensing data, Remote Sensing of Environment, (114): 2875-2887. [DOI:10.1016/j.rse.2010.07.005]
16. Torry, W.I. (1986). Economic Development, Drought, and Famines: Some Limitations of Dependency Explanations, GeoJournal 12(1), 5-18. [DOI:10.1007/BF00213018]
17. Tsakiris, G, Pangalou, D, Vangelis, H. (2007). Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI), Water Resource. Manage. 21(5), 821-833. [DOI:10.1007/s11269-006-9105-4]
18. Udelhoven, T, Stellmes, M, Del Barrio, G, Hill, J. (2009). Assessment of Rainfall and NDVI Anomalies in Spain (1989-1999) Using Distributed Lag Models, International Journal of Remote Sensing, 30(8): 1961-1976. [DOI:10.1080/01431160802546829]
19. Yaduvanshi, A, Srivastava, P. K, Pandey, A. C. (2015). Integrating TRMM and MODIS Satellite with Socio-economic Vulnerability for Monitoring Drought Risk over a Tropical Region of India, Physics and Chemistry of the Earth, Parts A/B/C, 83: 14-27. [DOI:10.1016/j.pce.2015.01.006]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)