|تعداد مشاهده مقاله||7,215,700|
|تعداد دریافت فایل اصل مقاله||5,604,774|
Spatial analysis of drought severity, duration and frequency using different drought indices (Case study: Fars Province, Iran)
|Caspian Journal of Environmental Sciences|
|مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 19 دی 1401 اصل مقاله (1.85 M)|
|نوع مقاله: Research Paper|
|شناسه دیجیتال (DOI): 10.22124/cjes.2023.6105|
|Mona Massoudi1؛ Massoud Goodarzi 2؛ Abolfazl Moeini3؛ Baharak Motamedvaziri 3|
|1Department of Watershed Management Engineering, Faculty of Environment and Natural Resources, Islamic Azad University, Science and Research Branch, Tehran, Iran|
|2Soil Conservation & Watershed Management Research Institute (SCWMRI), Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran|
|3Department of Forest, Range and Watershed Management, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran|
|The present drought is a phenomenon that can occur in any climate, hence, due to its creeping and mysterious nature, economic losses, social effects as well as crises in agricultural, natural resources and ecosystems, its study is of great importance. Therefore, in this study, by using 9 drought indices including SPEI, SIAP, DI, SPI, PN, MCZI, CZI, RDI and ZSI, the drought was analyzed using 40 meteorological and synoptic stations in Fars Province, Iran during the last half century. In order to select the best drought index, three methods including minimum amount of precipitation, normal distribution, and correlation were used. Also, the severity, duration and frequency of droughts and their return period were determined using Run Theory (RT) method and SDF curves.Finally, after determining the best index, the drought events of the region were interpolated using ArcGIS techniques along with the simple and conventional kriging methods with spherical, exponential, and Gaussian models as well as the inverse weighted distance (IDW) method. In order to determine the most appropriate interpolation method, Cross-Validation method and MAE and MBE indices were used. The results showed that the SPI index performed as the best indicator to describe the drought. The results of RT method and SDF curves showed that by increasing time scale and return period, drought continuity and magnitude increase and as drought persisted, the severity of drought not increase at a constant rate. According to the results, the most severe and widespread droughts in the province occurred in 1970, 1993, 1999, 2007, 2014 and 2016. Also, Gaussian conventional Kriging method was the best method of drought interpolation in the study area due to its lower error rate. Therefore, by spatial monitoring and distribution of droughts, necessary measures can be taken to better deal with and manage water and natural resources.|
|Biodiversity؛ Run theory؛ Interpolation؛ Drought؛ SDF؛ GIS|
Alipour, A, Hashemi, M, Hosseini, SA, Pajooh, F 2017, Evaluation and comparison of several climatic drought indices and determination of the best index in Central Iran. Journal of Echo-hydrology, 4: 147-133.
Alizadeh, A 2006, Principles of applied hydrology, 20th Edition, Astan Qods Razavi Publications, Mashhad, Iran, 807 p.
Arbabi Sabzevari, A 2010, Analysis the effect of drought in GIS environment in the Kashan region. Journal of Physical Geography, 3: 105-124.
Chou, J, Tian Xian, Runze Zhao, Yuan Xu, Fan Yang & Mingyang, S 2019, Drought Risk Assessment and Estimation in Vulnerable Eco-Regions of China: Under the Background of Climate Change. Sustainability, 11: 4463.
Gaucin, DO, Jesús De la Cruz, B, Heidy, V, Castellano, B 2018, Drought Vulnerability Indices in Mexico. Water Use and Scarcity, 10: 1671.
Ghanavati, R, Soleimanpour, SM & Jokar, L 2013, Monitoring and comparing drought trends in Omidieh city based on Z, SIAP, RAI and SPI indices, 6th National Conference on Watershed Management and Soil and Water Resources Management, Iran Irrigation and Water Engineering Association, Kerman, Iran.
Gibbs, WJ & Maher, JV 1967, Rainfall deciles as drought indicators. Bureau of Meteorology Bulletin. 48, Commonwealth of Australia, Melbourne, Australia.
Hayes, MJ 2006, Drought Indices. Van Nostrands Scientific Encyclopaedia, John Wiley & Sons, Inc., DOI:10.1002/0471743984.vse8593.
