Marinobacter azerbaijanicus sp. nov., a moderately halophilic bacterium from Urmia Lake, Iran.

A novel moderately halophilic, Gram-stain-negative and facultatively anaerobic bacterium, designated as strain TBZ242T, was isolated from water of Urmia Lake in the Azerbaijan region of Iran. The cells were found to be rod-shaped and motile by a single polar flagellum, producing circular and yellowish colonies. The strain could grow in the presence of 0.5-10 % (w/v) NaCl (optimum, 2.5-5 %). The temperature and pH ranges for growth were 15-45 °C (optimum 30 °C) and pH 7.0-11.0 (optimum pH 8.0) on marine agar. The 16S rRNA gene sequence analysis revealed that strain TBZ242T belonged to the genus Marinobacter, showing the highest similarities to Marinobacter algicola DG893T (98.8 %), Marinobacter vulgaris F01T (98.8 %), Marinobacter salarius R9SW1T (98.5 %), Marinobacter panjinensis PJ-16T (98.4 %), Marinobacter orientalis W62T (98.0 %) and Marinobacter denitrificans JB2H27T (98.0 %). The 16S rRNA and core-genome phylogenetic trees showed that strain TBZ242T formed a distinct branch, closely related to a subclade accommodating M. vulgaris, M. orientalis, M. panjinensis, M. denitrificans, M. algicola, M. salarius and M. iranensis, within the genus Marinobacter. Average nucleotide identity and digital DNA-DNA hybridization values between strain TBZ242T and the type strains of the related species of Marinobacter were ≤85.0 and 28.6 %, respectively, confirming that strain TBZ242T represents a distinct species. The major cellular fatty acids of strain TBZ242T were C16 : 0 and C16 : 1 ω7c/C16 : 1 ω6c and the quinone was ubiquinone Q-9. The genomic DNA G+C content of strain TBZ242T is 57.2 mol%. Based on phenotypic, chemotaxonomic and genomic data, strain TBZ242T represents a novel species within the genus Marinobacter, for which the name Marinobacter azerbaijanicus sp. nov. is proposed. The type strain is TBZ242T (= CECT 30649T = IBRC-M 11466T). Genomic fragment recruitment analysis showed that this species prefers aquatic saline environments with intermediate salinities, being detected on metagenomic databases of Lake Meyghan (Iran) with 5 and 18 % salinity, respectively.

Children exposed to salt-dust emission from Urmia Lake have short telomere length: a case-control pilot study.

This study aimed to measure telomere length in healthy children living next to Urmia Lake, Iran, which is exposed to salt dust from a drying lakebed. In this case-control pilot study, we recruited 39 sex- and age-matched healthy children from two different geographic regions to study the relative telomere lengths using qPCR. We categorized the study samples into high-impact and low-impact areas based on wind direction, aerosol particle level, and distance from the lake. Our main results revealed that children living in high-impact areas have shorter telomeres than those living in low-impact areas. Furthermore, according to our statistical model, parental age significantly affected telomere length in children, but inversely. When the father's age impact was positive, the mother had a negative effect. Based on our results, to prevent Urmia Lake from dying out completely, national and international organizations should implement comprehensive visions and strategies for its restoration.

Evaluating the impact of dam construction on extreme shrinkage of Urmia Lake using spatial data.

In this study, the extreme shrinkage of Urmia Lake is investigated, aiming to assess the impact of anthropogenic factors, particularly the over-construction of dams and natural anomalies associated with climate change. Historically available multispectral spatial data obtained from Landsat missions 4-5 TM and Landsat 8 OLI were utilized which totally covers a period of 36 years (1967-2020). Additionally, this data was employed to identify the locations of constructed water reservoirs and determine their construction timelines by analyzing the normalized difference vegetation index (NDVI). To examine the temporal patterns of annual precipitation in the lake basin, we obtained time series data from historical precipitation records, which were then converted into rasterized format. Our findings indicate that approximately 22% of the lake basin has been designated for feeding dam reservoirs. The impact of precipitation anomalies on the lake's water level was found to be relatively less significant when compared to the increased storage capacity of the dams. Furthermore, the construction of dams prior to 2000 contributed to enhancing the lake's stability during periods of drought. However, the substantial increase in the total storage capacity of dams after 2000 has significantly accelerated the shrinkage process. As a result, it was concluded that any effective rescue plan should prioritize ignoring a considerable portion of the reservoirs' storage capacity by releasing stored water, thereby allowing the lake to attain a stable condition.

