Monitoring and assessment of water health quality in the Tajan River, Iran using physicochemical, fish and macroinvertebrates indices
© Aazami et al.; licensee BioMed Central. 2015
Received: 7 July 2014
Accepted: 7 April 2015
Published: 16 April 2015
Nowadays, aquatic organisms are used as bio-indicators to assess ecological water quality in western regions, but have hardly been used in an Iranian context. We, therefore, evaluated the suitability of several indices to assess the water quality for an Iranian case study.
Measured data on biotic (fish and macroinvertebrates) and abiotic elements (28 physicochemical and habitat parameters), were used to calculate six indices for assessment of water quality and the impact of human activities in the Tajan river, Iran. GIS, uni- and multivariate statistics were used to assess the correlations between biological and environmental endpoints.
The results showed that ecological condition and water quality were reduced from up- to downstream. The reduced water quality was revealed by the biotic indices better than the abiotic ones which were linked to a variety of ecological water quality scales.
The fish index showed a strong relationship with long-term database of physicochemical parameters (12 years (94%)), whereas macroinvertebrates index is more correlated with short-term data (76%). Meanwhile, the biotic and abiotic elements in this study were also classified well by PCA. Pulp and wood plants and sand mining are indicated to have the most negative effects on the river ecosystem.
KeywordsWater health quality Bio-indicators Tajan Physicochemical parameters
One of the greatest environmental challenges of this century is to sustain natural biological structural and functional attributes of aquatic ecosystems, rivers in particular. This goal requires that we know the condition of these dynamic systems and how they are being affected by specific factors and forces . Nowadays, we can easily see that there are many pollutants in the environment due to anthropogenic activities. The destruction of natural habitats and the presence of environmental pollutants may affect the ecological balance of every ecosystem . Among various ecosystems in the world, rivers which cross different areas such as agriculture and industry are the most threatened and affected by anthropogenic activities . In developing countries such as Iran, water pollution is a common and widespread problem. Therefore, water resource management of rivers is of great importance and especially essential for semiarid and developing countries . Assessment and classification of ecological water quality using indices-based approaches can help the conservation and management of rivers. The measurement of physicochemical parameters is usually time-consuming, cost-intensive and also dependent on special instruments. However, physicochemical parameters can only show water quality at the moment of measurement and these can change over time. Nowadays, indicators based on the presence or absence aquatic organisms have been developed to assess water quality and for the classification of ecological status. Norris and Thoms suggested that the effects on biota are usually the final point of environmental degradation and pollution of rivers and thus are an important indication of ecosystem health .
Many living organisms (e.g. small mammals, fish, aquatic plants, algae, invertebrates) can be used to assess ecological water quality. Fish encompass different trophic levels, have a long life cycle, and high mobility, and can herewith be used to integrate the effects of habitat change and environmental pollution over a long period . Macroinvertebrates are used for bioassessment because they are relatively easily sampled and are a very biodiverse group of species inhabiting waters that is contaminated to a different extent (from clean to highly polluted) [7-9]. They are important for the cycling of organic matter and provide food resources for higher trophic levels. The fluctuation of macroinvertebrate richness in the aquatic environment may result in the change of the ecosystem function. Moreover, the relatively low mobility and long life cycles of macroinvertebrates ensure that the presence of a given taxon reflects the past conditions. Many previous studies have shown the importance of biotic indices in the world, especially in Europe .
However, there are only a few studies using biotic indices in Asian countries such as Iran. The water quality monitoring programs in Iran are mainly based on the determination of some physicochemical parameters and water quality indices have generally not yet been use as a tool for the assessment and management of river ecosystems. Meanwhile, scientific efforts have often focused on improving freshwater resources that are of economic, cultural or spiritual importance. Unfortunately, most of these efforts have proceeded without documentation of the relative successes and failures of individual activities. Even though success is noted, there is often a lack of biotic data to identify specific results or endpoints for the river management activity .
In this study, we tried to employ the most widely used biotic and physicochemical indices to classify the ecological water quality in one of the most important Iranian rivers, the Tajan River. This river was chosen as a pilot river from the 115 rivers in the north of Iran because of having a good water-flow, discharge regime, catchment area, Accessibility and environmental condition . Also, there are many similarities such as environmental landscape, climate and land uses between this river and European rivers. Besides, it is possible to select some stations as references because of being away of human activities.
