Journal of Ecology and Environment

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Published online March 11, 2024

Journal of Ecology and Environment (2024) 48:11

Ecological health assessment of Mae Kha Canal, Chiang Mai Province, Thailand in 2023

Onalenna Manene1 , Nick Deadman2 , Chotiwut Techakijvej3 , Songyot Kullasoot3 , Pitak Sapewisut4 , Nattawut Sareein3 and Chitchol Phalaraksh3,4*

1Master’s Degree Program in Environmental Science, Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
2Master’s Degree Program in Environmental Science, Department of Earth and Environmental Sciences, University of Manchester, Manchester M139PL, United Kingdom
3Environmental Science Program, Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
4Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

Correspondence to:Chitchol Phalaraksh

Received: October 10, 2023; Revised: November 29, 2023; Accepted: January 8, 2024

This article is licensed under a Creative Commons Attribution (CC BY) 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit The publisher of this article is The Ecological Society of Korea in collaboration with The Korean Society of Limnology

Background: The Mae Kha Canal is one of Chiang Mai’s most important waterways. It supports local agriculture, irrigation, and transportation as well as provides stormwater drainage to prevent floods. Due to the unregulated rapid urbanization of the city and lack of efficient waste and wastewater management systems over the past few decades, the canal has become heavily polluted. This study aimed to evaluate the water quality of Mae Kha canal through assessment of the physico-chemical water quality and coliform bacteria. Moreover, benthic macroinvertebrates were samples and assessed using the Biological Monitoring Working Party (BMWPThai) and Average Score Per Taxon (ASPTThai) as biological indices.
Results: The physico-chemical showed low dissolved oxygen levels, high levels of ammonia and phosphates, and elevated levels of biochemical oxygen demand, indicating that the water quality had significantly deteriorated. The canal was found to be heavily polluted, with most sites falling into the polluted to very heavily polluted. Coliform bacteria analysis revealed alarmingly high levels of total coliform bacteria and fecal coliform bacteria in the canal. The BMWPThai and ASPTThai scores indicated poor to very poor water quality.
Conclusions: The physico-chemical and coliform bacteria indicated that the water quality of the Mae Kha canal had significantly deteriorated. The biological indices also indicated the poor to very poor water quality. This study underscores the urgent need for comprehensive remediation efforts, emphasizing strategic planning, investment, and community engagement to revive the canal’s ecological health and water quality.

Keywords: chemical index, coliform bacteria, macroinvertebrates, Mae Kha Canal

Surface water quality degradation is a serious environmental issue that affects areas with heavy human activity (such as urbanization, industrial production, and intensive agriculture) worldwide, and it is expected to get worse without effective regulations or solutions (Tian et al. 2019). Water quality degradation has disturbed the balance of the environment and aquatic systems considerably, affecting their physical, chemical and biological characteristics by contaminating them with untreated domestic waste waters, agricultural and other industrial discharges. The microbial quality has also been affected causing coliform bacteria to be present in water bodies, often more than the acceptable level for home uses like drinking, recreation, or irrigation of crops intended for raw consumption (Aram et al. 2021; Griesel and Jagals 2002).

The longevity of anthropogenic activities on the aquatic ecosystems calls for the necessity to periodically assess and monitor the quality and ecological status of different water bodies (Abdelkarim 2020). Aquatic macroinvertebrates respond differentially to biotic and abiotic factors in their environment and therefore provides for a more reliable assessment of long-term ecological changes in the quality of aquatic systems compared to its rapidly changing physicochemical characteristics (Jun et al. 2016; Li et al. 2010; Malakane et al. 2020; Wolmarans et al. 2014). Macroinvertebrates has long been used as bio-indicators to assess the water quality of water bodies due to their varying tolerance levels to environmental stressors which render them useful in assessing temporal and spatial changes within an aquatic ecosystem (Rosenberg and Resh 1993). Biological monitoring systems can be cheap, require less sophisticated instruments and, most importantly, reflect the integrated expression of pollution load overtime (Oerte and Salánki 2003).

