Influence of water quality on the diversity of macroinvertebrates in the Mandakini River in India

This research work was carried out from July 2018 to June 2019. WQI method was utilized to examine the seasonal changes in water quality that can indicate the potential use of water in the future. Water samples were tested from three locations along the Mandakini River. Fourteen physical and chemical parameters were analyzed. All water quality parameters were inside the admissible furthest reaches of the WHO for drinking water except turbidity, especially in the monsoon season. Twelve taxa of macroinvertebrates (Philopotamus sp., Laptophlebia sp., Isoperla sp., Diploperla sp., Tabanus sp., Hydropsyche sp., Baetis sp., Glossosoma sp., Heptagenia sp., Ephemerella sp., Psephenus sp., and Protandrous sp.) were identified in the Mandakini River. The fundamental goal of this investigation was to evaluate the seasonal effects on benthic macroinvertebrate diversity from the physicochemical variables of the Mandakini River. The study also affirmed that tourist-generated waste disposal and poisonous and dangerous chemicals from farming are the key components liable for the deterioration of water quality during the monsoon season.


INTRODUCTION
The Like-Minded Megadiversity Countries are the richest sources of biodiversity (Kumar & Sharma ). India is one among the 18 megadiversity nations (Behera et al.

).
The Garhwal Himalaya is a store of the rich and extraordinary diversity of aquatic animals (Nautiyal & Thapliyal ). Freshwater biodiversity is an essential feature for the proper functioning of the fluvial system and to ensure its resistance and resilience against natural and anthropogenic stressors (Bellard et al. ). A riverine biological system is a necessary and significant segment of the freshwater environment, wherein the mountain fluvial environment is uncommon just as explicit in all conditions. The density and influence of biological factors in freshwater ecosystems differ significantly from non-biological factors. Every species has its explicit boundaries of physiology, biochemistry, and genetics with the effective divergence of physicochemical attributes of an ecosystem in due course of time (Wetzel & Likens ).
An increase in the human population exerts pressure on the environment and its assets. The growing level of urbanization, industrialization, agribusiness modernization, and expansion in traffic require exact information with respect to the water quality of an aquatic body, as people are generally relying upon waterways for their standard activities.
Expanded contamination level in streams is a central point of contention, as these waterways give water for consumption (Kazi et al. ). The WQI technique has been utilized to assess the wellbeing of a water body for human consumption. Specifically, water quality assessment indicates the degree of consistency with the principles suggested for drinking water by the WHO, BIS, CPCB, and ICMR. The biophysical diversity of an aquatic ecosystem increases with latitudinal and longitudinal gradients in geology and climate. Hence, it is essential to study the aquatic diversity of macroinvertebrates in response to the physicochemical characteristics for ensuring potable water of good quality (Ntislidou et al. ). The CCA strategy has been implemented to compute the effect of physicochemical factors on the seasonal diversity of macroinvertebrates (Kumari & Sharma ; Kumar et al. b). (iii) factors influencing the aquatic diversity.

THE STUDY AREA
The Garhwal Himalayan region of Uttarakhand is situated between the latitudes 29 26 0 N to 30 28 0 N and longitudes 77 49 0 E to 80 06 0 E covering an extent of 30,090 km 2 .
This extent is the unceasing home of ice sheets, high pinnacles, hanging valleys, and steep gullies. Mandakini River is a significant, persevering, snow-fed feeder of Alaknanda River. The altitudinal gradient of the river is quite high.
Inside the stretch of 90 km, the falling surface is from 6,664 m to 675 m above msl. The entire basin of the river reflects an outstanding network of 26 streams and rivulets of different measurements delightfully demonstrating a dendritic drainage pattern. These tributaries are either spring-fed or snow-fed in nature (Table 1). These tributaries bring and dump a large amount of sediments, rocks, and gravel that are responsible for the transparency, turbidity, pH, and various other important physicochemical parameters.
The origin source of these tributaries varies from a height of 4,690 m above msl to 1,240 m above msl. Each and every glacier and valley is the origin source of one basin.
The surface area of the basin including that of Mandakini River itself and its tributaries is spread over 165 km 2 .
Three water sampling locations (S 1 , S 2 , and S 3 ) were selected for the collection and detailed determination of water samples (Figure 1).