Health and ecological risks assessment of heavy metals and metalloids in surface sediments of Urmia Salt Lake, Northwest of Iran.

Urmia Lake, in the northwest of Iran, is the largest body of saline water in the Middle East, which has been desiccated in recent decades. To investigate the pollution status and ecological-health risks of heavy metals and metalloids in the surface sediments of this lake, 26 sediment samples were collected along the salt marshes of the lake and were analyzed for heavy metals and metalloid concentrations. The potential ecological risk assessment was carried out using enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (CF), and potential ecological risk (Eri) standard indices. The average concentrations (mg kg-1) of heavy metals and metalloids were as follows: Fe (11,714) > Sr (320.8) > Mn (274.3) > V (28.5) > Cu (24.7) > Zn (21.2) > As (17.3) > Ni (14.8) > Cr (12.6) > Pb (11) > Co (4.0) > U (1.7), Hg (0.6) > Mo (0.36). The concentrations of As, Hg, and Sr in lake sediments were higher than geochemical background values. The non-carcinogenic risks caused by heavy metals and metalloids were insignificant regarding health risks. Levels of carcinogenic risk for metal(loid)s were in the acceptable ranges (10-6-10-4). The ecological risk was low, except for As, Sr, and Hg which showed moderate to significant EF, Igeo, and CF values. Arsenic and Sr were enriched in the surface sediments in desiccated parts of the lake due to complete lake water evaporation. It seems that further drying of the lake increases the potential ecological risk of heavy metals and metalloids in the surface sediments of Urmia Lake.

Determining the most appropriate probability distribution function for meteorological drought indices in Urmia Lake Basin, Iran.

Normalization is believed to be one of the most important parts of numerical computation in discrete mathematics. This process aims to transform a wide numerical range into a narrower one. Hence, in a number of fields of study, numerous distribution functions (DF) have been extended based on their applications, one of which is drought calculation. In this research, annual drought was calculated via standard precipitation index (SPI) and China Z Index (CZI) through seven three-parametric DFs (Pearson 5, Weibull, Pearson 3 (gamma), log Pearson, Fréchet, log-logistic, and fatigue life) in order to determine the most appropriate one for each index in Urmia Lake Basin. To this end, the results of both SPI and CZI, with DFs and without them, were compared with statistical analyzers (RMSE, ME, R2, and pearson correlation). The results indicated that Weibull-CZI and Pearson 5-SPI had the highest correlation with the normal ones. Therefore, they could be used as the best DFs for these drought indices in this basin. Moreover, among the studied years, Gelazchay and Daryanchay stations experienced the most severe drought in 2008 and 1999 based on the CZI and SPI, respectively. It should be noted that in another section of the current study, the correlation between the two indices was analyzed and the results showed high correlations between them.

Ecological risk assessment of the riverine and deltaic environments (Rozechai River, Urmia Lake, Iran), using sediment quality indices.

Rozechai River is one of the tributaries of Urmia Lake (the nrthwest of Iran), which has experienced severe pollution and water level fluctuations in the coastal zone over the past four decades. The present study aimed to assess the ecological risk for aquatic life and human health. Research methods were designed for applying the sediment quality guidelines (LEL, PEL, SEL), sediment quality indices (Cf, Cd, Er, RI), and enrichment factor (EF) based on the concentration of toxic metals in sediments. Event-based geochronology of the sediment column showed that the high stands in the water level of the Urmia Lake (> 1274 m) occurred in 1983, 1989, and 1995. Thus, As, Pb, Zn, Cd, Cr, and Ni reached a moderate to considerable enrichment under the oxidation and alkaline condition. Consequently, a moderated level of ecological risk index (RI) was predominant between 1983 and 1999. The uppermost 35 cm of the sediment column was deposited during a severe drought period to which H2S bearing water and reducing status contributed. In such conditions, the low ecological risk was resulted in the basin due to the lower rate of the toxic metal influx. The industrial, urban, and agricultural wastewaters contributed to the release of toxic metals and the dominance of moderate to considerable enrichment, which led to a moderate ecological risk at the coastal zone of the Rozechai River. The sediment column of the deltaic area has experienced a mean sedimentation rate of 1.66 cm year-1 since 1982.

