Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) in water and edible fish species of Karun River, Ahvaz, Iran: spatial distribution, human health, and ecological risk assessment.

Per- and polyfluoroalkyl substances (PFASs) such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are environmental contaminants with unfavorable impacts on human health and nature. This study aimed to determine the PFOA and PFOS concentration in water and fish samples from Karun, the largest river in Iran. According to the results, the PFOA and PFOS in water samples were 5.81-69.26 ng/L and not detected (n.d.)-35.12 ng/L, respectively. The dry season displayed higher concentrations in water samples than in the wet season. The maximum PFOS concentration measured was related to Barbus barbules sp. (27.89 ng/g). The human health risk assessment indicated minor risks (hazard ratio, HR < 1) from PFOA and PFOS through consuming contaminated drinking water and fish. Only HR value of PFOS in downstream area exceeded slightly 1.0, indicating potential health risk due to consumption of the river fish. Considering the average PFASs concentration, the risk quotients (RQs) showed low ecological risk.

Distribution of total petroleum hydrocarbons in superficial sediments of Karun River Basin, southwest of Iran: spatial and seasonal variations, source identification, and ecological risk.

Total petroleum hydrocarbons (TPHs) are common environmental pollutants in aquatic ecosystems that tend to adsorb onto the sediments. This study aimed to monitor the concentration and assessment of contamination level of TPHs in the sediments of Karun River and Bahmanshir estuary, which will eventually flow into the Persian Gulf. GIS-mapping technique was used to indicate the distribution of TPHs. The samples were collected during dry and wet seasons at 15 monitoring stations. - The maximum amount of TPHs was obtained at station No. 14 in the dry season (225.29 µg/g). The indices of determining the pollution source showed that hydrocarbons in polluted areas were mainly of biogenic origin. Compared to sediment quality guidelines (SQGs) and contamination factor (Cf), the study area sediments were in the conditions of moderate pollution and had a low ecological risk.

Revised Iranian Water Quality Index (RIWQI): a tool for the assessment and management of water quality in Iran.

Water quality indices use biological, chemical, and physical data and information to classify the condition of surface waters, ultimately contributing to their management. We used multicollinearity and principal components analyses to develop the Revised Iranian Water Quality Index (RIWQI) as an indicator of agricultural and urban effects in the Karun River Basin of southwestern Iran. Seasonal sampling and analysis of water quality parameters from 54 sites across 18 rivers of the Karun River Basin include fecal coliform, total dissolved solid, phosphate, biological and chemical oxygen demand, nitrate, dissolved oxygen saturation, turbidity, pH, and water temperature. This study updates the previous version of Iranian Water Quality Index (IWQI) by differentially weighting individual variables, refining the main sub-indices, adding phosphate (PO4-), biological oxygen demand (BOD), chemical oxygen demand (COD), and temperature (T), and improving the aggregation calculation. Sensitivity testing of the RIWQI resulted in a mean value for discrimination efficiency (DE) > 85.6%, the highest of other indices calculated with the same dataset.

Assessment of the impact of 2019 Karun River flood on river sediment in Ahvaz city area, Iran.

Following the 2019 Karun River's flood, this study was conducted to evaluate the impact on the physicochemical characteristics and potentially toxic elements (PTEs) concentrations in the sediments as compared to 2015 pre-flood study. Surficial and core samples were collected from the river bed stretching through Ahvaz city for analysis and evaluation. The physicochemical properties of the sediments and the concentrations of PTEs (Mn, Fe, Cr, Ni, As, Zn, Pb, and Cu) in samples were determined by standard methodology. The PTEs contamination in sediments was assessed by calculating the contamination factor and the contamination degree. The potential ecological risk index (RI) was used to assess the contamination degree and ecological effects of PTEs in sediments. The comparative results showed that the flood reduced the concentration of PTEs and organic carbon in the sediments. The flood also decreased the silt and clay content and increased the acidity and sand content compared to pre-flood samples. The post-flood ecological risk assessment revealed that the sediments remained as low risk as compared to pre-flood state. Reduction of post flood PTEs concentration in the sediments as compared to pre-flood concentrations is probably due to long-term exposure to pollutants in the pre-flood sediments. It appears the reduction in the amount of clay particles and organic carbon (as important adsorbents for pollutants) has resulted in reduction of pollutants in the sediments. Statistical analysis of PTEs in the post-flood sediments showed that the major source of metals is geogenic. It seems that despite being destructive for the inhabitants, the flood, has reduced the amount of pollutants and the ecological risk, in the study area, at least for a while.

