Zayandehrood River Research Articles

A machine learning framework for spatio-temporal vulnerability mapping of groundwaters to nitrate in a data scarce region in Lenjanat Plain, Iran.

The temporal aspect of groundwater vulnerability to contaminants such as nitrate is often overlooked, assuming vulnerability has a static nature. This study bridges this gap by employing machine learning with Detecting Breakpoints and Estimating Segments in Trend (DBEST) algorithm to reveal the underlying relationship between nitrate, water table, vegetation cover, and precipitation time series, that are related to agricultural activities and groundwater demand in a semi-arid region. The contamination probability of Lenjanat Plain has been mapped by comparing random forest (RF), support vector machine (SVM), and K-nearest-neighbors (KNN) models, fed with 32 input variables (dem-derived factors, physiography, distance and density maps, time series data). Also, imbalanced learning and feature selection techniques were investigated as supplementary methods, adding up to four scenarios. Results showed that the RF model, integrated with forward sequential feature selection (SFS) and SMOTE-Tomek resampling method, outperformed the other models (F1-score: 0.94, MCC: 0.83). The SFS techniques outperformed other feature selection methods in enhancing the accuracy of the models with the cost of computational expenses, and the cost-sensitive function proved more efficient in tackling imbalanced data issues than the other investigated methods. The DBEST method identified significant breakpoints within each time series dataset, revealing a clear association between agricultural practices along the Zayandehrood River and substantial nitrate contamination within the Lenjanat region. Additionally, the groundwater vulnerability maps created using the candid RF model and an ensemble of the best RF, SVM, and KNN models predicted mid to high levels of vulnerability in the central parts and the downhills in the southwest.

Potentially Toxic Elements' Accumulation in Relation to Sediment Physicochemical Attributes and Microplastic Content in Zayandeh-Rood River, Iran.

Microplastics (MPs) are an emerging pollutant whose ability to adsorb potentially toxic elements (PTEs) poses a serious threat to aquatic ecosystems, including rivers. In highly developed basins, the abundance of MPs in river sediment is expected to be high, elevating the sedimentary accumulation of PTEs. This hypothesis was tested in the Zayandeh-Rood River, Central Iran, with 21 sediment sampling stations distributed along the entire river stretch. Results of sediment analysis showed significant variations in the abundance and size of MPs, with concentrations ranked as Ba (270.71mg/kg) > Li (21.29mg/kg) > Cs (2.50mg/kg) > Be (1.44mg/kg) > Sn (1.17mg/kg) > Mo (1.06mg/kg) > Ag (0.76mg/kg), along with sediment physicochemical attributes such as EC, TOC, pH and grain size. MPs were identified in all sediment samples with a mean of 588 items/kg dry weight. Except for Ag, all other PTEs were classified as uncontaminated but exhibited increased enrichment downstream. According to the results of the generalized additive model (maximum R-sq of 0.766), the sedimentary concentration of the majority of PTEs is nonlinearly and positively associated with smaller and more abundant MPs. This study acknowledges that MPs might influence sediment porosity, permeability and structure, thereby directly affecting the settling dynamics of other particles, especially PTEs.

Sedimentary abundance and major determinants of river microplastic contamination in the central arid part of Iran

The proliferation of anthropogenic activities around the Central Iranian Rivers shows a warning alarm of river microplastic (MP) pollution. In the Zayandeh-rood River, the mean abundance of sedimentary MPs trapped at the mouth of 21 modified sub-catchments was 588 items/kg d.w and followed the order: downstream (1701 items/kg d.w) > midstream (269.2 items/kg d.w) > upstream (57.2 items/kg d.w). The widespread distribution of fiber and fragment forms across all stations and the high MP abundance near the discharge of the largest wastewater treatment plant indicate their origin from both point and non-point sources. Using the linear multiple linear regression (MLR) and nonlinear artificial neural network (ANN), we assessed the contribution of three types of variables including the sediment physio-chemical properties, river geometry and land-use characteristics. According to both modeling results, the mean annual number of local people and tourist visitors (0.35 million people) are the most important determinants of river MP pollution whose contribution dominates through the use of plastic products and their direct and indirect release into the environment. The ANN model (R2 = 0.99) outperformed the MLR model (R2 = 0.80) and showed the importance of total organic carbon (TOC)-rich regions as MP hotspots. To alleviate the river MP pollution, suggested measures involve altering plastic usage and disposal practices among visitors and reducing the TOC content in the industrial/municipal wastewater entering the river.