Homdee, T, Pongput, K & Kanae, S 2016, A comparative performance analysis of three standardized climatic drought indices in the Chi River basin, Thailand. Journal of Agriculture and Natural Resources, 50: 211-219.
Hosseini, SA, Ahmadi, H, Mohammadpour, K 2012. Drought monitoring of Saghez using rainfall data analysis method. The first specialized scientific conference on rural and agricultural development with emphasis on national production, Payam Noor University, Piranshahr Branch, Piranshahr, Iran, 13 p.
Hosseini, SA, Mohammadpour, K, Mesgari, A 2014, Drought monitoring of Marivan city using PNPI, Z score, DI, RAI and SPI indices. National Conference on Strategies for Advancing the Water Crisis in Iran and the Middle East, Shiraz, Iran, 7 p.
Jamali, S 2013, Study of drought and its spatial variations using geostatistical methods in the north of Bushehr province in GIS environment, MSc. Dissertation, Department of Irrigation and Drainage, Islamic Azad University, Firoozabad Branch. Firoozabad, Iran.
Jun, LY, Zx, D, Lu, F & Ma, J 2012, Analysis of drought evolvement characteristics based on standardized Precipitation index in the Huaihe River Basin. Journal of Procedia Engineering, 28: 434- 437.
Kendall, MG & Stuar,t A 1977, The Advanced Theory of Statistics. Charles Griffin & Company: London, High Wycombe, pp. 400-401.
Khalili, A & Bazrafshan, J 2003, Evaluation of the effectiveness of several meteorological drought indices in different climatic samples of Iran. Nivar, 49: 93-79.
Khalili, A., Bazrafshan, J 2007, Evaluation of return period and drought duration risk using annual secular precipitation data in ancient stations of Iran. 2nd Conference on Water Resources Management. Isfahan University of Technology. Science and natural resources, 15: 176-182
Lashanizand, M 2004, Climatic study of droughts in Iran and strategies to deal with it. PhD Dissertation, University of Isfahan, Isfahan, Iran.
Mackee, TBN, Doesken, J & Kleist, J 1993, The Relationship of Drought Frequency and Duration to Time Scales, Preprints, 8th Conference on Applied Climatology, 17-22 January, Anaheim, CA, pp. 379-384.
Moghaddasi, M, Murid, S, H Ghaemi, H & Samani, M 2005, Daily Drought Monitoring in Tehran Province, Journal of Agricultural Sciences, 36: 51-62.
Nasabpour, S, Heidari, A, Khosravi, H, Vesali, A 2018, Zoning of Drought Vulnerability in Iran Using AHP Model and Fuzzy Logic. Journal of Agricultural Meteorology, 6: 13-22.
Naumann, G, Dutra E, Barbosa, P, Pappenberger F, Wetterhall F & Vogt, V 2014 Comparison of drought indicators derived from multiple data sets over Africa. Hydrological Earth Systems Science, 18: 1625-1640.
Shabani, M 2009, Evaluation of the application of geostatistical methods in the zoning of drought intensities in Fars Province, Journal of Water Engineering, 2: 31-36.
Steinmann, A 2003, Drought indicators and triggers: A stochastic approach to evaluation, Journal of the American Water Resources Association (JAWRA). 39: 1217-1233.
Triola, MF 1995, Elementary Statistics (6th edition). Addison-Wesley, Reading, MA; pp. 691-693
Tsakiris, G, Pangalou D & Vangelis, H 2007, Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resources Management, 21: 821-833.
Vicente-Serrano, SM, Begueria, S & Lopez-Moreno, JI 2010, A multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate, 23: 1696-1718.
Wilhite, D 1994, Drought a alobal assessment, Rutledge hazards and disasters series, London and New York.
Yevjevich, V 1967, An objective approach to definitions and investigations of continental hydrologic droughts, Colorado State University, Fort Collins, CO.
Zabihi, A, Soleimani, K, Shabani, M & Abroosh, P 2011, Investigation of spatial distribution of annual rainfall using Geostatistical methods (Case study: Qom). Physical Geography Research, 78: 101-112.
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