The 1960s and 1970s saw increasing awareness in the public about worsening environmental conditions; a thriving counterculture in the USA and books such as Silent Spring (1962) served as a medium through which the public could understand the extent of anthropogenic impact on the environment, and voice their questions and concerns [1]. The emergence of environmental issues as a global concern was driven by several important social movements brought about by the public, such as the first official Environmental Justice Movement in North Carolina. Environmentalists who communicated to people the dangers they were in due to environmental degradation received immense public backing and went on to campaign successfully for the introduction of regulatory laws; an example being Claire Patterson and his research on lead in the ocean and atmosphere, which he used to lobby for the Clean Air Act[1].

To this day, people remain integral to the cause of environmental justice and protection. They have the right to be involved in the management and conservation of the world around them, and when aware of environmental issues, they can contribute significantly to sustainability efforts. For example, a study cited in a report [2] by the National Environmental Education and Training Foundation shows that environmentally knowledgeable individuals are:

1. 50% more likely to recycle
2. 50% more likely to avoid using chemicals in yard care
3. 10% more likely to save energy at home
4. 10% more likely to purchase environmentally safe products 

Clearly, some base level of environmental understanding in the public is vital. At this juncture, it is important to define the terms Environmental Education and Environmental Literacy, and further explore the connection between them.

 

Defining Environmental Education and its Importance:

Environmental Education is defined by UNESCO as a learning process that increases people's knowledge and awareness about the environment and associated challenges, develops the necessary skills and expertise to address the challenges, and fosters attitudes, motivations, and commitments to make informed decisions and take responsible action. In short, we may say that the true aim of EE is to inculcate Environmental Literacy in individuals.

Environmental Literacy is a neat term comprising these values as defined by the NAAEE: an awareness of and concern about the environment and its associated problems, as well as the knowledge, skills and motivations to work toward solutions of current problems and the prevention of new ones.

Today, most of us pick up environmental knowledge in bits and pieces from the news, social media, our peers, and perhaps even entertainment media. Rife with bias and misinformation as these sources are, they do not help us gain much meaningful knowledge of our surroundings, ie, environmental literacy cannot be achieved. This is why environmental education is vital- by introducing it at all levels of formal education and elsewhere, awareness and respect of the environment may be developed in individuals from childhood.

Environmental education must provide a scientifically sound knowledge base of various aspects of the natural environment, as well as a systems thinking approach to understanding the various ecological, climatic, political and social contexts that shape this environment, and their relationships with each other. Learners should develop critical thinking skills, (especially in today’s social media landscape of fake news and misinformation), so they can make informed decisions about how they interact with the environment and other structures related to it. Creative problem solving should also be encouraged, so that learners may develop innovative solutions for the issues facing society today [3,9,10,11].

 

Importance of Widespread Environmental Literacy:  

Environmentally literate citizens are vital, as the emergence of environmental science in the US and movements closer to home such as the Chipko movement demonstrate. Public awareness can increase public participation [6], and encourage people to be proactive in environmental protection- through engagement with the making/implementation of government policies,  making environmentally conscious lifestyle changes and championing environmental causes in their communities. By developing environmental literacy and understanding of stewardship in the future generation, we can prepare them to manage resources more responsibly. Conducting training programs may help officials and decision makers to integrate sustainable development principles in their proposals and policies.

 

A Brief History of Environmental Education:

The importance of imparting a working knowledge of the environment to the public started to be recognised in the 1970s, with the first United Nations Conference on Human Environment taking place in Stockholm in 1972, and the first Intergovernmental Conference on Environmental Education being held in Tbilisi, Georgia (then USSR) in 1978. Chapter 36 of Agenda 21, the report of the Earth Summit held in Rio De Janeiro in 1992, encouraged member states to increase awareness and education on the environment and development[3].

Environmental education was seriously considered in India as early as 1964, with the Kothari Commission recommending some form of EE, and the Centre for Environmental Education was formed in 1984. However, it was not till December 2003 that the Supreme Court mandated that NCERT prepare a syllabus (effective from 2004) that included environmental education in the curriculum for all years (1-12), which the states would then implement in all their schools. In an affidavit from 2007, NCERT describes an inclusion based approach, wherein principles of environmental science are included in other core subjects[5].

 

A Brief Review of EE in India and The World Today:

Problems with India’s approach to environmental education persist. The focus in most schools is still direct transmission of theoretical, textbook-centric knowledge, rather than a holistic, locale-specific approach that encourages analysis and critical thinking. Dr. David Orr[10], a stalwart of the field, describes how boxing of knowledge into core subjects (as is done in the inclusion approach recommended by NCERT) creates a divide between students and the environment, by excluding the interconnectedness of these principles[4].

Also concerning is the lack of inclusion of traditional knowledge concerning land stewardship in current EE programs (the Eurocentrism of EE, that ignores perspectives from marginalized people who have experienced ecological poverty[4]), and fewer initiatives that empower communities to maintain their own resources. Community resource management is vital for a number of reasons- people deserve to participate in decisions made about their surroundings, they can hold authorities accountable, improving the quality and procedural legitimacy of decisions taken[8].

Activities such as debate, research projects, and community outreach initiatives, as well as actual interaction with the environment for younger students would be far more effective in helping students connect with their surroundings meaningfully.(see in detail study cited below that demonstrated which kinds of education had the highest positive impact on students)(CEE has initiated some programs with respect to this, such as EOSE[4], but systemic change is required)

Very few honors/bachelors programs specifically for environmental science exist at an undergraduate level, and even if they do they are usually not well developed. School teachers often do not have a background in environmental science; they do not receive adequate training in teaching the subject, and are only briefed on the material. Activities that students are encouraged to do, such as tree planting and community cleanups, are often performative and tokenistic, with no real thought given to underlying issues or proper scientific methodology[7,9]. 

Dr. Orr also describes the aspects of environmental science that require questioning current political or economic structures are left out at higher levels of education, where they are critical. Within the confines of centralized, discipline-centric EE, students are not directed to truly think about their relationship to nature[11], and question the societal power structures that exist in relation to it. Research shows that other non-school avenues hold immense potential- such as community engagement activities and sites, extra curricular workshops and hands-on research and experience, and eco-based tourism[9].

 

Initiatives From the United Nations:

1. Young Champions of The Earth (2020): Seven young people, selected from every global region based on the merit of their ideas for positive environmental change, were provided with seed funding, attendance at high level UN meetings, an introduction to dignitaries, as well as guidance and mentorship to continue working on their ideas.
2. Earth School: A joint project by UNEP and Ted-Ed introduced during the pandemic to help students, parents and educators remain connected to the natural world. With over 30 different lessons on different aspects of the natural world and what it takes to conserve them, the program aimed to develop stewardship and environmental literacy in learners around the globe.
3. Massive Open Online Courses (MOOCs): These are highly accessible courses covering subjects such as Nature-based Solutions for Disaster and Climate Resilience, and Marine Litter.
4. Playing for the Planet Alliance: An initiative to raise awareness among young people through the massive reach of online gaming platforms. Members of this alliance have pledged to reduce their emissions, support the global environmental agenda, and integrate environmental principles and concepts into their gameplays.
5. Publications such as the Little Book of Green Nudges (a guide describing how to reduce a campus’ environmental impact through behavioral changes) and Green Jobs for Youth (a document that raises awareness and provides information on the growth of green jobs, green job pathways, how to incorporate a green aspect in any organization and relevant information on how to provide student with green opportunities, mostly aimed at higher education institutes)[12]

 

Initiatives From the Centre for Environmental Education (India):

CEE has spearheaded several important initiatives over the years, a few of which are listed below.

1. Paryavaran Mitra: National level school network initiative, introduced by CEE and the Ministry of Environment, Forest and Climate Change. This program provides schools with resources that enable them to conduct action projects and engage students in such projects that focus on local environmental issues (the five themes delineated by the program are Water & Sanitation, Biodiversity and Greening, Energy, Waste Management and Culture & Heritage. Other curricular and extracurricular activities are also conducted by CEE.
2. Eco Club Programs: Encouraging the formation of eco clubs in schools across the country in collaboration with NGOs and the Ministry of Environment, Forest and Climate Change. National Green Corps, Clean Ganga Club and Dolphin Club are examples of such initiatives.
3. Sustainable School Campus Programme- Anandshala was developed by CEE in collaboration with UNICEF and the Government of Gujarat, working with schools to increase the quality of education and sustainability of the schools’ infrastructure. This program has also been implemented in Jammu and Kashmir, Rajasthan, Andhra Pradesh and Karnataka.

  

Initiatives From Energy and Wetlands Research Group:

https://wgbis.ces.iisc.ac.in

In light of this review, we describe some of the initiatives conducted by the ENVIS program (https://wgbis.ces.iisc.ac.in/) and the Energy and Wetlands Research Group (https://wgbis.ces.iisc.ac.in/energy/) at IISc. These are community-driven, with strong emphasis on developing deep rooted scientific understanding of immediate surroundings and care and respect for nature, and tackling local environmental challenges as a base for studying more global/national scenarios. The initiatives include but are not limited to symposiums, lectures, full-fledged courses and mentoring programs.

 

1. Biennial Lake Symposium: As part of this international event, students and teachers from schools and colleges around the state are invited to present papers on research/project work they have done in the field of environmental science, and network with peers and experts. EWRG interacts with these students throughout the course of their projects, helping to develop their ideas, concepts and scientific inquiry skills further, and encouraging them to think deeply about issues in their surroundings. Keeping with the themes of Lake 2022, students this year presented projects involving water/soil quality testing in nearby lakes, biodiversity surveys, innovative experiments with the effects of pollutants on plants and vice versa, identification of problems in local waste management and measures to overcome them, as well as awareness campaigns they had conducted in their communities.
   
