Jajrood River Research Articles

Quality Evaluation of Jajrood River (IRAN) by Quality Indices Methods

This Regular evaluation and analysis of river quality helps accurate management to reach acceptable quality. In this study, water quality indices (WQI) method applied to evaluate quality of Jajrood River which is one of the main sources of Tehran drinking water. It helps to subsidize management actions in Jajrood watershed. Sampling carried out for 9 years during 2001-2010 in 10 stations along the river in wet and dry stations to identify water quality and the main source of pollution. Results show water quality in all stations classifies as medium according to National Sanitation Foundation (NSF) and water quality index in wet season is better than the corresponding value in dry seasons. Entrance of pollution during the upstream of Latian Dam (especially in populated centers) has negative effect on the water quality, however river has a good natural attenuation capacity, therefore quality index of river in the main inlet of Latian dam (Lashkarak Bridge) classifies as medium. Collecting wastewater at the populated centers and developing soil conservation and controlling erosion at the upstream of watershed can effectively improve the water quality of river.

Prediction of water quality parameter in Jajrood River basin: Application of multi layer perceptron (MLP) perceptron and radial basis function networks of artificial neural networks (ANNs)

River water quality is a significant concern in many countries, considering agricultural and drinking consumptions. Therefore, prediction of salinity index, as the main water quality condition is a necessary tool for water resources planning and management. This paper describes the application of artificial neural networks (ANNs) models for computing the total dissolved solids (TDS) level in Jajrood River (Iran). Two ANN networks, multi-layer perceptron (MLP) and radial basis function (RBF), were identified, validated and tested for the computation of TDS concentrations. Both networks employed five input water quality variables measured in river water over a period of 40 years. The performance of the ANN models was checked through the coefficient of determination (R2) and root mean square error (RMSE). Jajrood River is one of the most important rivers which is located adjacent to Tehran city and supplies drinking water for people who live in this mega-city and recreational uses. Tehran is the most populous city and largest industrial pole in Iran, which caused the river, to be exposed to various pollutants. Matlab 2007 was selected for modeling goals in this research. Results show that MLP and RBF modeling as two methods of ANN are able to simulate water quality variables of Jajrood River with more than 90% accuracy. After modeling in MLP and RBF formatting and comparing simulation results (output) show that, the RBF result (R2 of validation is 0.9362) are more closely to reality than the MLP (R2 of validation is 0.8968). In other words, because of large number of input data, the RBF modeling performance has a better prediction than MLP modeling. Key words: Water quality variables, artificial neural network (ANN), multi-layer perceptron (MLP), radial basis function (RBF).

Comparison of automated and manual landform delineation in semi detailed soil survey procedure

ASTER DEM data was used to automate landform classification during soil survey in the Varamin area. For comparison, manual landform classification was done in the same area. Study area was located at South of Jajrood river watershed, Southeast of Tehran province (Iran). The main purpose of this study was to compare the effect of automated and manual landform classification methods in semi-detailed soil survey procedure. Eight geomorphometric parameters were extracted from DEM using the TAS and DiGem software. The Pearson correlation coefficient analysis elucidated that, the most effective of parameters were: analytical hill-shade, plan and profile curvature, and slope and divergence-convergence index. In addition to these terrain attributes, principal component analyses (PCA) of primary geomorphometric parameters were produced to increase the quality of classification and to reduce modeled data. First three PCAs cover 97% of variance of the data. These PCAs and mentioned terrain parameters were selected for performing of K-means unsupervised landform classification model. Results indicated that unsupervised and manual classification can be complemented, such that conflation of the final maps obtained by these methods can produce a more accurate map. Also, the K-means algorithm with correct iterations, tolerance and suitable number of classes can be used for automated landform classification as well. Hybrid landform classification method is useful for soil survey and soil mapping especially, in watersheds and natural resource fields. Key words: Hybrid landform classification, geomorphometric parameters, K-means classifier, Pearson correlation coefficient.

Assessment of surface water resources quality in Tehran province, Iran

Abstract Karaj and Jajrood rivers are important sources of water supply for Tehran province and special attention should be paid to water quality and its change trends in these rivers. In this study NSFWQI method as well as analytical methods was applied to determine water quality of these rivers. Water quality data sets consist of 9 parameters related to NSFWQI of three years (from April 2006 to March 2009). Parameters in 20 stations of Karaj river and 24 stations of Jajrood river have been examined monthly (except in spring and summer of 2007, as seasonally). On the basis of NSFWQI classification, water quality of two rivers classified as moderate to good quality in this period of time. Results show Karaj river has had better quality, however the WQI of dams’ effluent of two rivers are similar. WQI has improved annually over time and the most and the least significant amounts of that occurred during winter and spring, respectively. Correlation analysis showed that DO and temperature have strong negative correlation; however some of other parameters have significant correlation with each other (TS and turbidity). Of the nine parameters, PO4 has had little effect on deterioration of water quality and BOD5 and temperature have had the most and least variations, respectively.

