Search Results (9)

The duration of dust days (DDD) is one of the most important parameters that may worsen the effects of the presence of dust in the affected areas. Persistent pollution over consecutive dusty days can have particularly negative effects on the human respiratory system. The present analysis was conducted in Central Iran, where the phenomenon of dust is one of the most important problems. In this study, using dust codes recorded at 35 synoptic stations, the homogeneity of DDD across the region was investigated using the L-moments method. Then, characteristics of DDD over the period 1999–2018 were calculated. The results showed that the region is statistically homogeneous. Furthermore, Zabol and Zahdan are the stations worst affected, with the longest durations of 22 and 21 days in 2014. Additionally, the values of DDD with return periods of 5, 10, 25, and 50 years were calculated using fitted statistical distributions and kriging and mapped. Finally, using the K nearest neighbor method the most important factor affecting DDD of the spatial characteristics, including longitude, latitude, elevation, average daily temperature (t_m), dew point (t_d), wind altitude (u), maximum wind speed (ff_max), and direction of the fastest wind (dd_max), was determined. It was found that the southeastern parts of the study area are affected by the longest dust storm duration in all return periods; over longer return periods, long dust storms are also found in the central parts, especially the central desert of Iran. Therefore, these areas should be given priority in fighting and controlling wind erosion. Furthermore, the results showed that the maximum wind speed has the greatest effect on DDD. Full article

Soil moisture is one of the most important parameters affecting dust emission flux. This study was conducted to investigate the effects of soil moisture on vertical dust flux in the central plateau region of Iran. In this study, the WRF-Chem (Weather Research and Forecast with Chemistry) model, with the GOCART (Global Ozone Chemistry Aerosol Radiation and Transport) scheme, was used to estimate the dust emission flux during a major storm from 19 to 21 July 2015, and to discriminate between dust sources. The results showed that the Kyrgyz deserts in Turkmenistan, the Arabian deserts in Saudi Arabia, the deserts of Iraq, and the Helmand region in Afghanistan are sources of foreign dust. Additionally, the central desert plain was identified as an internal dust source, where the dust level reached 7000 µg m⁻² s⁻¹. The results of WRF-Chem simulation were verified with reanalysis data from MERRA2 and AERONET data from Natanz station, which showed good agreement with the simulation. Based on the GLDAS reanalysis, soil moisture content varied between 2.6% and 34%. Linear and nonlinear regression of vertical dust flux values and soil moisture showed nonlinear behavior following the exponential function, with a correlation coefficient of 0.8 and a strong negative association between soil moisture and vertical dust flux. Full article

Today, in developing countries, the low surface water distribution efficiency and the lack of supplying water needs of farmers by surface water resources are compensated by excessive aquifer water withdrawal. This mismanagement has caused a sharp drop in the groundwater level in many countries. On the other hand, climate change and drought have intensified the pressure on water resources. This study aims to evaluate novel strategies for developing surface water distribution systems for stress reduction of the Najafabad aquifer in Isfahan, central plateau of Iran. The performance of several strategies for agricultural water distribution and delivery, such as hydro-mechanical operating system, manual-based operating system, and centralized automatic operating system, was evaluated in this study. In the first step, two indices, i.e., water distribution adequacy and dependability, were obtained using a flow hydraulic simulation model. Then, the water distribution adequacy map and amount of reduction in the water withdrawal of existing wells were determined for each strategy. Finally, using the MODFLOW groundwater simulation model, the changes in groundwater levels due to the normal and drought scenarios (15 and 30%) were extracted during five years for each strategy. The findings for the normal scenario showed that the centralized automatic operating system strategy had the most significant impact on agricultural water management in the surface water distribution system with a 30% increase in agricultural water distribution adequacy index compared to the current situation. This strategy increased the groundwater level by 11.6 m and closed 35% of the groundwater wells. In this scenario, the hydro-mechanical operating system strategy had the weakest performance by increasing the aquifer level by only 1.31 m. In the 15% and 30% drought scenarios, the centralized automatic operating system strategy exerted the best performance among other strategies by increasing the aquifer water level by 10.18 and 9.4 m, respectively, compared to the current situation. Finally, the results showed that the spatial segmentation of the aquifer exerted better efficiency and better monitoring in the more susceptible regions. Full article