   200 participating students from over 6 schools gained in-depth, practical environmental knowledge, as well as necessary skills and experience working with the social and political structures which manage the local environment (such as city development boards, panchayats etc) This program encourages critical thinking, creative problem solving and environmental responsibility. By allowing children to think for themselves and innovate, it aims to inculcate the confidence and skills to make significant changes in the next generation. 12 such symposiums have been held till this date, with this being the 13th.
   
   
2. Know your ecosystem: Consisting of workshops held both in city school premises and the lush IISc campus, this program program aims to help kids brought up in Bangalore’s highly urbanized environment reconnect with their surroundings; providing expert insight into local biodiversity and local environmental issues in a scientific, hands-on way for older children, and with fun activities and games for younger children. By inculcating appreciation for the environment and science in these children, this program hopes to foster the desire and skills to actively protect their environments. 412 such events have been held since 1998, with a few examples being: (more details can be found on the EWRG webpage)
   1. World Ozone Day celebration at BGS National Public School
   2. Workshop on Wetlands at Ideal International School
   3. Workshop on Field Ecology at R.K.Mission Auditorium
   4. Village Biodiversity Mapping in Kanakpura Through School Students and Teachers on Science Day
   5. Workshop on Role of Students in Coastal Ecosystem Management - multiple locations
      
      
3. Environmental Management Course: These rigorous, capacity building courses for working professionals from industry, universities and governmental and non governmental organizations help them integrate sustainability principles and environmental concerns into their fields. This year, the course involved four months of teaching, a final project, and expert lectures from stalwarts of the fields of urban planning, resource management, remote sensing and ecology. The diverse backgrounds of the participants allowed them to provide unique insights on the concepts, making it an enriching experience for all. Common workshops are also conducted as part of the course, such as the Workshop on Ecological Sampling Techniques conducted in 2021. 20 such sessions have been held from 2003 to 2022.
   
   
4. Invited talks, keynotes addresses and lectures- 1813 such talks drawing on disciplines from environmental science have been given at various institutions across the country.
   
   
5. Mentorship For Interns: EWRG has hosted 55 postgraduate, graduate, undergraduate and high school students as interns so far. 185 Master’s thesis dissertations from various institutions have been presented through this research group, with 16 in the year 2021-2022. 17 Doctoral theses have also been completed through EWRG, with majority of these students currently serving as faculty in institutions such as IIT, MSRIT, Petroleum Research Institute and Agarkar Research Institute.
   
   
6. Other Initiatives:
   
   1. Water testing labs have been set up at 8 network schools, empowering students with environmental knowledge through monitoring of ecosystems, and hands-on experience with handling scientific equipment.
   2. AICTE-QIP short term courses have been held on topics such as Principles and Applications of GIS and Remote Sensing, Municipal Solid Waste Management, Free and Open Source Geospatial Technologies for Natural Resource Management. 18 such courses have been conducted by EWRG so far.
   3. Green Skill Development Program (GSDP): As part of an initiative by the Ministry of Environment, Forest and Climate Change to develop green skills in workers for a sustainable future, IISc-EWRG provided 3 courses on valuation of ecosystem services and green GDP in the period of 2018-2022.

 

Analysis:

Initiatives by EWRG are unique in that they do not rely on indirect engagement through school teachers and school curriculum structures- which is possible as they are local and don’t need to be coordinated nationwide. Direct engagement of learners and educators with EWRG scientists and researchers with expertise and experience in the field of environmental science was integral to the success of these efforts- as they could provide insight and knowledge that educators without a background in the field might not have. 

With school-level engagement being extracurricular, EWRG programs are not confined to operate within the rigid framework of the school curriculum. Efforts have also been made to make these programs inclusive and accessible to smaller schools for underprivileged children, both through online platforms and through actually visiting these schools present all over the state.

Smaller scale initiatives such as these also have the advantage of being able to take into account local cultures and perspectives to help illustrate concepts, which global programs such as MOOCs might not be able to (for example, language might be a barrier for many students in India, so a more local program is beneficial ) It’s not a matter of one over the other- rather, both programs should exist and be accessible in order to provide holistic environmental education to students.

 

Conclusion: 

Environmental education is a critical component of today’s society, and is essential for responsible citizenship and the prevention of further environmental degradation. It is especially important for countries that are developing as rapidly as India, as much environmental destruction has accompanied this growth, and needs to be stopped. However, EE as a field requires reformation in India- premier educational institutions can help this process along by conducting grassroots-level programs with a sound scientific base for whole communities as well as students.

Abstract

The worth of wetlands is evident from the provision of various ecosystem services, such as provisioning, regulating, and cultural services. The wetlands are important feeding and breeding grounds for ichthyofauna. But the water quality and ichthyofaunal biodiversity of the wetlands are dependent on various abiotic and biotic factors. Water pollution and wetland degradation have been increasing for decades as a result of untreated or partially treated wastewater inflows and solid waste dumping. These pollutants influence the water quality and disturb the life cycles of aquatic organisms. As a result, habitat destruction and a decline in native species of ichthyofauna were recorded. Hence, these wetlands need to be protected from further degradation. With the improvement of the internet, decision support systems (DSS), geographic information systems (GIS), and visualization tools, the development of a web-enabled spatial decision support system (SDSS) for ichthyofauna is necessary for initiating conservation measures. The main objective of this paper is to design and implement the Ichthyofauna spatial decision support system (ISDSS), focusing on ichthyofauna in the lakes of Bangalore. ISDSS has been designed through free and open source software such as Geoserver, PostgreSQL, GeoTools, and Openlayers and spatial information of Open Geospatial Consortium (OGC) standards for multiple criteria analysis. The present study includes 36 lakes in 3 valleys of Bangalore (Koramangala and Challaghatta valley, Vrishabhavathi valley, and Hebbal valley). The ISDSS includes a total of 18 ichthyofauna species belonging to 14 genera, 4 orders, and 7 families. The ISDSS is an interactive, computerized, spatial decision support system with a repository of data pertaining to the quality of ecosystems and ichthyofauna diversity that assists the decision makers in the analysis and visualization of information towards strategic decision-making.

Key words: Spatial decision support system, GIS, Wetlands, Habitat quality, Ichthyofauna

Introduction

Wetlands are vital ecosystems that provide numerous ecosystem services (SEEA, 2021; Ramachandra et al., 2021a), such as provisioning (products obtained from the ecosystem), regulating (benefits obtained through the regulation of various ecosystem processes), and cultural services (nonmaterial benefits obtained through spiritual enrichment, cognitive development, aesthetics, and recreation), as shown in figure 1.

Figure 1: Ecosystem services from wetlands

The Ramsar convention on wetlands, an international treaty for the conservation and sustainable use of wetlands signed in 1971, defined wetlands as "areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish, or salt, including areas of marine water, the depth of which at low tide does not exceed 6 m.’’ Currently, there are about 2,455 Ramsar sites in the world, covering an area of 255,897,678 hectares (https://www.ramsar.org/). In India, 75 wetlands have been identified as Ramsar sites or wetlands of international importance (as of August 2022), with the Sundarbans in Kolkata being the largest and the Renuka wetland in Himachal Pradesh being the smallest Ramsar site in India. Now, Tamil Nadu State has the highest number of Ramsar sites with 14, followed by Uttar Pradesh with 10 Ramsar sites. The Ranganathittu Bird Sanctuary in the Mandya district of Karnataka State has been recently declared as Ramsar site (figure 2).

Figure 2: Ramsar sites in India

Ichthyofauna, or fish, help in nutrient cycling, controlling the growth of aquatic weeds and vegetation, and mosquito control, apart from providing both recreational and cultural values. Fish is highly nutritious, low in fat, high in protein content, and an excellent source of Omega-3 fatty acids. Fish act as a valuable bioindicator for evaluating environmental contamination as well as trace element pollution (Sincy et al., 2022; Plessl et al., 2017). Fish mortalities in lakes are triggered by both abiotic and biotic factors like variations in weather patterns, water temperature, dissolved oxygen, pH, turbidity, salinity, ammonia, carbon dioxide, pesticides, toxic algae, thermal shock, organic pollutants, and the overgrowth of microalgae and macrophytes in lakes (Ramachandra et al., 2016). Threats to fishdiversity include alteration of habitat, reduction of habitat area, overfishing, construction of dams, drought, loss of interconnectivity among water bodies, siltation, pollution of water bodies, introduction of non-native (exotic) species, etc. (Gupta et al., 2015).

Even though wetlands provide numerous ecosystem services, they are very fragile and threatened ecosystems due to anthropogenic stress. The effluents emanating from industries, the extensive use of fertilizers, pesticides, and insecticides in agricultural fields, and the discharge of domestic waste and sewerage from urban areas contribute to the deterioration of the water quality in wetlands, resulting in the loss of aquatic biodiversity. Polluted waters are enriched with nutrients, ions, and organic matter (Ramachandra et al., 2020a; Ramachandra et al., 2021b). Heavy metals such as zinc, copper, nickel, mercury, cadmium, lead, and chromium discharged from wastewater into the environment at higher concentrations are toxic or carcinogenic and persist for longer periods in the environment (Fu and Wang, 2011). Heavy metal pollution of aquatic ecosystems results in bioaccumulation and biomagnification in biota at different trophic levels (Ramachandra et al., 2020b; Adhikari et al., 2009). An increase in heavy metal concentrations in fish and water may induce mutagenic and genotoxic effects in aquatic organisms as well as cause deleterious effects on human health upon consumption (Ali et al., 2020). Thus, it is important to conserve wetlands and their ichthyofauna. 

An interactive computer-based decision support system (DSS) helps to compile, analyze, and present the data for decision-making. For example, DSS has been developed for regional energy planning (Ramachandra et al., 2006); for assessing regional biomass energy potential (Ramachandra et al., 2005); and for assessing micro, mini, and small hydel potential (Ramachandra et al., 2004). Geographic information system (GIS) use maps to help people view, interpret, and visualize data and reveal trends. Thus, it is a promising tool that helps in depicting the spatio-temporal dynamics of environmental factors and the distribution of biodiversity in lakes. Spatial decision support system (SDSS) that integrates both geographic information systems (GIS) and decision support systems (DSS) makes use of geographic or spatial data for effective decision-making (Ramachandra et al., 2017; Keenan, 2006; Jarupathirun, 2007). The characteristics of SDSS are shown in figure 3.