Molecular Survey of Leishmania Infection of Sand Flies in Karun County, Southwestern Iran.

Background: Zoonotic cutaneous leishmaniasis (ZCL) is widely distributed in Iran and around the world. Also, Khuzestan Province is an endemic focus of ZCL. This study aims to investigate the natural infection of sand flies with the Leishmania parasite in Karun County. Methods: Sand flies were collected from Jangiyeh, Qaleh Chanan, Kut-e-Navaser, and Ghazavieh in the spring and summer in the year of 2019, by installing 60 sticky paper traps each time (30 traps outdoors and 30 traps indoors). Two hundred female sand flies with different abdominal conditions (empty, blood-fed, semi-gravid, and gravid) were examined for infection rate using the Nested-PCR method. Results: In this study, seven species of sand flies including Phlebotomus papatasi, Ph. alexandri, Ph. sergenti, Ph. caucasicus, Sergentomyia tiberiadis, Se. sintoni, and Se. antennata were reported from Karun County, with a frequency of 79.64%, 16.96%, 1.07%, 0.18%, 0.36%, 1.61%, and 0.18%, respectively. Only eleven specimens of Ph. papatasi were found to be positive for Leishmania major, with an overall infection rate of 7.8%. The infection of Ph. papatasi was specifically reported in blood-fed, gravid, and semi-gravid specimens, with infection rates of 17.02%, 4.35%, and 14.29%, respectively. Conclusion: In this study, the infection of L. major from Ph. papatasi was reported. The results can be used in planning the control of ZCL in the study area.

Applying the new multi-objective algorithms for the operation of a multi-reservoir system in hydropower plants.

The optimal operation of the multi-purpose reservoir system is a difficult, and, sometimes, non-linear problem in multi-objective optimization. By simulating biological behavior, meta-heuristic algorithms scan the decision space and can offer a set of points as a group of solutions to a problem. Because it is essential to simultaneously optimize several competing objectives and consider relevant constraints as the main problem in many optimization problems, researchers have improved their ability to solve multi-objective problems by developing complementary multi-objective algorithms. Because the AHA algorithm is new, its multi-objective version, MOAHA (multi-objective artificial hummingbird algorithm), was used in this study and compared with two novel multi-objective algorithms, MOMSA and MOMGA. Schaffer and MMF1 were used as two standard multi-objective benchmark functions to gauge the effectiveness of the proposed method. Then, for 180 months, the best way to operate the reservoir system of the Karun River basin, which includes Karun 4, Karun 3, Karun 1, Masjed-e-Soleyman, and Gotvand Olia dams to generate hydropower energy, supply downstream demands (drinking, agriculture, industry, environmental), and control flooding was examined from September 2000 to August 2015. Four performance appraisal criteria (GD, S, Δ, and MS) and four evaluation indices (reliability, resiliency, vulnerability, and sustainability) were used in Karun's multi-objective multi-reservoir problem to evaluate the performance of the multi-objective algorithm. All three algorithms demonstrated strong capability in criterion problems by using multi-objective algorithms' criteria and performance indicators. The large-scale (1800 dimensions) of the multi-objective operation of the Karun Basin reservoir system was another problem. With a minimum of 1441.71 objectives and an average annual hydropower energy manufacturing of 17,166.47 GW, the MOAHA algorithm demonstrated considerable ability compared to the other two. The final results demonstrated the MOAHA algorithm's excellent performance, particularly in difficult and significant problems such as multi-reservoir systems' optimal operation under various objectives.

Improving the performance of macroinvertebrate based multi-metric indices by incorporating functional traits and an index performance-driven approach.