A probabilistic water quality index for river water quality assessment: a case study

Available water quality indices have some limitations such as incorporating a limited number of water quality variables and providing deterministic outputs. This paper presents a hybrid probabilistic water quality index by utilizing fuzzy inference systems (FIS), Bayesian networks (BNs), and probabilistic neural networks (PNNs). The outputs of two traditional water quality indices, namely the indices proposed by the National Sanitation Foundation and the Canadian Council of Ministers of the Environment, are selected as inputs of the FIS. The FIS is trained based on the opinions of several water quality experts. Then the trained FIS is used in a Monte Carlo analysis to provide the required input-output data for training both the BN and PNN. The trained BN and PNN can be used for probabilistic water quality assessment using water quality monitoring data. The efficiency and applicability of the proposed methodology is evaluated using water quality data obtained from water quality monitoring system of the Jajrood River in Iran.

Determination of organochlorine pesticides in river water using dispersive liquid–liquid microextraction and gas chromatography–electron capture detection

Dispersive liquid–liquid microextraction (DLLME) coupled with gas chromatography–electron capture detection (GC–ECD), has been developed for the extraction and determination of 14 organochlorine pesticides (hexachlorocyclohexanes (α-HCH, β-HCH and δ-HCH), Lindane (γ-HCH), Aldrin, Dieldrin, Endrin, Heptachlor, Heptachlor epoxide, α-Chlordane, β-Chlordane and p,p′-DDT, p,p′-DDD, p,p′-DDE) in river water samples. Factors relevant to the microextraction efficiency, such as the kind of extraction and disperser solvent, their volume and the salt effect was investigated and optimised. In this method the appropriate mixture of extraction solvent (13.5 µL carbon disulphide) and disperser solvent (0.50 mL acetone) were rapidly injected into the aqueous sample by syringe. The values of the detection limit of the method were in the range of 0.05–0.001 µg L−1, while the relative standard deviations for five replicates varied from 2.7 to 9.3%. A good linearity (0.9894 ≤ r 2 ≤ 0.9998) and a broad linear range (0.01–200 µg L−1) were obtained. The method exhibited enrichment factors ranging from 647 to 923, at room temperature. The relative standard deviations varied from 2.7 to 9.3% (n = 5). The relative recoveries of each pesticide from water samples at spiking levels of 2.00 and 10.0 µg L−1 were 88.0–111.0% and 95.8–104.1%, respectively. Finally, the proposed method was successfully utilised for the preconcentration and determination of the organochlorine pesticides in the Jajrood River water samples.

Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.

Competitive heavy metals adsorption on natural bed sediments of Jajrood River, Iran

The presence of heavy metal concentrations was examined in natural sediments from four sites along the Jajrood river in northeast of Tehran, the capital of Iran. Besides determination of elemental concentrations (Pb, Cu, Zn, Cd, Ni and Cr), X-ray fluorescence and X-ray diffraction tests were carried out to determine other chemical components in these adsorbents. Also the ability of sediments to adsorb these heavy metal ions from aqueous solutions was investigated. Results show that the extent of adsorption increases with increase in adsorbent concentration. The amount of adsorbed Pb, Cu and Zn in sediments was much greater than that of the other metals, and Cr was adsorbed much less than others. The adsorbabilities of sediments to heavy metals increased in the order of Pb > Cu > Zn > Cd > Ni > Cr. Based on the adsorption data, equilibrium isotherms were determined at selected areas to characterize the adsorption process. The adsorption data followed Freundlich and Langmuir isotherms in most cases. Correlation and cluster analysis was performed on heavy metals adsorption and sediment components at each site to evaluate main adsorbing compounds in sediments for each metal. Results demonstrated that heavy metals sorption is mostly related to load of organic matter in the Jajrood river sediments.

ASSESSMENT OF JAJROOD RIVER WATERSHED MICROBIAL POLLUTION: SOURCES AND FATES

The Jajrood River watershed is one of the main drinking water resources of Tehran, the capital city of Iran. In addition it provides many recreational usages. However, a variety of microbial pollutions is commonly perceived in the Jajrood River, among them a high concentration of coliform group bacteria that has caused strong concerns. In this article, different aspects of microbial pollution as well as the main microbial pollution sources in the region are discussed. Coliform group bacterial die-off rates have been evaluated as the key parameters that govern bacterial fate in the watershed and were estimated using both laboratory and field data investigations. The high values of the bacterial die-off rates cause significant reduction in the bacteria population naturally. According to the first order decay equation, around 74% of the microbial pollution from domestic wastewater of the 3 main cities in the study area would be attenuated naturally before arrivals to the watershed outlet. In addition, around 98.1% of the microbial population of the animal excretion in the surface area would be decayed naturally. By investigating both sources and fates in the Jajrood River watershed, our knowledge about coliform group bacteria dynamics in this watershed would be enhanced. Therefore, microbial pollution can be managed in a sustainable way by evaluation and use of natural capacity of bacteria die-off in the environment. The derived values for bacterial die-off rates can be a useful reference in microbial studies and modeling attempts.