Halomonas azerbaijanica sp. nov., a halophilic bacterium isolated from Urmia Lake after the 2015 drought.

A novel, slightly halophilic bacterium, designated TBZ202T, was isolated from water of Urmia Lake, in the Azerbaijan region of north-west Iran. The strain was facultatively anaerobic, Gram-stain-negative, rod-shaped and motile. Colonies were creamy, circular, convex and shiny. It grew at NaCl concentrations of 0-12 % (w/v) (optimum 3-5 % w/v), at temperatures of 20-45 °C (optimum 30 °C) and at pH 5.0-10.0 (optimum pH 7.0). Based on the 16S rRNA gene sequence, strain TBZ202T belongs to the genus Halomonas in the Halomonadaceae and the most closely related species are Halomonas gudaonensis CGMCC 1.6133T (98.6 % similarity), Halomonas ventosae Al12T (96.8 %) and Halomonas rambilicola RS-16T (96.6%). The G+C content was 67.9 % and the digital DNA-DNA hybridization and average nucleotide identity values with H. gudaonensis were 35.8 and 83.8 %, respectively, indicating that the isolate differs from all species described. The major fatty acids were C18 : 1 ω7c, C16 : 0 and C16 : 1 ω7c. The only respiratory quinone detected was Q-9 and polar lipids consisted of diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, aminophospholipid and three unknown phospholipids. On the basis of a polyphasic taxonomic analysis, the isolate is considered to represent a novel species of the genus Halomonas, for which the name Halomonas azerbaijanica sp. nov. is proposed. The type strain is TBZ202T (=KCTC 62817T=CECT 9693T).

A quantitative approach to resource effectiveness assessment: Application in the Urmia Lake Basin.

This paper aims to present a new quantitative systematic approach to evaluate the effectiveness of utilizing and allocating resources based on the concept of "Work" in physics. This method is examined in the Urmia Lake Basin (ULB), shrinking of which has threatened the life of about five million inhabitants and ecosystem biodiversity. In the proposed approach, the role of three types of financial, human, and environmental resources in the development process is evaluated quantitatively, and they have been compared in two periods before and after the severe reduction of the lake water volume. Results show that although financial resources have increased by 1.9 times in the second period, the effectiveness of the development process has decreased. Therefore, the resources have not been utilized properly in a direction compatible with sustainable development strategies. Additionally, the improperly-spent financial resources on the development projects especially in the second period have had a more destructive role than the human and environmental resources in the ULB crisis.

Determination of nano and microplastic particles in hypersaline lakes by multiple methods.

Microplastics and nanoplastics have a range of impacts on the aquatic environment and present major challenges to their mitigation and management. Their transport and fate depend on their composition, form, and the characteristics of the receiving environment. We explore the spatial and temporal dynamics of plastic particles in the world's second-largest hypersaline lake, combining information from microscopic, thermal gravimetric, and fractional methods. Studies on microplastic and nanoplastic pollution in these important environments are scarce, and there is limited understanding of their dynamics and fate. Our results for Urmia Lake (Iran) in 2016 and 2019 show a discrepancy in the composition and quantity of microplastics measured in river tributaries to the lake and the lake itself, suggesting an active microplastic sink. Potential sink mechanisms in hypersaline lakes are explored. The present study indicates that microplastics have different transport mechanisms and fate in these extreme environments, compared to lake and ocean environments.

Halomonas urmiana sp. nov., a moderately halophilic bacterium isolated from Urmia Lake in Iran.

