پایش خشکسالی کشاورزی با استفاده از شاخص خشکسالی RDI و مدل زمین آماری کریجینگ (مطالعه موردی: مناطق مرکزی و جنوبی استان فارس)

نوع مقاله: مقاله اصلی

نویسندگان

1 استادیار، گروه مهندسی آب، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران

2 استادیار، گروه مهندسی آب، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، یران

10.22034/jewe.2020.242605.1400

چکیده

خشکسالی از مهم‌ترین بلایای طبیعی است که به دلیل فراوانی رخداد نیازمند ارزیابی و پایش به‌خصوص در حوزه کشاورزی می­باشد. در پژوهش حاضر از شاخص شناسایی خشکسالی (RDI) جهت پایش خشکسالی و ارزیابی مکانی شدت آن در مناطق مرکزی و جنوبی استان فارس استفاده‌شد. رابطه شدت و مدت‌زمان تداوم خشکسالی طی سال‌های مختلف دوره آماری موردنظر (1991-1990 تا 2013-2012) موردبررسی قرار گرفت. جهت ارزیابی مکانی از مدل کریجینگ در محیط سامانه اطلاعات جغرافیایی (GIS) استفاده‌شد. براساس مقایسه میان نیم­تغییرنماهای مختلف مدل کریجینگ، مناسب‌ترین مدل انتخاب شد. بر اساس نتایج به‌دست‌آمده شدت خشکسالی، تداوم و روند آن طی دوره آماری موردمطالعه تعیین شد. نتایج نشان داد در ایستگاه‌های شهرستان‌های داراب و نیریز طی سال‌های 2000 تا 2002 و 2008 تا 2010 خشکسالی­های شدیدی رخ‌داده است. در ایستگاه‌های شهرستان‌های فسا و جهرم نیز در بیش­تر سال‌ها نوسانات اقلیمی منجر به وقوع خشکسالی با شدت‌های کم تا زیاد شده است. در ایستگاه منطقه لارستان نیز نتایج نشان داد خشکسالی‌های متعددی رخ ‌داده است و تعداد رخداد خشکسالی ها در دهه 2000 تا 2010 بسیار زیاد بوده است. در ارزیابی مکانی خشکسالی، با استفاده از مدل کریجینگ، نتایج نشان داد بر اساس مقایسه انجام‌گرفته مناسب‌ترین نیم­تغییرنما، مدل کروی است. ارزیابی آسیب‌پذیری خشکسالی در مناطق موردمطالعه نیز نشان داد مناطق شمالی شهرستان نیریز، استهبان، فسا، داراب و لارستان دچار آسیب بیش­تری گردیده‌اند. لذا استفاده از شاخص‌های خشکسالی، روش‌های پایش و پهنه‌بندی شدت خشکسالی جهت مدیریت بهتر و برنامه‌ریزی جهت پیش‌آگاهی ضروری می‌باشد و استفاده از آن جهت تصمیم‌گیری‌های مدیریت منابع آب پیشنهاد می‌شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Agricultural Drought Monitoring Using Reconnaissance Drought Index (RDI) and Kriging Geostatistical Model (Case Study: Central and Southern Regions of Fars Province)

نویسندگان [English]

  • Seyed Amir Shamsnia 1
  • Davoud Khodadadi Dehkordi 2
1 Assist. Professor, Department of Water Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
2 Assist. Professor, Department of Water Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
چکیده [English]

Drought is one of the most important natural disasters that due to the frequency of occurrence needs to be assessed and monitored, especially in the field of agriculture. In the present study, the Reconnaissance Drought Index (RDI) was used to monitor drought and spatially assess its severity in central and southern regions of Fars province. The relationship between the severity and duration of drought during different years of the statistical period (1990-1991 to 2012-2013) was investigated. Kriging model was used in the geographic information system (GIS) environment for spatial evaluation. Based on the comparison between the different semivariogram of the kriging model, the most suitable model was selected. Based on the results of drought severity, its continuity and trend were determined during the statistical period. The results showed that severe droughts occurred in Darab and Neyriz stations during 2000-2002 and 2008-2010. In Fasa and Jahrom stations, in most of the years, climate fluctuations have led to drought with low to high intensities. At Larestan station, the results also showed several droughts have occurred, especially during the years 2000 to 2010. In spatial evaluation of drought using the Kriging model, the results showed that the best semivariogram is the spherical model. The evaluation of drought vulnerability in the studied areas also showed that the northern areas of Nayriz, Estahban, Fasa, Darab and Larestan have suffered more damage. Therefore, the use of drought indices, drought intensity monitoring and mapping methods are essential for better management and planning for advance planning and it is recommended for water resources management decisions.