Prey size selection of the Eurasian Otter, Lutra lutra (Linnaeus, 1758), at the Jajrood River, Iran

Eurasian Otters, Lutra lutra (Linnaeus, 1758), prey at the River Jajrood, east of Tehran, generally on fish between 3 and 21 cm in length, but the size range varied with different species and at different sites. The length of Alburnoides bipunctatus in the diet correlates with the length of fish found in the river, but a similar correlation is not found regarding Leucuscus cephalus and Capoeta spp. Otters appear to select these two species according to their size: L. cephalus and Capoeta spp. with a size between 9 and 15 cm and A. bipunctatus with a size between 3 and 9 cm. At site 2, a significant correlation was found between the length of A. bipunctatus in the diet and in the river, but there was no similar correlation for L. cephalus and Capoeta spp. As at site 1, otters appear to select L. cephalus and Capoeta spp. according to their length. At site 3, finally, we found a significant correlation between the length of A. bipunctatus and L. cephalus in the diet and in the river, but not in Capoeta spp. These results emphasise the diverse spectrum of the diet of the Otter in Iran. The differences between the three sites on the same river suggest that the Otter preys opportunistically.

Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran, Iran)

In this paper, principal component analysis (PCA) and hierarchical cluster analysis (CA) methods have been used to investigate the water quality of Jajrood River (Iran) and to assess and discriminate the relative magnitude of anthropogenic and “natural” influences on the quality of river water. T, EC, pH, TDS, NH 4, NO 3, NO 2, Turb., T.Hard., Ca, Mg, Na, K, Cl, SO 4, SiO 2 as physicochemical and TC, FC as biochemical variables have been analyzed in the water samples collected every month over a three-year period from 18 sampling stations along a 50 km section of Jajrood River that is under the influence of anthropogenic and natural changes. Exploratory analysis of experimental data has been carried out by means of PCA and CA in an attempt to discriminate sources of variation in water quality. PCA has allowed identification of a reduced number of mean 5 varifactors, pointing out 85% of both temporal and spatial changes. CA classified similar water quality stations and indicated Out-Meygoon as the most polluted one. Ahar, Baghgol, Rooteh, Befor Zaygan, Fasham, Roodak and Lashgarak were identified as affected by organic pollution. A Scree plot of stations in the first and second extracted components on PCA also gave us a classification of stations due to the similarity of pollution sources. CA and PCA led to similar results, though Out-Meygoon was identified as the most polluted station in both methods. Box-plots showed that PCA could approximately demonstrate temporal and spatial variations. CA gave us an overview of the problem and helped us to classify and better explain the PCA results.

Effects of bilateral eyestalk ablation on gonadal maturity, moulting and biochemical changes in the hemolymph of female Potamonpersicum crabs (Decapoda, Brachyura, Potamidae)

Adult female crabs (Potamonpersicum; n=65) were collected from the Jajrood River in the east of Tehran, Iran. Both eyestalks were removed in crabs that weighed 27.6 ± 2.1 g. Changes in the levels of glucose and protein titers in the hemolymph, the number of hemocytes, gonadal and hepatic indices, body weight and carapace length were determined. The level of glucose in the hemolymph was significantly decreased at the end of the first week following eyestalk ablation and significantly increased by the end of the second and third weeks following eyestalk removal compared to the control groups with intact eyestalk (p < 0.05). A significant increase was observed in the total protein level of the hemolymph of destalked crabs at the end of the third week compared to those in the control group (p < 0.05). The fractions of total protein showed significant changes at the end of the third week compared to the control group (p < 0.05). The mean total hemocytes count (THC) in the hemolymph was significantly increased in ablated crabs at the end of the second and third weeks compared to the control group (p < 0.05). The gonadal and hepatic indices of the ablated crabs were significantly increased and decreased, respectively, at the end of the second week compared to the control groups (p < 0.05). The mean body weight of the ablated crabs was increased significantly at the end of the second and fourth weeks compared to the control group (p < 0.05). No significant change was observed in the mean carapace length of the ablated crabs at the end of the second week, but it had increased significantly by the end of the fourth week compared to the control group (p < 0.05). The ablated crabs moulted four weeks after the removal of their eyestalks, but no precocious moulting was observed in the control group.

Habitat selection of the Eurasian Otter, Lutra lutra, in Jajrood river, Iran

The Jajrood River, with 140 km length in the east of Tehran, was selected for this study. To study otter distribution, 16 sites at about 5 km intervals were selected and otter signs, habitat parameters such as vegetation cover, river width and the presence of fish in the river were recorded for each 600 m stretch by walking its entire length. A total of 599 signs of otter presence (spraints, tracks, holts, rolling places and passes) were identified over the whole study period, the most common being spraints. Otter spraints were found in 6 of the 16 sites, and three core distribution areas were identified. A seasonal change was found in spraint frequency in the study area. Multiple linear regressions was used for predicting the variables that influence sprainting activity. Significant and positive relationships were found between the number of otter signs, the altitude and the presence of pools.