Multi-indicator monitoring of agricultural drought in township Kermanshah

Document Type : Original Article

Authors

1 Ph.D Candidate, Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran

2 Assistant Professor, Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran

3 Professor, Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran

4 Associate Professor, Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran

Abstract

It is necessary to study the spatial-temporal trend of drought, which affects agriculture and food supply with its slow process and Multiple generating factors; Therefore, the present study was conducted to assess agricultural drought in Kermanshah using satellite indicators (Average images of Sentinel2 and Landsat8 satellites during the growing season) and terrestrial (using rainfall and temperature data from 1990 to 2020). The results of terrestrial indicators the absence of drought in 2002, 2007, 2018 and 2019. The 12-month and 24-month SPEI of 2001 and the 24-month SPI estimated 1999 in the category of very severe drought. Satellite indicators in 2015 and 2017 increased the Land Surface Temperature and in 2019 (increasing soil surface moisture and Temperature Vegetation Dryness) and 2020 estimated vegetation density. The decrease in sugar beet yield in the years 1999 to 2003 and the increase in the years 2006 to 2009, 2012/2011 and 2021/2020 confirm the high results. In the north, northeastern and eastern regions; High temperature, low rainfall and low humidity have dried the soil and negatively affected the growth, health and density of plants, but the southern region has always been humid. The presence of drought during the study period and Sentinel II images were more sensitive to vegetation indicators.

