Research Gaps

Chapter 2 presented extensive bibliographical research on the topics related to water quality, sediment quality and modelling techniques simulating real-life situations attributing to eu- trophication in aquatic ecosystems. The review analyses resulted in qualitative discussions, wherein the current research trends for all the aspects were discussed. The research gaps were identified and discussed in the subsequent sub-sections based on those qualitative dis- cussions.

3.1.1. Research gaps relating to water quality

The current research in water quality indexing suffers from the following limitations:

I. Specific indices

Various water quality indices developed have been based on the problems associated with a regional scale, a highly specific problem, or a definite water body. For instance, Semiromi et al. (2011) proposed an overall water quality index to assess the Karoon River's water quality in Iran. For this purpose, six water quality variables were chosen; Dissolved Oxygen, Total Dissolved Solids, Turbidity, Nitrate, Faecal coliform and pH. Likewise, Gharibi et al. (2012) developed a water quality index for dairy cattle’s drinking water. They considered 20 param- eters, based on the literature, for assessing water quality suitable for drinking purposes of

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dairy cattle, taking into consideration their health impacts. Singh et al. (2012) proposed a wa- ter quality index for India's rural part of the Gajraula region, based on the significant problems associated with that particular region, i.e., industrialization. Lauringson et al. (2012) devel- oped an index primarily for the coastal brackish waters in the N.E. Baltic Sea, correlating the climatic and anthropogenic interferences to the region's biological diversity.

Similarly, many authors have attempted to develop several indices depending on the local problem boundary and for specific water use pertaining to a definite watershed boundary (Wu et al. 2017; de Almeida & de Oliveira 2018; Ng et al. 2018; Abbasnia et al. 2019; Wertz &

Shank 2019; Tian et al. 2020). These specific indices become highly regional, and the re- searchers' methodologies may not be applied globally. Furthermore, the indices developed or proposed to consider those water quality parameters that are problematic in those regions, while those problems may not fit suitable for other water bodies or regions of consideration.

Hence, certain tools or techniques need development that would take care of such limitations, i.e., the indices should not only deem fit for that particular study area or watershed but can be suitably applied globally. Also, each index developed for a specific end-use of water such as drinking, irrigation, industries, heavy metals, etc., which considers specific parameters, needs a comprehensive assessment when choosing the water quality parameters.

II. Human intervention

The primary approach to developing a WQI from the outset has been consulting various ex- perts from different areas of expertise. This approach is carried out through different tools such as preparing author questionnaires, conducting surveys, etc. Teikeu et al. (2016) pre- sents the survey conducted in the Yaoundé area, focused on determining the quality of groundwater resources as an emergency drinking water supply program in the region. A da- taset comprising various groundwater parameters from 42 bore wells were considered in the study. Malamos and Koutsoyiannis (2018) conducted a biannual survey of 104 irrigation wa- ter wells of a Mediterranean island using a multi-parameter probe. Tests were conducted to develop an irrigation-water quality index, and the results were analyzed using various spatial interpolation methods. Mazhar et al. (2019) prepared a questionnaire survey to examine wa- ter-borne diseases in the Gujranwala district of Pakistan. An Averaged Water Quality Index was developed to determine the region's groundwater quality status using ArcGIS model builder. Bhat et al. (2020) surveyed 30 villages of the Kashmir valley, about 59 in number, and recorded their responses. Based on the responses, a WQI was developed for drinking purposes of the 30 freshwater springs. There are also studies conducted based on recorded responses from experts of different fields of expertise which were considered for developing WQIs, the Delphi method being the most effective (Meyer & Booker 1990). Some of the famous

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WQIs involving expert judgements include the National Sanitation Foundation (NSF) Index (Brown et al. 1970), the Scottish Research Development Department (SRDD) index (SRDD 1976), Ross’s Index (Ross 1977), Oregon Index (Dunnette 1979), House’s Index (House 1986;

House & Ellis 1987; House 1989; House 1990), and Almeida’s Index (Almeida et al. 2012). All the tools adopted for conducting surveys or recording responses from people of the regions and, in most cases, from various experts may prove inconsequential to water bodies other than those considered for the study. Additionally, these proposed WQIs may often be mislead- ing, thereby creating ambiguities among other researchers worldwide.

