Water quality assessment in two lakes of Panchkula, Haryana, using GIS: case study on seasonal and depth wise variations.

Water is the most important commodity available on earth and exists as both surface and sub-surface sources, but increased water pollution has reduced its potability. In this context, it has become imperative to regularly monitor the water quality. In situ and laboratory experimental procedures involve point wise collection of samples for quality determination which are too elaborative and time consuming. As such, the use of methods like Geographic Information System (GIS) modelling if used in collaboration with the traditional methods can prove to be a great tool as they are less expensive and gives a complete spatial resolution of the study site. Therefore, the present study focuses on the determination of water quality using traditional methods in collaboration with GIS modelling system using the inverse distance weighing (IDW) method for two natural lakes in Haryana. The IDW technique was used to interpolate parameters like temperature, dissolved oxygen (DO), nitrates (NO3) and total phosphorous (TP) as they represent the effects of recent and old pollution in lake waters at different depths. These parameters were interpolated for determining the overall water quality status for the lakes. The collaboration can prove to be of great practical significance in today's time by giving an elaborative view of the present water quality status, easing daily telemetric monitoring of the sites as well as give an opportunity for futuristic modelling. The technique can work for almost all the sites around the globe which have either not been evaluated from quality aspect or are inaccessible for monitoring. Parameters like temperature and DO show significant depth wise and seasonal variations for both the lakes with highest values observed at the surface levels, whereas the NO3 and TP represented effects of point pollution sources to a smaller extent. The maximum value of temperature was determined to be of 30.7 °C and 9 mg/l for DO and was recorded at the surface of lakes 2 and 1, respectively. Further, nitrate and phosphorous concentrations were observed to have maximum values of 0.99 and 0.5 mg/l at the centre of the lake 1 for monsoon season due to influx of pollutants and settlements in the bed. The primary reason for the variation of water quality may be attributed to increased sedimentation at the bottom of lake due to agricultural activities in the vicinity which creates impacts on different hydrodynamic processes leading to increased levels of TP and NO3 concentrations. Further, increased recreational activities lead to induced variations in the water quality as well.

Assessment of spatio-temporal variations in lake water body using indexing method.

The study assesses the characteristics of two lakes located in close vicinity to each other in identifying the status of the lakes based on Designated Best Use (DBU) criteria for optimum utilization and use. Further, the study reports the characteristic assessment of the lakes for two seasons with sampling carried out in August and October months of 2019 and samples collected at different depths and locations to present the comprehensive existing water quality conditions of the lake. The study utilized about twenty parameters evaluated experimentally for determination of Water Quality Indices. In this context, different water quality indices including National Sanitation Foundation Method (NSFWQI) and BIS 10500 (BISWQI) were utilized in determining the indices. The WQI were determined depth wise and a weighted average method was utilized in presenting the overall WQI of the lakes which represents the true water quality based on depth wise evaluation. Hence, the study represents both spatial and temporal variations in the lake water quality. The overall classification of water quality for both the lakes using the NSFWQI methodology was good for both the sampling periods. Similarly, the overall water quality was categorized to be excellent for both the sampling periods using the BISWQI. Further, a new approach in determining water quality indexing is presented through introduction of a Modified Water Quality Index (MWQI) which utilizes the maximum number of parameters and thereby provides a means to reduce ambiguity and eclipsing problems of WQI. Using this newly developed MWQI, the water quality was categorized to be excellent and good for samples collected in August and October respectively for both the lakes. However, conservative estimation considering spillover effects may lead to classification of good category using MWQI. The Heavy Metal Pollution Index (HMI) were classified to be good for both the lakes and sampling periods. Spectral characterization of water samples revealed the presence of oxygen (O), tantalum (Ta), sodium (Na) and Zinc (Zn). However, further monitoring studies are being carried out to cover a period of 1 year to observe if there is a change in water quality due or any seasonal variations.