پایش مکانی و زمانی خشکسالی کشاورزی در اراضی تحت کشت گندم با استفاده از شاخص بارش استاندارد‌شده (مطالعه موردی غرب استان گلستان)

نوع مقاله : علمی - پژوهشی

نویسندگان

دانشگاه علوم کشاورزی و منابع طبیعی گرگان

چکیده

مدیریت منطقی برای مقابله با خشکسالی، ایجاد نظام مدیریتی و ارائه اطلاعات صحیح در مقیاس‏های زمانی مختلف امری لازم و ضروری است. شاخص­های خشکسالی از طریق ارزیابی ساده و کمّی این پدیده، ابزار کارآمدی برای تحلیل خشکسالی هستند. این مطالعه با هدف پایش مکانی و زمانی خشکسالی کشاورزی در اراضی گندم با استفاده از شاخص بارش استاندارد­شده (SPI) در غرب استان گلستان انجام شد. برای این منظور، در سال‏های 1379 تا 1395 شهرستان­های آق‌قلا، علی‏آباد کتول، گرگان، بندر‏ گز، بندر ‏ترکمن و کردکوی از آمار بارندگی 15 ایستگاه با طول دوره آماری (30 ساله) مشترک از سال 1363 تا 1395 استفاده شد. پس از محاسبه شاخص بارش استاندارد­شده و همبستگی بهتر شاخص SPI سه ماهه منتهی به اردیبهشت‏ماه با میانگین عملکرد گندم، نقشه این شاخص با روش درون­یابی‏ کریجینگ معمولی تهیه و پهنه­بندی شد و سپس به ارزیابی و بررسی خشکسالی پرداخته شد. برای تهیه نقشه ریسک خشکسالی ابتدا نقشه‌های شاخص SPI3 منتهی به اردیبهشت‏ماه طی یک دوره 17 ساله (1379 تا 1395) به‌صورت دودویی (بولین) طبقه‏بندی شدند. سپس از ترکیب نقشه­های بولینی به‌دست آمده نقشه فراوانی وقوع خشکسالی تهیه شد. با استفاده از نقشه­های احتمال فراوانی خشکسالی شاخص­ SPI، نقشه ریسک خشکسالی کشاورزی نهایی تولید شد. با بررسی نقشه‏های شدت خشکسالی و ریسک خشکسالی در این مطالعه، شاخص SPI سه‌ماهه جهت بررسی الگوهای خشکسالی در ابعاد زمانی و مکانی مختلف و شدت آن در دوره‏های خشکسالی و مرطوب مؤثر شناخته شد. هم‌چنین، نتایج نشان داد که شش شهرستان مورد مطالعه در استان گلستان به دو منطقه خطرپذیر از نظر خشکسالی (شامل خطر شدید و خیلی شدید) طبقه‏بندی شده‏است. نقشه ریسک نشان می‏دهد که در دوره آماری 1379 تا 1395 بخش گسترده‏ای از منطقه مطالعاتی (حدود 98 درصد) در معرض خطر خشکسالی شدید قرار گرفته ‏است. هم‌چنین بخش کوچکی از شمال شهرستان بندر ترکمن (حدود دو درصد از کل منطقه) خطر خشکسالی بسیار شدید را تجربه کرده‏است. در واقع دامنه نوسانات خشکسالی در این منطقه به‌دلیل هم­جواری با صحرای ترکمنستان و وضعیت آب‌وهوایی خشک و نیمه­خشک بیش‌تر بوده و این مناطق دارای پتانسیل حساسیت به خشکسالی می‏باشند. نتایج نشان داد عملکرد گندم در شهرستان‏های آق‏قلا، علی‏آباد کتول، بندر‏گز، گرگان و کردکوی همبستگی مثبت و معنی­داری با مقادیر SPI3 منتهی به اردیبهشت ماه داشت. این رابطه می­تواند هشداری برای تأثیر خشکسالی هواشناسی (به‌خصوص در مناطق مستعد خشکسالی) بر تولید محصولات کشاورزی باشد و نشان می­دهد که SPI3 می­تواند به پیش­بینی کاهش تولید ناشی از خشکسالی کمک کند.