Keywords


حلبیان، ا.ح.، خمری، ح. و علیقلی، س. ۱۳۹۲. ارزیابی شرایط آب‌وهوایی کشت چغندرقند در شهرستان کرمانشاه. اولین همایش ملی جغرافیا. شهرسازی و توسعه پایدار. تهران.
حمزه، س.، فراهانی، ز.، مهدوی، ش.، چترآبگون، ا. و غلام نیا، م. ۱۳۹۶. پایش زمانی و مکانی خشکسالی کشاورزی با استفاده از داده‌های سنجش‌ازدور موردمطالعه: استان مرکزی ایران. نشریه تحلیل فضایی مخاطرات محیطی. ۴ (۳): ۵۳-۷۰.
جهانگیر، م.ح. و مشیدی، ض. ۱۳۹۹. ارزیابی پایش خشکسالی کشاورزی مبتنی بر سنجش‌ازدور با استفاده از شاخص استاندارد شده بارش در ماه‌های رشد (مطالعه موردی: حوضه آبریز کارون بزرگ). آبیاری و زهکشی ایران . ۱۴ (۴): ۱۲۵۲-۱۲۶۴.
دهقانی تفتی، ا.ع.، زارع، م.، حسینی، س.ز.، عربی. و علی آبادی، ف. ۱۳۹۷. تعیین ارتباط روند تغییرات خشکسالی با عناصر اقلیمی در دشت یزد-اردکان. نشریه مدیریت بیابان. ۱۳: ۱-۱۴.
شاه مرادی، ص.، غفاریان مالمیر، ح. و امینی، م. ۱۴۰۰. استخراج شاخص رطوبت سطحی خاک (TVDI) با استفاده از نمودار پراکندگی دما/ پوشش گیاهی و تصاویر مودیس. فصلنامه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 12 (۱): ۳۸ – ۶۲.
صیدایی، س.ا. و رستمی، ش. ۱۳۹۱. سنجش تأثیرات اقتصادی و اجتماعی - فرهنگی توسعه گردشگری (نمونه موردی شهر کرمانشاه). برنامه‌ریزی فضایی. ۲ (۳): ۷.
کوه بنایی، ح.، یزدانی، م. ۱۳۹۷. پهنه‌بندی رطوبت خاک سطحی با استفاده از تصاویر لندست ۸ (مطالعه موردی: حومه شهر سمنان). جغرافیا و پایداری محیط. ۸ (۳)، ۲۸: ۶۵-۷۷.
لویمی، ن.، اکرم، ا.، باقری، ن.، حاجی احمد، ع. ۱۳۹۸. ارزیابی چند شاخص طیفی برای برآورد عملکرد کلزا با استفاده از تصاویر سنجنده سنتینل2. نشریه ماشین‌های کشاورزی. ۱۱ (۲): ۴۶۴-۴۴۷.
نخعی نژاد فرد، س.، غلامی، ح.، اکبری، د.، تلفر، م. و رضایی، م. ۱۳۹۸. ارزیابی الگوریتم‌های مختلف برای یکپارچه‌سازی تصاویر در تهیه نقشه‌های شاخص‌های گیاهی. اطلاعات جغرافیایی سپهر. ۲۸ (۱۱۲): ۱۹۹-۲۱۷.
Afshar, M.H., Bulut, B., Duzenli, E., Amjad, M. and Yilmaz, M.T. 2022. Global spatiotemporal consistency between meteorological and soil moisture drought indices. Agricultural and Forest Meteorology. 316, 108848.  https://doi.org/10.1016/j.agrformet.2022.108848
Aliyar, Q., Zulfiqar, F., Datta, A., KMKuwornu, J. and Shrestha, S. 2022. Drought perception and field-level adaptation strategies of farming households in drought-prone areas of Afghanistan. International Journal of Disaster Risk Reduction. 102862. https://doi.org/10.1016/j.ijdrr.2022.102862
Atif, R.M., Almazroui, M., Saeed, S., Abid, M.A., Islam, M.N. and Ismail, M. 2020. Extreme precipitation events over Saudi Arabia during the wet season and their associated teleconnections. Atmospheric Research. 231, 104655.
Barneston, J., S.Phinn, S. and Scarth, P.2019. Mapping woody vegetation cover across Australia's arid rangelands Utilising a machine-learning classification and low-cost Remotely Piloted Aircraft System. International Journal of Applied Earth Observation and Geoinformation. 83:101909.
Bera, B., KumarShit, P., Sengupta, N., Saha, S. and Bhattacharjee S. 2021. Trends and variability of drought in the extended part of Chhota Nagpur plateau (Singbhum Protocontinent), India applying SPI and SPEI indices. Environmental Challenges. 5, 100310.
Chatterjee, S.R., Desai, A., Zhu, J.A., Townsend, P. and Huang J. 2022. Soil moisture as an essential component for delineating and forecasting agricultural rather than meteorological drought. Remote Sensing of
Environment. 269, 112833. https://doi.org/10.1016/j.rse.2021.112833
Cheng, F.Y. and Chen, Y. 2018. Variations in soil moisture and their impact on land–air interactions during a 6month drought period in Taiwan, Geoscience Letters. 26(5):26-31.
Dubinin, V., Stavi, I., Svoray, T., Dorman, M. and Yizhaq, H. 2021. Hillslope geodiversity improves the resistance of shrubs to prolonged droughts in semiarid ecosystems. Journal of Arid Environments. 188, 104462.
Ebmeyer, H., Fiedler-Wiechers, K.M. and Hoffmann, C. 2021. Drought tolerance of sugar beet–Evaluation of genotypic differences in yield potential and yield stability under varying environmental conditions. Agronomy. 262621, 521
Alsaady, W. and Mohammed, R. 2021. Detecting of climatic drought by combination geo-information system and remote sensing in semi-arid zones: A case study. Materials Today: Proceedings. 57(6).
Geng, G., Yang, R. and Liu, L. 2022. Downscaled solar-induced chlorophyll fluorescence has great potential for monitoring the response of vegetation to drought in the Yellow River Basin, China: Insights from an extreme event. Ecological Indicators. 13, 108801. https://doi.org/10.1016/j.ecolind.2022.108801