The Mae Kha is one of the canalized urban streams that flows through Chiang Mai City in Northern Thailand. The canal is a vital component of Chiang Mai’s water system, feeding local agriculture, irrigation, and transportation while also providing rainwater drainage to prevent floods (Mettes 2014; Nuanla-Or 2016). Due to the unregulated rapid urbanization of the city and the lack of efficient waste and wastewater management systems over the past few decades, the canal has been heavily polluted (Mettes 2014; Nuanla-Or 2016). Following the floods in Chiang Mai in 2010, the need for and importance of restoring and re-establishing the Mae Kha Canal was encouraged (Nuanla-Or 2016); however, the process requires time, finance and participation of all affected and concerned parties, including government, communities and organizations (Nuanla-Or 2016).

This study aimed to evaluate the water quality of Mae Kha canal through assessment of the physicochemical, biological water quality parameters and macroinvertebrates as bioindicators. Furthermore, the study drew comparisons between the measured biotic and abiotic water quality variables. Information provided by this study is expected to give guidance towards strategic planning for the resuscitation of the canal.

Study area and sampling sites

This study evaluated the water quality of Mae Kha Canal, an urban canal in Chiang Mai City in Northern Thailand. Mae Kha Canal is one of Chiang Mai’s most important waterways running 30 km parallel to the Ping River, flowing from north to south, bordering the floodplains of the Ping River to the west (Fig. 1). Historically the canal was considered a valuable environmental asset, as a source of fresh water and fish, used for agriculture (rice paddies) and forest, flood prevention, transport and recreation. Seven sampling sites along the Mae Kha Canal (MK), from MK1 to MK7 (Fig. 1), were selected for this study. Site MK1 was positioned most upstream outside of the Mae Kha canal on the tributary of the Mae Sa River to act as a reference site with less urban impact. Sites MK2–MK7 were located within the course of the canal from upstream to downstream under different land uses or activities as much as possible. Global positioning systems and Google earth mapping tools were used to determine the exact location of the sampling sites.

Figure 1. Location map of sampling sites along Mae Kha Canal (MK), Chiang Mai City.

Physico-chemical water quality assessment

Measured physico-chemical water quality parameters were selected based on Merck’s chemical index (MCI) (Merck 1989); which uses eight water quality parameters inclusive of water temperature (WT), pH, electrical conductivity (EC), saturated oxygen (O2-S%), biochemical oxygen demand (BOD5), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3--N), and orthophosphate (o-PO43-). WT, pH, EC, and dissolved oxygen (DO) (used for calculating saturated oxygen) were measured onsite using a multiparameter (HORIBA U-52; HORIBA, Kyoto, Japan), BOD5 using the azide modification method whereas NH4+-N, NO3--N and o-PO43- were determined by nesslerization, cadmium reduction and ascorbic acid method respectively following standard methods procedures (Baird et al. 2017). The assessment was conducted in three seasons; February 2023 (cool dry season), April 2023 (hot dry season) and June 2023 (wet/rainy season) at 7 selected sites. Readings or measurements were taken in triplicate per site for each parameter. Water samples were collected in plastic water bottles that were prewashed with the sample at each site and stored under cool conditions prior to analysis.

Measurements of the physico-chemical parameters were then used to calculate MCI which was then used to characterize the water quality of the sampling sites guided by its set classification, described in Table 1. The MCI is a multiplicative index calculated using the eight above mentioned water quality parameters, using the formula below:

Table 1 . Classification of Merck’s chemical index.

ClassRange of chemical indexClassification
I83–100Very clean
II56–73Fairly clean
III–IV17–27Heavily polluted
IV0–17Very heavily polluted

MCI = ∏qiwi = q1w1 × q2w2 × q3w3… qnwn

Where, MCI = a number without dimension on a scale with zero point and interval (0, 100).

qi = sub-index (potential value) for the measurement of parameters on a scale with definition zero point and interval (0, 100).

n = number of parameters.

wi = relative weight of n parameter; summation of wi is equal to one; each parameter has its own weight depending on its impact (Table 2).

Table 2 . Parameters used for Merck’s chemical index and their weights.

ParametersWeight (Wi)
1. Water temperature (°C)0.08
2. pH0.10
3. Conductivity (µS/cm)0.07
4. Saturated oxygen (%)0.20
5. BOD5 (mg/L)0.20
6. Ammonium (NH4+-N) (mg/L)0.15
7. Nitrate (NO3--N) (mg/L)0.10
8. Ortho-phosphate (o-PO43-) (mg/L)0.10
Chemical index1.00

BOD: biochemical oxygen demand.