The relationship between place identity and community resilience: Evidence from local communities in Isfahan, Iran

Today, many cities are experiencing many natural disasters and hazards due to climate change, particularly in the Global South. Environmental risks increase acute community vulnerabilities that worsen the effects of these hazards and make a recovery more difficult. However, community resilience can decrease people's vulnerabilities and improve their capacity to cope with and adapt to environmental hazards. It is assumed that place identity, as a cultural resource, can positively affect the resilience of communities. This exploratory survey research, thus, aims to understand the relationship between place identity and community resilience. Data is gathered using a questionnaire survey and analyzed using the principal component analysis. Case studies are two local communities in Isfahan, Iran, the Abbas Abad neighborhood and Barazandeh neighborhood, affected by the drying up of Zayandehrood River's aqueducts. The study results show a positive correlation between place identity and community resilience in the selected communities. The community with a stronger place identity tended to show stronger community resilience than the other. Therefore, it can be concluded that improving place identity might contribute to better community adaptation and recovery in times of slow-onset or sudden environmental disruptions. However, this relationship should not be considered a causal relationship. The present study highlights the role of place identity in community adaptive capacities and helps policymakers better plan to enhance community resilience. Policymakers can use the study's results to empower the communities facing slow-onset environmental disruptions.

Electrochemical molecularly imprinted polymer sensor for ultrasensitive indoxacarb detection by tin disulfide quantum dots/carbon nitride/multiwalled carbon nanotubes as a nanocomposite

Unsuitable use of agricultural pesticides has caused excessive pollution of the environment. Therefore, it is very important to identify the remaining contamination in environmental samples. Indoxacarb (IDC) as an oxadiazine fungicide use on large part of corps. In this work, we reported voltammetric sensor-based molecularly imprinted polymers (MIP) film on a tin disulfide quantum dots-carbon nitride-multiwalled carbon nanotubes (MIP@SnS2 QDs/pg-C3N4/MWCNTs) nanocomposite for ultrasensitive detection of IDC. Cyclic and differential pulse voltammetry (CV and DPV), electrochemical impedance spectroscopy (EIS), UV-Vis absorption spectroscopy, photoluminescence spectroscopy, Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), X-ray diffraction (XRD), energy dispersive X-ray (EDX), elemental mapping used for characterization of the proposed electrode. Under optimum conditions, the current response for IDC was obtained in the linear range of 20.0 nmol L−1 to 10.0 µmol L−1 and a detection limit of 7.1 nmol L−1. Using this MIP sensor, IDC has been determined in samples of Zayandeh Rood river water and apple. Several advantages of the proposed sensor were demonstrated, including its sensitivity, selectivity, and simplicity.

Water resources assessment of zayandeh-rood river basin using integrated surface water and groundwater footprints and K-means clustering method

The lack of an integrated approach to assess the quantity and quality of surface water and groundwater resources undesirably affects their sustainability and errors in users' decisions in the optimal development of basins. Therefore, to help to solve the problem of water resources sustainability assessment in various parts of the basin, for the first time, this article has presented a practical approach for the temporal-spatial evaluation of surface water and groundwater resources. The method presented in this study is based on investigating the behavior of sustainability indicators for surface water and groundwater in different years and separately for the sub-basins and aquifers. Evaluation of water quality and quantity criteria provides the main components of the proposed approach using spatial clustering. Water quality and quantity evaluations were implemented, focusing on drinking water and irrigation water uses in all sub-basins of the Zayandeh-Rood river basin in Iran for the years 2006 and 2016 using groundwater footprint (GF) and integrated groundwater footprint (iGF). The GF to area ratios (GF/A) in the first and last years of the study period were 1.1 and 0.8, respectively, while the iGF/A values were 8.9 and 7.3 in the drinking water use, and 1.3 and 1.1 in the irrigation water use, respectively. In order to apply a perspective in investigating the sustainability of the basin, surface water footprint (SF) and integrated surface water footprint (iSF) indices are introduced in this study for the first time. The SF/A values ​​in the study period were 2.2 and 1.8, respectively. The iSF/A values ​​were 3.8 and 3.3 in the drinking water use, and 2.4 and 2 in the irrigation water use for 2006 and 2016, respectively. Values greater than or equal to one in the above indicators indicate water resources' critical and unsustainable state. The comparison of groundwater and surface water indices shows that despite the slight improvement of the average values of the indices in the whole basin, some sub-basins are still in critical condition. Therefore, by using the K-means algorithm, the sub-basins were clustered into three categories favorable, unfavorable, and critical in the mentioned years. Finally, this research provides spatial planning based on water resources, which provides a comprehensive approach to maintaining the sustainability of basin water resources proportional to each sub-basin's capacity and baseline status. In this way, the factors affecting the status of the basin, the effect of the plans implemented in previous years, and the main priority of each sub-basin to solve its problems are identified. This information leads to the best planning for the sustainability of water resources and increasing social welfare based on the water resource capacity of the river basin.