Gong, P., Wang, J., Le, Y., Chao Zhao, Y., Yuan Zhao, Y., Liang, L., Guo Niu, Z. and et al. 2013. Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. International Journal of Remote Sensing. 34 (7): 2607-2654.
Guha, S., Govil, H., Gill, N. and Dey, A. 2021. A long-term seasonal analysis on the relationship between LST and NDBI using Landsat data. Quaternary International. 575-576:249-258.
Hereher, M., Alghmdi, A., Mseddi, K. and El Kenawy, A. 2022. Remote sensing of vegetation prolonged drought at the salt playas of Hail – Saudi Arabia. The Egyptian Journal of Remote Sensing and Space Science. 25(1): 135145. 
He, Y., Chen, F., Jia, H., Wang, L., Bondur, V. 2020. Different Drought Legacies of Rain-Fed and Irrigated Croplands in a Typical Russian Agricultural Region. Remote sensing. 12, 1700; doi: 10.3390/rs12111700
Holzman, M.E., Rivas, R. and Piccolo, M.C. 2014. Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index. International Journal of Applied Earth Observation and Geoinformation. 28: 181-291.
Hu, X., Ren, H., Tansey, K., Zheng, Y., Ghen, D., Liu, X. and Yan, L. 2019. Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries. Agricultural and Forest Meteorology. 279, 107707.
Javed, T., Li, Y., Rashid, S., Li, F., Hu, Q., Feng, H. and et al. 2021. Performance and relationship of four different agricultural drought indices for drought monitoring in China's mainland using remote sensing data. Science of the Total Environment. 759: 143530.
Jiang, T., Su, X.P., Singh, V. and Zhang, G. 2022. Spatio-temporal pattern of ecological droughts and their impacts on health of vegetation in Northwestern China. Journal of Environmental Management. 305, 114356. https://doi.org/10.1016/j.jenvman.2021.114356
Ji, Z., Pan, Y. and Li, N. 2021. Integrating the temperature vegetation dryness index and meteorology parameters to dynamically predict crop yield with fixed date intervals using an integral regression model. Ecological Modelling. 445. 10965.  
Peterson, E.D., Jones, C.C., Sandmeier, F.P., Arellano Rivas, A. A., Back, C., Canney, A. and et al. 2021. Drought influences biodiversity in a semi-arid shortgrass prairie in southeastern Colorado. Journal of Arid Environments. 195: 104633. 
Karnieli, A., Agam, N.T., Pinker, R., Anderson, M.L., Imhoff, M.G., Gutman, G. and et al. 2010. Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and Limitations. Journal of Climate. 23(3): 618-633.
Languille, F., Gaudel, A., Vidal, B., Binet, R., Poulain, V. and Trémas, T. 2017. Sentinel-2B image quality commissioning phase results and Sentinel2 constellation performances. "Con Proc. SPIE. Digital Library, Sensors, Systems, and Next-Generation Satellites XXI Location: Warsaw, POLAND.
Li, L., Qian, R., Liu, W. and Wang, W.A. 2022. Biederman J, Zhang Bet al Drought timing influences the sensitivity of a semiarid grassland to drought. Geoderma. 412(15):115714.
Liang, L., Zhao, S., Qin, Z., He, K., Chen, C., Luo, C., Luo, Y. and Zhou, X. 2014. Drought Change Trend Using MODIS TVDI and Its Relationship with Climate Factors in China from 2001 to 2010. Journal of Integrative Agriculture. 13(7): 1501-1508.
Masroor, m., Sajjad, H., Rehman, S., Singh, R., Rahaman, A.H., Sahana, M., Ahmed, R. and Avtar, R. 2022. Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin, India. Geoscience Frontiers. 13(2): 101312.
Mehravar, S., Amani, M., Moghimi, A., Dadrass, F., Javan, D., Samadzadegan, F. and et al. 2021. Temperature-Vegetationsoil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine. Advances in Space Research. 68(11):4573-4593.
Mckee, T.B., Doesken, N.J. and Kleist, J. 1993. The Relationship of Drought Frequency and Duration to Time Scale, 8th Conference on Applied Climatology, Anaheim, CA, American Meteorological Society. 179-184.  
Miller, D., Alonzo, M.K., Meerdink, S.A., Allen, M.L., Tague, C.A., Roberts, D.P. and McFadden, J. 2022. Seasonal and interannual drought responses of vegetation in a California urbanized area measured using complementary remote sensing indices. ISPRS Journal of Photogrammetry and Remote Sensing. 183: 178-195.
Oroud, I. and C.Balling, R. 2021. The utility of combining optical and thermal images in monitoring agricultural drought in semiarid mediterranean environments. Journal of Arid Environments. 189:104499.  