Figure 3: Characteristics of SDSS

Several web-based spatial decision support systems have been developed, such as WebWMPI for watershed management (Zhang et al., 2011); DSS-WMRJ for watershed management (Zhang et al., 2015); SDSS for watershed management (Choi et al., 2005); for land management and soil conservation (Terribile et al., 2015); and interactive well water risk estimation (iWWRE) to monitor water contamination in private wells in North Carolina (Lan et al., 2020). Databases that provide information on fish include FishBase (a global biodiversity information system on finfishes); Ffish.asia (freshwater fish biodiversity of Southeast and East Asia); Ichthyology Collection Database (freshwater fish biodiversity); Fish Pathogens Database (information on isolates of fish pathogens); etc. These databases record only the biodiversity information and distribution patterns of fish species but do not provide habitat quality data. There are only a few studies in Bangalore on ichthyofauna diversity and its habitat conditions. But a database on ichthyofauna and its habitat (wetlands) has not yet been developed. The main objective of this paper is to design the Ichthyofauna Spatial Decision Support System (ISDSS), focusing on ichthyofauna in freshwater ecosystems in Greater Bangalore.

Materials and Methods

Study area

Greater Bangalore (12°49’5’’N to 13°08’32”N latitude and 77°27’29”E to 77°47’2”E longitude), covers an area of 741 square kilometers. The district is located at an altitude of 920 m above mean sea level, and is divided into three watersheds: Hebbal, Koramangala-Challaghatta, and Vrishabhavathi (figure 4). The undulating terrain in the region has facilitated the creation of a large number of tanks providing water for irrigation, drinking, fishing, and washing purposes (Ramachandra and Kumar, 2008).

Figure 4: Lakes of Greater Bangalore

Water sampling and physicochemical analysis

The water samples from 36 lakes in Bangalore (figure 4) were collected in clean and sterile polypropylene bottles and carried to the laboratory for physicochemical analysis. Some physicochemical parameters are measured on site, such as water temperature (WT), electrical conductivity (EC), total dissolved solids (TDS), pH, and dissolved oxygen (DO). The parameters, such as total alkalinity (TA), chlorides (Cl), nitrate (N), orthophosphate (OP), total hardness (TH), calcium (Ca), magnesium (Mg), chemical oxygen demand (COD), and biochemical oxygen demand (BOD), were analyzed in the laboratory using standard methods (APHA, 2005). 

Ichthyofauna sampling and identification

Ichthyofauna (fish) specimens were collected from the monitored lakes of Bangalore with the help of a gill net or cast net by local fishermen. The geographical coordinates of sampled sites were measured with the help of Garmin GPS (Garmin GPSMAP 64S, USA). Photographs of fresh specimens were taken with the help of a digital camera. Then the specimens were preserved in a 10% formaldehyde solution. The specimens were identified up to the species level through standard taxonomic keys, reference books (Jayaram, 1999; Talwar and Jhingran, 1991), and a virtual database - Fish Base (http://fishbase.org). The conservation status of fish was recorded (IUCN Red List of Threatened Species).

Development of Spatial DSS on fish data

Ichthyofauna spatial decision support system (ISDSS) has been designed through free and open source software such as Geoserver, PostgreSQL, GeoTools, and Openlayers and spatial information of Open Geospatial Consortium (OGC) standards for multiple criteria analysis.

Results and Discussion

Spatial DSS for managing fish resources

The current study involved the design of the Ichthyofauna Spatial Decision Support System (ISDSS). The ISDSS gives details like lake name, village name, latitude, longitude, water quality, and fish species found in the lakes of Bangalore, Karnataka, India. Since water quality parameters such as temperature, pH, carbon dioxide, DO, ammonia, nitrite, suspended solids, and alkalinity influence the growth, reproduction, and survival of ichthyofauna (Okoliegbe et al., 2020), it is necessary to include habitat quality in the ISDSS. The present study covers 36 lakes in 3 valleys of Bangalore and recorded a total of 18 ichthyofauna species belonging to 14 genera, 4 orders, and 7 families.

The Home page contains sections like Lakes, Ichthyofauna, Literature, Fish Database, and Contact (figure 5).

Figure 5: ISDSS

Figure 6: Lakes section in ISDSS

Lakes include information on lakes lying under Koramangala and Challaghatta valley, Hebbal - Nagavara valley, and Vrishabhavati valley in Bangalore, Karnataka, India. The attributes include: the geographical location and description of the lakes; water quality parameters; and ichthyofauna species in the lake.

Ichthyofauna includes attributes such as: Kingdom; Phylum; Class; Order; Family; Common name; Synonym; Kannada name; Feeding habit; Fish diet; IUCN status; Moisture, Protein; Fat; and Ash content of each species; description of the ichthyofauna species; their ecological and economic importance; as well as habitat condition (figure 7). The economic importance of fish is included in the ISDSS as they constitute a valuable source of protein, vitamins, and minerals along with polyunsaturated fatty acids (PUFA) that are essential for human health (Barik, 2017).

Figure 7: Ichthyofauna section in ISDSS

Literature contains published articles, reports, and useful links pertaining to ichthyofauna species and habitat quality.

Fish Database provides links to other databases on ichthyofauna (fish) in the world. 

Contact contains address and contact number of Environmental Information System (ENVIS), Centre for Ecological Sciences (CES), Indian Institute of Science, Bangalore.

ISDSS is a user-friendly, computerized, spatial decision support system that helps decision makers improve water quality and protect aquatic diversity in urban wetlands.

Conclusion

The present study focused on the design and implementation of the Ichthyofauna Spatial Decision Support System (ISDSS). ISDSS will improve knowledge of urban wetlands and ichthyofauna diversity for wise use of wetlands. It covers 36 lakes in 3 valleys of Bangalore, which recorded 18 ichthyofauna species belonging to 14 genera, 4 orders, and 7 families. A web-based Ichthyofauna spatial decision support system handles, displays, analyses data to allow effective visualization and querying that satisfy the end users. ISDSS will help the public and policymakers easily understand the ecosystem dynamics and biodiversity so that appropriate conservation measures can be taken.

Recommendations

Fish growth and development are influenced by both abiotic and biotic factors. A change in the water quality parameters may affect the growth and survival of fish. Conservation measures to maintain fish biodiversity include: (a) avoiding pollution due to untreated sewage, industrial effluents, fertilizers, pesticides, and other anthropogenic activities; (b) avoiding harvesting fish during the spawning period; (c) avoiding harvesting juveniles; (d) banning the introduction of exotic species into lakes; and (e) educating locals about the importance of lakes and ecology of freshwater fishes.

Acknowledgments

We are grateful to the EIACP (ENVIS) Division, The Ministry of Environment, Forests and Climate Change, the Government of India and the Indian Institute of Science for the sustained support for ecological research.

Abstract

Microalgae are the primary producers and represent flora diversity in wetlands. The composition of algae depends on the environmental conditions of its habitat, based on the water quality parameters including physical, chemical, and biological parameters. Microalgae as bioindicators, aid in the biomonitoring of wetland ecosystems, due to their nutrient requirements, rapid reproduction rate, and very short life cycle. Decision support system based on microalgae helps in monitoring fragile wetlands. An interactive computer-based Decision Support Systems (DSS) helps to compile, analyse and present the data for wetland management. Spatial Decision Support System (SDSS) combines the technologies of Geographic Information Systems (GIS) and DSS to aid decision-makers with problems that have spatial dimensions. The current study presents a Microalgae Spatial Decision Support System (MSDSS) designed for assessing the status of wetlands, based on microalgal data. The SDSS is developed with the integration of spatial data through free and open source software such as Geoserver, PostgreSQL, GeoTools, and Openlayers, which aids in data analyses for assessing the quality of wetland ecosystems and microalgal biodiversity. A total of 101 genera of phytoplankton belonging to 5 phyla, 9 classes, 24 orders, and 41 families were recorded through monitoring of 115 lakes in Bangalore. The microalgae in Bangalore lakes belonged to Chlorophyta, Bacillariophyta, Cyanobacteria, Charophyta, and Euglenozoa.The MSDSS, with the location-specific information of wetlands, aids in decision-making through data interpretation and visualization. MSDSS will help with wetland protection, management, and conservation in Bangalore, Karnataka, India.

Key words: Wetlands, Microalgae, Spatial decision support system, Water quality, GIS

 

Introduction

Wetlands are ecotones (transition zones) between terrestrial and aquatic environments that provide abundant beneficial services. Wetlands provide crucial ecosystem services such as provision of fish, fodder, fuelwood, water supply, water purification, groundwater recharge, nutrient cycling, erosion control, flood control, carbon sequestration, and providing habitats for aquatic flora and fauna, as well as providing opportunities for education, aesthetics, and recreation (Ramachandra et al., 2016). The provisioning service, regulating service, and cultural service provided by Karnataka wetlands were 1.8 lakh Rs/ha/year, 7 lakh Rs/ha/year, and 1.3 lakh Rs/ha/year, respectively. The TESV and NPV of Karnataka wetlands were 285 billion rupees/year and 7321 billion rupees, respectively (Ramachandra et al., 2021). Wetlands in Bangalore are polluted and more degraded due to pollutants from untreated sewage or wastewater released from industrial, commercial, and residential areas as well as agricultural runoff (Ramachandra et al., 2020a). The inflow of untreated domestic sewage into lakes results in water quality deterioration, alteration of the physicochemical characteristics of water, nutrient (nitrogen and phosphate) accumulation in lakes, groundwater contamination, eutrophication, excessive growth of microalgae and aquatic macrophyte, silt and organic matter accumulation, and the occurrence of blue-green algal blooms, which cause taste and odour problems. This in turn decreases dissolved oxygen levels in lakes, affecting aquatic biota and ultimately hampering ecosystem functioning (Hilton et al., 2006). Analyses of urban dynamics in Greater Bangalore using temporal remote sensing data revealed an increase in urban area (1028%) with decreases in vegetation (88%) and water bodies (79%) during 1973–2017 (Ramachandra and Bharath, 2016).