Integrated river water quality and quantity management based on undesirability and cost‐effectiveness

AbstractIntegrated water resources management aims to simultaneously solve water shortage and contamination problems by considering economic, social, and environmental criteria. To that view, this study has developed a two‐objective optimization model regarding water allocation (WA) and wasteload allocation (WLA) in the Zayandehrood river basin, the central part of Iran. The model aimed to supply the users' water demand considering the downstream environmental flow to fulfill the social‐environmental requirements. Besides, satisfying the river water quality standards was regarded as the environmental‐economic criteria. The WA objective function minimizes the undesirability caused by reduced allocated water and downstream environmental flow. The QUAL2K model was used to simulate the wasteload discharge impacts on the river water quality. The water quality parameters included biochemical oxygen demand (BOD), TP, and TN for the urban and industrial wasteload and nitrate for the agricultural drainage. The results showed that a joint WA ‐ WLA optimization reduced the total average WA by 15% and increased the downstream flow by three times the base level. Also, the water quality violations of the standard limits were reduced by 18, 4, and 15 times for BOD, NO3, and TP, respectively.

Strategies for building community resilience against slow-onset hazards

Over the recent years, community resilience has been the center of attention in many theoretical approaches and policies against hazards and creeping environmental changes. However, the issue of how to achieve resilient communities has received less attention. The present study aims to develop a framework for devising strategies in order to improve community resilience, particularly to slow-onset hazards such as drought. Hence, the relevant literature was reviewed in order to establish a conceptual framework. Afterwards, the researchers investigated the framework in the context of two local communities (Barazandeh and Abbas Abad neighborhood) in Iran, i.e., Isfahan, against drought as well as drying up of Zayandehrood River and its aqueducts using a qualitative research design and retroductive strategy. For data gathering, semi-structured in-depth interviews were used and data analysis was performed through qualitative content analysis using ATLAS-ti software. Totally, 32 interviews with authorities, experts, researchers, and other stakeholders were conducted in two local communities of Isfahan. Findings indicated that any policy making regarding community resilience should not be restricted to local community level and should be expanded to multiple scales of local, regional, urban, and national community levels, even considering the two major disaster risk reduction (DRR) and climate change adaptation (CCA) categories.

Instrumental and bioanalytical assessment of pharmaceuticals and hormone-like compounds in a major drinking water source-wastewater receiving Zayandeh Rood river, Iran.

Zayandeh Rood river is the most important river in central Iran supplying water for a variety of uses including drinking water for approximately three million inhabitants. The study aimed to investigate the quality of water concerning the presence of pharmaceutical active compounds (PhACs) and hormonelike compounds, which have been only poorly studied in this region. Sampling was performed at seven sites along the river (from headwater sites to downstream drinking water source, corresponding drinking water, and treated wastewater) affected by wastewater effluents, specific drought conditions, and high river-water demand. The targeted and nontargeted chemical analyses and in vitro bioassays were used to evaluate the presence of PhACs and hormonelike compounds in river water. In the samples, 57 PhACs and estrogens were detected with LC-MS/MS with the most common and abundant compounds valsartan, carbamazepine, and caffeine present in the highest concentrations in the treated wastewater in the concentrations of 8.4, 19, and 140 μg/L, respectively. A battery of in vitro bioassays detected high estrogenicity, androgenicity, and AhR-mediated activity (viz., in treated wastewater) in the concentrations 24.2 ng/L, 62.2 ng/L, and 0.98 ng/L of 17β-estradiol, dihydrotestosterone and 2,3,7,8-TCDD equivalents, respectively. In surface water samples, estrogenicity was detected in the range of <0.42 (LOD) to 1.92 ng/L of 17β-estradiol equivalents, and the drinking water source contained 0.74 ng/L of 17β-estradiol equivalents. About 19% of the estrogenicity could be explained by target chemical analyses, and the remaining estrogenicity can be at least partially attributed to the potentiation effect of detected surfactant residues. Drinking water contained several PhACs and estrogens, but the overall assessment suggested minor human health risk according to the relevant effect-based trigger values. To our knowledge, this study provides some of the first comprehensive information on the levels of PhACs and hormones in Iranian waters.

