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Assessment Of Water Quality Index Of An Urban Lake: Implications For Wetland Management In India

Congress: 2015
Author(s): Nitin Bassi, M. Dinesh Kumar
Institute for Resource Analysis and Policy [IRAP]1

Keyword(s): Sub-theme 11: Key vulnerabilities and security risks,
Abstract
Introduction

Worldwide, wetlands are subjected to increasing anthropogenic pressures resulting in loss of their hydrological and ecological benefits. Water in most Asian wetlands is heavily degraded, mainly due to agricultural runoff containing pesticides and fertilizers, and industrial and municipal wastewater discharges. In India, less than 31% of the domestic wastewater from urban centres can be treated with the existing facilities, compared to 80% in the developed world. Actual sewage treatment is further low due to inadequacy of the sewage collection system and non-functional treatment plants. As a result, problem of deteriorating water quality is getting more alarming particularly in the case of urban water bodies such as lakes and ponds.

The foremost requirement for management of urban wetlands is to determine the extent of water quality deterioration. Thereafter, based on wetland water quality parameters, appropriate management decision should be taken for their restoration. Water quality index (WQI) can be an important tool for decision and policy makers to formulate wetland management strategies based on water quality parameters. The major objective of this study is to estimate the WQI for an urban lake and to discuss its utility in strategizing actions which can lead to improvements in environmental conditions of the small wetlands, particularly quality of their water.

Methods

Lake Bhalswa, a natural freshwater oxbow lake, situated in the north-western part of Delhi, India was selected for assessing the WQI. The lake, which used to provide numerous ecosystem benefits and services, has undergone substantial degradation in terms of its water quality and water spread area in the recent past. WQI developed by National Sanitation Foundation (NSF) was used to express the lake water quality based on the data generated by performing various physical, chemical and bacteriological tests on collected water samples from the lake.

NSF WQI is considered to provide the best results for the indexation of the general water quality and consist of nine analytes which include: dissolved oxygen (DO); faecal coliform (FC); pH; biochemical oxygen demand (BOD); temperature change; total phosphate; nitrates; turbidity; and total solids (TS). Spot water samples were collected at a depth of 45 cm from three sites located near to northern end (site 1), middle (site 2) and southern end (site 3) of the lake. From all the sites, samples were collected in three different seasons, i.e. monsoon, winter and summer, to capture the temporal variation in the water quality.

Results and Discussion

For estimating the NSF WQI of the lake, first of all the site wise and season wise Q or Quality value range of the observed analytes were calculated. The Q-values were then multiplied by weighing factor to get the water quality index for a particular analyte. The water quality index for each analyte was then summed up to get the overall water quality index for the lake. Based on the index value, water quality is categorised as: excellent (90-100), good (70-90), medium (50-70), bad (25-50) and very bad (0-25).

As per the results (Table 1), highest WQI value was found to be at site 3 during summer season and lowest for site 2 during winter season. Further, an independent sample t-test results showed that there is a significant difference between WQI in winter and that for the other two seasons. However, WQI across sites does not vary significantly. Nevertheless, in winter, the lake water quality falls in 'bad' category and in summer and monsoon water quality was just above the range from being 'bad'. Overall, water quality of the lake was found to be 'bad' with a mean WQI value of 46.27.

Table 1: Summary of water quality index of the selected lake


As indicated by the WQI assessment of the lake, the water quality has deteriorated to the extent that it is no longer useful for most of the domestic, economic and environmental uses. Main reasons identified for the high degree of pollution in the lake water are discharge of storm-water loaded with sediments during monsoon months and untreated municipal wastewater effluent from the surrounding urban habitations. As a result, the lake water was found to have high BOD, turbidity, TDS, and phosphates concentrations. Other major reason is the lack of government's effort in monitoring lake water quality. Also, no effort has been made to control discharge of untreated agricultural and municipal wastewater directly into the lake. Further, as majority of the water inflow is only during monsoon months, lake capacity to treat pollutants during non-monsoon months has declined significantly (as indicated by the low WQI values during winter and summer).

Conclusion

Increasingly urban water bodies are undergoing large scale deterioration in terms of both water availability and quality. It has been also found that the State has failed in protecting urban water bodies from large scale pollution and regulating land use changes in their catchments. Given the current state of affairs, WQI as estimated for lake Bhalswa can be an important tool for policy makers and natural resource managers and agencies to chalk out plans that reflect the extent of effort required to restore these wetlands located near the urban areas. Presently, such exercises are undertaken randomly and only for a few important rivers. Therefore, most of the wetlands which provide numerous social and environmental benefits remain out of pollution control ambit. It is proposed that a community supported water quality monitoring exercise be taken up for such urban wetlands. As community itself would be a major stakeholder, its involvement would help in achieving greater success in terms of improvement in the physical condition and restoring the wetland. The exercise will also generate a reliable data on the existing condition of wetlands in terms of their water quality and will help in devising and monitoring schemes on water quality improvement.

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