Microalgae play a pivotal role in the food web, as they are the primary producers and provide food for consumers like zooplankton and fish. Microalgae are chlorophyll-bearing, photosynthetic organisms that have the ability to convert sunlight into food and energy and release oxygen as a by-product of photosynthesis (Asulabha et al., 2022). Microalgae aid in wastewater treatment (phycoremediation), due to their ability to use inorganic nitrogen and phosphorus for their growth and reproduction. They are capable of removing heavy metals, pesticides, and hydrocarbons from water (Kaloudas et al., 2021). Microalgae are a significant component of biological monitoring programmes for assessing water quality. They aid in the cost effective assessment of water quality because of their ability to uptake nutrients, rapid reproduction rate, and very short life cycle. Microalgae act as bioindicators, which provide information on ecosystem status and trends, thus, serving as a cost-effective biomonitoring tool.

A decision support system (DSS) is an interactive computer-based system that helps decision makers utilize data and models to solve unstructured problems (Ramachandra et al., 2005). For example, decision support systems have been developed for wetland management (Janssen et al., 2005); biodiversity conservation (Guillet et al., 2012); and forest management (Blondeel et al., 2021). Spatial decision support systems (SDSS) are an extension of the decision support system (DSS) concept, with spatial data used for the analysis of decisions (Ramachandra et al., 2004; Keenan, 2006; Jarupathirun, 2007). Thus, SDSS, which integrates technologies from both GIS (geographic information system) and DSS, helps in decision-making. Recent advancements in DSS, remote sensing, and GIS technologies have found increased applications in ecosystem management and nature conservation (Jafary et al., 2018; Greco et al., 2017; Geneletti, 2004; Vacik and Lexer, 2001). A web-based spatial decision support system (WSDSS) with multiple criteria decision analysis (MCDA) helped to prioritize ecologically sensitive regions in the Uttara Kannada district of Karnataka based on ecological, biological, geo-climatic, renewable energy, and social variables (Ramachandra et al., 2017). Web mapping application (WMA) is developed for for wetland management (SDSS) . An open-source GIS software and JavaScript library plugins, including a PostGIS database, GeoServer, and Leaflet library, were used for WMA for the Kolleru Lake aquaculture system (Kolli et al., 2022). A web-based SDSS, namely, web-based participatory urban planning (WPUP), was developed to enhance public participation in urban planning processes (Mansourian et al., 2011). Numerous databases on algae have been developed worldwide, for example, AlgaeBase (a global algal database); Australian Fresh Water Algal Name Index (records freshwater algae); Algae of India (records algae diversity); Algal Bloom Information Service (for bloom monitoring in the Indian Ocean); Diatoms of North America (diatom diversity); etc. One of the drawbacks of these databases is that they do not provide habitat quality. Thus, a database needs to be designed that provides information of both the freshwater algae diversity and the water quality. The main objective of the current study is to design a Microalgae Spatial Decision Support System (MSDSS) for assessing the status of wetlands, focusing on microalgae data of lakes in Bangalore, Karnataka State, India.

 

Materials and Methods

Study Area

Greater Bangalore (12°49’5’’ N to 13°08’32” N latitude and 77°27’29” E to 77°47’2” E longitude) in Karnataka State covers an area of 741 square kilometers. The district is located at an altitude of 920 m above mean sea level, delineating three watersheds, namely Koramangala and Challaghatta valley, Vrishabhavathi valley, and Hebbal valley. The mean annual rainfall in Bangalore is 880 mm, with 60 rainy days a year over a decade. The summer temperature ranges from 18°C - 38°C, while the winter temperature ranges from 12°C - 25°C. The present study surveyed 115 lakes in Bangalore, Karnataka State, India. Water quality monitoring and recording of microalgal diversity in 96 lakes in Bangalore were performed as part of a biomonitoring exercise and the creation of a database (figure 1).

Figure 1: Lakes of Bengaluru, Karnataka State, India.

Water quality analysis and Microalgal diversity

Water samples were collected in clean and sterile polypropylene bottles and transported to the aquatic ecology laboratory (at Indian Institute of Science) for water quality analysis. Physicochemical parameters like water temperature (WT), pH, electrical conductivity (EC), total dissolved solids (TDS), and dissolved oxygen (DO) were measured at site. Other chemical parameters were estimated in the laboratory, such as total hardness (TH), calcium (Ca), magnesium (Mg), chlorides (Cl), total alkalinity (TA), nitrate (N), orthophosphate (OP), chemical oxygen demand (COD), and biochemical oxygen demand (BOD), using standard methods (APHA, 2005). Microalgae were collected from the lakes of Bangalore using a plankton net and then fixed with 4% Lugol’s iodine solution. Microalgae taxa were identified to the taxonomic level, according to the standard keys (Desikachary, 1959; Prescott, 1970; AlgaeBase, 2021), and enumerated with an optical microscope at 10 X, 40 X, and 100 X magnifications.

Creation of Microalgal SDSS

Microalgae Spatial Decision Support System (MSDSS) designed to visualize the status of wetlands in Bangalore, focusing on microalgae diversity data. The SDSS has been designed through the integration of spatial data using free and open source software such as Geoserver, PostgreSQL, GeoTools, and Openlayers. MSDSS aids in visualizing lake wise water quality and microalgal biodiversity.

Results and Discussion

Microalgae SDSS

The water quality parameters play a decisive role in the structure and composition of microalgae (phytoplankton) in aquatic ecosystems. The deterioration of the wetland environment or variations in the physicochemical characteristics of water affect the community structure and biodiversity of aquatic organisms (Kock et al., 2019; Wang et al., 2019). The increasing water pollution and harmful cyanobacterial algal blooms due to nutrient enrichment in lakes pose a serious threat to freshwater resources and biodiversity. MSDSS provides a framework for integrating database management systems, with WMS (Web map service) and WFS (web feature service) to viusalise water quality and microalgal diversity , which provides insights for prudent management by decision-makers.

The Microalgae Spatial Decision Support System (MSDSS) provides information on the microalgae diversity of lakes in Bangalore with water quality for monitored 96  lakes in Bangalore (figure 2). 

Figure 2: Data input to MSDSS

Figure 3: Microalgae Spatial Decision Support System (MSDSS)

 

Figure 3 illustrates MSDSS GUI (graphic user interface) of MSDSS with options to visualize lake-wise water quality, microalgae diversity, and associated details such as Literature, Algae Database, and Contact (figure 3).

Lakes section provides information regarding the monitored lakes valley-wise (Koramangala and Challaghatta valley, Hebbal - Nagavara valley, and Vrishabhavati valley) in Bangalore. The attributes for each lake include the geographical location, details ; water quality parameters; and microalgae in the lakes (figure 4).

Figure 4: Lake section (MSDSS)

Microalgae data include attributes such as Kingdom; Phylum; Class; Order; Family; bio-chemical composition (Protein; Carbohydrate, and Lipid content) of each microalgae genus; description of the microalgae and their ecological and economic importance; as well as habitat condition (figure 5). The present study records a total of 101 genera of phytoplankton belonging to 5 phyla, 9 classes, 24 orders, and 41 families. The microalgae recorded in 96 lakes of Bangalore belonged to 5 major groups, such as Chlorophyta, Bacillariophyta, Cyanobacteria, Charophyta, and Euglenozoa. Microalgal biomass has valuable components like carbohydrates, long-chain fatty acids, pigments, and proteins. Lipid in microalgae is used for biodiesel production . Thus, microalgae have widerange applications including the pharmaceutical and nutraceutical industries. They also serve as bioindicators and help in CO2 mitigation (Yen et al., 2013).

Figure 5: Microalgae section (MSDSS)

Literature section in MSDSS contains published articles, reports, and useful links pertaining to microalgae and water quality of lakes.

Algae Database provides links to other databases on microalgae around the world. 

Contact provides address of Environmental Information System (ENVIS), Centre for Ecological Sciences (CES).

Thus, the Microalgae Spatial Decision Support System (MSDSS) with the location-specific information of wetlands aids in decision-making through data interpretation and visualization.

Conclusion

Microalgal biomass has emerged as a sustainable source of lipids and proteins, with numerous applications in the pharmaceutical and nutraceutical industries. Thus, documentation of microalgal diversity is important. The Microalgae Spatial Decision Support System (MSDSS) is an interactive, computer-based system that integrates both DSS and GIS technologies, designed to support in the efficient decision-making. A total of 101 genera of phytoplankton belonging to 5 phyla, 9 classes, 24 orders, and 41 families were identified in 96 lakes in Bangalore. The microalgae belonged to Chlorophyta, Bacillariophyta, Cyanobacteria, Charophyta, and Euglenozoa. The data gathered from MSDSS will help in the biomonitoring of lakes. Thus, MSDSS would aid in the wetland protection, management, and conservation in Bangalore, Karnataka, India.

Recommendations

Wetlands are highly productive ecosystems, supporting wide array of biological diversity by providing habitat for a huge number of life forms such as bacteria, phytoplankton, zooplankton, fungi, insects, snails, grasses, weeds, macrophytes, fish, birds, etc. Water quality monitoring and management of lakes at regular intervals would help in mitigating water pollution, the deterioration of freshwater ecosystems, and the decline in biodiversity. Integration of wastewater treatment plants with constructed wetlands and algal ponds helps in efficient nutrient removal from urban lakes. The management of microalgal blooms is possible only if measures are taken to control the levels of nutrients (N and P) and organic matter and promote the aeration of water bodies (to increase the dissolved oxygen levels).

