Spatial assessment of meteorological drought features over different climate regions in Iran

Abstract

Iran has a predominantly arid and semi‐arid climate where the drought hazards and their variability are the crucial concerns for water resources management. This study assesses the characteristics and trends of meteorological droughts features in different climate regions of Iran. Monthly rainfall data are analysed using Standardized Precipitation Index (SPI) to reconstruct meteorological droughts for different time steps (1, 3, 6, 9 and 12). The drought events are decomposed into three features, namely Severity (S), Duration (D) and Peak (P) to assess their spatial variations in different climate regions. The Mann–Kendall (MK) test is used to detect the trends in drought features in different climate regions. The percentage area (PA) of increasing/decreasing trend in drought features is computed to assess the spatial variations of trends in each region. Besides, SPI is compared with Standardized Precipitation Evapotranspiration Index (SPEI) to understand the importance of evapotranspiration on meteorological droughts. The high correlations between SPI and SPEI indicate that the results obtained using SPI would not vary if a similar analysis is conducted using SPEI. The results obtained using SPI reveal that short‐duration droughts (6 months or less) are more frequent and severe in the northwest and the north along the Caspian plains while the longer‐duration droughts (more than 6 months) are more frequent and severe in the south, southeast and southwest. Overall, the northwest region of Iran is found most susceptible to droughts in terms of S, P and D. Moderate (40% < PA < 60%) or significant (PA > 60%) increase in the drought features are observed in all climate regions for shorter SPI (3 months or less) except northwest, while no drought feature is found to increase significantly for SPI‐12. Overall, the higher increase in drought S, P and D are found in the central arid region and at higher altitudes.

Meteorological Drought in Northwestern Escarpment of Ethiopian Rift Valley: detection seasonal and spatial trends

“…Shortage of precipitations for continuous months particularly during the consecutive rainy seasons has great impacts on rain feed agriculture systems. If there is a period of months to years of prolonged dry weather conditions due to precipitation departure in a certain region, meteorological drought may occur and these may have high impacts on water resources, agricultural activities, meteorological cycles, ecosystem processes, and social affairs (Sharafati et al 2019). Consequently, the focus of this spatiotemporal drought study was emphasized on short (the Belg and Kiremt), combined (March-August) rainy season drought trends.…”

Standardized precipitation index based dry and wet conditions over a dryland ecosystem of northwestern India

“…The increased drier situations in northeastern, eastern and southeastern regions are, in reality, noteworthy for the water resource planning and management since these areas are chief producers of various food grain crops, causing a massive threat to food grain productivity. Also, the poor water availability can negatively impact the maintenance of valuable tree species diversity (Sharafati et al, 2020).…”

“…Of late, SPI has been extensively used in estimation, monitoring, watching and forecasting of droughts universally (Spinoni et al, 2014) as well as in several realms namely, Africa (Dhurmea et al, 2019;Dutra et al, 2013), Europe (Barker et al, 2016;Karabulut, 2015), North America (Ford & Labosier, 2014), South America (Seiler et al, 2002), West Asia (Awchi & Kalyana, 2017;Mossad & Alazba, 2018;Mustafa & Rahman, 2018;Zakhem & Kattaa, 2016) and South-East Asia (Bong & Richard, 2019;Du & Shi, 2013;Kundu et al, 2020;Rahman et al, 2018;Zin et al, 2013). Apart from this, SPI has been modelled using geostatistical techniques to generate spatial maps (Bhuiyanet al, 2006;Sharafati et al, 2020).…”

Performance evaluation of different probability distribution functions for computing Standardized Precipitation Index over diverse climates of Iran

“…(2012) related the SPI time variability to atmospheric circulation types. Some studies used SPI to evaluate the temporal trend of drought characteristics and dry and wet periods in whole or a part of Iran (Kazemzadeh and Malekian, 2016; Sharafati et al ., 2020) while many others used it for drought prediction using different approaches (Choubin et al ., 2014; Kousari et al ., 2017; Dehghani et al ., 2019). Such studies have used the available codes that use Gamma as the default distribution for SPI computation, assuming that in all climate types of Iran, the cumulative precipitation at all commonly used timescales best fits with Gamma distribution.…”