کلیدواژه‌ها [English]

  • Drought
  • Fars province
  • Geographic information systems
  • Semivariogram
Afzalia A., Keshtkar H., Pakzad S., Moazami N., Azizabadi Farahania E., Golpaygania A., Khosrojerdi E., Yousefi. A. and TaghiNaghilou M. (2016). Patio-Temporal analysis of drought severity using drought indices and deterministic and geostatistical methods (Case Study: Zayandehroud River Basin). Desert J., 21(2), 165-172.
Asadi Zarch M. A., Malekinezhad H., Mobin M.H., Taghi Dastorani M. and Kousari M. R. (2011). Drought Monitoring by Reconnaissance Drought Index (RDI) in Iran. Wat. Resour. Manag., 25(13), 3485-3504.
Cambardella C. A., Moorman T. B., Novak J.  M., Parkin T. B., Karlen D. L., Turco R. and Konopka A. E. (1994). Field-scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J., 58(5), 1501-1511.
Figueiredo M. A. T. (2008). Lecture notes on the EM algorithm. Instituto Superior Tecnico. 35 pp.
Fooladmand H. R., Zandilak H. and Ravanan M. H. (2008). Comparison of different types of Hargreaves equation for estimating monthly evapotranspiration in the south of Iran. Arch. Agron. Soil Sci., 54, 321–330.
Fooladmand H. R. (2011). Evaluation of some equations for estimating evapotranspiration in the south of Iran. Arch. Agron. Soil Sci., 57(7), 741-752.
Guttman N. B. (1999). Accepting the standardized precipitation index: A calculation algorithm. J. Am. Wat. Resour. Assoc., 35(2), 311-322.
Hayes M. J. and Svoboda N. D. (1999). Monitoring the 1996 drought using SPI. Bull. Am. Meteorol. Soc., 80, 429–438.
Hejazi Jahromi K., Pirmoradian N., Shamsnia S.A. and Shahidi N. (2013). Quantitative and qualitative evaluation of groundwater resources for use in irrigation systems (Case study: southern and southeastern plains of Fars province). J. Nat. Geogr., 6(19), 33-44 [In Persian].
Hejazi Jahromi K. (2014). Temporal and spatial drought monitoring by using meteorological index of RDI, spectral and thermal indices resulted of remote sensing Case study: Rainfed wheat areas in Fars Province). M. Sc. Dissertation. Shiraz Branch, Islamic Azad University. 185pp.
Isaaks H. E. and Srivastava R. M. (1989). An introduction to applied geostatisitics. Oxford University Press, New York.
Jemai S., Ellouze M., Agoubi B. and Abida H. (2016). Drought intensity and spatial variability in Gabes Watershed, south-eastern Tunisia. J. Wat. Land Develop., 31, 63-72.
Karavitis C. A., Alexandris S., Tsesmelis D. E. and Athanasopoulos G. (2011). Application of the standardized precipitation index (SPI) in Greece. Wat. J., 3, 787-805.
Li D. and Deogun J. S. (2004). Interpolation models for spatiotemporal association mining. Fundam. Inform., 59(2-3), 153-172.
Loukas A. and Vasiliades L. (2004). Probabilistic analysis of drought spatiotemporal characteristics in Thessaly Region, Greece. Nat. Hazard. Earth Syst. Sci., 4,719–731.
Masoudi M. and Barzegar S. (2015). Assessment and mapping of qualitatative and quantitative severity degradation of groundwater resourses using the modified IMDPA desertification model and GIS. A Case Study: Firuzabad Plain of Fars Province. Iran. Irrig. Wat. Eng., 5(20), 86-98 [In Persian].
Merabti A., Martins D. and Meddi M. (2018). Spatial and time variability of drought based on SPI and RDI with various time scales. Wat. Resour. Manag., 32(3), 1087-1100.
Moghimi M. M., Zarei A. and Mahmoudi M. R. (2020). Seasonal drought forecasting in arid regions, using different time series models and RDI index. Wat. Clim. Change, 11(3), 633-654.
Memon A. V. and Shah N. V. (2019). Assessment and comparison of SPI and RDI meteorological drought indices in Panchmahals District of Gujarat, India. Int. J. Curr. Microbiol. Appl. Sci., 8(8), 1995-2004.