کلیدواژه‌ها


عنوان مقاله [English]

Spatial and Temporal Monitoring of Agricultural Drought in the Wheat Cultivated Area using Standard Precipitation Index (Case Study: West of Golestan Province)

نویسندگان [English]

  • parisa alizadeh
  • behnam kamkar
  • Shaban shataee
  • hosien kazemi
Gorgan University of Agricultural Sciences and Natural Resources
چکیده [English]

Introduction
Drought is not a characteristic of a region and may occur in any weather regime. Therefore, reasonable management is required to deal with this natural disaster which can be creating a management system and providing accurate information at different time scales. Meteorological, agricultural, hydrological and socioeconomic drought are defined based on lack of rainfall, lack of soil moisture, shortage of rivers stream and the shortage of some commodities affected by the drought trend. One of the effective methods for analyzing various kinds of drought is the evaluation of drought indices, which aims to provide a simple and quantitative assessment of drought characteristics. The purpose of this research is to investigate the Spatial and temporal monitoring of agricultural drought in the Wheat cultivated area using standard precipitation index in west of Golestan province.
Material and Methods
In this research, in order to monitor the spatial and temporal distribution of drought in the years of 2000 to 2016 in AQ-Qala, Ali Abad, Gorgan, Bandar-e- Gaz, Bandar-e- Torkaman and Kordkouy counties, 15 meteorological stations with common statistical database (1984 to 2016) were used to estimate the rainfall. After calculating the standard precipitation index (hereafter SPI) and more reliable correlation of May’s three-month SPI index (hereafter SPI3) with the mean wheat yield, this index was zoned with ordinary Kriging interpolation method and then drought was assessed. In order to prepare a drought risk map, SPI3 rasters were reclassified as binary (BOOLEAN) for a time span of 17 years (2000 to 2016). Then, a map of the drought frequency was provided by the overlaying of Boolean maps. Using drought frequency maps of the SPI index, a final agricultural drought risk map was generated.
Results and Discussion
In 2000, 88% of the total area were affected by moderate drought and another 12% (the majority of which was in Aliabad) was affected by moderate classes of drought. But in 2007 and 2016 there was no drought in the investigated counties. In this research, by studying the drought severity and drought risk maps, it was clarified that the SPI index was an effective index in evaluating the drought patterns in different temporal and spatial scales and during drought periods. Also, the results showed that six studied counties in Golestan Province were classified into two risky drought areas (including severe and extreme classes). Risk map showed that in the applied statistical time period (2000 to 2016), an extensive part of the study area (about 98%) is at extreme risk class. Also, a small northern part of the Bandar-e-Torkaman (about 2% of the total area) has experienced an extreme drought. In fact, the magnitude of the drought range in this region is greater due to coexistence with the Turkmen desert and its dry and semiarid weather conditions, which leads to a potential for drought sensitivity.  
Conclusion
The results revealed a positive correlation between wheat yield and SPI3 in AQ-Qala, Ali Abad, Gorgan, Bandar-e- Gaz, and Kordkouy counties. The effect of meteorological drought on the crop production can be a concern (especially in drought-prone areas) and suggests that SPI3 can be helpful for predicting drought-induced yield loss. These results indicate that the western region of Golestan province is one of the areas where droughts will increase in the future. Therefore, rain-fed cropping systems will be in danger in the future, and some of the agroecosystems currently dedicated to the cultivation of rain-fed products will be excluded from the production process. rainfall reduction in recent years, has been led to retreat the Caspian Sea in Bandar-e-Torkaman area, as well as the eliminating of many crops in recent years, which reveals that the consequences of these droughts have been emerged.  Therefore, agricultural policy makers need to consider the replacement of crops with high efficient water usage instead of current ones in cropping patterns in the coming years, as well as be concerned more about land salinization.