Water sampling
Three water testing destinations were perceived and examined along the Mandakini River to assess the physicochemical factors and WQI for the duration of 12 months (July 2018 to June 2019). Aside from these two investigations, the physiography of the study area and benthic macroinvertebrate diversity were also recorded. Site S 1 was identified as Agastyamuni (782 m above msl), which was located at latitude 30 23 0 37″ N and longitude 79 01 0 45″ E; S 2 was recognized as Tilwara (706 m above msl), which was located at latitude 30 20 0 36″ N and longitude 78 58 0 25″ E. However, S 3 was recognized as Rudraprayag (633 m above msl before the confluence with the Alaknanda River), which was located at latitude 30 17 0 18″ N and longitude 78 58 0 46″ E. During the research work, water samples were gathered from all predetermined sites of the waterway from a depth of 10 cm by plunging spotless and contamination-free containers in the morning.
A few of the physicochemical factors (pH, AT, WT, transparency, WV, turbidity, free CO 2 and DO) were investigated at the water testing destinations; later the sterilized sample bottles were filled with water samples and those bottles were placed in a dark, airtight container filled with ice. The container was moved to the examination research center at the Department for additional assessment of leftover parameters within 4-5 hours of sample collection.
All samples of water gathered from the waterway had experienced the research center strategy to assess 16 physicochemical factors by utilizing the system accessible in APHA (). The air and water temperature were recorded by utilizing a precise thermometer. The pH was estimated at the site utilizing the versatile pH meter of Electronics India (model no. 7011). DO was estimated utilizing the modified Winkler's iodometric strategy at the testing site.
Conductivity, TDS, alkalinity, hardness, chlorides, nitrates, sulphates, and phosphates were observed inside the laboratory (APHA ). TDS was likewise estimated by utilizing the multiparameter analyzer. Free CO 2 , absolute alkalinity, absolute hardness, and chlorides were estimated by using the protocols accessible in APHA (). The spectrophotometric strategy (Systronic UV-Vis Spectrophotometer: model no. 117) was utilized to estimate the concentration of nitrates at 410 nm, sulphates at 420 nm, and phosphates at 690 nm of wavelength. The digital turbidity meter of Electronics India (model no. 331) was utilized to measure the concentration of turbidity in the river water.

WQI
WQI is a novel measure made to combine various water quality norms suggested by various health organizations into a specific number by normalizing all the surveyed  Table 2 (1: least important; 4: most important).

Second step
The following formula was applied to evaluate the relative weight (RW): Here, RW ¼ relative weight, AW ¼ assigned weight of each environmental factor, n ¼ complete number of assessed factors. The assessed relative weight (RW) estimations of each environmental factor appear in Table 3.

Third step
The quality rating scale (Q i ) for the surveyed environmental factors barring pH and DO was allotted after dividing the determined amount in water by its tolerable limit endorsed for drinking water by WHO/BIS, and then the resultant was multiplied by 100: However, the following formula was applied to compute the quality rating for pH and DO:  Here, Q i ¼ quality rating, C i ¼ value of a specific environmental factor obtained after investigations at the department, S i ¼ value of the physicochemical factor suggested by the health organizations for drinking water, V i ¼ optimal value (pH: 7.0; DO: 14.6).
Equations (2) and (3) confirm that Q i ¼ 0 when a contaminant is totally inadequate in the water sample and Q i ¼ 100 when the estimation of the physicochemical factor is identical to its recommended value. The Q i value indicates the contamination level (Kumar et al. ).