The goals of this study were to determine and classify the ecological water quality of Tajan River based on different indices of water quality and to evaluate their performance, to zone the water quality based on these indices and GIS (Geographic Information System), to assess the effects of human land uses on the river and to compare the results between up- and down-stream parts of the river. This is the first study that compares biotic and physicochemical indices, as well as uses fish species as a bio indicator in an Iranian River.
Materials and methods
Physicochemical and habitat parameters
Width, length, depth, altitude (m), dissolved oxygen (mg/l), pH, water and air temperature (°C), conductivity (μS/cm), turbidity (NTU) and nutrients (NO3-N, NO2-N, NH4-N, and PO4-P, mg/l) were measured in situ by using Portable multi-parameter water analyser and UV–vis Spectrophotometry 8000. Biochemical Oxygen Demand (BOD5, mg/l) and Total Suspended Solids (TSS, mg/l) were determined according to APHA  with three replicate samples being measured in the laboratory. Some stations in this study overlapped with the stations of Iranian Water Resources Management (IWRM). Therefore, the accuracy of the collected data of physicochemical parameters was checked with the data of IWRM which had collected monthly data for twelve years. Average water flow (m/sec) was calculated by calculating the average of the recordings available from the IWRM for the same period as our sampling. According to the Field Manual for Water Quality Monitoring, the National Sanitation Foundation Water Quality Index (NSFWQI) surveyed 142 sites representing a wide range of locations at the local, state, and national level, using about 35 water quality tests which outcomes were combined in an index . Nine parameters (dissolved oxygen, faecal coliform, biochemical oxygen demand, pH, nitrates, total phosphate, temperature, turbidity, and total solids) were chosen and some were judged to be more important than others, so the values were combined by calculating a weighted mean, based on the method described by Nikoo . For this, field measurements were converted to index values using a questionnaire in which respondents were asked to estimate the level of water quality (0 through 100) corresponding to the field measurements (e.g., pH 2–12). The curves were then averaged and are assumed to represent the best professional judgment of the respondents. When the test results were not available for all 9 measurements, we preserved the relative weight for each factor and scale the total so that the range remains 0 to 100 . The IRWQIsc index is a modification of NSFWQI based on the local condition in Iran. Habitat assessment was performed using 10 factors assessed by four experts and the Rapid Bioassessment Protocol (RBP) was used for river habitat assessment by visual observations at each site . The range of each habitat parameters was from 0 (very perturbed) to 20 (pristine) and included Epifaunal Substrate/Available Cover, Embeddedness (Embed), Velocity/Depth Regime, Sediment Deposition, Channel Flow Status, Channel Alteration, Frequency of Riffles (Freq), Bank Stability, Vegetative Protection, Distance of References (DisRef), and Riparian Vegetative Zone Width. Finally, an average of the ranges of the parameters resulted in an overall RBP index.
Indices used to classify water and habitat quality
15 – 29.9
30 – 44.9
45 - 55
55.1 - 70
70.1 - 85
Physicochemical and biological indices of water quality
Physical habitat quality (type, stability, availability, etc.) and water quality are reflected by the diversity of stream communities. Based on these relationships, environmental quality of aquatic systems can be described or categorized using integrated approaches that incorporate an evaluation of the physical, chemical and biological components. The guidelines associated with the RBP provide systematic approaches for identifying habitat quality and biotic integrity of river systems [26-28].
Qi = sub-index for each water quality parameter;
Wi = weight associated with each water quality parameter;
n = number of water quality parameters.
Ii = sub-index for each water quality parameter;
Wi = weight associated with each water quality parameter;
n = number of water quality parameters;
a = the sum of the weight.
B = the value for each species;
n = abundance of each species;
N = total number of species.
Subsequently, ecological water quality is assessed with Karr Biotic Index of Fish (KBI). KBI was firstly invented by Karr to study the River Trent basin in Champaign, then applied by other researchers, and is nowadays used all over the world and well documented by Karr and Ruaro [22,31]. The index is designed to assess the present the status of the community using twelve fish community parameters. These parameters can be roughly grouped into two sets: ecological factors (including number of individuals in samples, the proportion of omnivore individuals, proportion of insectivorous cyprinids, proportion of top carnivorous, proportion of individuals with disease, tumours, fin damage, and other anomalies) and species composition and richness (including number of species, presence of intolerant species, species richness and composition of darters, suckers and sunfish (except green sunfish) and proportion of green sunfish and hybrid individuals) . Habitat condition is classified based on US EPA Rapid Bioassessment Protocol (RBP) .