In the course of screening halophilic bacteria in Urmia Lake in Iran, which is being threatened by dryness, a novel Gram-negative, moderately halophilic, heterotrophic and short rod-shaped bacteria was isolated and characterized. The bacterium was isolated from a water specimen and designated as TBZ3T. Colonies were found to be creamy yellow, with catalase- and oxidase-positive activities. The growth of strain TBZ3T was observed to be at 10-45 °C (optimum, 30 °C), at pH 6.0-9.0 (optimum, pH 7.0) and in the presence of 0.5-20 % (w/v) NaCl (optimum, 7.5 %). Strain TBZ3T contained C16 : 0, cyclo-C19 : 0 ω8c, summed feature 3 (comprising C16 : 1 ω7c and/or C16 : 1 ω6c) and summed feature 8 (comprising C18 : 1 ω7c and/or C18 : 1 ω6c) as major fatty acids and ubiquinone-9 as the only respiratory isoprenoid quinone. Diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, glycolipid, unidentified phospholipid and unidentified polar lipids were detected as the major polar lipids. Strain TBZ3T was found to be most closely related to Halomonas saccharevitans AJ275T , Halomonas denitrificans M29T and Halomonas sediminicola CPS11T with the 16S rRNA gene sequence similarities of 98.93, 98.15 and 97.60 % respectively and in phylogenetic analysis strain TBZ3T grouped with Halomonas saccharevitans AJ275T contained within a large cluster within the genus Halomonas. Based on phenotypic, chemotaxonomic and molecular properties, strain TBZ3T represents a novel species of the Halomonas genus, for which the name Halomonas urmiana sp. nov. is proposed. The type strain is TBZ3T (=DSM 22871T=LMG 25416T).

Trend and abrupt change analysis in water quality of Urmia Lake in comparison with changes in lake water level.

Urmia Lake, as the largest lake in Iran borders, has a special role in the ecosystem of the region. The water level in this lake declines in recent year remarkably, so monitoring the lake water quality is important from an environmental view. In this research, the changes in the qualitative variables of the lake water (including electrical conductivity (EC), pH, total dissolved solids (TDS), and sodium adsorption ratio (SAR)) are compared with the changes in the lake's water level based on the Mann-Kendall nonparametric test. Further, abrupt change points in the time series of quality variables were detected by the Pettitt test. Studies were carried out on samples collected from five different stations during 2005-2015. The results showed that the water level of Urmia Lake had a significant decreasing trend and also, except for TDS, the other investigated quality variables had negative trends during the studied period. It was observed that in general, the values of the Z statistic in the stations located in the eastern part of the lake were more than the stations located in the western part, and also the stations located in the northern parts had a higher trend than those in the south of the bridge.

Rainfall time series disaggregation in mountainous regions using hybrid wavelet-artificial intelligence methods.

In mountainous regions, rainfall can be extremely variable in space and time. The need to simulate rainfall time series at different scales on one hand and the lack of recording such parameters in small scales because of administrative and economic problems, on the other hand, disaggregation of rainfall time series to the desired scale is an essential topic for hydro-environmental studies of such mountainous regions. Hybrid models development by combining data-driven methods of least square support vector machine (LSSVM) and Artificial Neural Network (ANN) and wavelet decomposition for disaggregation of rainfall time series are the purpose of this paper. In this study, for disaggregating the Tabriz and Sahand rain-gauges time series, according to nonlinear characteristics of observed time scales, wavelet-least square support vector machine (WLSSVM) and wavelet-artificial neural network (WANN) hybrid models were proposed. For this purpose, daily data of four rain-gauges and monthly data of six rain-gauges from mountainous basin of the Urmia Lake for seventeen years were decomposed with wavelet transform and then using mutual information and correlation coefficient criteria, the sub-series were ranked and superior sub-series were used as input data of LSSVM and ANN models for disaggregating the monthly rainfall time series to the daily time series. Results obtained by these hybrid disaggregation models were compared with the results of LSSVM, ANN and classic multiple linear regression (MLR) models. The efficiency of WANN model with regard to the WLSSVM, ANN, LSSVM and MLR models at validation stage in the optimized case for Tabriz rain-gauge showed up to 9.1%, 22%, 20% and 50% increase and in the optimized case for Sahand rain-gauge showed up to 4.5%, 21.1%, 30.2% and 53.3% increase, respectively.

Halomonas tabrizica sp. nov., a novel moderately halophilic bacterium isolated from Urmia Lake in Iran.