تلفیق نقشهسازی آلودگی هوا در برنامهریزی کاربری اراضی نمونة پژوهش: شهرستان مبارکه

تلفیق نقشهسازی آلودگی هوا در برنامهریزی کاربری اراضی نمونة پژوهش: شهرستان مبارکه

Estimation of total dissolved solids in Zayandehrood River using intelligent models and PCA

Artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC) and support vector machine models were used to determine total dissolved solids (TDS) of the Zayandehrood River in Iran. In total, nine hydrochemical parameters [Ca2+, SO42−, Na+, Cl−, EC, pH, HCO3−, Mg2+ and sodium adsorption ratio (SAR)] were utilized to estimate the TDS of the river at a monthly time scale. Statistical data were categorized into low-flow and wet periods based on river discharge. Principal component analysis (PCA) was used to determine the input of the models. The results indicate that the PCA method, in both wet and low-flow periods, performed suitably based on the evaluation criteria for all models. The parameters of the first component included Ca2+, SO42−, Cl−, EC, Mg2+ and SAR in both periods. In contrast, the parameters pH and HCO3− of the second component provided unacceptable precision. The ANFIS-SC model was more precise than the other two models, with an RMSE value of 12.33 meq/l for the first component in the low-flow period. However, the ANN model was most precise in the wet period, with a calculated RMSE value of 13.87 meq/l.

Quantifying of surface urban cool island in arid environments case study: Isfahan metropolis

The cities that are built on the arid biomes with the hot and dry climates can adjust the temperature (oasis effect) and create the urban cool island (UCI) during the day. As the background climate of the Isfahan metropolis is warm and dry, we can expect an UCI during the day. The MODIS land cover product data were used to distinguish between the urban and nonurban areas. The MODIS/Terra/LST data from 2000 to 2016 were then used for day-time view to examine the UCI. In the next step, the UCI intensity index was calculated by the spatial correlation representative pixel method for the city and the background. This study showed that due to the passage of the Zayandehrood river from the middle of the city and the expansion of vegetation in the urban environment, the metropolitan area of Isfahan is 3.5° cooler than the suburban barren lands during the day. The UCI intensity index has been intensified over the last few years and has fallen below − 4.5°. The studies have shown that the UCI intensity index is weakened during the cold months and intensified in the warm months of the year. The seasonal changes in UCI intensity in the metropolitan area of Isfahan can be related to the high variability of vegetation throughout the year.

Explore the Metal Elements of Chadegan Based on Geophysical Data and Remote Sensing

The studied area is located on the one hundred thousand page of Chadegan, in the middle of Sanandaj-Sirjan zone and on the metalogenic belt of Malayer-Golpayegan, in the western part of this to Isfahan province. With regard to the anomalies of metallic minerals in the region and considering the growing demand for metals from metals-related industries, particularly lead and zinc and while most exploration and geological activities in the region are old has never lead to any comprehensive results. In this project, first the geographical and geological location of the region is studied and then remote sensing was applied in the area and then satellite images sensors ETM+ were analyzed with ENVI 4.8 software and reflective elements and promising areas were introduced. In the next step, Lead and Zinc anomalies were studied by geochemical methods and by data obtained from 900 samples from the region, map of lead and zinc anomalies of the area was drawn by software SURFER 10, then we matched it with the report from the agency and finally we compared the results together. As a result, it became clear three areas were determined for Pb-Zn which are mostly located in the eastern half of the Chadegan 1:100 000 page, which is the area around Tiran A and Asgaran-Krone B, meaning Northeastern part of the page, and around Hoorah C (around Zayandeh Rood River) which is the Southeastern part of the Chadegan page, they were all introduced for more detailed studies.