Statistical analysis of the resulting data was performed using Excel and SPSS software version 19 (licensed by Tarbiat Modares University, Iran) and Canoco version 5 (licensed by Wageningen University, The Netherlands). Normality of data was checked by ShapiroWilk test. Because the data were not normally distributed, Mann–Whitney U test were used to assess the significance of the difference between up- and downstream values of physicochemical parameters. Cluster analysis was used for the classification of the stations on the basis of the indices and Casewise analysis was used for assessing the correlation between the classifications (with using SPSS). Principal component analysis (PCA) was used to analyse the correlations between abiotic (habitat and physicochemical) parameters and biotic (macroinvertebrates and fish) community. Before analysis, all the macroinvertebrates were divided into 5 groups based on the pollution tolerance owned by the dominant species in each family (Very sensitive, Sensitive, Neutral, Resistant and Very resistant) that was provided in Appendix B of RBP, EPA .
Results and discussion
For irrigating of the vast plain area of downstream rice farms, the dam valves are opened from spring to late summer and closed in early September, with a minimal flow at all time of 1 m3/s. The rains start in early autumn and therefore the best time for sampling is September in accordance with local condition and some previous studies . The main land-use in the upstream areas is not similar to that in the downstream areas, so no similar anthropogenic impact may be expected. Furthermore, there is a larger downstream flow, and herewith also a larger move of pollutants, most of the year because of the opening of the dam valves and irrigation. Habitat parameters show significant differences between up- and downstream sites (see Figure 1 for better understanding). Some land uses such as mining that affect the rivers’ physical status are less development upstream compared to downstream. In the downstream part, there are many mining industries that have altered the physical status of the river. Humans have channelized, diverted, drained and filled streams because of the dredging of sand. In the upstream part of the Tajan River, the higher number of residents has no major impact on the physical structure of habitat. Also, the accessibility of the upstream part of the river is lower than downstreams. Therefore, there are more pristine habitats in upstream. Padmalal et al. showed that in the past 3–4 decades, rivers in the densely populated areas of the world are subjected to immense pressures due to various kinds of human interventions, among which indiscriminating mining for construction-grade sand from alluvial reaches is among the most disastrous one .
The value of the calculated indices for each station
This study provides an assessment and comparison of biotic and abiotic indices-based approaches for the Tajan River. As well as Yazdian et al. concluded, we cannot claim that all of the indices would work in other regions as well , because of the different range in biodiversity, physicochemical parameters and land-uses. Actually, we have to use, modify and develop some native indices for Iranian ecosystems that they can be used for a rapid assessment of environmental health condition. A comparison between the indices shows that the classification based on biotic indices can show the long-term environmental condition better than those based on abiotic indices. We suggest that macroinvertebrates and fish can be used as indicators of water pollution with having the advantages of low cost, easy identification and it provides a better reflection of water quality than using physicochemical parameters alone. We also suggest to develop and modify the biotic indices for research and management of Iranian rivers, since Iran is located in the mid-dry area where water resources management is particularly urgent and important.
The manuscript is part of the PhD thesis of Jaber Aazami and is supported by Tarbiat Modares University, Iran. He would never have been able to do this investigation without the guidance of his committee members, help from friends, and support from his family.