Acknowledgements

We are grateful to the EIACP (ENVIS) Division, The Ministry of Environment, Forests and Climate Change, the Government of India and the Indian Institute of Science for the sustained support for ecological research.

ABSTRACT 

Sambhar Lake is a Ramsar site located in Rajasthan, and is home to rich diversity including numerous migratory birds The current study focusses on the assessment of the existing conditions of the lake and its catchment in the context of natural resources and richness of biodiversity based on field investigations, and literature reviews, pertaining to documentation of geographic and biological characteristics of the wetland, spatial characterisation of the lake and catchment,  spatio-temporal analysis of water spread and documentation of biodiversity, including total bird species, IUCN status of visiting birds, historic population patterns, migratory paths, factors affecting bird populations have also been analysed. Further, the study proposes recommendations and suggestions to maintain and improve the ecological health of the wetland and mitigate the potential contemporary as well as future anthropogenic damages. 

 

1.0 INTRODUCTION

Sambhar wetland is located at latitude 26° 58'- 27° 2' N and longitude 74° 54' - 75° 15' E on the east of the Aravalli hills (the Sambhar-Sirohi ranges) in the state of Rajasthan. It is one of the popular Ramsar sites of India, with an area of 23000 ha (230 km2). The lake has a historical and cultural significance, attracting thousands of flamingos, pelicans, and other migratory birds. This ecosystem is an integral flamingo habitat with the greatest number of sightings second only to the Rann of Kutch (Kulshreshtha et al. 2011). As it is the Second most frequented wetland by thousands of migratory birds, especially Lesser and Greater Flamingos, a comprehensive environmental assessment, conservation and management plan is required to take the right steps before implementation of such a large-scale project so that there is zero or minimal environmental harm and degradation.

 

2.0 STUDY AREA

Sambhar Lake is surrounded by majorly Nagaur, Jaipur districts and borders the Ajmer district. The lake is India's largest inland saline water body (Bohra, 2020) with a catchment area of 4,888 km2 comprising of dry deciduous forests with sparse thorny scrubs typical of arid and semi-arid zones (Kulshreshtha et al. 2011). Commercial activities carried out in the region mainly consist of tourism, salt production and livestock grazing. The lake is a lifeline for the people of Rajasthan and is responsible for 3% of India's salt production (Bhat et. al 2015). The Sambhar Salt Lake became a designated Ramsar Site of international ecological importance on the 23rd of March 1990 (Ref. No. 464 at rsis.ramsar.org). Sambhar region is also internationally identified as an Important Bird Area (IBA) and a Key Biodiversity Area (KBA) (wiienvis.nic.in).

 

Figure 2.1: Study Area and Figure 2.2: Conceptual representation of bird diversity

The lake basin is divided by a 5.16 km long dam made of sandstone. To the east of the dam are salt evaporation ponds of about 80 square km comprising of salt reservoirs, canals and salt pans separated by narrow ridges. Also on the east side, is an 1876 railroad by the British before independence to provide connectivity from Sambhar city to the salt works (Aggarwal, 1951). Based on the season and quantity of water present, the lake occupies an area of 190 - 250 km2. The lake is dynamic, with water depth fluctuating from as few as 60 centimetres (24 in) during the dry season to about 3 meters (10 ft) at the end of the monsoon season. The depth of the lake varies from west to east significantly, and its elevation varies from 359.96 to 364.77 m (1181 to 1196.76 ft) above the mean sea level (MSL). Except for the reservoir and salt pans, the whole lake dries up, exposing salt flakes during summer. The region has 260-300 sunny days. In figure 2.3 given below, blue line denotes the lake boundary, red line marks maximum water spread area, dark blue line marks the dam that segments the lake from kyars and the yellow line marks the road connecting villages Nawa and Khakardi. Most water is collected by Sambhar Lake due to depression in elevation. Total catchment area is 4,888 km2 comprising of dry deciduous forests with sparse thorny scrubs typical of arid and semi-arid zones.

Figure 2.3: Digitized Boundary of Sambhar Lake using Google Earth and QGIS

Figure 2.4: Catchment of Sambhar Lake with buffer zone
 

3.0 RESULTS

3.1 Water Spread Area

For determination of ecologically sensitive regions, maximum water spread area was determined. This was done by spatiotemporal analysis from the year 1984 till 2020. The result shows that maximum water extent observed was 156.77 km2  in the year 1996. It is evident how water level keeps fluctuating as per climatic conditions, especially because Rajasthan is a desert state.

(i) 1984	(ii) 1989
(iii) 1990	(iv) 1991
(v) 1992	(vi) 1993
(vii) 1994	(viii) 1995
(ix) 1996	(x) 1997
(xi) 1998	(xii) 1999
(xiii) 2000	(xiv) 2001
(xv) 2002	(xvi) 2003
(xvii) 2004	(xviii) 2005
(ixx) 2006	(xx) 2007
(xxi) 2008	(xxii) 2009
(xxiii) 2010	(xxiv) 2011
(xxv) 2012	(xxvi) 2013
(xxvii) 2014	(xxviii) 2015
(xxix) 2016	(xxx) 2017
(xxxi) 2018	(xxxii) 2019
(xxxiii) 2020

Figure 3.1: Spatiotemporal Analysis 1984 - 2020

 

3.2 Avifaunal Biodiversity 

Sambhar habitat actively supports a total of 137 bird species. Out of which 2 are endangered (EN), 3 vulnerable species (VU), 13 near threatened (NT) and 119 least concern (LC) species according to the IUCN red list. The populations are in the tens of thousands, certainly implying multiple beneficial factors of the Sambhar ecosystem such as (Kulshreshtha 2011): 

• Highly saline water with unique microbial diversity
• Vast expanse and secure environment
• Availability of abundant food stock
• Opportunity for breeding and wintering
• Rest stop before migration to other parts of India

Table 3.2 containing list of all avian fauna that has been recorded in the Sambhar Wetland with scientific name, common name, habitat, rarity, resident/migrant and IUCN status has been attached in the annexure. 

Figure 3.2.1: Avian migratory path - International

Sambhar supports a large number of migratory avifauna. Migratory birds usually migrate from Central Asia, Africa, Siberia, parts of Russia, Iran and parts of Europe as well as per some of the banding studies.

Figure 3.2.2: Avian migratory path - National

After wintering at Sambhar, they then disperse across the country, especially towards southern region. Some wetlands that attract these birds, especially flamingos include Rann of Kutch, Keoladeo National Park, Mumbai, Chillika Lake, Thrissur and Pulicat Lake.

 

Figure 3.2.3: District wise terrain patterns of lesser and greater flamingos

 

Figure 3.2.4: Avian migratory path – Intrastate

Based on some records available, the Greater Flamingos arrive at Sambhar first. Then move to various locations like Anasagar lake, Jawai dam, Alaniya Dam, Chandlai Lake, Chambal region and Keoladeo National Park. The Lesser Flamingo on the other hand do not move much within Rajasthan. They have only been spotted in Chambal region other than Sambhar Lake. Flamingo populations keep fluctuating every year. Generally, because of rainfall patterns, water and food availability, water conditions etc.

Occurrence of 244 species of orders Raptores, Incessores, Gemitores, Rasores, Grallatores, Natatores. Sides of open wells are densely clothed with a species of willow, tiger and sarpat grass and are the favourite haunts of numerous birds. Dense masses of flamingos are to be seen everywhere swimming or wading in the lake-bed, flying overhead, bearing "The rich hues of all glorious things." or stalking sedately along the edge in search of food. Long lines of big and little birds, of all shades of plumage, from the gorgeous rose-coloured adult to the dingy brown-and-white young, march along, and invariably here from west to east, all wagging their down-bent heads in search of the animalcules with which the brackish water abounds. Records of poaching of avian species. When animalcules disappear, many of the swimmers and waders go off or frequent. (Adam 1873).

Number of species observed amount to 252. (Ten additions). Large flocks reached from a westerly direction during the month of September. Prefer working for food along the exposed portions of the low mud walls which separate the salt pans from lake water. Flocks congregate in places covered with a slushy slime-like soil which is very difficult to walk in - on the surface of which existed a quantity of dark greenish microscopic vegetable matter. On which the birds seemed to feed eagerly. Flocks of over five hundred birds closely packed together were spotted. (Adam 1874). About the region in general, if there ever was an unpromising field for an ornithologist it was here; and yet only were a good many species to be found, but two or three of these, species of some interest. (Hume 1878). Opening of sluice gates to drain the water to salt pans has dried up the lake suddenly on many occasions. Such situations like the drying up of majority of the lake bed have forced the birds to abandon the lake in mass. More than 20,000 birds were present in September 2001 however after the release of water by Sambhar Salts, author found only 200 Greater Flamingos left. The chemistry of the lake and its variations need to be studies. On 4th December 1994, 8,500 Lesser Flamingos were seen on the lake, but no Greater Flamingos. Similarly, on 31st January 1995 there were 5,000 Lesser Flamingos but Greater Flamingos and other species were missing, probably due to high level of salinity.