The economic development, livelihood and drinking water of millions of people in the central plateau of Iran depend on the Qarah-Chay River, but due to a lack of inappropriate monitoring, it has been exposed to destruction and pollution. Consequently, an assessment of the river’s water quality is of utmost importance for both the management of human health and the maintenance of a safe environment, which can be achieved by determining the best locations for pollution monitoring stations along rivers. In this study, artificial neural networks (ANNs) has been used to optimize the locations for Qarah-Chay River monitoring stations in Markazi province, Iran. The data are collected based on the Iranian Water Quality Index (IRWQI), the US National Sanitation Foundation Water Quality Index (NSFWQI) and the Oregon Water Quality Index (OWQI). The database is given to a multilayer perceptron (MLP) neural network along with a geographic information system (GIS). The output of this study identified six pollution monitoring stations on the river, which are mainly downstream due to the accumulation of land uses and the concentration of pollution. The gradient of the MLP network training courses model from the proposed monitoring stations is 0.062299. In addition, the performance evaluation criteria of the proposed MLP model for F1-score, recall, precision and accuracy were 0.85, 0.84, 0.88 and 0.88, respectively. The results obtained help managers to properly monitor the river’s water resources with accuracy, efficiency and lower cost; furthermore, the findings were able to provide scientific references for river water quality monitoring and river ecosystem protection. Full article

Iran is experiencing significant water challenges that have now turned water security into a national priority. By estimating secular trend groundwater storage in Iran between 2002 and 2017, we see that there is an intensive negative trend, even −4400 Mm³ in some areas. These estimations show shifting in the climate and extra extraction from aquifers for agricultural use in some areas in Iran. The secular trend of groundwater storage changes across the whole of Iran inferred from observation well data is −20.08 GT/yr. The secular trends of GWS changes based on observation well data are: −11.55 GT/yr for the Central Plateau basin, −3.60 GT/yr for the Caspian Sea basin, −3.0 GT/yr for the Persian Gulf and Oman Sea basin, −0.53 GT/yr for the Urmieh Lake basin, −0.57 GT/yr for the Eastern Boundary basin, and −0.83 GT/yr for the Gharaghom basin. The most depleted sub-basin (Kavir Markazi) has secular trends of GWS changes of −4.503 GT/yr. This study suggests that groundwater depletion is the largest single contributor to the observed negative trend of groundwater storage changes in Iran, the majority of which occurred after the drought in 2007. The groundwater loss that has been accrued during the study period is particularly alarming for Iran, which is already facing severe water scarcity. Full article

The South China Sea (SCS) summer monsoon (SCSSM) onset signifies the commencement of large-scale summer monsoon over East Asia and the western North Pacific (WNP). Previous studies on the influencing factors of the SCSSM onset mainly focus on the tropical systems, such as El Niño-Southern Oscillation (ENSO). This study reveals that the wave train along the Asian jet could act as an extratropical factor to modulate the SCSSM onset, and it is largely independent of ENSO. The SCSSM onset tends to be earlier during the positive phase of the wave train (featured by northerly anomalies over Central Iran plateau and eastern China, southerly anomalies over Arabian Peninsula, eastern Indian subcontinent, and eastern Bonin islands). The wave train affects the SCSSM onset mainly via modulating the WNP subtropical high. The wave train during the positive phase can induce negative geopotential height anomalies in the mid-troposphere and anomalous cyclones in the lower-troposphere over the SCS and the Philippine Sea, leading to the weakening of the WNP subtropical high. Specifically, the anomalous ascending motions associated with the low-level cyclone are favorable for the increased rainfall over the SCS, and the anomalous westerly on the south of the anomalous cyclone is conducive to the transition of the zonal wind (from easterly to westerly). The above circulation anomalies associated with the positive phase of the wave train provide a favorable environment for the advanced SCSSM onset. Full article