- Ogren SA. Using indicators of biotic integrity for assessment of stream condition. Michigan Tech. 2014;7(5):10–9.Google Scholar
- Begon M, Townsend CR, Harper JL. Ecology: from individuals to ecosystems. London, UK: Blackwell Publishing; 2009.Google Scholar
- Leprieur F, Beauchard O, Blanchet S, Oberdorff T, Brosse S. Fish invasions in the world's river systems: when natural processes are blurred by human activities. PLoS biology. 2008;6(2), e28.View ArticleGoogle Scholar
- Kivaisi AK. The potential for constructed wetlands for wastewater treatment and reuse in developing countries: a review. Ecological Engineering. 2001;16(4):545–60.View ArticleGoogle Scholar
- Norris RH, Thoms MC. What is river health? Freshwater Biology. 1999;41(2):197–209.View ArticleGoogle Scholar
- Mathuriau C, Silva NM, Lyons J, Rivera LMM. Fish and Macroinvertebrates as Freshwater Ecosystem Bioindicators in Mexico: Current State and Perspectives. Water Resources in Mexico. USA: Springer; 2011. p. 251–61.Google Scholar
- Cheimonopoulou MT, Bobori DC, Theocharopoulos I, Lazaridou M. Assessing Ecological Water Quality with Macroinvertebrates and Fish: a case study from a small Mediterranean river. Environmental management. 2011;47(2):279–90.View ArticleGoogle Scholar
- Li F, Cai Q, Fu X, Liu J. Construction of habitat suitability models (HSMs) for benthic macroinvertebrate and their applications to instream environmental flows: A case study in Xiangxi River of Three Gorges Reservior region. China Progress in Natural Science. 2009;19(3):359–67.View ArticleGoogle Scholar
- Schultz R, Dibble E. Effects of invasive macrophytes on freshwater fish and macroinvertebrate communities: the role of invasive plant traits. Hydrobiologia. 2012;84(1):1–14.View ArticleGoogle Scholar
- Ogleni N, Topal B. Water Quality Assessment of the Mudurnu River, Turkey. Using Biotic Indices Water Resour Manage. 2011;25(10):2487–508.View ArticleGoogle Scholar
- Ahmadi M, Khorasani N, Rafiee G. Investigation of pollution sources and water quality of Tajan River. J Nat Environ. 2011;63(4):327–17.Google Scholar
- Shokri M, Rossaro B, Rahmani H. Response of macroinvertebrate communities to anthropogenic pressures in Tajan River (Iran). Biologia. 2014;69(10):1395–409.View ArticleGoogle Scholar
- Ahmadi-Mamaqani Y, Khorasani N, Talebi K, Hashemi SH, Rafiee G, Bahadori-Khosroshahi F. Diazinon Fate and Toxicity in the Tajan River (Iran) Ecosystem. Environmental Engineering Science. 2011;28(12):859–68.View ArticleGoogle Scholar
- Eaton AD, Franson MAH. Standard methods for the examination of water & waste water. USA: American Public Health Association (APHA); 2005.Google Scholar
- Bharti NK. Water quality indices used for surface water vulnerability assessment. Int J Environ Sci. 2011;2(1).Google Scholar
- Nikoo MR, Kerachian R, Malakpour-Estalaki S, Bashi-Azghadi SN, Azimi-Ghadikolaee MM. A probabilistic water quality index for river water quality assessment: a case study. Environmental monitoring and assessment. 2011;181(1–4):465–78.View ArticleGoogle Scholar
- Mitchell M, Stapp W. Field Manual for Water Quality Monitoring–An Environmental Education Program for Schools. Kendall: Hunt Publishing Company; 2000.Google Scholar
- Water USEPAOo, Barbour MT, Gerritsen J, Synder BD, Stribling JB. Rapid bioassessment protocols for use in wadeable streams and rivers: periphyton, benthic macroinvertebrates, and fish. USA: EPA Publishing; 1999.Google Scholar
- Consortium F. Manual for the application of the European Fish Index–EFI; A fish-based method to assess the ecological status of European rivers in support of the Water Framework Directive. Wat Fram Direc. 2005;10(1):12–9.Google Scholar
- Extence C, Bates A, Forbes W, Barham P. Biologically based water quality management. Environmental pollution. 1987;45(3):221–36.View ArticleGoogle Scholar
- Gabriels W, Lock K, De Pauw N, Goethals PL. Multimetric Macroinvertebrate Index Flanders (MMIF) for biological assessment of rivers and lakes in Flanders (Belgium). Limnologica-Ecology and Management of Inland Waters. 2010;40(3):199–207.View ArticleGoogle Scholar
- Karr JR. Assessment of biotic integrity using fish communities. Fisheries. 1981;6(6):21–7.View ArticleGoogle Scholar
- Management IWR. Iranian Water Quality Index for Surface Water Resource-Conventional Parameters “IRWQI”. Tehran: IWRM; 2013. p. 5–14.Google Scholar
- Said A, Stevens DK, Sehlke G. An innovative index for evaluating water quality in streams. Environmental management. 2004;34(3):406–14.View ArticleGoogle Scholar