کلیدواژه‌ها [English]

  • SPI index
  • Drought severity
  • Drought risk
  • yield
Arshad, S., Morid, S., Mobasheri, M.R., and Alikhani, M.A. 2007. Development of Agricultural Drought Risk Assessment Model for Kermanshah Province (Iran), using satellite data and intelligent methods. Proceeding: The First International Conference on Drought Management, Zaragoza, Spain, pp. 303-310.
Barua, S. 2010. Drought assessment and forecasting using a nonlinear aggregated drought index. PhD Dissertation, Victoria University, Australia.
Bazrafshan, A. 2006. Management and zoning of drought risk using standard rainfall index. 2nd International Conference on Integrated Natural Disaster Management. (In Persian)
Bazrafshan, O., Mohseni, S.M., Malekian, A., and Moeini, A. 2011. A study on drought characteristics of Golestan province using standardized precipitation index (SPI). Iranian Journal of Range and Desert Reseach 18 (3): 395-407. (In Persian with English Summary)
Carrao, H., Naumann, G., and Barbosa, P. 2016. Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability. Global Environmental Change 39: 108-124.
Chaudhari, K., and Dadhwal, V. 2004. Assessment of impact of drought-2002 on the production of major kharif and rabi crops using standardized precipitation index. Journal of Agrometeorology 6: 10-15.
Deihimfard, R., Eyni, N.H., and Haghighat, M. 2016. Zoning of drought incident in Fars province under climate change conditions using standardized precipitation index. Journal of Agroecology 7 (4): 528-546. (In Persian with English Summary)
Du, L., Tian, Q., Yu, T., Meng, Q., Jancso, T., Udvardy, P., and Huang, Y. 2013. A comprehensive drought monitoring method integrating MODIS and TRMM data. International Journal of Applied Earth Observation and Geoinformation 23, 245-253.
Eivazi, M., and Mosaedi, A., 2011. Monitoring and spatial analysis of meteorological drought in Golestan province using geostatistical methods. Iranian Journal of Natural Resources 64(1): 65-78. (In Persian with English Summary)
Gonfa, L. 1996. Climate Classification of Ethiopia, In: Meteorological Research Report Series 3: 1-8.
Hao, C., Zhang, J., and Yao, F. 2015. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China. International Journal of Applied Earth Observation and Geoinformation 35: 270-283.
Heim Jr, R.R. 2002. A review of twentieth-century drought indices used in the United States. Bulletin of the American Meteorological Society 83: 1149-1165.
Iranian Space Agency. 2017. Available at Web site www.isa.ir (verified 5 September 2017). (In Persian)
Khosravi, H., Haydari, E., Shekoohizadegan, S., and Zareie, S. 2017. Assessment the effect of drought on vegetation in desert area using landsat data. The Egyptian Journal of Remote Sensing and Space Science 20: S3-S12. (In Persian with English Summary)
Łabędzki, L., and Bąk, B. 2014. Meteorological and agricultural drought indices used in drought monitoring in Poland: a review. Meteorology Hydrology and Water Management. Research and Operational Applications 2.
Loukas, A., Vasiliades, L., and Dalezios, N. 2003. Intercomparison of meteorological drought indices for drought assessment and monitoring in Greece. Proceedings of the International Conference on Environmental Science and Technology pp. 484-491.
Manatsa, D., Mukwada, G., Siziba, E., and Chinyanganya, T. 2010. Analysis of multidimensional aspects of agricultural droughts in Zimbabwe using the Standardized Precipitation Index (SPI). Theoretical and Applied Climatology 102: 287-305.
Mathbout, S., Lopez-Bustins, J.A., Martin-Vide, J., Bech, J., and Rodrigo, F.S. 2018. Spatial and temporal analysis of drought variability at several time scales in Syria during 1961–2012. Atmospheric Research 200: 153-168.
McKee, T.B., Doesken, N.J., and Kleist, J. 1993. The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology. American Meteorological Society Boston, MA, pp. 179-183.