Human-driven multiple pressures impact freshwater ecosystems worldwide, reducing biodiversity, and impacting ecosystem functioning and services provided to human societies. Multi-metric indices (MMIs) are suitable tools for tracking the effects of anthropogenic pressures on freshwater ecosystems because they incorporate various biological metrics responding to multiple pressures at different levels of biological organization. However, the performance and applicability of MMIs depend on their metrics' selection and their calibration against natural environmental gradients. In this study, we aimed to unravel i) how incorporating functional trait-based metrics affects the performance of MMIs, ii) how disentangling the natural environmental gradients from anthropogenic pressures effects affects the performance of MMIs, and iii) how the performance of MMIs developed using a metric performance-driven approach compares with MMIs developed using an index performance-driven approach. We carried out a field survey measuring abiotic and biotic variables at 53 sites in the Karun River basin (Iran) in 2018. For functional trait-based metrics, we used 15 macroinvertebrate traits and calculated community-weighted mean trait values and functional diversity indices. We used random forest modeling to account for the effect of natural environmental gradients on each metric. Based on our results, incorporating functional traits increased the MMI performance significantly and facilitated ecological interpretation of MMIs. Both taxonomic and functional components of macroinvertebrate assemblages co-varied strongly with natural environmental gradients, and accounting for these covariations improved the performance of MMIs. Finally, we found that index performance-driven MMIs performed better in terms of precision, bias, sensitivity, and responsiveness than metric performance-driven MMIs.

Distribution and Expansion of Alien Fish Species in the Karun River Basin, Iran.

We assessed the distribution of alien fishes in the Karun River Basin, Iran. Fish were collected from 39 sites during the November-December 2018 low-flow period. In total, 39 fish species from nine orders and 14 families were documented. Among these, 10 species were alien to the basin (986 individuals; 15.7%). Four species were the most abundant alien species and primarily in impounded, downstream reaches. Redundancy analysis (RDA) was conducted to identify the extent of changes in alien fish assemblages with environmental parameters. RDA1 and RDA2 accounted for 36.24% and 25.33% of the variation of alien species, respectively. Altitude, depth, electrical conductivity, water temperature, turbidity, dissolved oxygen, and river width were the most significant parameters affecting alien species distributions. We present a dual-pathway cause-and-effect hypothesis proposing that alien fish species presence causes declines in the ecological status of native fish communities. We then explore how human-induced aquatic ecosystem degradation creates opportunities for alien species to invade new ecosystems, further impacting native fish communities. Our study contributes insight into the cause and effect of the presence of alien fish species in the Karun River Basin and emphasizes the urgency of conservation measures to protect this critically endangered watershed.

Fish Species Composition, Distribution and Community Structure in Relation to Environmental Variation in a Semi-Arid Mountainous River Basin, Iran.

We analyzed spatial variation in fish species richness and community composition in the Karun River basin, Iran. Knowledge about fish diversity in the basin is incomplete and varies widely along spatial and temporal scales: The Karun is the longest river in Iran (950 km) with the largest drainage area (about 67,000 km2). Fish samples were collected from 54 sites from July through August 2019 using a backpack electro-fisher. Physico-chemical and habitat parameter data collected at each site included pH, conductivity (µS/cm), dissolved oxygen (mg/L), water temperature (°C), turbidity (NTU), stream width (m), stream depth (m), water velocity (m/s) and elevation (m). In total, 37 species were collected (5241 individuals weighing 110.67 kg). The species collected represented 12 families and 27 genera. A total of 13 endemic species (35.14%), 16 native species (43.24%), and eight non-native species (21.62%) were recorded. Diversity indices were calculated and used to measure the spatial variation in community composition. Relationships between native and endemic species assemblage structure and environmental descriptors were assessed using canonical correspondence analysis (CCA). The first two axes of the canonical correspondence analysis explained 62.57% of the variation in the data. Of the nine environmental descriptors analyzed, eight significantly affected species distribution; however, electrical conductivity and elevation were most influential. Our study provides up-to-date status information on the distribution of freshwater fishes in the Karun River basin. This information is essential for developing conservation and management strategies to support the long-term sustainability of fish populations in the Karun River basin.

Data on optimization of the Karun-4 hydropower reservoir operation using evolutionary algorithms.

This article describes the time series data for optimizing the hydropower operation of the Karun-4 reservoir located in Iran for a period of 106 months (from October 2010 to July 2019). The utilized time-series data included reservoir inflow, reservoir storage, evaporation from the reservoir, precipitation on the reservoir, and release of water through the power plant. In this data article, a model based on Moth Swarm Algorithm (MSA) was developed for the optimization of water resources. The analysis showed that the best solutions achieved by the MSA, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were 0.147, 0.3026, and 0.1584, respectively. The analysis of these datasets revealed that the MSA algorithm was superior to GA and PSO algorithms in the optimal operation of the hydropower reservoir problem.