Fourth step
In conclusion, to compute the WQI value, the sub-indices (SI i ) were at first assessed for each physicochemical factor, and later by implementing the following equations: The estimation of determined WQI for water quality could be classified as <50 ¼ excellent; 50-100 ¼ good;

Analysis of benthic macro-biota (Macroinvertebrates)
The Surber sampler (0.50 mm mesh net) was carefully uti-

Statistical treatment
The software Microsoft Excel 2013 was utilized to ascertain the minimum, maximum, mean, and standard deviation for all sites (Kumar et al. a). The Shannon-Wiener diversity index method was implemented for the recorded data set of benthic macroinvertebrates. The species relative abundance was utilized to calculate the diversity index (H). This method also calculates the species richness and abundance.
However, CCA was also calculated for all the sites by using the statistical software Paleontological Statistics (PAST).
CCA is a multivariate method that has been adopted for graphical representation. It was also applied to elucidate the relationships between biological samples and their environment.

Physicochemical factors
Physicochemical factors of water were evaluated for a period of one year (July 2018 to June 2019) (Tables 4-6).
The variation in mean air temperature was found to be lowest (15.5 C) in winters and highest (29.07 C) in monsoon. The fluctuation in mean water temperature was noticed to be a minimum of 9.33 C in winters and a maxi-        Table 1 are also responsible for the unsuitable water quality, especially during the monsoon season.

Aquatic macroinvertebrates diversity
The numerical counting method was used for quantitative estimation, i.e. individuals per m 2 (ind.m À2 ). A sum of 12 taxa of five major groups were recorded within the duration of research (Tables 7-9; Figure 2). Monthly fluctuations in the macroinvertebrates density showed that at S 1 the highest density (305 ind·m À2 ) was recorded during the winters while the lowest (190 ind·m À2 ) was recorded in the monsoon period. At site S 2 , it was recorded from 148 ind·m À2 to 264 ind·m À2 , whereas at S 3 the highest density (326 ind·m À2 ) was noticed during winters and the lowest (226 ind·m À2 ) during the monsoon.
Plecoptera was characterized by two taxa (Isoperla sp. and Diploperla sp.). were significantly negatively correlated at axis 2. Chloride represented a significant negative correlation at axis 2 and EC showed a significant positive correlation at axis 2 ( Figure 3).

Diversity index
The Shannon-Wiener Index value for aquatic macroinvertebrates was reported to be the maximum (4.179) in July and minimum (0.758) during February at S 1 . It was reported to be the maximum (3.720) in January and minimum (3.165) in July at S 2 . However, it was reported to be the maximum (3.833) in May and minimum (3.350) in June at S 3 (Table 10). This index value signifies the scale of water

FACTORS INFLUENCING THE AQUATIC DIVERSITY
Degradation of the freshwater ecosystem is one of the most pressing issues of environmental concern of the present time.
Freshwater diversity is seriously threatened today. The significant natural factors that are accountable for the reduction of river diversity are flash floods, landslides, and soil erosion.
Construction activities, extraction of substratum, irregular agricultural practices, heavy sedimentation and dumping of sewage waste are the major anthropogenic factors accountable for the loss of river biodiversity (Kumar et al. b).

CONSERVATION AND MANAGEMENT OF AQUATIC DIVERSITY
Rivers are among the most alluring and complicated ecosystems on the planet Earth. Both predictable (annual temperature pattern) and unpredictable (major flood event) variations are important in maintaining a structural and functional river ecosystem. The river biodiversity is

CONCLUSION
The seasonal effect on benthic macroinvertebrates was highest in the monsoon season, which adversely affects the frequency and variety of these organisms. The key factors that disturbed the river water quality were the velocity of the water and the expansion of poisonous and perilous synthetic compounds in the water body from the nearby agricultural fields. The calculated value of WQI ranged from 47.91 to 483.81. A total of 12 taxa of macroinvertebrates from five major groups (Ephemeroptera, Coleoptera, Trichoptera, Diptera, and Plecoptera) were recognized during the study period. It can also be concluded that the river water is polluted and unsafe for human consumption without proper treatment. Components that upset the variety and environment of the lake are credited to natural and anthropogenic factors, for example, soil disintegration, overgrazing, the travel industry burden, and solid waste. A technique for protection and management, for example, off-site and on-site conservation, regular monitoring of water quality and biodiversity, public awareness, waste management, and research programmes, could be helpful.