A Preliminary Introduction to the Vascular Plants of Zayandeh-Rood River

Abstract Rivers are a part of the national and natural treasures of the country with a variety of living organisms have high importance. In the present study, in order to investigate the flora of Zayandeh-Rood River, a list of aquatic macrophytes (submerged and emergent) and coastal plants along with geographical distribution (chorotype) and their life forms were compiled. A total of 92 species and 79 genera belonging to 36 families were identified. Poaceae (15 genera and 16 species), Amaranthaceae (8 genera and 10 species), Asteraceae (7 genera and 7 species), Brassicaceae (5 genera and 5 species), Fabaceae (4 genera and 4 species), and Potamogetonaceae (3 genera and 6 species) were the most important plant families. The highest number of identified species had the life forms of hemicryptophytes and throphytes (31.52%), helophytes and hydrophytes (13.04%), geophytes and phanerophytes (4.35), and chamaephytes (2.18%), respectively. Investigating the geographical distribution showed that the largest portion of the geographical distribution of plants in the region belonged to plural elements (25%), cosmopolitan elements (14.13%), Irano–Turanian elements (13.04%), and Irano-Turan-Euro-Sieberian elements (7.61%). The study indicated the diversity of aquatic and coastal vegetation of Zayandeh-Rood River that should be considered for conservation.

Urban Heat Island Monitoring and Impacts on Citizen's General Health Status in Isfahan Metropolis: A Remote Sensing and Field Survey Approach.

Urban heat islands (UHIs) are one of the urban management challenges, especially in metropolises, which can affect citizens’ health and well-being. This study used a combination of remote sensing techniques with field survey to investigate systematically the effects of UHI on citizens’ health in Isfahan metropolis, Iran. For this purpose, the land surface temperature (LST) over a three-year period was monitored by Landsat-8 satellite imagery based on the split window algorithm. Then, the areas where UHI and urban cold island (UCI) phenomena occurred were identified and a general health questionnaire-28 (GHQ-28) was applied to evaluate the health status of 800 citizens in terms of physical health, anxiety and sleep, social function, and depression in UHI and UCI treatments. The average LST during the study period was 45.5 ± 2.3 °C and results showed that the Zayandeh-Rood river and the surrounding greenery had an important role in regulating the ambient temperature and promoting the citizens’ health. Citizens living in the suburban areas were more exposed to the UHIs phenomena, and statistical analysis of the GHQ-28 results indicated that they showed severe significant (P < 0.05) responses in terms of non-physical health sub-scales (i.e., anxiety and sleep, social functioning, and depression). Therefore, it can be concluded that not all citizens in the Isfahan metropolis are in the same environmental conditions and city managers and planners should pay more attention to the citizens living in the UHIs. The most important proceedings in this area would be the creation and development of parks and green belts, as well as the allocation of health-medical facilities and citizen education.

A comparison of Zayandehrood River water values for agriculture and the environment

AbstractRiver water management is challenging not only since they are open systems with changing physical structures, but also because the water values are mostly unknown over varied sectors. If policymakers grasp water values, water management will be more efficient. This research intends to examine the values of water in agriculture, which receives the most substantial portion of water resources, with the values of water in the environment in Isfahan located in the Zayandehrood River basin of Iran. The consequences of contingent valuation and production function methods revealed that per cubic metre value of water is 13 times higher in the environment than agriculture. The government should reconsider the higher value of the environment despite it is a non‐market value. The contingent valuation model additionally proved that women exhibited 21% more willingness to pay than men in order to protect the environment; however, they are paid less by 36%.

Assessment of environmental and health hazards arising from the physical and chemical parameters existing in Zayandehrood Water (2013–2015)

