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.

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.

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.

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.

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.

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.

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.

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.

Designing a Surveillance System to Monitor the Adverse Health Effect of Environmental Disasters: A Case Study of Drying Lake Urmia-Iran.

Background: Through designing a surveillance system, steps to policy making and designing measures needed to reduce the potential risks of environmental disasters on human health could be taken. Therefore, this study aimed to develop a model for Environmental Disasters Diseases Surveillance System (EDDS) to monitor Adverse Health Effects (AHEs) of Environmental Disasters (AHEEDs). Methods: As the first step, the literature review was conducted to identify the AHEEDs. Then, using the results of the first step and analyzing the existing documents, the AHEEDs were identified, and, based on the experts' opinions, high-priority effects were included in the EDDS. Then, using semi-structured interviews, 20 experts' views on the appropriate model of EDDS were investigated. To design the initial model, a panel of experts was formed with six participants. Finally, the Delphi technique was used for expert opinion and model finalization. Results: As a result of the literature review and document analysis, 41 hazards/diseases were identified. Finally, ten diseases were suggested to enter the EDDS. In the experts' view, it is better that communicable diseases be reported actively and urgently and Non-Communicable Diseases (NCD) actively and non-urgently. From the participants' point of view, the most significant achievements of the EDDS can be organizational and managerial, health promotion, and economic achievements. Conclusion: Developing a dedicated EDDS for AHEEDs can be very helpful for better management of these effects. To this end, the model proposed in this study can serve as a guide for national and local policymakers to implement surveillance systems for AHEEDs.

Monitoring of aquatic birds and surveillance of avian influenza and Newcastle disease of waterfowls at the National Park of Urmia Lake.

BACKGROUND: Urmia lake, as a national park, is one of the most valuable aquatic ecosystems in the Middle East and quatitative and qualitative changes in Urmia lake water have a great impact on its ecological performance and in the region. OBJECTIVES: This project was designed to study the effects of the extent of Urmia lake water surface area on the area size and on the number of aquatic birds of the six selected habitats in 2011-2019. The presence of avian influenza (AI) and Newcastle disease (ND) viruses in migratory aquatic birds together with their impacts on poultry farms as well as on rural birds was also under surveillance in 2018-2019. METHODS: Changes of Urmia lake and its impacts on area size of the six selected birds habitats were monitored by GIS. The small monitoring program with circular plot point counts was used for counting of the number of birds of the six selected habitats. At least, 100 samples (oropharyngeal and cloacal swabs) were collected. each sample was placed in a sterile plastic tube containg transport media and assigned with an number and store untill used. Reverse transcription-polymerase chain reaction (RT-PCR) and real-time RT-PCR test were used for detection of AI and ND viruses in the samples. RESULTS: The results revealed that changes in the water surface area of Urmia lake had a gsignificat impacts on area size and the number of aquatic birds of the six selected habitats. The surveillance results showed that 5% of the samples were AIV positvie while 25% of the samples were pasitive for NDV including 20% for non-virulent NDV (lNDV) and 5% for virulent NDV (vNDV) strains. CONCLUSION: This study showed that fluctuation of Urmia lake's water surface area influenced (p < 0.05) the area size of the six selected aquatic birds' habitats and had a great impacts on the number of the migratory birds. Detection of AIV and vNDV emphesises that the seasonal migratory waterfowls spread AI and vND viruses to the ponds and estuaries as well as to the rural birds and industrialised poultry units around the Urmia lake. Potential public health treats were also discussed.

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.

Exploring Water Governing System Fit Through a Statistical Mechanics Approach.

Water governing systems are twisted with complex interplays among levels and scales which embody their structures. Typically, the mismatch between human-generated and natural systems produces externalities and inefficiencies reflectable in spatial scales. The largely known problem of fit in water governance is investigated to detect the issues of fit between administrative/institutional scales and the hydrological one in a lake basin. To implement the idea, constraining the level of analysis interlinked to the concentrated levels of administration in spatial scales, the fit of the governing system was analyzed by means of statistical mechanics. Modeling the structure of water demand/supply governing system in a given region through the Curie-Weiss Mean Field approximation, the system cost in relation to its structure and fit was appraised and compared with two other conceptual structures in the Urmia Lake Basin in Iran. The methodology articulated an analysis framework for exploring the effectiveness of the formulated water demand/supply governing system and its fit to the relevant hydrological system. The findings of this study may help developing strategies to encourage adaptations, rescaling/reforms for effective watershed management.

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.

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.

Evaluating water resources management scenarios considering the hierarchical structure of decision-makers and ecosystem services-based criteria.