Coliform bacteria analysis

Sampling for coliform bacteria analysis was done in sterile unused water bottles and stored under cool conditions using ice boxes during transportation to the laboratory for testing. Total coliform bacteria (TCB) and fecal coliform bacteria (FCB) were tested at the Central Laboratory Thailand in Chiang Mai using the multiple tubes fermentation technique method (Baird et al. 2017). The presence of coliform bacteria was expressed in most probable number (MPN/100) of coliform organisms. This method involves culture of replicate portions of the original sample to determine the presence or absence of microorganisms in each portion (Chandrapati and Williams 2014). Multiple serial dilutions inoculated into a suitable growth medium (Lauryl Sulfate or Lauryl Tryptose Broth) and the development of some acid production or turbidity, is used to indicate growth of microorganisms (Bari and Yeasmin 2022).

Benthic macroinvertebrate sampling and analysis

Macroinvertebrates were sampled three times at each sampling site: at the center of the canal and at 80 cm from either bank. Samples were taken by placing a D-frame dip net on the substrate of the canal, with the net opening facing the direction of water flow, then kicking and stomping vigorously in front of the opening for one minute per sample. This semi-quantitative sampling method was the suitable way to obtain the macroinvertebrate data. Due to the low diversity with polluted sampling site (Mustow 1999). Samples were then stored in bags of 90% ethanol prior to identification. After identification, the macroinvertebrate data were combined, with three samples taken per site. Macroinvertebrates were analyzed for diversity following Wilhm and Dorris (1966), including the calculation of Shannon index, evenness, richness, and abundance. After that, macroinvertebrate taxa were analyzed for the Biological Monitoring Working Party (BMWPThai) and Average Score Per Taxon (ASPTThai) scores (Mustow 2002) to assess the diversity of macroinvertebrate communities. Sampling of macroinvertebrates was only carried out during the first two seasons (cool dry and hot dry seasons) due to limitation.

BMWPThai and ASPTThai are techniques for measuring water quality based on the presence of aquatic life, specifically benthic macroinvertebrates. Aquatic animals have variable tolerances to pollutants and may not be found living in polluted freshwater bodies based on this tolerance, making them useful pollution indicators. The BMWPThai has been well described by Mustow (2002). Each taxonomical family has been assigned a score of 1–10 based on their pollution tolerance, with 1 being the most tolerant and 10 the least. Therefore, a high score indicates a low pollution tolerance and less polluted water. The BMWP score is the sum of each independently scored family identified during sampling, while the ASPT is calculated by dividing the BMWP score by the number of scored taxa, producing a mean value between 1–10. Consequently, ASPT does not depend on family richness. Benthic Macroinvertebrates are sampled with a net and then identified to provide a water quality score for a given location. The scores are then compared to the following water quality classifications. For BMWP; very good (over 130), good (81–30), fair (51–80), poor (11–50), very poor (0–10). For ASPT; very good (7 or over), good (6.0–6.9), fair (5.0–5.9), poor (4.0–4.9), very poor (3.9 or less).

Statistical analysis

The mean and standard deviation of the physico-chemical water quality variables were determined. The analysis of variance (ANOVA) was performed to determine whether there were significant differences among the different sites and seasons of the water quality variables with p < 0.05 set as a significant value. Pearsons’s correlation statistical test was applied to check the level of correlation between any pair of the water quality variables. Furthermore, cluster analysis was performed to determine similarity groupings in water quality variables and macroinvertebrates communities.

Physico-chemical water quality parameters

Figure 2 and Table 3 show results of the 8 physico-chemical parameters and the resulting MCI values respectively across the three seasons. WT ranged from 23°C in the cool dry season at MK1 to 31°C in the rainy season at MK5 and 6. The highest pH was 9.47 at MK5 in the rainy season whereas the lowest was 5.24 at MK7 in the cold dry season. Cold dry season had slightly acidic waters at all sites except MK1 and the rest of the seasons had slightly alkaline waters at all sites. DO ranged from 0.33 mg/L at MK4 in the hot dry season to 8.21 mg/L at MK1 in the cold dry season. MK4 recorded the highest measurements and concentrations of all the remaining parameters including EC, BOD, NH4+-N, NO3--N, and o-PO43-. The MCI shows very clean to moderate water quality for MK1, whereas all other sites from MK2–MK7 across all seasons range from class III (polluted) to class IV (very heavily polluted).