A novel moderately halophilic, Gram-stain negative and aerobic bacterium, designated strain TBZ21T, was isolated from a water sample of Urmia Lake, Iran. Cells were observed to be non-motile rods with no flagellum, showing positive catalase and oxidase reactions. Strain TBZ21T was found to grow at 10-40 °C (optimum, 30 °C), at pH 7-10 (optimum, pH 8) and in the presence of 1-22% (optimum, 10%). The major fatty acids were identified as C19:0 cyclo ω8c, C16:0, Summed features 3 (C13:0 3-OH and/or iso-C15:1 H) and 8 (C18:1 ω7c and/or C18:1 ω6c) and C12:0 3-OH. The major polar lipids were identified as diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine and an unidentified phosphoaminolipid. The genomic DNA G+C content of strain TBZ21T was determined to be 63.3 mol%. Phylogenetic analyses based on 16S rRNA gene sequences indicated that strain TBZ21T belongs to the genus Halomonas, and shows high sequence similarities to Halomonas fontilapidosi 5CRT (99.43%), Halomonas ventosae AL12T (98.64%), Halomonas sediminicola CPS11T (98.63%) and Halomonas aestuarii Hb3T (98.08%), and has low similarities (below 98.0%) with other members of the genus. The values of DNA-DNA relatedness between strain TBZ21T and the closely related strains H. fontilapidosi LMG 24455T and H. ventosae LMG 26187T were 42 ± 11% and 54 ± 16%, respectively. On the basis of phenotypic, chemotaxonomic and molecular characteristics, strain TBZ21T is concluded to represent a novel species of the genus Halomonas, for which the name Halomonas tabrizica sp. nov. is proposed. The type strain is TBZ21T (=LMG 25445T=DSM 23018T).

Quantitative assessment of Urmia Lake water using spaceborne multisensor data and 3D modeling.

Preserving aquatic ecosystems and water resources management is crucial in arid and semi-arid regions for anthropogenic reasons and climate change. In recent decades, the water level of the largest lake in Iran, Urmia Lake, has decreased sharply, which has become a major environmental concern in Iran and the region. The efforts to revive the lake concerns the amount of water required for restoration. This study monitored and assessed Urmia Lake status over a period of 30 years (1984 to 2014) using remotely sensed data. A novel method is proposed that generates a lakebed digital elevation model (LBDEM) for Urmia Lake based on time series images from Landsat satellites, water level field measurements, remote sensing techniques, GIS, and 3D modeling. The volume of water required to restore the Lake water level to that of previous years and the ecological water level was calculated based on LBDEM. The results indicate a marked change in the area and volume of the lake from its maximum water level in 1998 to its minimum level in 2014. During this period, 86% of the lake became a salt desert and the volume of the lake water in 2013 was just 0.83% of the 1998 volume. The volume of water required to restore Urmia Lake from benchmark status (in 2014) to ecological water level (1274.10 m) is 12.546 Bm3, excluding evaporation. The results and the proposed method can be used by national and international environmental organizations to monitor and assess the status of Urmia Lake and support them in decision-making.

Characterization of basidiomycetous yeasts in hypersaline soils of the Urmia Lake National Park, Iran.

Urmia Lake, located in northwest Iran, is an oligotrophic and extremely hypersaline habitat that supports diverse forms of life. Owing to its unique biodiversity and special environmental conditions, Urmia Lake National Park has been designated as one of the biosphere reserves by UNESCO. This study was aimed to characterize basidiomycetous yeasts in hypersaline soils surrounding the Urmia Lake National Park using a polyphasic combination of molecular and physiological data. Soil samples were collected from eight sites in Lake Basin and six islands insides the lake. Yeast strains were identified by sequencing the D1/D2 domains of the 26S rRNA gene. When D1/D2 domain sequencing did not resolve the identity of the species, strain identification was obtained by ITS 1 & 2 sequencing. Twenty-one species belonging to the genera Cystobasidium, Holtermanniella, Naganishia, Rhodotorula, Saitozyma, Solicoccozyma, Tausonia, Vanrija, and Vishniacozyma were identified. Solicoccozyma aeria represented the dominant species. The ability of isolates to grow at 10 and 15 % of NaCl was checked; about two-thirds of the strains grew at 10 %, while about 13 % of the isolates grew in medium with 15 % NaCl. this study is the first study on the culturable yeast diversity in hypersaline soils surrounding an Asian lake.

Investigating the salinization and freshening processes of coastal groundwater resources in Urmia aquifer, NW Iran.