Mirabbasi, R., Anagnostou, E.N., Fakheri-Fard, A., Dinpashoh, Y., and Eslamian, S. 2013. Analysis of meteorological drought in northwest Iran using the Joint Deficit Index. Journal of Hydrology 492: 35-48. (In Persian with English Summary)
Mishra, A.K., and Singh, V.P. 2011. Drought modeling–A review. Journal of Hydrology 403: 157-175.
Mkhabela, M., Bullock, P., Gervais, M., Finlay, G., and Sapirstein, H. 2010. Assessing indicators of agricultural drought impacts on spring wheat yield and quality on the Canadian prairies. Agricultural and Forest Meteorology 150: 399-410.
Moradi, P. 2014. Drought trend study using climatic indices and remote sensing data in Golestan province. Master's Thesis, Faculty of Agriculture, University of Zabol. Iran. (In Persian with English Summary)
Mosaedi, A., KhaliliZadeh, M., and Mohammadi, O.A. 2008. Drought monitoring in Golestan province.Final report from Research Project, Gorgan University of Agricultural Sciences and Natural Resources. p. 17. (In Persian with English Summary)
Naresh Kumar, M., Murthy, C., Sesha Sai, M., and Roy, P. 2012. Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index. Meteorological Applications 19: 256-264.
Patel, N., Chopra, P., and Dadhwal, V. 2007. Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorological Applications 14: 329-336.
Potop, V., Türkott, L., Kožnarova, V., and Možný, M. 2010. Drought episodes in the Czech Republic and their potential effects in agriculture. Theoretical and Applied Climatology 99: 373-388.
Quiring, S.M., and Ganesh, S. 2010. Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas. Agricultural and Forest Meteorology 150: 330-339.
Sarabi, S., Heshmatpour, A., Komaki, B., and Tahmasebi, A. 2015. Relationship between MODIS vegetation indices and drought in northern rangelands of Golestan province. Iranian Journal of Range and Desert Research 22: 392-405. (In Persian with English Summary)
Sarhadi, A., Soltani, K.S., and Modares, R. 2008. The analysis of drought extension over Isfahan province based on four drought indices. Iranian of Journal Natural Research 61 (3): 555-570. (In Persian with English Summary)
Shahabfar, A., Ghulam, A., and Eitzinger, J. 2012. Drought monitoring in Iran using the perpendicular drought indices. International Journal of Applied Earth Observation and Geoinformation 18: 119-127.
Shahid, S. 2008. Spatial and temporal characteristics of droughts in the western part of Bangladesh. Hydrological Processes 22: 2235-2247.
Son, N., Chen, C., Chen, C., Chang, L., and Minh, V. 2012. Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation 18: 417-427.
Subash, N., Mohan, H.R., and Banukumar, K. 2011. Comparing water-vegetative indices for rice (Oryza sativa L.)–wheat (Triticum aestivum L.) drought assessment. Computers and Electronics in Agriculture 77: 175-187.
Tabouzadeh, Sh., Zarei, H., and Bazrafshan, O. 2014. Analysis of Severity, Duration, Frequency and Zoning Map of Meteorological Drought of Bakhtegan River Basin. Journal of Irrigation Sciences and Engineering 38: 109-123.
Tsakiris, G., Pangalou, D., and Vangelis, H. 2007. Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resources Management 21: 821-833.
Vicente-Serrano, S.M., Begueria, S., and Lopez-Moreno, J.I. 2010. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate 23: 1696-1718.
Vicente‐Serrano, S.M., Cuadrat‐Prats, J.M., and Romo, A. 2006. Early prediction of crop production using drought indices at different time‐scales and remote sensing data: application in the Ebro Valley (north‐east Spain). International Journal of Remote Sensing 27: 511-518.
Wilhite, D.A. 2000. Drought as a natural hazard: concepts and definitions. Routledge Publishers: London, U.K.; pp: 3–18.
Wilhite, D.A., Svoboda, M.D., and Hayes, M.J. 2007. Understanding the complex impacts of drought: a key to enhancing drought mitigation and preparedness. Water Resources Management 21: 763-774.
Zargar, A., Sadiq, R., Naser, B., and Khan, F.I. 2011. A review of drought indices. Environmental Reviews 19: 333-349.