III. Performance assessment

The efficacy assessment of the proposed or developed WQIs is often neglected. Only a few researchers have attempted using specific tools or mathematical models for determining the general applicability of WQIs. These tools majorly include artificial neural networks for pre- dicting the developed WQIs, thereby ascertaining its reliability (Alizadeh & Kavianpour 2015;

Khan & Chai 2017; Gupta et al. 2019). Others primarily employ regression models (Haridas &

Antony 2019) or machine learning approaches (Leong et al. 2019). Hence, there exists a sig- nificant scope in the area of employing various tools, mainly introducing the concept of sen- sitivity analysis to the domain of water quality indexing, which would help in addressing the reliability of the indices.

IV. Emerging techniques

Newly emerging water quality indexing techniques such as multivariate statistics, probability, and the randomness of water quality datasets (information entropy) need further research to develop a new and more comprehensive water quality index. Furthermore, modifications in the existing mathematical approach can also prove vital in improvising the indices. At present, the applicability of mathematical tools in this domain is still in its primitive stage, which can be further enhanced through an integrated approach of adopting multiple techniques in the practice of water quality indexing.

3.1.2. Research gaps relating to sediment quality

The sediment contamination assessment has been relatively new as compared to the water quality assessment. Various aspects of the research have been covered in the past (details are provided in 2.7.7), which suffer from specific gaps, described as follows.

i. The bulk of the studies carried out on sediment contamination assessment are attributed to heavy metals. However, there is limited literature on studying the heavy metal contam- ination in an aquatic ecosystem's sediment column through a large-scale monitoring pro- gram. Additionally, the use of indices and factors for determining the sediment pollution

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load status is still at a dormant stage. This needs proper attention for appropriate use, like the water quality indices.

ii. Studies pertaining to pollution source identification and their apportionment are not avail- able. The site and source characterization studies thus demand immediate attention.

iii. There is also limited evidence of literature on the speciation studies of the sediment col- umn of aquatic ecosystems. Metal speciation analyses provide strong indications of the forms of heavy metals present in the sediment columns, thereby aiding in assessing the heavy metal toxicity levels. Such studies carry immense significance when it comes to de- termining the sediment quality of any water body.

iv. Not much published literature provides information about the health risks associated with heavy metals due to prolonged exposure levels. Contaminated sediments carry huge tox- icity concentrations with them, which carry immense health risks if exposed for a pro- longed period. Therefore, it is essential that the health risks be evaluated.

v. There is no literature available that states the spatial and temporal variability of the ele- mental composition and morphological changes associated with the sediment column.

vi. Finally, since it was observed that most of the studies concentrated on addressing the heavy metal contamination in the sediment column, there exists minimal literature that addresses the nutrient contamination levels. When accumulated in the sediment column, these nutrients leach back into the water column, thereby enhancing the chances for eu- trophication in an aquatic ecosystem. Hence, there is an existential need for studying the nutrient contamination in the sediment column.

3.1.3. Research gaps in the domain of eutrophication-based ecological modelling While much work has been done on ecological modelling, the quest for better ecological mod- els is far from over. Most ecological models have site-specific limitations, and hence a com- pletely robust generalized ecological model is yet to be developed. However, developing such a model will be a herculean task, and until such a model is developed, ecological modellers have to compromise with site-specific models and continue to develop models for different wetlands separately. The need to develop an ecological model becomes far more urgent if it is currently endangered.

From the results of the qualitative analyses presented in 2.8.7, it has been observed that most ecological models developed have revolved around the more developed nations, while the lesser developed or developing nations are still in the dormant stage in this research do- main. This may be attributed to technological advancements in computational facilities that these countries lack. However, the lack of studies does not mean that the problem of eutrophic

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water bodies is of no concern in these countries; instead, there is significant evidence of van- ishing water bodies and ecologies in these countries. Therefore, a collaborative research ap- proach is a way forward to find proper governing measures to conserve the natural systems and restore them to their near-original state.

The models developed by modellers are seldom assessed for their performance and reli- ability. Only a handful of modellers have successfully proposed measures of evaluating the correctness of the model, which will solve real-life problems, for example, the use of artificial neural networks, regression analyses and machine learning approaches. However, the most effective tool that needs attention to all modellers is sensitivity techniques, wherein the sen- sitivity indices of all parameters can be computed. This, in turn, will aid in addressing the reliability and correctness of the models.

Finally, with the advancements in the programming world and the development of so- phisticated languages and software, it becomes highly essential that the modellers adapt to the changes and keep updated. Also, mutual collaboration among scholars worldwide will help initiate novel ideas and scientific techniques based on their individual perceptions, which can be integrated into a single framework.