Desiccation of the Transboundary Hamun Lakes between Iran and Afghanistan in Response to Hydro-climatic Droughts and Anthropogenic Activities

Akbari, Mahdi; Mirchi, Ali; Roozbahani, Amin; Gafurov, Abror; Kløve, Bjørn; Haghighi, Ali Torabi

doi:10.1016/j.jglr.2022.05.004

Cited by 34 publications

(6 citation statements)

References 35 publications

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“…The main Ephemeral lake in eastern Iran is Hamun Lake, which is made up of three smaller lakes called Hamun‐e Puzak, Hamun‐e Saberi, and Hamun‐e Hirmand. The Gaud‐e Zirreh ephemeral lake is also act as an active source of dust in eastern Iran when it dries up (Akbari et al, 2022). The locations of these lakes are shown in Figure 1b.…”

Section: Resultsmentioning

confidence: 99%

Climatology and the dynamic mechanism of the Levar wind and dust events in eastern Iran

Alizadeh

Abniki

Babaei

et al. 2022

Intl Journal of Climatology

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Dust storms in eastern Iran have a wide range of socioeconomic impacts, yet long-term numerical model analysis of the mechanism of strong winds and dust events in this region is limited. The regional climate model version 4 (RegCM4) coupled with a dust module is used to understand the climatology, climatic change, and the dynamic mechanism of the Levar wind and dust events in eastern Iran for the period 1991-2017. It is found that the strong Levar wind is the main driver of dust events in eastern Iran, particularly from June to September. Both model simulation and observations indicate that the Levar wind is strongest on the border between South Khorasan Province in Iran and Afghanistan. Our analysis indicates that the Levar wind is caused by the development of anomalous surface high pressure in Central Asia extending toward northeastern Iran and anomalous surface low pressure on the border between western Afghanistan and Pakistan. The strong pressure gradient force associated with these anomalous high-and low-pressure systems is responsible for the strong northerly Levar wind on the border between Iran and Afghanistan. Dust activity in eastern Iran exhibits a distinct seasonality. The highest dust emission occurs on the border between eastern South Khorasan Province in Iran and western Afghanistan from June to September, where near-surface winds are also the strongest. Relatively less dust emission occurs in dry beds of Jazmourian from June to September, south of Saravan in May, and Rig-e Yalan in June. The removal of dust particles from the atmosphere is mainly by dry deposition in eastern Iran. The main sink of dust is located in the western parts of the Sistan Basin. Dust emission and burden in the main source of dust in eastern Iran have significantly decreased during the period 1991-2017, while near-surface wind speed has remained nearly unchanged. K E Y W O R D S climatic change, dust events, eastern Iran, Levar wind,

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Section: Resultsmentioning

confidence: 99%

Climatology and the dynamic mechanism of the Levar wind and dust events in eastern Iran

Alizadeh

Abniki

Babaei

et al. 2022

Intl Journal of Climatology

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“…This study acknowledges that there are knowledge gaps which can be filled by utilising satellite-based remote sensing systems [20,32] which offer valuable sources of data and observations capable of partially or fully replacing field survey and gauged data. The study aims to determine the suitability of the use of GEE coupled with the QGIS platform to understand the hydroclimatic behaviour and determine stream flow patterns, especially for inaccessible [33][34][35] and transboundary areas.…”

Section: Introductionmentioning

confidence: 93%

“…As concerns over Doosti Dam's shrinking increase [29], so it is vital that authorities identify the cause/s of shrinkage whether they are climatic or anthropogenic [20]. The research area's available gauge data in Iran and Turkmenistan do not have adequate geographical or temporal coverage [28][29][30][31], and this study provides useful information.…”

Section: Introductionmentioning

confidence: 96%

“…Drinking water in Mashhad city has been seriously affected by water shortages that have forced water authorities to investigate the reasons for the reduction of water flow from the Doosti Lake considering climatological and hydrological aspects and agricultural expansion [20]. However, in most cases, realistic climatological data are not readily available, especially in the inaccessible ungauged part of the catchments.…”

Section: Introductionmentioning

confidence: 99%

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Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam

Pakdel-Khasmakhi

Vazifedoust

Paudyal

et al. 2022

IJGI

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Understanding the effects of global change and human activities on water supplies depends greatly on surface water dynamics. A comprehensive examination of the hydroclimatic variations at the transboundary level is essential for the development of any adaptation or mitigation plans to deal with the negative effects of climate change. This research paper examines the hydroclimatic factors that contribute to the desiccation of the Doosti Dam’s basin in the transboundary area using multisensor satellite data from the Google Earth Engine (GEE) platform. The Mann–Kendall and Sens slope estimator test was applied to the satellite datasets to analyse the spatial and temporal variation of the hydroclimate variables and their trend over the transboundary area for 18 years from 2004 to 2021 (as the dam began operating in 2005). Statistical analysis results showed decreasing trends in temperature and an increase in rainfall with respect to station-observed available data. Evapotranspiration and irrigated area development followed the increasing pattern and a slight decrease in snow cover. The results confirmed a large expansion of the irrigated area, especially during the winter growing season. The increase in irrigated cultivated areas during both winter and summer seasons is possibly the main reason for the diversion of water to meet the irrigation requirements of the developed agriculture areas. The approach followed in this study could be applied to any location around the globe to evaluate the hydrological conditions and spatiotemporal changes in response to climate change, trend analysis and human activities.

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“…Each of these has its strengths and weaknesses. Gauges provide the most accurate measurements, but they are geographically sparse, especially in remote areas, inaccessible topographies, and harsh climates (Akbari et al., 2022; Bakhtar et al., 2022; Ghajarnia et al., 2014; Sun et al., 2018). Moreover, gauge observations suffer from sampling errors and undercatch issues (Ehsani & Behrangi, 2021; Kidd et al., 2017; Panahi & Behrangi, 2019; Saemian et al., 2022; Song et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

Ghajarnia

Akbari

Saemian

et al. 2022

Earth and Space Science

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Precipitation is one of the most important components of the hydrological cycle (Eltahir & Bras, 1996;Oki & Kanae, 2006) and great efforts have been invested in monitoring its spatiotemporal variability (Arabzadeh et al., 2020;Koohi et al., 2021;Teague & Gallicchio, 2017). Multiple methods have been developed to measure and monitor precipitation in the field, but accurate estimation of precipitation is still challenging (Adhikari et al., 2020;Foufoula-Georgiou et al., 2020). For example, this difficulty is due to, high spatiotemporal variability in complex topographical regions (Beck et al., 2019) and different sources of uncertainty associated with different measurement methods and scales (Behrangi & Wen, 2017). These uncertainties impede the study of climate and interconnections of hydroclimatic variables, water resources management, and hydrological forecasts (Foufoula-Georgiou et al., 2020;Sun et al., 2018).There are three main sources of precipitation data: (a) ground-based data (mainly from precipitation gauge networks), (b) satellite remote sensing (RS) data, and (c) reanalysis data sets (Hosseini-Moghari et al., 2018;Shayeghi et al., 2020;Sun et al., 2018). Each of these has its strengths and weaknesses. Gauges provide the most accurate measurements, but they are geographically sparse, especially in remote areas, inaccessible topographies, and harsh climates (

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Desiccation of the Transboundary Hamun Lakes between Iran and Afghanistan in Response to Hydro-climatic Droughts and Anthropogenic Activities

Cited by 34 publications

References 35 publications

Climatology and the dynamic mechanism of the Levar wind and dust events in eastern Iran

Climatology and the dynamic mechanism of the Levar wind and dust events in eastern Iran

Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam

Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

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