The Aral Sea basin is the most active source of salt-dust storms in the central Asian region, while its exposed bottom is acting as a “distributer” of salts and chemicals over the adjoining areas. In this study, the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT-4) is used to identify the trajectories of air parcels from the dried bottom of the Aral Sea region (45.40° N, 61.30° E) that are potentially containing salt-dust and their probability of influencing the downwind area in the period of 2016–2020. The frequency of air parcel trajectory was mapped for six levels: 100, 300, 500, 1000, 2000, and 3000 m agl. The trajectories were categorized by k-means clustering into four clusters that are named by their direction of movement as follows: Cluster 1: E category, Cluster 2: NE category, Cluster 3: W category, and the Cluster 4: S category. The 72 h of forward trajectories showed that salt-dust storms starting from the dried bottom of the Aral Sea had the highest probability of affecting the northeastern region e.g., Siberian Plain, followed by the southern region e.g., Iran Plateau. Total number of trajectories within these two clusters (NE and S) accounts for 90% (or 413 days) of trajectories in examined days. The main area of influence of salt-dust is close to the source area. The potential transport distance of salt-dust particles increases with the height of the starting point. The surface wind, which results from the changes of the Siberian High (SH), has a major role in shaping the surface atmospheric circulation which determines the transport pathway of salt-dust particles over the Aral Sea region. The results of this study could be useful to forecast the potential occurrence of salt-dust storms in downwind affected areas and would also be helpful to understand the possible causes of salt-dust storms which can provide the scientific basis for mitigation of the negative impact of salt-dust storms on the environment and human health. Further research should be conducted by using monitoring data to confirm the deposition of dust and salt particles in those areas mapped by our study. Full article

Dust and sand storms are among the major threats to central Iran. These phenomena pose irreparable risks to natural ecosystems and human societies, including effects on health. In this study, the spatial and temporal pattern of vertical dust flux (VDF) was used to identify dust sources as well as areas with high potential for dust generation. To simulate VDF, two intense dust storms, from 21 February 2015 and 14 February 2018, were selected using synoptic data and Moderate Resolution Imaging Spectroradiometer (MODIS) images. These dust storms were identified as responsible for a reduction of horizontal visibility to less than 1000 m, using remote sensing tools and Ackerman Dust Index. MODIS images show that these two storms covered most of Central Plateau of Iran. The Weather Research and Forecasting model with chemistry (WRF-Chem) was used to simulate the storms, with either the Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) or Air Force Weather Agency (AFWA) scheme to calculate VDF. Modeled vertical dust fluxes in both events indicate that the Arabian deserts in Saudi Arabia and in southwestern Iran can be identified as main sources of the dust in the central Iranian plateau. The other source of dust is the Hirmand Basin, located in the country of Afghanistan and in the southeast of Iran. The results of VDF simulations indicate that central southeast Iran could be the main dust source of internal origin. Additionally, over seasonal wetlands in Iran, the amount of VDF was simulated to be sometimes over 4000 μg/(m²s), an indication that these areas are sensitive to wind erosion in dry conditions and can be a source of dust. The WRF-Chem results were compared with the horizontal visibility measured in synoptic stations in the area. The results showed that the coefficients of determination of GOCART results with the measured horizontal visibility on 21 February 2015 and 14 February 2018 were 0.72 and 0.76, respectively, while the coefficient values from the simulations with AFWA scheme on 21 February 2015 and 14 February 2018 with the measured horizontal visibility were lower, 0.44 and 0.50, respectively. Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2) re-analysis data also showed timing of peak dust levels consistent with the GOCART scheme. Full article

Drought monitoring needs comprehensive and integrated meteorological and hydrologic data. However, such data are generally not available in extensive catchments. The present study aimed to analyze drought in the central plateau catchment of Iran using the terrestrial water storage deficit index (TSDI). In this arid catchment, the meteorological and hydrologic observed data are scarce. First, the time series of terrestrial water storage changes (TWSC) obtained from the gravity recovery and climate experiment (GRACE) was calculated and validated by the water budget output. Then, the studied area was divided into semi-arid, arid, and hyper-arid zones and the common drought indices of SPI and RDIe within a timescale of 3, 6, and 12 months were calculated to compare the results obtained from the TSDI by using the meteorological data of 105 synoptic stations. Based on the results, the study area experienced a drought with extreme severity and expansion during 2007–2008. The drought spatial distribution map obtained from three indices indicated good conformity. Based on the maps, the severity, duration, and frequency of drought in the semi-arid zone were greater than that in other zones, while no significant drought occurred in the hyper-arid zone. Furthermore, the temporal distribution of drought in all three zones indicated that the TSDI could detect all short- and long-term droughts. The study results showed that the TSDI is a reliable, integrated, and comprehensive index. Using this index in arid areas with little field data led to some valuable results for planning and water resource management. Full article