This paper introduces a new methodology for evaluating water resources management scenarios considering different aspects of their hydrological ecosystem services. The temporal variations of supplied water to different demands are assessed as provisioning hydrological ecosystem services. Then, three agricultural drought management policies have been defined for each water supply-demand alternative to reduce the irrigation water and cultivated area of the agricultural demand nodes during droughts. In addition to the net primary productivity criterion (NPP) and economic profit, the ecological condition of the system has been evaluated as an ecosystem services-based criterion. To prioritize and select the best water resources management (WRM) scenario(s), a game theory-based hierarchical evidential reasoning (ER) technique with multiple decision-makers has been used. The proposed methodology has been applied to the Urmia Lake basin, which is the largest saline lake in the Middle East. The grade-based values of the criteria have been used to compare the WRM scenarios. The results show that a scenario that includes supplying 100% of the lake's water demand has the highest priority. This scenario also suggests reducing the cultivated area of dominant crops and using deficit irrigation practices.

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).

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.

A generalized linear stochastic model for lake level prediction.

Endorheic lakes are one of the most important factors of an environment. Regarding their morphology, these lakes, in particular saline lakes, are much more sensitive and can either benefit or pose a threat to their surroundings. Thus, constant monitoring of such lakes' water level, modeling and analyzing them for future planning and management policies is vitally important. We proposed a generalized linear stochastic model (GLSM) for forecasting the weekly and monthly Urmia lake water levels, the sixth-largest saltwater lake on Earth. In this methodology, three approaches are defined to pre-process data. The first approach is merely based on the differencing method, while the second and third are a one-step (the combination of de-trending with standardization and spectral analysis) and two-step (the combination of the 2nd approach with normalization transform) preprocessing, respectively. A thorough comparison of the GLSM results with eminence nonlinear AI models (Adaptive Neuro-Fuzzy Inference Systems, ANFIS, Multilayer Perceptron, MLP, Gene Expression Programming, GEP, Support Vector Machine with Firefly algorithm, SVM-FFA, and Artificial Neural Networks ANN) showed that by using an appropriate method that delivers accurate information of the entailing terms in time series, it is possible to model Urmia lake level with acceptable precision. Concisely, the GSLM with coefficients of determination (R2) 99.957% and root mean squared error (RMSE) of 2.121% outperformed the SVM-FFA with R2 99.59%, RMSE 3.27%, ANN with R2 99.56%, RMSE 3.3%, ANFIS with R2 98.9%, RMSE 4.3%, GP with R2 99.89%, RMSE 3.47%, GEP with R2 94.75%, RMSE 4.15% for forecasting weekly time series. In forecasting monthly time series, the GLSM method with R2 99.517% and RMSE 6.91% also outperformed GEP R2 91.95%, RMSE 15.3%, ANFIS R2 92.85%, RMSE 47.55% models. Consequently, GSLM proved that by applying proper comprehensible linear techniques promising results can be obtained rather than using sophisticated AI methods.

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).

A system dynamics model to quantify the impacts of restoration measures on the water-energy-food nexus in the Urmia lake Basin, Iran.

Water scarcity exacerbated by growing demand in different sectors has created environmental, social, and economic challenges in the Urmia Lake Basin, Iran. Tackling this problem requires an integrated approach considering the basin as an interconnected system where a change in one sector affects others. Here, a System Dynamics Model is developed to simulate the water-energy-food nexus in the Urmia Lake Basin as a holistic multi-sectoral system and to assess the impacts of proposed lake restoration measures, especially looking for trade-offs. Besides considering climate change impacts, the effect of different sets of measures including increasing irrigation efficiency, increasing return flows, inter-basin water transfers, crop land retirement, and reviving a portion of the lake on the natural resources and socio-economic state of the basin are analysed. Results show that Urmia Lake level is sensitive to climate change scenarios. A holistic restoration approach could be effective in increasing the lake level to the proposed ecological level by 2040. However, in doing so, electricity demand in the agricultural sector could grow significantly. It is shown that a 20% retirement of irrigated wheat lands to curb water demand, if coupled with a 20% increase in yield on 80% and 50% of irrigated and rain-fed fields respectively, will not reduce wheat production in the basin. The effectiveness of water demand management measures is highly dependent on continuous monitoring and enforcement, particularly in restricting growth in agricultural water consumption. This study considered all nexus sectors in a holistic way to assess the total impact of proposed measures which on paper look positive, but may have unexpected consequences such as increasing energy demand for electric pumps. In dialogue with Urmia Lake restoration practitioners, this work can feed in to inform effective decisions for the restoration of Urmia Lake.