Table 3 . Merck’s chemical index results with their corresponding water quality classes.

SitesCool dryHot dryRainyAverage
MK184 (I)54 (II–III)47 (II–III)62 (II)
MK233 (III)23 (III–IV)31 (III)29 (III)
MK314 (IV)18 (III–IV)12 (IV)14 (IV)
MK48 (IV)7 (IV)7 (IV)7 (IV)
MK512 (IV)9 (IV)12 (IV)11 (IV)
MK614 (IV)11 (IV)8 (IV)11 (IV)
MK715 (IV)12 (IV)13 (IV)13 (IV)
Average16 (IV)13 (IV)14 (IV)14 (IV)

MK: Mae Kha Canal.

Figure 2. Seasonal measurements of physico-chemical parameters at different sites. MK: Mae Kha Canal.

One way ANOVA indicated significant differences (p < 0.05) between sites for EC, DO, BOD5, NH4+-N, NO3--N, and o-PO43- and significant differences (p < 0.05) between seasons. For WT, pH and TSS. The strongest positive correlations were between EC and NH4+-N (r = 0.829, p < 0.05) and between EC and o-PO43- (r = 0.832, p < 0.05). Cluster analysis produced three main clusters or groupings of sites based on similarities of physico-chemical parameters and chemical index (Fig. 3). The first cluster is inclusive of less impacted upstream site MK1 for the three seasons, whereas the second group is composed of MK2 site in all seasons and the third included all the other remaining sites from MK3–MK4 for the various seasons. Site groupings or clusters were based on three similarity groupings of physico-chemical parameters with the 1st group inclusive of DO, pH and WT, the 2nd inclusive of the nutrients group (NH4+-N, NO3--N, and o-PO43−) and the third one BOD5 and EC. The MK1 cluster is for the moderate to very clean water quality, MK2 for polluted and the rest of the sites (MK3–MK7) being very polluted to very heavily polluted based on MCI.

Figure 3. Seasonal cluster analysis of the seven sampling sites based on physico-chemical parameters. MK: Mae Kha Canal; HDS: hot dry season; RS: rainy season; CDS: cold dry season; BOD: biochemical oxygen demand; EC: electrical conductivity; NO: nitrate nitrogen; PO: orthophosphate; NH: ammonium nitrogen; WT: water temperature; CI: chemical index; DO dissolved oxygen.

Coliform bacteria

TCB count ranged from 16,000 to 160,000 MPN/100 mL whereas FCB ranged from 330 to 160,000 MPN/100 mL (Fig. 4). The highest levels of TCB and FCB were obtained at site MK4 reaching the maximum measurable levels of 160,000 MPN/100 mL. The lowest levels of TCB that are within the Thai surface water quality standards (≤ 20,000 MPN/100) were obtained at sites MK1, 3 and 7 whereas for FCB only MK1 was within the limits of the standards (≤ 4,000 MPN/100). Seasonal averages for both TCB and FCB are also higher than the water quality standards indicating that the canal is heavily contaminated with pathogens or disease-producing bacteria or viruses from human and animal wastes.

Figure 4. Seasonal measurements of total coliform bacteria (TCB) and fecal coliform bacteria (FCB) of seven sampling sites. MPN: most probable number; MK: Mae Kha Canal.

Benthic macroinvertebrates diversity

Sampling each of the seven sites during the cool dry season and hot dry season resulted in identification of 8,322 benthic macroinvertebrates across 32 taxa. Insects were the most diverse group with 47 families belonging to 9 orders. The dominant groups of insects with the highest taxa richness were Diptera (11 families; 23.40%), followed by Odonata (8 families; 17.02%), Hemiptera (7 families; 14.89%), and Trichoptera (7 families; 14.89%) respectively. Based on abundance, the Micronectidae (Hemiptera) showed the highest percentages (30.70%) followed by Chironomidae (24.39%), and Naididae (17.40%) respectively. It was noted that Micronectidae showed higher abundance in the site MK6, while Chironomidae showed higher abundance in the site MK1, and Naididae in the site MK3, during both cool dry and hot dry seasons. Some representative families of those benthic macroinvertebrates are shown in Figure 5.