Table 3.2.2: Historical review of avian populations at Sambhar

Year	Number of avifauna reported	Reference
1873	244 species	Adam 1873
1874	252 species	Adam 1874
1878	25,000 flamingos	Hume 1878
1939	Arrival of flamingos	MacCann 1939
1951	5000-8000 flamingos	Agrawal 1951
1968	Arrival of flamingos	Mukherjee 1968
1969	Arrival of flamingos	Roonwal 1969
1981	5000 flamingos	Alam 1981
1984	6000-8000 flamingos	Gole 1984
1988	No arrival of flamingos (Drought year with severe water scarcity)	Kulshreshtha 2011
1994	5000-8500 flamingos; 8500 flamingos	Gopal & Sharma 1994, Sangha 2009
1995	5000 flamingos, no other species	Sangha 2009
1997	8 species and 1500 – 2000 flamingos	Rahmani 1997
1998	22,500 flamingos	Sangha 1998
2000	No arrival of flamingos (Drought year with severe water scarcity)	Kulshreshtha 2011
2001	15,000 flamingos	Sangha 2009
2005	71 species & 50,000 – 100,000 flamingos	Kumar 2005
2006	600-700 flamingos	Kulshreshtha 2011
2008	98 species & 3,000 flamingos	Kulshreshtha 2011
2009	83 species	Sangha 2009
2010	52 terrestrial & 46 aquatic birds	Kulshreshtha 2011

 

4.0 RECOMMENDATIONS AND CONCLUSIONS

Lake Fragmentation

To ensure the sustained water flow into the lake:

• Removal of blockages and the encroachments including enhancing water storage capacity removal of fragmentation of lake and ensuring the continuity of water spread area in the lake.
• Restriction of unauthorized extraction of brine in the lake bed as well as buffer zones.
• Removal of unauthorized salt pans in the lake bed and in the buffer zone.
• Maintaining the integrity of the buffer zone (200m) with no permanent structures, as buffer zones are flood plains and aid as water sink sponge.
• Enhancing the green cover in the catchment area by planting native species.
• Providing green barricade in NW portion (Nawa, Nagaur, Ulana, Kansera and Mohanpura) with native tree species would help in mitigating dust deposition or soil erosion. 

The fragmentation of the lake has to be removed to maintain the integrity of the wetland with the continuity in water spread area may be planned and implemented to connect the villages for mobility of people. Immediate removal of the 12.4 km road from Nawa to Khakardi village is necessary, because of the road, multiple anthropogenic activities are increasing and promoted such as poaching and irresponsible tourism. This road divides the lake bed into to two unequal parts which has affected the movement of migratory birds and reduced the overall condition of the Ramsar Site (Z.S.I 2005).

Figure 4.1: Photographs of the road dividing the lake

Removal of salt pans

T Removal of encroached areas with appropriate compensations for the individuals running the salt pans privately is required to sustain water in the lake. Restriction of unauthorized extraction of brine in the lake bed as well as buffer zones. Removal of unauthorized salt pans in the lake bed and in the buffer zone.

Desilting

The silt accumulated in the lake amounts to 18.6 million cubic meters (49.29 million tons), The silt has to be removed immediately to improve the functional capability of the wetland. Removal will not only improve the water storage capacity but also improves the habitat condition of aquatic fauna. Desilting will also provide opportunity for youth and also the silt could be used for beneficial purposes such as the compressed mud blocks for buildings, and also to improve the soil condition in agriculture and horticulture fields.

Constructed Wetland

Suggestion is to implement economical and optimal option through Constructed Wetland at City Bittern Area (which has many inlets of untreated sewage) treated waste water would help in sustaining the water in the lake and also for regular cleaning of panels (to remove the dust). Technical drawings for the constructed wetland have been attached in the annexure.

Eco-sensitive Zone Restrictions

Restriction of developmental activities in eco-sensitive areas including breeding and roosting locations. Transmission towers and distribution network to be planned in such a way that it is not located in the path of the bird movement or closer to the habitat of birds. During the visiting period of migrants, authorities have to ensure adequate quantity of water in the reservoir. As drying up of the lake has affected the avifauna visiting pattern which has been reported earlier.

Figure 4.2: Avifauna and mammal movement paths and habitat hotspots

Figure 4.3: Map of restricted region (developmental activities not permitted) 

 

Conclusion

No development should be undertaken in the area demarcated in figure above (4.3). Factors that are adversely affecting the environmental conditions of the lake should be immediately mitigated or removed. Steps should be taken to improve the health of the Sambhar ecosystem. Negligent attitude towards conservation should be avoided and a proactive approach should be adopted.

Abstract:

Electricity generation through harvesting solar energy is gaining significance in the tropical regions because of its decentralized nature and abundant availability of sunlight. Economically efficient, environmentally friendly solar energy harnessing through photovoltaic cells is dominant among all other technologies and also takes a major portion in large-scale deployment of solar power plants. Although solar power plants are beneficial in achieving the Net zero carbon emission goal of the country and are still encounter many challenges. Assessment of the potential of solar insolation, climate regime, photovoltaic power generation potential, and environmental implications are essential for setting up a power plant. The current study focuses on the estimation of the solar potential, and the possible temperature variation with installed PV panels also depicts the area identification for the deployment of large-scale solar plants considering the ecology and biodiversity of the region.

Keywords: Large scale PV power plant, solar potential, LST, Air Temperature

Introduction:

The Sun is the prime source of energy, and has been revered as a life-giver to our planet since ancient times. Most of the energy on the Earth is derived from Sun as known as heliocentric. In India, major share of the installed power generation capacity is from fossil fuels i.e. 57.9% (Figure 1) as of 2019. (mnre.gov.in). Also Power generation in India from renewable energy sources have increased from 6 GWh in 2002 to 1,38,337 GWh in 2020 (Figure 2). 

Imminent climatic changes and the demand for clean energy sources have induced significant global interest in solar energy. Solar energy has the potential to provide solutions to the longstanding energy problems being faced by developing countries like India.  Solar energy can be an important part of India’s plan not only to add new capacity but also to increase energy security, address environmental concerns, and lead the massive market for renewable energy. Solar is emerging as viable alternative for power generation among the available clean energy sources has the highest global warming mitigation potential. Deployment of large-scale Solar power plants are increased in the world as well as in India. India is one of the best recipients of solar energy due to its favorable location in the solar belt (40◦S to 40◦N).  

Figure 1. Share of different sources in installed power generation capacity in India.

Figure 2. Growth of power Generation from renewable energy in India.

As India’s green energy sector prepares to leap forward, it is worth examining the landscape and charting out the path ahead. Reforms in this sector have been ongoing for over a decade and the total installed capacity from renewable sources has doubled in the last five years, touching the 100 GW mark this August. While this is surely a noteworthy improvement, India continues to depend on oil and gas imports. So, on this Independence Day, in alignment with SDG Goal 7 – “Ensure access to affordable, reliable, sustainable and modern energy for all”, the Prime Minister took a pledge to make India energy-independent by 2047. This requires challenging the status quo of policy implementation and starting with the grassroots, instead of highly developed regions. In solar power, although capacity has increased by more than 11 times in the last five years from 2.6 GW in March 2014 to 28.18 GW in March 2019 (which includes a total of  28,180.68 MWp grid connected and 212.05 MWp off grid Solar Power Plants (2018-2019)), a target of installing 100 GW of grid connected solar power by 2022 has been kept. The country’s vision is to achieve Net Zero Emissions by 2070, in addition to attaining the short-term targets which include:

• Increasing renewables capacity to 500 GW by 2030,
• Meeting 50% of energy requirements from renewables,
• Reducing cumulative emissions by one billion tonnes by 2030, and
• Reducing emissions intensity of India’s gross domestic product (GDP) by 45% by 2030

India is endowed with vast solar energy potential. About 5,000 trillion kWh per year energy is incident over India's land area with most parts receiving 4-7 kWh per sq. m per day. Solar photovoltaic power can effectively be harnessed providing huge scalability in India. Solar also provides the ability to generate power on a distributed basis and enables rapid capacity addition with short lead times. Off-grid decentralized and low-temperature applications will be advantageous from a rural application perspective and meeting other energy needs for power, heating and cooling in both rural and urban areas. From an energy security perspective, solar is the most secure of all sources, since it is abundantly available. Theoretically, a small fraction of the total incident solar energy (if captured effectively) can meet the entire country's power requirements. solar energy sector in India has emerged as a significant player in the grid connected power generation capacity over the years. It supports the government agenda of sustainable growth, while, emerging as an integral part of the solution to meet the nation’s energy needs and an essential player for energy security. (mnre.gov.in/solar/current-status)

 

Materials and Method

Study Area 

Figure 3. India with the federal state boundaries and agro-climatic zones.

In India there are 28 states and 8 Union territories in the country (knowindia.india.gov.in). India falls under 15 different agro-climatic zones including Island regions as represented in the Figure 3. Whole land footprint of India is considered for the calculation of the Solar insolation potential and Solar PV potential.

For assessment of environmental implication of the solar power generation, two major PV solar power plants of India, based on their power producing capacity, spatial extent, and climatic zones commissioned before 2018 and 2019 chosen, include (i) Bhadla solar Power Plant in Rajasthan and (ii) Pavagada solar PV plant of Karnataka. Study is based on the comparative analysis of both Land surface temperature and Air temperature at PV plant locations and surrounding regions before and after the installation of a solar PV power plant.

Bhadla Solar Park

The Bhadla Solar Park, is the largest solar power plant in the world, total capacity of the solar park is 2245MW (https://energy.rajasthan.gov.in) is located in a semiarid to the arid region at Bhadla village, Jodhpur district of Rajasthan (27°28'37.00"N and 71°57'42.53"E) in uncultivated land with a land footprint of 5700 ha, and an elevation ranging between 168 to 185 m above mean sea level (figure 4). The installation was completed in 2018. Some portion of land was under seasonal cultivation of castor oil seed, Gawar, and Bajara, and agriculture in the area is purely dependent on rainfalls or bore pumps.

Pavagada Solar Park

Pavagada Solar Park (Photovoltaic) a capacity of 2,050 MW was completed in 2019, in the eastern dry agro climatic zone at Tumkur district (14°16'18.06"N latitude 77°24'24.89"E longitude) with an elevation ranging between 450 to 840 m above msl in the plains; and hilly areas ranging between 840 to 1500m above msl (https://cdkn.org). It covers an area of 5300 ha (~13000 acres) across five villages (figure 4), namely, Balasamudra, Tirumani, Kyataganacharlu, Yallur and Rayacharlu of Pavagada Taluk, Tumukur District of Karnataka (https://kspdcl.karnataka.gov.in). As of April 2021, it is the World's third largest photovoltaic solar park after the 2,245 MW Bhadla Solar Park in Rajasthan and the 2,200 MW Huanghe Hydropower Hainan Solar Park in China.