This paper presents the results of an assessment about interaction between Urmia Lake (UL) and coastal groundwater in the Urmia aquifer (UA). This aquifer is the most significant contributor to the freshwater supply of the coastal areas. The use of hydrochemical facies can be very useful to identify the saltwater encroachment or freshening phases in the coastal aquifers. In this study, the analysis of salinization/freshening processes was carried out through the saturation index (SI), ionic deltas (Δ), binary diagrams, and hydrochemical facies evolution (HFE) diagram. Based on the Gibbs plot, the behavior of the major ions showed that the changes in the chemical composition of the groundwater are mainly controlled by the water-soil/rock interaction zone and few samples are relatively controlled by evaporation. A possible explanation for this phenomenon is that the deposited chloride and sulfate particles can form the minor salinity source in some coastal areas when washed down by precipitation. The SI calculations showed that all groundwater samples, collected in these periods, show negative saturation indices, which indicate undersaturation with respect to anhydrite, gypsum, and halite. In addition, except in a few cases, all other samples showed the undersaturation with respect to the carbonate minerals such as aragonite, calcite, and dolomite. Therefore, these minerals are susceptible to dissolution. In the dry season, the SI calculations showed more positive values with respect to dolomite, especially in the northern part of UA, which indicated a higher potential for precipitation and deposition of dolomite. The percentage of saltwater in the groundwater samples of Urmia plain was very low, ranging between 0.001 and 0.79 % in the wet season and 0.0004 and 0.81 % in the dry season. The results of HFE diagram, which was taken to find whether the aquifer was in the saltwater encroachment phase or in the freshening phase, indicated that except for a few wells near the coast, there is very little hydraulic interaction between UA and UL. In this coastal area, most of the samples that were collected repeatedly in both wet and dry seasons showed the same hydrochemical facies, which suggested that the seasonal groundwater fluctuations cannot significantly change the chemical composition of groundwater.

Incorporating hydraulic gradient and pumping rate into GALDIT framework to assess groundwater vulnerability to salinity in coastal aquifers: a case study from Urmia Plain, Iran.

The critical role of groundwater in meeting diverse needs, including drinking, industrial, and agricultural, highlights the urgency of effective resource management. Excessive groundwater extraction, especially in coastal regions including Urmia Plain in NW Iran, disrupts the equilibrium between freshwater and saline boundaries within aquifers. Influential parameters governing seawater intrusion-groundwater occurrence (G), aquifer hydraulic conductivity (A), the height of groundwater level above the mean sea level (L), distance from the shore (D), impact of the existing status of seawater intrusion (I), and thickness of the saturated aquifer (T)-merge to shape the GALDIT vulnerability index for coastal aquifers. This study enriches the GALDIT framework by incorporating two additional hydrogeological variables: hydraulic gradient (i) and pumping rate (P). This expansion produces seven distinct vulnerability maps (GALDIT, GAiDIT, GAiDIT-P, GALDIT-i, GALDIT-iP, GALDIT-P, GAPDIT). In the Urmia Plain, the traditional GALDIT index reveals vulnerability values ranging from 2 to 8.1, categorized into six classes from negligible to very high vulnerability. However, the modified indices, GAiDIT and GAiDIT-P, yield a three-class categorization, ranging from low to high vulnerability. The introduction of the "i" and "P" parameters in GALDIT-i and GALDIT-iP enhances the precision of vulnerability mapping, altering class distribution and intensifying vulnerability ratings. The eastern, central, and coastal areas of the Urmia Plain demonstrate high to very high vulnerability levels, in contrast to the lower vulnerability observed in the western regions. Both the GALDIT-P (r = 0.82) and GALDIT-iP (r = 0.81) indices show strong correlations with Cl concentration, thereby improving mapping accuracy over the traditional GALDIT index (r = 0.72). A sensitivity analysis highlights the critical influence of the "i" parameter, suggesting its weighting should be revised. Parameter recalibration serves to amplify the significance of "G," "L," "D," and "i" parameters, while diminishing others. The integration of multiple hydrogeological variables considerably enhances the precision of groundwater vulnerability assessments.

Assessing the soil salinity vulnerability and groundwater quality variations due to drying up of the lake.