Figure 5. Benthic macroinvertebrate families were found in the study localities, with the dominant families being (A-C and J-L), sensitive families (D-I), and tolerance families (J-O). The identified families include Baetidae (A), Coenagrionidae (B), Micronectidae (C), Heptageniidae (D), Ephemeridae (E), Perlidae (F), Hydropsychidae (G), Odontoceridae (H), Lepidostomatidae (I), Chironomidae (J), Lymnaeidae (K), Oligocheta (L), Stratiomyidae (M), Culicidae (N), and Syrphidae (O). Scale bars: 3 mm.

The diversity of benthic macroinvertebrates (Shannon diversity index, evenness, richness, and abundance) of each sampling site in both season were showed in Table 4. The highest abundance was observed in site MK6 during both the cool dry season (1,226 individuals) and the hot dry season (1,526 individuals), while the lowest abundance was recorded in site MK2 during both the cool dry season (69 individuals) and the hot dry season (265 individuals). The highest abundance was observed in site MK6 during both the cool dry season (1,226 individuals) and the hot dry season (1,526 individuals), while the lowest abundance was recorded in site MK2 during both the cool dry season (69 individuals) and the hot dry season (265 individuals). The highest richness was observed in site MK1 during both the cool dry season (33 taxa) and the hot dry season (36 taxa), while the lowest richness was found in site MK5 (6 taxa) during both seasons and MK7 in the cool dry season (6 taxa). Regarding diversity indices, the Shannon diversity index showed the highest diversity in site MK1 during the cool dry season (2.206) and MK2 during the hot dry season (2.181), while the lowest diversity was observed in MK7 during the cool dry season (0.807) and MK3 during the hot dry season (0.782). Lastly, evenness was highest in site MK3 during the cool dry season (0.583) and MK4 during the hot dry season (0.5362), while the lowest evenness was recorded in MK6 during the cool dry season (0.242) and MK1 during the hot dry season (0.167).

Table 4 . The diversity indices of benthic macroinvertebrates of Mae Kha Cannel in cool dry and hot dry season.

SitesShannon diversity indexEvennessRichnessAbundance
Cool dry season
Hot dry season

MK: Mae Kha Canal.

BMWPThai and ASPTThai score

The abundance and presence of pollutant intolerant species fell along the course of the canal, suggesting a drop in water quality (Table 5). The BMWPThai and ASPTThai scores are not in agreement of how to grade each site due to the ASPTThai not being dependent on family richness. Consequently, while more families were found at MK1, the ASPTThai does not consider them pollutant intolerant enough to give the site a score above ‘fair’. The quality of the canal proper (MK2–MK7) based on BMWPThai and ASPTThai scores is typically poor or very poor.

Table 5 . BMWPThai and ASPTThai scores for each site and each sampled season.

SitesBMWPBiological qualityASPTWater quality
Cool dry season
MK1166Very good5.53Fair
MK232Poor2.67Very poor
MK331Poor2.82Very poor
MK430Poor3.00Very poor
MK526Poor2.36Very poor
MK630Poor2.73Very poor
MK715Poor2.14Very poor
Hot dry season
MK1254Very good5.41Fair
MK2102Good3.92Very poor
MK336Poor3.00Very poor
MK460Fair3.75Very poor
MK518Poor2.00Very poor
MK643Poor3.31Very poor
MK743Poor2.87Very poor

BMWP: Biological Monitoring Working Party; ASPT: Average Score Per Taxon; MK: Mae Kha Canal.

Physico-chemical water quality parameters

The upstream land use along the Mae Kha Canal is predominantly agricultural and suburban-residential, transitioning to urban-residential in the mid to downstream regions, with the added impact of extremely low dry-season streamflow primarily composed of wastewater from the city drainage system, households, and businesses influencing Mae Kha’s water quality (Mettes 2014). Moreover, wastewater treatment facilities in the city are insufficient, with a municipal wastewater treatment plants treating only a fraction of the wastewater, primarily in tourist hotspots and the Chiang Mai University campus, while the majority of urban runoff and wastewater, including from hospitals, markets, and a slaughterhouse, is discharged into canals, with decentralized septic tanks handling black water, and there is limited monitoring for healthcare-specific standards (Mettes 2014). The results from this study indicate the canal to be heavily polluted due to the above cited issues. This is evidenced by low levels of DO and high BOD5 across most sites of the canal (< 4 mg/L), and high levels of ammonia and phosphates that are beyond the limits of the surface water quality standards of Thailand. BOD5 was also found to be extremely high across all sites within the canal indicating that the waters are within the category of wastewater. Sites within the most urbanized area exhibited most impacted water quality due to waste discharges that are high in organic matter and nutrients from domestic sewage and industrial waste.