Biochemical oxygen demand prediction: development of hybrid wavelet-random forest and M5 model tree approach using feature selection algorithms.

Supplying adequate water to individuals and maintaining water supplies to support human life, particularly to rapidly urbanizing communities, are of paramount importance in the development of urban areas in each country worldwide. In turn, maintaining water resource quality and avoiding permanent damage as a consequence of environmental pollution and unsustainable off-take from sources such as rivers and aquifers should be considered as important as the water supply quantity. In this study, random forest (RF) and M5 model tree (M5) models were used to predict water biochemical oxygen demand (BOD). Having decomposed the input variables by wavelet transform, based on the feature selection algorithms (FS) (relief (RA), correlation (CA), principal component analysis (PCA), and ant colony optimization (ACO) algorithms), the important components were recognized and inserted into the RF and M5 models. The proposed approach was applied to Karun River in Ahvaz station on a monthly basis from 2006 to 2018. The results showed that the RF model had better performance with R = 0.872, MAE = 0.0312, and RMSE = 0.0332 values for the variable of BOD compared with the M5 model with R = 0.751, MAE = 0.0377, and RMSE = 0.0468 values. In addition, comparing RF and hybrid models, the purposed hybrid models were considered as viable options to improve the prediction accuracy of BOD. The findings also showed that, among the hybrid models, the WRF-PCA model with R = 0.927, MAE = 0.0198, and RMSE = 0.0241 values was the best model for the prediction of BOD values.

Estimation of nonlinear parameters of the type 5 Muskingum model using SOS algorithm.

The Symbiotic Organisms Search Algorithm (SOS) is used as an algorithm based on the social behavior of Symbiotic Organisms in optimization of Non-linear 5 model parameters for flood routing. The data used in this article is 4 day observations from 30 November 2008 to 3 December 2008, which is located between the Molasani, and Ahwaz station on the Karun River. The time series data used included river inflow, storage volume, and river outflow. The results of the developed model with the Symbiotic Organisms Search Algorithm (SOS) were compared with the other Evolutionary algorithms including Genetic Algorithm (GA, and Harmony Search Algorithm (HS). The analysis showed that the best solutions achieved from the objective function by the SOS, GA, and HS algorithms were 143052.02, 143252.35, and 142952.45, respectively. The processes of these datasets determined that the SOS algorithm was premiere to GA, and HS algorithms on the optimal flood routing river problem.•In this article applied the Symbiotic Organisms Search Algorithm for Estimation of nonlinear parameters of the Muskingum hydrologic model of the Karun River located in Iran.•This method can be useful for managers of water, and wastewater companies, water resource facilities for predicting the flood process downstream of the rivers.•The present algorithm performs better than the other algorithms in the discussion of the optimization of Nonlinear 5 parameters of Muskingum model in flood routing.

The organochlorine pesticides residue levels in karun river water.

BACKGROUND: The organochlorine pesticides (OCPs) are among the most commonly used in water streams around the world. Most of these contaminants are highly hydrophobic and persist in sediments of rivers and lakes. Studies have suggested that OCPs may affect the normal function of the human and wildlife endocrine systems. OBJECTIVES: The aim of this study is to determine the concentrations of selected organochlorine pesticides residues [OP'DDT, PP'DDT, alderin, dieldrin, heptachlor, (α,ß,γ,δ) HCH, (α, ß) endosulfan and metoxychlor] in samples from Karun River water at Khuzestan province in Iran , by GC-µ-ECD. MATERIALS AND METHODS: Water was extracted with n-hexane and then purified by passing through a glass column packed with Florisil and Na2SO4, which was then eluted with ether: hexane solution v/v. RESULTS: In general, all of 12 investigated organochlorine pesticides (OCPs) were detected. Regardless of the kind of OCPs, the highest OCP pollution level in Karun River were seen from August to November 2009 ranging 71.43 - 89.34 µg/L, and the lowest were seen from Dec 2010 to March 2011 at levels of 22.25 - 22.64 µg/L. The highest and lowest mean concentrations of 12 investigated pesticides were ß-Endosulfan and pp' DDT with 28.51and 0.01 µg/L respectively. CONCLUSIONS: Comparison of total organochlorine pesticides residues concentration with WHO guidelines revealed that the Karun River had total OCPs residues above the probable effect level (0.2-20 µg/L, P < 0.05), which could pose a risk to aquatic life.