Aim: Zayandehrood River is an important drinking water source in Isfahan Province which has been exposed to contamination. The high variation of physical and chemical properties of water is an important factor influencing on the consumers' health and the recipient environment. This study aims to access the health and ecological hazards related to water quality-determining parameters. Materials and Methods: In present work, all the existing data on the physical and chemical quality of Zayandehrood water for two years (March 2013 to March 2015) were collected from Isfahan Province Regional Water Company. The collected data are including dissolved oxygen, turbidity, conductivity, nitrate, phosphate, ammonia, and heavy metals such as arsenic and cadmium. The environmental hazard were determined using the contamination indices such as heavy metal pollution index, positive index, and organic pollution index, and health hazards arising from the absorption of chemical parameters were assessed based on the Environmental Protection Agency model and the use of Rural Access Index. Results: The highest noncarcinogenic hazard due to the absorption of chemical parameters was for the children group, and the ratio of health hazard and the probability of exposure to each of the chemical compounds lies in the permissible limit. The hazard higher than 1 revealing the medium hazard was, however, found in the children age group. Assessment of environmental hazards accordingly shows that the quality of the water environment has low contamination. Conclusion: The contamination of Zayandehrood water with chemical compounds can play an important role in diseases due to the exposure of low-quality water. It is thus advised to properly treat water before drinking it, and in order to decrease the concentration of poisonous chemicals in Zayandehrood Lake water, appropriate actions should be taken to conserve it.

Tempo-Spatial Behavior of Surface Urban Heat Island of Isfahan Metropolitan Area

The population of Isfahan City has been increased by ten times during the last six decades. This increase has had extensive environmental consequences. In this period, drying up of Zayandehrood River, increase in temperature and variability of precipitation has exacerbated the environmental conditions. Formation of the heat island is only one of the consequences of environmental changes in the last decades. The heat island also has many consequences in terms of health and water and energy consumptions. In this research, the land surface temperature (LST) data corresponding to daytime and nighttime using MODIS Aqua/LST from 2000 to 2016 are utilized. Using these data, the background climate of Isfahan metropolis was detected by the distance–azimuth diagram method. Then, the representative pixel within the city and the representative pixel of the background climate were identified. Based on time series of LST over these two pixels, SUHI index of Isfahan metropolis was calculated. Investigations showed that Isfahan metropolis area is colder than suburbs during the day but at night is about 2 K warmer than its surroundings. The intensity of the SUHI is maximal in January and turns weaker in summer. Regarding the temporal and spatial behavior of Isfahan metropolis SUHI, it seems that changes created by the urban concerning the moisture, albedo and composition of the atmosphere have a great role in the formation of the SUHI. Zayandehrood River has a major role in mitigation of temperature at the land surface, and its drying up has environmental consequences.

SPATIOTEMPORAL MONITORING OF THERMAL ENVIRONMENT IN ISFAHAN METROPOLITAN AREA

Abstract. Urban Heat Island (UHI) phenomenon is regarded as one of the most critical issues in cities caused by unsustainable urban development. UHI has significant effects on air quality and energy consumption of urban buildings and it directly affects life quality the citizens. The current study aims to analyze and evaluate the spatiotemporal changes of thermal environment in Isfahan Metropolitan Area (IMA), Iran, during 1998-2014 time profile. A mono-window algorithm was applied to extract Land Surface Temperature (LST) values from Landsat thermal bands (TM and OLI sensors). Temporal and spatial changes in IMA’s thermal environment were then analyzed using statistical methods, Mann-Kendall analysis and Urban-Heat-Island Ration Index (URI). Results indicated LST in IMA is of an increasing trend and the intensity of this trend is mainly concentrated in northwest and northeast of the city and around Zayandeh-Rood River in the south. This arrangement of UHI distribution is primarily due to compact and high-density patterns of city development in its boundaries, destruction of Zayandeh-Rood riverine ecosystem and its drying up during the last decade as well as excessive consumption of green covers by urban structures. Finally, it was concluded that the URI has witnessed an increasing trend from 0.25 in 1998 to 0.312 in 2014, which is in line with the spatiotemporal dynamics of thermal environment in the study location. The results of this study provide practical planning implications for identifying UHI hotspots in growing cities and optimization of green cover plantations to alleviate UHI effects in urban environments.

Modeling river water quality parameters using modified adaptive neuro fuzzy inference system

Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling water quality. The evolutionary algorithm (EA) is a new technique for improving the performance of artificial intelligence models such as the adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANN). Attempts have been made to make the models more suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization (PSO) and ant colony optimization for continuous domains (ACOR) in estimating water quality parameters at three stations along the Zayandehrood River, in Iran. The ANFIS-PSO and ANFIS-ACOR methods were also compared with the classic ANFIS method, which uses least squares and gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity (EC), total dissolved solids (TDS), the sodium adsorption ratio (SAR), carbonate hardness (CH), and total hardness (TH). Correlation analysis was performed using SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with ANFIS-ACOR. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.