Spatiotemporal variations of aridity in Iran using high‐resolution gridded data

Araghi, Alireza; Martinez, Christopher J.; Adamowski, Jan; Olesen, Jørgen E.

doi:10.1002/joc.5454

Cited by 58 publications

(22 citation statements)

References 40 publications

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“…The aridity index (AI) is often used to quantify the longterm climatic conditions of an area (Ashraf et al, 2014). (Thornthwaite, 1948) and Penman-Monteith (Monteith, 1965) methods are the most widely used.…”

Section: Aridity Indexmentioning

confidence: 99%

Spatiotemporal changes in aridity of Pakistan during 1901–2016

Ahmed

Shahid

Wang

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. The changing characteristics of aridity over a larger spatiotemporal scale have gained interest in recent years due to climate change. The long-term (1901–2016) changes in spatiotemporal patterns of annual and seasonal aridity during two major crop growing seasons of Pakistan, Kharif and Rabi, are evaluated in this study using gridded precipitation and potential evapotranspiration (PET) data. The UNESCO aridity index was used to estimate aridity at each grid point for all the years between 1901 and 2016. The temporal changes in aridity and its associations with precipitation and PET are evaluated by implementing a moving window of 50 years of data with an 11-year interval. The modified Mann–Kendall (MMK) trend test is applied to estimate unidirectional change by eliminating the effect of natural variability of climate, and Pettitt's test is used to detect year of change in aridity. The results revealed that the climate over 60 % of Pakistan (mainly in southern parts) is arid. The spatial patterns of aridity trends show a strong influence of the changes in precipitation on the aridity trend. The increasing trend in aridity (drier) is noticed in the southwest, where precipitation is low during Kharif, while there is a decreasing trend (wetter) in the Rabi season in the region which receives high precipitation due to western disturbances. The annual and Kharif aridity is found to decrease (wetter) at a rate of 0.0001 to 0.0002 per year in the northeast, while Kharif and Rabi aridity are found to increase (drier) at some locations in the south at a rate of −0.0019 to −0.0001 per year. The spatial patterns of aridity changes show a shift from arid to the semi-arid (wetter) climate in annual and Kharif over a large area while showing a shift from arid to hyper-arid (drier) region during Rabi in a small area. Most of the significant changes in precipitation and aridity are observed in the years between 1971 and 1980. Overall, aridity is found to increase (drier) in 0.52 %, 4.44 % and 0.52 % of the area and decrease (wetter) in 11.75 %, 7.57 % and 9.66 % of the area for annual, Rabi and Kharif seasons respectively during 1967–2016 relative to 1901–1950.

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Section: Aridity Indexmentioning

confidence: 99%

Spatiotemporal changes in aridity of Pakistan during 1901–2016

Ahmed

Shahid

Wang

et al. 2019

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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“…Trend analysis is usually conducted to investigate the long-term systematic changes in climatic variables (Wang et al, 2006;Dinpashoh et al, 2011;Sonali and Nagesh Kumar, 2013;Goyal, 2014;Li et al, 2015;Rashid et al, 2015;Zhang et al, 2015;Araghi et al, 2018;Şen, 2018). Different trend detection methods (e.g., parametric, nonparametric and Bayesian) have been developed to assess trends in hydroclimatic time series (Reeves et al, 2007;Khaliq et al, 2009;Sonali and Nagesh Kumar, 2013;Dabanlı et al, 2016) which include Mann-Kendall (MK) test, Sen's slope estimator, Spearman's rho tests, linear regression and innovative trend test (Şen method).…”

Section: Introductionmentioning

confidence: 99%

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

Sharafati

Nabaei

Shahid

2019

Intl Journal of Climatology

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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.

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“…The assessment and monitoring of such a phenomenon is particularly important in those regions where agriculture is one of the largest sectors of the tradable economy. Climatic indices are reliable tools to classify climate and investigate the aridity or humidity in any region (Araghi, Martinez, Adamowski, & Olesen, 2018). Different indices have been proposed for different parts of the world.…”

Section: Introductionmentioning

confidence: 99%

The De Martonne aridity index in Calabria (Southern Italy)

2019

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In this paper, the annual rainfall and temperature values, measured in the period 1951-2016 in a region of southern Italy (Calabria), have been spatially interpolated using deterministic and geostatistical techniques in an R environment. In particular, Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Kriging with External Drift (KED) and Ordinary Cokriging (COK) were compared to evaluate the best suitability method in reproducing the actual surface. Then, the spatial variation of aridity in Calabria has been evaluated using the De Martonne aridity index (IDM), which is based on rainfall and temperature data. As a result, geostatistical methods incontrovertibly show a better estimate than the IDW. Specifically, the KED was identified as the best predictor method for both rainfall and temperature data. Moreover, the spatial distribution of the IDM evidenced that the majority of the study area can be classified as humid, with semi-arid conditions mainly identified in the coastal areas.

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Spatiotemporal variations of aridity in Iran using high‐resolution gridded data

Cited by 58 publications

References 40 publications

Spatiotemporal changes in aridity of Pakistan during 1901–2016

Spatiotemporal changes in aridity of Pakistan during 1901–2016

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

The De Martonne aridity index in Calabria (Southern Italy)

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