- Mali L, Boaf N. Environmental condition of rivers and streams in the ovens catchment. Freshwater Sci. 2003;909(1):10–65.Google Scholar
- Barbour MT, Gerritsen J, Snyder BD, Stribling JB. Rapid bioassessment protocols for use in streams and river: Pryphyton, Benthic Macroinvertebrates and fish. 2nd edition. Washington D.C: USEPA; 1999:841-B-99-002. 408p.Google Scholar
- Barbour MT, Stribling JB, Verdonschot PF. The multihabitat approach of USEPA’s rapid bioassessment protocols: Benthic macroinvertebrates. Limnetica. 2006;25(3):839–50.Google Scholar
- Winger PV, Lasier PJ, Bogenrieder KJ. Combined use of rapid bioassessment protocols and sediment quality triad to assess stream quality. Environmental monitoring and assessment. 2005;100(1–3):267–95.View ArticleGoogle Scholar
- Tyagi S, Sharma B, Singh P, Dobhal R. Water quality assessment in terms of water quality index. American Journal of Water Resources. 2013;1(3):34–8.Google Scholar
- Nabizadeh R, Amin MV, Alimohammadi M, Naddafi K, Mahvi AH, Yousefzadeh S. Development of innovative computer software to facilitate the setup and computation of water quality index. Journal of Environmental Health Science and Engineering. 2013;10(1):32.View ArticleGoogle Scholar
- Ruaro R, Gubiani ÉA. A scientometric assessment of 30 years of the Index of Biotic Integrity in aquatic ecosystems: applications and main flaws. Ecological Indicators. 2013;29:105–10.View ArticleGoogle Scholar
- Padmalal D, Maya K, Sreebha S, Sreeja R. Environmental effects of river sand mining: a case from the river catchments of Vembanad lake, Southwest coast of India. Environmental geology. 2008;54(4):879–89.View ArticleGoogle Scholar
- Saremi A, Saremi K, Sadeghi M, Sedghi H. The effect of aquaculture effluents on water quality parameters of Haraz River. Iranian Journal of Fisheries Sciences. 2013;12(2):445–53.Google Scholar
- Rempel LL, Gill G, Fisheries Do, Oceans W, MB. Freshwater Inst. Bioassessment of streams along the Mackenzie River Valley, Canada, using the reference condition approach: biological, habitat, landscape and climate data. Winnipeg, MB (Canada): DFO; 2011.Google Scholar
- Raczyńska M, Machula S, Choiński A, Sobkowiak L. Influence of the fish pond aquaculture effluent discharge on abiotic environmental factors of selected rivers in Northwest Poland. Acta Ecologica Sinica. 2012;32(3):160–4.View ArticleGoogle Scholar
- McCarthy KA, Johnson HM. Effect of agricultural practices on hydrology and water chemistry in a small irrigated catchment, Yakima River basin. Washington: US Geological Survey; 2009.Google Scholar
- Smakhtin V. Environmental water needs and impacts of irrigated agriculture in river basins. A Framework for a New Research Program IWMI Working Paper. 2002;42Google Scholar
- Abdoli A, Naderi M. Biodiversity of fishes of the southern basin of the Caspian Sea. Tehran: Abzian Scientific Publication; 2009.Google Scholar
- Mostafavi H, Pletterbauer F, Coad BW, Mahini AS, Schinegger R, Unfer G, et al. Predicting presence and absence of trout (Salmo trutta) in Iran. Limnologica - Ecology and Management of Inland Waters. 2014;46:1–8.View ArticleGoogle Scholar
- Nnaji J, Uzairu A, Harrison G, Balarabe M. Effect of pollution on the physico-chemical parameters of water and sediments of river Galma, Zaria, Nigeria. Research Journal of Environmental and Earth Sciences. 2011;3(4):314–20.Google Scholar
- Benítez-Mora A, Camargo JA. Ecological responses of aquatic macrophytes and benthic macroinvertebrates to dams in the Henares River Basin (Central Spain). Hydrobiologia. 2014;728(1):167–78.View ArticleGoogle Scholar
- Walker SL, Hedley K, Porter E. Pulp and paper environmental effects monitoring in Canada: An overview. Water Quality Research Journal of Canada. 2002;37(1):7–19.Google Scholar
- Thompson G, Swain J, Kay M, Forster C. The treatment of pulp and paper mill effluent: a review. Bioresource technology. 2001;77(3):275–86.View ArticleGoogle Scholar
- Banagar GR, Kiabi BH, Homayoonnezhad I, Piri I, Amirian P. Biodiversity of Fish Species in Haraz River (An Ecological Approach). World Applied Sciences Journal. 2008;5(1):05–11.Google Scholar
- Yazdian H, Jaafarzadeh N, Zahraie B. Relationship between benthic macroinvertebrate bio-indices and physicochemical parameters of water: a tool for water resources managers. Journal of Environmental Health Science and Engineering. 2014;12(1):30.View ArticleGoogle Scholar
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