Figure 4. Location of Bhadla and Pavagada Solar Park

 

Method

Solar Insolation potential and solar PV potential too understand the opportunities of the decentralized solar power generation in India , which helps in prioritizing solar energy harvestable regions in India. The environmental implication of plants is the variation in the local temperature . In this regard, assessment is done at locations where large-scale solar power plants are operational considering land surface temperature and 2 m Air temperature. as well as the solar insolation potential, solar PV potential, ecology and biodiversity of the region, and legal compliances  

The potential of the region for solar power plant is assessed through the quantum of solar radiation (electromagnetic energy) with duration of the sunshine hour, and temperature. If solar energy can be harnessed to its potential, humans will have a permanent and unlimited supply of free and clean energy, withminimum or no long-term environmental impact (Phillips, 2013). Solar insolation is the amount of solar energy that strikes a square meter of the earth’s surface in a single day. Solar insolation mapping has been done to identify the potential of solar energy . 

The photovoltaic (PV) potential represents the expected lifetime average electricity production (in kWh) from a kW-peak grid-connected solar photovoltaic (PV) power plant. PVOUT map provides a summary of estimated solar photovoltaic (PV) power generation potential (https://solargis.com).

 

Solar insolation Potential (Ramachandra et al. 2011)

For assessment of solar insolation potential, the NASA SSE monthly average Global insolation data is collected for more than 900 grids which optimally cover the entire topography of India within the latitudes 8 - 380 N and longitudes 68 - 980 E. These datasets are derived from a physical model based on the radiative transfer in the atmosphere along with parameterization of its absorption and scattering properties. Visible and infrared radiation, inferred cloud and surface properties, temperature, perceptible water, column ozone amounts, and atmospheric variables such as temperature and pressure measured using diverse satellite instruments are the primary inputs to this model. The longwave and shortwave solar radiations reflected to the satellite sensors along with the collected primary inputs are studied to obtain the global insolation for different locations and durations. The global insolation datasets have a spatial resolution of 1º × 1º. After extraction of the data geo-statistical bilinear interpolation is employed to produce monthly average Global insolation maps for the country detailed with isohels (defined as lines/contours of equal solar radiation) using Geographical Information Systems (GIS). Regions receiving favorable annual global insolation for electricity generation with technologies like SPV and CSP and the prospects for successful solar devices dissemination are demarcated as solar hotspots.

Photovoltaic Power Potential (PVOUT)

The photovoltaic (PV) potential data are available in the global solar atlas where the calculation is done through Solargis, whichprovides the PV modelling software and high-resolution solar resource data for solar electricity calculation. The calculation takes into account solar radiation, air temperature, and terrain, to simulate the energy conversion and losses in the PV modules and other components of a PV power plant. In the simulation, losses due to dirt and soiling were estimated to be 3.5%. The cumulative effect of other conversion losses (inter-row shading, mismatch, inverters, cables, transformer, etc.) is assumed to be 7.5%. The power plant availability is considered to be 100%. PV system configuration consists of ground-based, free-standing structures with crystalline-silicon PV modules mounted at a fixed position, with optimum tilt to maximize yearly energy yield. Use of high-efficiency inverters is assumed for the calculation (https://solargis.com/maps-and-gis-data/tech-specs). Complete description of the modeling approach and related uncertainties is available in Solargis (https://solargis.com).

For the current study the GIS data of PVOUT extracted from the Global solar atlas for India and having the special resolution of 1Km. Annually and Monthly averaged Daily Total Photovoltaic Power Potential (PVOUT) of India with the highlighted Rajasthan boundary maps are produced with the help of Quantum Geographical Information Systems (QGIS).

Land surface Temperature 

Data from space-borne remote sensors (RS) (Landsat series satellites) are widely used for environmental studies. TIR region corresponding to 8–14 µm in the electromagnetic spectrum is used for quantifying the thermal urban environment (Ramachandra et.al 2018). LST from thermal data have been derived considering the emissivity and atmospheric effects (Sekertekin and Bonafoni 2020). Algorithms consider the number of TIR bands used as (i) single-channel or mono-window algorithms use one TIR band, (ii) split window or multi-channel methods include more than one TIR band (Sekertekin and Bonafoni 2020).

LST of the two different environments of arid/semi-arid region (Bhadhla, Rajasthan) and central dry zone (Pavagada, Karnataka) where the solar PV power plants are already installed, were computed from the Landsat 8 OLI/TIR satellite, in Google Earth Engine (GEE). Landsat 8 Operation Land Imager (OLI) sensor with nine bands (band 1 to 9) and Thermal Infrared sensor (TIR) with two bands (band 10 and 11). LST of a region is computed as follows:

TOA Brightness Temperature

The atmosphere (TOA) radiance is the net radiance of the emitted radiance from the earth’s surface upwelling radiance from the atmosphere, and down welling radiance from the sky and acquired in remote sensors in the thermal infrared (TIR) region. The value of Top of Atmospheric (TOA) spectral radiance (Lλ) in watts/ (m2 srad µm) is determined by multiplying the multiplicative rescaling factor (OLI ML=0.000342) of TIR bands of with its corresponding TIR band (Qcal = band 10) and adding Band specific additive rescaling factor (OLI AL = 0.1). λ represent the wavelength of the thermal band. (Ramachandra et.al 2018 and Jeevalakshmi, Narayana Reddy., Manikiam 2017). Computation of the emissivity corrected land surface temperature(Ts) involves computation of L_λ, T _B, NDVI as follows (equations 1 to 5):

L _λ is computed by equation 1.

L_λ = M _L * Q _cal + A _L   ………. (Eq.1)

The radiance to equivalent brightness temperature at the satellite using equation 2

………. (Eq.2)

where, TB represents the At-satellite brightness temperature, K1 and K2 (kelvin) represents the pre-launch calibration coefficients. Whose value is K1 = 774.8853, K2 = 1321.0789 (for OLI band 10), Lλ is the TOA spectral radiance.

Normalized Difference Vegetation Index (NDVI)

Computation of Normalized Difference Vegetation Index (NDVI) helps in mapping regions with vegetation and non-vegetation. NDVI is calculated on the per-pixel basis as the normalized difference between the near-infrared band (0.85-0.88µm) and red band (0.64 - 0.67µm) using equation 3.

………. (Eq.3)

Where NIR is the near-infrared band (B5) value of a pixel and RED is the red band (B4) value of the same pixel. NDVI ranges between -1 to +1. very low values of NDVI (-0.1 and below) correspond to soil or barren areas of rock, sand, or urban built-up. Zero indicates water cover. Moderate values (0.1 to 0.3) represent low-density vegetation, while high values (0.6 to 0.8) indicate thick canopied vegetation (Ramachandra et.al 2018). NDVI is used to calculate proportional vegetation (Pv) and emissivity (ԑ).

 

Land Surface Emissivity(ԑ) 

Emissivity is a critical variable for the LST estimation, as a small uncertainty in the emissivity (1%) can lead to large errors in the LST (up to 1K) depending on the setting of the sensor, the climatological conditions and geographical setting of the area (Mitraka et al. 2012, Chen et al. 2016, Parastatidis D et al.). In the current study NDVI-based emissivity is estimated from Landsat red and near-infrared data.

 ………. (Eq.4) (Dissanayake, et al. 2019, Sobrino et al. (2004))

where m represents (εv – εs) − (1 − εs) Fεv; n represents εs + (1 − εs) Fεv; εs is soil emissivity; εv is vegetation emissivity; and F is a shape factor whose mean value, assuming different geometrical distributions, is 0.55 (Dissanayake, et al. 2019, Sobrino et al. (2004)). Value of m is considered as 0.004 and n as 0.986 based on previous results (Sobrino et al. (2004)), the Pv is the proportional vegetation and it is calculated from the Eq.5

………. (Eq.5) (Dissanayake, et al. 2019, Sobrino et al. 2004)

Land Surface Temperature(Ts)

The emissivity corrected land surface temperature(Ts) is computed as per equation 5 (Ramachandra et.al 2018)

………. (Eq.5)

where, is the wavelength of emitted radiance for which the peak response and the average of the limiting wavelengths ( =10.895µm) were used, ρ is h × c/σ (1.438 × 10–2 m K) with σ being the Boltzmann constant (1.38 × 10–23 J/K), h is Planck’s constant (6.626 × 10–34 Js), and c is the speed of light (2.998 × 108 m/s); TB is satellite brightness temperature and ε is land-surface emissivity estimated using Eq.2 and Eq.4 respectively. Then, calculated LST values (Kelvin) were converted to degrees Celsius (◦C). Finally, LST data is further analyzed and represented spatially with the help of QGIS.

Air Temperature

Data under the topics like atmosphere, Biosphere, cryosphere, land surface, ocean, Earth, etc. are available for open access from NASA's Earth Observing System (https://www.earthdata.nasa.gov). Earth Observation Data and Information System (EOSDIS) provides end-to-end capabilities for archiving and distributing Earth science data from multiple missions since 1994 to users.

 

Daily maximum 2-meter air temperature data is available in the GIOVANNI, an online (Web) environment for the display and analysis of geophysical parameters in which the provenance (data lineage) can easily be accessed (https://giovanni.gsfc.nasa.gov). Air temperature data have a spatial resolution 0.5o * 0.625o and a temporal resolution of 1 day. M2SDNXSLV, a 2-dimensional daily data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), consists of daily statistics, such as daily maximum (or daily minimum and mean) air temperature at 2-meter. MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with a latency of ~3 weeks after the end of a month (https://gmao.gsfc.nasa.gov).

 

Data for Bhadla and Pavagada locations corresponding to the pre-installation period (2015 to 2018 and 2017 to 2019) and post-installation (2019 to 2022 and 2020 to 2022) are considered for analyses. 2-m daily maximum Air temperature data of the peak summer months for Bhadla (April, May, and June months) and for the Pavagada (March, April, and May months) are downloaded from the GIOVANNI. The maximum temperature of each month is considered for the analysis of annual variation. Graphical representation and statistical analysis of Grid wise data were done . Air temperature data is presented spatially with the help of QGIS.