Shrinkage of lakes is considered a serious ecological challenge. The impact of this phenomenon on the environment can be devastating. Monitoring the spatiotemporal variations of lake's water surface and its salinization is essential for planning and adopting mitigation measures. In this study, a new multiscale-kernel-based method was used to assess the spatiotemporal variations of the shrinkage of the Urmia Lake and develop soil salinity vulnerability map for its basin. For this aim, remote sensing, empirical wavelet transform (EWT), differential symbolic entropy (DSE), and Gaussian regression process (GPR) techniques were used. Vulnerable areas were identified using geo-environmental parameters extracted from the in situ observations and satellite datasets. In the next step, considering three time periods including the lake normal period, lake drying period, and lake restoration period, the variations in the quality of groundwater were investigated. Results showed that the east and south sections of the lake were more prone to severe salinization. Saline lands caused negative impacts on air quality and agricultural activities in these areas. It was found that both climate change and human activities had contributed to the shrinking of the lake. Results showed that the quality of groundwater in the area around the lake has been affected by the excessive salinity of the lake water and the encroachment process of saline water. The water quality index has increased during the drying period of the lake and caused negative effects on the quality of water used for drinking and agricultural activities. In the lake restoration period, a slight increase in water quality was observed.

Spatial trend and probabilistic health risk assessment of heavy metals, nitrate, and fluoride in groundwater resources, West Azerbaijan province, Iran.

The quality of water resources used for drinking and their health effects is vitally important. The present study investigated the concentrations of F-, NO3-, and metal elements like Hg, Mn, As, and Pb in the groundwater resources and their health risk assessment on the west margin of Urmia Lake, Iran. Sampling points were selected and taken from 121 groundwater resources in the summer of 2014. Heavy metals (Pb, As, Mn, and Hg) were measured by ICP-OES (inductively coupled plasma optical emission spectrometer, model: Arcos, Germany), and some ions (Na+, NO3-, F-, and Cl-) by flame photometer and spectrophotometer according to the standard methods, respectively. The nitrate concentration range in groundwater samples measured from 1.7 to 137 mg/L and fluoride from 0.4 to 4.5 mg/L. The probabilistic method and Monte Carlo simulation were used to estimate carcinogenic and noncarcinogenic risks. The concentration of study elements in most samples was obtained in the WHO (World Health Organization) recommended range. The order of HM (heavy metal) concentration is based on the overall mean: Mn > As > Hg > Pb. The HI (hazard index ) level was found to be more than 1 for noncarcinogenic risk for As and NO3- and permissible risks for the other elements and fluoride. ELCR (excess lifetime cancer risk) levels of As were acceptable, except for some sampling points, the central region in the study area, near the seashore of Urmia Lake. Finally, it can be stated that the groundwater resources in the studied area are acceptable for drinking in most places. Still, due to the effects of As and NO3- contaminated water, the quality is unacceptable for drinking in some places. So, monitoring water quality is recommended by finding contamination sources to decrease the health risks of drinking consumption.

Developing an optimized groundwater exploitation prediction model based on the Harris hawk optimization algorithm for conjunctive use of surface water and groundwater resources.

Due to the lack of surface water and groundwater resources, especially in the agricultural parts, the simultaneous and sustainable use of water resources to supply water demands is essential. In this study, a conjunctive use optimization model is developed to minimize the shortage of water demand. This model is implemented for the Mahabad study area in northwestern Iran to improve the conditions of surface water and groundwater resources and the reclamation of Urmia Lake. For this purpose, the current research is accomplished in three parts. At first, the Mahabad aquifer is numerically simulated to investigate the aquifer conditions. In the second part, the optimized model of conjunctive use obtained by the Harris hawk optimization (HHO) algorithm is investigated over a 20-year period in the study area. In the last part of this research, seven scenarios are developed to predict the optimized groundwater exploitation (OGE) using the results of HHO, meteorological data, and some input information on the dam reservoir. Then, the OGE values are predicted using the artificial neural network (ANN) and ANN-HHO machine learning models for the scenarios. The results showed that the scenario that includes all input variables and the ANN-HHO model outperformed other models. Furthermore, the HHO algorithm provides suitable allocation of the surface water and groundwater resources in optimized conjunctive use and also improves the performance of ANN in predicting the OGE values. The findings of this study also show that groundwater resources can be more applied to supply water demand, and in contrast, surface water resources can be used for supplying downstream environmental demands and reclamation of Urmia Lake.