Nicholson S. E., Davenport M. L. and Malo A. R. (1990). A comparison of vegetation response to rainfall in the Sahel and east Africa, using normalized difference vegetation index from NOAA-AVHRR. Clim. Change, 17(2-3), 209-241.
Pirmoradian N., Shamsnia S. A., Boustani F. and Shahrokhnia M. A. (2008). Evaluation of drought return period using standardized precipitation index (SPI) in Fars province, Iran. Agroecol. J., 4(13), 7-21 [In Persian]. 
Popova Z., Kercheva M. and Pereira L. S. (2006). Validation of the FAO methodology for computing ETo with limited data, application to south Bulgaria. Irrig. Drain., 55, 201–215.
Salehi V. (2018). Evaluation of the relationship between meteorological and hydrological drought and the quality of groundwater resources using SPI, SWI and SECI indices. M.Sc. Dissertation, Shiraz Branch, Islamic Azad University, Shiraz, Iran. 166 pp.
Shahidi N., Shamsnia S. A., Honar M. R. and Gholami A. R. (2009). Investigating the effect of drought on the quantitative status of groundwater in selected plains of Fars province. 2nd   National Conference on Drought Impacts and Management Strategies. Isfahan Agricultural and Natural Resources Research Center [In Persian].
Shamsnia S. A and Pirmoradian N. (2009). Rectification of the standardized precipitation index (SPI) classification for drought evaluation in Fars Province (IRAN). 2nd  India Disaster Management Congress. National Institute of Disaster Management, 4-6 November.
Shamsnia S. A., Honar M. R., Shirfath N., Zarei Z. and Adinekharat N. (2010). Determining the most appropriate model for interpolation and zoning of rainfall information using geostatistical techniques in Fars province.1st International Conference on Plant, Water, Soil & Weather Modeling International Center for Science, High Technology & Environmental Sciences Shahid Bahonar University of Kerman [In Persian].                                                                    
Shokoohi A. and Morovati R. (2015). Basinwide Comparison of RDI and SPI Within an IWRM Framework.Wat. Resour. Manag., 29(6), 2011-2026. 
Sobral B. S., Oliveira‐Júnio J. S., de Gois G. and Pereira‐Júnior E. R. (2018). Spatial variability of SPI and RDIst drought indices applied to intense episodes of drought occurred in Rio de Janeiro State, Brazil. Int. J. Clim., 38(10), 3896-3916.
Sönmez F. K., Kömüscü A. Ü., Erkan A. and Turgu E. (2005). An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat. Hazard., 35, 243–264.
Subedi M. R., Xi W., Edgar C., Rideout-Hanzak S. and Hedquist B. (2019). Assessment of geostatistical methods for spatiotemporal analysis of drought patterns in East Texas, USA. Spatial Information Research., 27, 11-21.
Tsakiris G. and Vangelis H. (2005). Establishing a drought index incorporating evapotranspiration. Europ. Water, 9/10, 3-11.
Tsakiris G., Pangalou D. and Vangelis H. (2007). Regional drought assessment based on the reconnaissance drought index (RDI). Wat. Resour. Manag., 21, 821-833.
Vangelis H., Tikas D. and Tsakiris G. (2013). The Effect of PET method on reconnaissance drought index (RDI) calculation. Mitigation in Europe. Kluwer, The Netherlands. 119–132pp.
Zandilak H., Fooladmand H.R. and Boustani F. (2014). Evaluation of the return period of wheat drought in Fars province using the index. J. Wat. Resour. Eng., 7(22), 1-10 [In Persian].
Zarei A. R., Moghimi M. M. and Mahmoudi M. R. (2016). Parametric and non-parametric trend of drought in arid and semi-arid regions using RDI index. Wat. Resour. Manag., 30(14), 5479-5500.