Coliform bacteria

Total and fecal coliform are important sanitary parameters used for evaluating water quality, especially that of drinking water (Armah 2014). They are pollution indicator bacteria associated with disease-causing organisms which are of great concern to public health (Aram et al. 2021). Coliform bacteria are a sign of contamination by human and animal wastes or from improperly treated septic and sewage discharge (Divya and Solomon 2016). Sites within the city center had the highest microbial contamination which is an indication of possible release of untreated residential wastewater into the canal.

Benthic macroinvertebrates and BMWPThai score

The biological indices indicate that there is a significant drop in water quality between sites MK1 (the Mae Sa tributary) and Mae Kha canal proper. This result is consistent with a previous study by Mustow (2002), which found a significant decrease in the diversity of benthic macroinvertebrates from the upstream tributary to the Mae Kha Canal. Evidently, pollution in the urban waterway limits the viable habitat for many species of benthic macroinvertebrate, which will have negative feedback effect on the ecosystem and over all water quality of the canal (Mustow 2002). BMWPThai demonstrated good performance as a tool for indicating water quality in terms of high organic pollution, as reported by Mustow (2002). This study reveals that benthic macroinvertebrates in families such as Heptageniidae, Perlidae, and Lepidostomatidae, which are indicative taxa of good water quality, have BMWPThai scores of 10. This aligns with the observed trend in family richness and the relationship between physical and chemical data, consistent with both BMWPThai scores (Mustow 2002) and the original BMWP score (Hawkes 1998). However, Chironomidae does not appear to be a reliable indicator, contrary to the findings of the previous study by Mustow (2002). Molineri et al. (2020) note that the presence of Chironomidae data at the family level cannot classify data as polluted or non-polluted.

For balanced aquatic life to return to Mae Kha Canal, it is necessary to take steps to rejuvenate the canal and limit pollution. Should more aquatic life return to the canal, macroinvertebrates may fulfill their ecosystem functions and contribute to a positive feedback loop in which physico-chemical parameters of the water become healthier and in turn cleaner.

Physico-chemical analysis consistently revealed low dissolved oxygen, high ammonia, phosphates, and BOD5, indicating severe pollution. Coliform bacteria readings exceeded standards, indicating health risks. Benthic macroinvertebrates indicated a drop in water quality, especially within the canal proper. Based on the outcome of this study, Mae Kha Canal was found to be heavily polluted and facing a severe ecological crisis. The findings of this study underscore the urgent need for remediation and restoration efforts to revive the ecological health of the canal.

Special thanks go to the staff of the Environmental Science Research Center (ESRC) and Freshwater Biomonitor Research Laboratory (FBRL) for their kind support in the field and laboratory. Special thanks also to Korea University, Asian Society for Hydrobiology (ASH) and EAFES 2023 for invitation and warm hospitality in the EAFES 2023 Congress in Jeju, Korea.

BMWP: Biological Monitoring Working Party

ASPT: Average Score Per Taxon

MK: Mae Kha Canal

TCB: Total coliform bacteria

FCB: Fecal coliform bacteria

MCI: Merck’s chemical index

WT: Water temperature

EC: Electrical conductivity

BOD: Biochemical oxygen demand

NH: Ammonium nitrogen

NO: Nitrate nitrogen

DO: Dissolved oxygen

MPN: Most probable number

OM collected samples and analyzed the physicochemical and biological data and drafted the original manuscript. ND assisted in analysis of physicochemical data analysis, collected macroinvertebrate samples in field and sample identification and contributed to manuscript drafting and editing. CT assisted on data analysis and contributed to manuscript drafting, SK and PS assisted on field studies, NS reviewed the manuscript and CP planed and organized the overall project together with reviewed the manuscript. The final manuscript was read and approved by all authors.

This study was partially funded by the Thailand International Cooperation Agency (TICA) under the Thailand International Postgraduate Programme (TIPP) Scholarships and the Environmental Science Research Center, Faculty of Science, Chiang Mai university, Thailand.

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