Namjoyan, S., Rajabi, A., Sorooshzadeh, A. and AghaAlikhani, M. 2021. The potential of tebuconazole for mitigating oxidative stress caused by limited irrigation and improving sugar yield and root quality traits in sugar beet. Plant Physiology and Biochemistry. 162:547-555.
Olivera-Guerra, L., Quintanilla, M., Moletto-Lobos, I., Pichuante, E., Zamorano-Elgueta, C. and Mattar, C. 2022. Water dynamics over a Western Patagonian watershed: Land surface changes and human factors. Science of the Total Environment. 804, 150221. https://doi.org/10.1016/j.scitotenv.2021.150221
Rouse, J.W., Haas, R.H., Schell, J.A. and Deering, D.W. 1974. Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite (ERTS) Symposium. NASA Goddard Space Flight Center3d ERTS-1 Symp. 1, SP-351: 309-317. Washington D. C. USA.
Sandholt, I., Rasmussen, K. and Andersen, J. 2002. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environ. 79 (2–) 3, 213–422.
Samiul Islam, S.M., Ashraful Islam, K.M. and Mullick, R.A. 2022. Drought hot spot analysis using local indicators of spatial autocorrelation: An experience from Bangladesh. Environmental Challenges. 6. 100410. https://doi.org/10.1016/j.envc.2021.100410
Soer, G.J.R. 1980. Estimation of regional evapotranspiration and soil moisture conditions using remotely sensed crop surface temperatures. Remote Sens. Environ. 9 (1): 27-45.
Uygan, D., Cetin, O., Alveroglu, V. and Sofuoglu, A. 2021. Improvement of water saving and economic productivity based on quotation with sugar content of sugar beet using linear move sprinkler irrigation. Agricultural Water Management. 255: 106989.
Vicente-Serrano, S.M., Beguería, S.I. and López-Moreno, J. 2010. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate. 23(7): 1696-1718.
Wang, Q., Qi, J., Wu, H., Zeng, Y., Shui, W., Zeng, J. and Zhang, X. 2020. Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change. CATENA. 195: 104767.
Wang, T., Tu, X., Singh, V., Chen, X., Lin, K., Lai, R. and Zhou, Z. 2022. Socioeconomic drought analysis by standardized water supply and demand index under changing environment. Journal of Cleaner Production. 347:131248. https://doi.org/10.1016/j.jclepro.2022.131248
Weng, Q., Lu, D. and Schubring, J. 2004. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Rem. Sens. Environ. 89 (4):467–483.
 Wolteji, B.N., Badhadha, S.T., Gebre, S.L., Alemayehu, E. and Gemeda, DO. 2022. Multiple Indices Based Agricultural Droughts Assessment in Rift Valley Region of Ethiopia. Environmental Challenges. 7: 100488. https://doi.org/10.1016/j.envc.2022.100488
Wu, J.J., Geng, G.P., Zhou, H.K., Liu, J.H., Wang, Q.F. and Yang, J.H. 2017. Global vulnerability to agricultural drought and its spatial characteristics. Journal of Petroleum Exploration and Production Technology. 60: 910–.029.
Wu, J.,  Mallakpour, V.I., Yuan, X., Ya, H., Wang, G. and Chen, X. 2022. Impact of the false intensification and recovery on the hydrological drought internal propagation. Weather and Climate Extremes. 36:10043. https://doi.org/10.1016/j.wace.2022.100430
Xie, F. and Fan, H. 2021. Deriving drought indices from MODIS vegetation indices (NDVI/EVI) and Land Surface Temperature (LST): Is data reconstruction necessary. International Journal of Applied Earth Observation and Geoinformation. 101, 102352. https://doi.org/10.1016/j.jag.2021.102352
Zhang, H., Ding, J., Wang, Y., Yang Zhou, D. and  Zhu, Q. 2021. Investigation about the correlation and propagation among meteorological, agricultural and groundwater droughts over humid and arid/semi-arid basins in China. Journal of Hydrology. 603(B): 127007.
Zhang, J., Yang, J., An, P., Ren, W., Pan, Z., Dong, Z. and et al. 2017. Enhancing soil drought Enhancing soil drought induced by climate change and agricultural practices: Observational and experimental evidence from the semiarid area of northern China. Agricultural and Forest Meteorology. 243: 74-83.
Zhang, L., Jiao, W., Zhang, H., Huang, C. and Tong, Q. 2017. Studying drought phenomena in the Continental
 United States in 2011 and 2012 using various drought indices. Remote Sensing of Environment. 190: 96-106.
 Zeng, J., Zhang, R., Qu, Y., A.Bento, V., Zhou, T., Lin, Y. and et al. 2022. Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018.
Weather and Climate Extremes. 35: 100412. https://doi.org/10.1016/j.wace.2022.100412
Zheng, J., Zhang, R., Lin, Y., Wu, X., Tang, J., Guo, P. and et al. 2020. Drought frequency characteristics of China, 19812019, based on the vegetation health index. Climate Research. 81:131-147.