Fig 1. Method adopted for assessing LST

 

Result

Solar insolation Potential

The study on Hotspots of solar potential in India using high resolution satellite data and techno-economic feasibility assessment demonstrated that Rajasthan also one of Hotspot of solar potential (Ramachandra et al. 2011).

Fig.2 illustrates that the Gangetic plains (Trans, Middle and Upper) Plateau (Central, Western and Southern) region, Western dry region, Gujarat Plains and hill region as well as the West Coast plains and Ghat region receive annual Global insolation above 5kWh/m2/day. These zones include major federal states of Karnataka, Gujarat, Andhra Pradesh, Maharashtra, Madhya Pradesh, Rajasthan, Tamil Nadu, Haryana, Punjab, Kerala, Bihar, Uttar Pradesh and Chattisgarh. The Eastern part of Ladakh region (Jammu & Kashmir) and minor parts of Himachal Pradesh, Uttarakand and Sikkim which are located in the Himalayan belt also receive similar average Global insolation annually. Regions receiving Global insolation of 5 kWh/m2/day and above can generate at least 77 W/m2 (actual on-site output) at 16% efficiency.

 

Fig.2. Annual average Global insolation map of India showing the isohels and solar hotspots.

 

Photovoltaic Power Potential (PVOUT) of India 

Annually averaged daily total of PVOUT (Fig.3.) across the different regions of India varies from 2.031 to 5.925 kWh/kWp, Rajasthan shows the 4.16 to 5.04 kWh/kWp PVOUT potential variation across the state. Fig.4.1 and 4.2 illustrates good PVOUT potential of above 3 kWh/kWp, where in the July month it is low (2.59-4.25kWh/kWp) and high(5.03-6.08kWh/kWp) in the month of March in Rajasthan. PVOUT power generation capacity would enhance considerably with the improvement in efficiency of Solar PV technology.

India has the potential of daily solar radiation incidence varying from 4.5 to 6.0 kWh/m2/day in different parts of the country. Total solar radiation at Sambhar is 2080 kWh/m2/year, translating to 5.70 kWh/m2/day (Solar energy corporation of India, ‘Prefeasibility Report for setting up of Ultra megawatt solar PV power plant at surplus salt pan lands at sambhar Rajasthan’ 2013).

Figure: 4.1. Annual average  daily total PVOUT

 

January	Febuary	March
April	May	June
July	August	September
October	November	December

Figure  4.2. Monthly Averaged Daily Total Photovoltaic Power Potential (PVOUT) of India

Land Surface Temperature

Temporal pattern of the Land surface temperature of the study region (land print of PV power plant and landprint of PV power plant along with 5 km buffer) is assessed through the remotely sensed Landasat-8 sensor remote sensing data. Figure 5.1 and 5.2 illustrates the temporal LST in (i) Bhadhla (Rajasthan) PV Solar Power Plant with 5 km buffer and (ii) Pavagada (Karnataka) PV Solar Park with 5 km buffer. Table 2 lists average LST before and after the installation of PV solar plant.

 

The installation of Bhadla solar plant was completed in 2018. The year wise LST analysis of Bhadla solar park from 2015 to 2021 was done to understand the potential changes in land surface temperature after installation of PV panels. In 2016 Average LST was observed very high (54.24°C).  Variability in LST before 3(2016-2018) and after 3 (2019-2021) years of PV installation was assessed statistically (F- test), which indicate there is no significant(P<0.05) variation in the LST during the chosen study periods. The temporal analyses of LST, highlights that the temperature has declined during the post 2019 (post installation of PV) suggesting cooling effect with a difference of ~2°C (2021), ~1.3°C (2019)) and ~0.5°C (2020) (Fig.5.1 and 5.3).

The Pavagada solar park was commissioned in 2019. The temporal assessment LST from the period before (2019) and after (2019 onwards) installation of PV does not show any significant variations, which is evident from statistical test (F-test, p<0.05). The average LST in 2015 are 39.42°C in PV, and 38.40°C in buffer, which has increased in 2019 to 45.2°C in PV region, 44.81°C in the buffer region and in 2021, LST are 39.72°C in PV and 40.47°C in the buffer region which highlights of decrease in LST (after installing PV) compared to 2019 in the PV region, and also in the buffer region (Figure 5.2 and 5.4). Comparison of the LST of the PV region with its surrounding (5 km Buffer) after installation of PV shows a significant cool island effect (p<0.05) PV region has a maximum LST of 45.56°C (2020), and 41.06°C (2021), which is lower than the surrounding(5 km) maximum land surface temperature of 48.67°C (2020), and 43.48°C (2021). LST in the panel deployed region is ~3°C lower than the buffer region (5 km surrounding PV region).

Assessment of LST at both locations with large-scale PV plants, highlights of land surface cooling effect, which are in conformity with the earlier studies (Zhang, Xu, 2020 and Guoqing, Hernandez, Blackburn et al. 2021). Also, statistical analyses of LST of two time periods (pre and post installation) at both study regions indicate that there are no significant temporal variations (p < 0.05) in the LST.

 

Figure 5.1. Land Surface Temperature of Bhadhla (Rajasthan) PV Solar Power Plant 

Figure 5.2. Land Surface Temperature of Pavagada (Karnataka)PV Solar Park before and after PV installation

Table 2. Average LST before and after the installation of PV solar plant of both locations in the PV and Buffer area.

PV Solar power plants	year	Pre-Installation		Year	Post-Installation
		PV area	Buffer Area		PV area	Buffer Area
Bhadla  Solar Park	2015	45.34	45.33	2019	48.90	50.13
	2016	54.24	53.95	2020	43.48	44.00
	2017	50.64	50.73	2021	45.44	47.14
	2018	50.38	50.70
Pavagada  Solar Park	2015	39.41	38.4	2020	44.44	44.83
	2016	44.63	43.23	2021	39.72	40.47
	2017	42.38	42.21
	2018	42.98	42.1
	2019	45.19	44.81

Figure 5.3. Temporal variation and difference in the Land Surface Temperature of PV region and 5 km buffer of Bhadla (Rajasthan) PV Solar Park. Dotted line bifurcate years as pre/post PV panel installation year

Figure 5.4. Temporal variation and difference in the Land Surface temperature of PV region and 5 km buffer of Pavagada (Karnataka) Solar PV Power Plant. Dotted line bifurcate years as pre/post PV panel installation year

Air Temperature

Assessed temporal variations in the daily maximum 2 m air temperature of summer months for semiarid to arid regions and eastern dry agro-climatic zone using NASA's Earth (GIOVANNI) data (https://giovanni.gsfc.nasa.gov/giovanni/). Despite the temperature data being coarse resolution,  the spatial and temporal pattern of air temperature still provide insights to understand the likely changes in the temperature with the installation of PV solar plant.

Comparative analyses of location-wise and year-wise temporal variation of  2-m Air Temperature at PV region and 5 km buffer in Pavagada (Karnataka) PV Solar Park are depicted in Figure 6.1 (and 6.2), Figure 6.3 (and 6.4) and Figure 6.5 (and 6.6) for March, April and May months respectively, which illustrates that there are no significant changes in the 2-m air temperature during summer months at Pavagada power plant and also in buffer region during post installation compared to the period before installing PV solar plant. Figure 6.7, 6.8, and 6.9 depict the maximum daily, maximum 2-m Air temperature for March, April, and May months at Pavagada PV and surrounding regions, which further highlights that there are no significant variations in temperature (i) at PV locations and buffer regions, and (ii) during post installation period compared with the air temperatures of pre-installation period.

 

Figure 6.1 and 6.2 Location wise and year wise temporal variation in 2-m Air Temperature for March month at PV region and 5 km buffer in Pavagada (Karnataka) PV Solar Park.

 

Note: Green box indicates the location were PV plant is installed. Dotted line bifurcate years as pre/post PV panel installation year.

Figure 6.3 and 6.4. Location wise and year wise temporal variation of 2-m air temperature for April at PV region and 5 km buffer in Pavagada (Karnataka) PV Solar Park.

 

Note: Green box indicates the location were PV plant is installed. Dotted line bifurcate years as pre/post PV panel installation year.

Figure 6.5 and 6.6 Location wise and year wise temporal variation of 2-m Air Temperature for May at PV region and 5 km buffer in Pavagada (Karnataka) PV Solar Park.

Note: Green box indicates the location were PV plant is installed. Dotted line bifurcate years as pre/post PV panel installation year.

 

  

Pre-Installation
2017	2018	2019
Post-Installation
2020	2021	2022

Figure  6.7. maximum of daily maximum 2-m Air temperature in March at Pavagada PV and Surrounding area

Pre-Installation
2017	2018	2019
Post-Installation
2020	2021	2022

Figure 6.8. maximum of daily maximum 2-m Air temperature for April at Pavagada PV and Surrounding area

 

Pre-Installation
2017	2018	2019
Post-Installation
2020	2021	2022

Figure  6.9. maximum daily maximum 2-m Air temperature for May at Pavagada PV and Surrounding area

Figure 6.1 to 6.6 depicts the variation in the air temperature in the summer months at Pavagada solar power plant. The maximum temperature is 41.370C in 2021 and 41.17 0C in 2022, which is ~10C (or >10C) higher than pre-installation years at the location-2 with the Solar power plant, the increased temperature in the PV region is noticed for all years except 2020 at all locations including at PV. The lowest temperature in all 6 locations, including the PV region, is in 2017, then increased by an average of 2.50C in 2018 and 2019. However, there is 10 C decrease in 2020 compared to the preceding year, 2019. There are significant variations in temperature during the post-installation period compared to the earlier period for March, evident from the statistical F-test (P<0.05).

Air temperature in 2022 of April in PV region is 0.1 0C higher than 2018, but is ~20C lower in 2020 than the pre-installation period in all locations except Bagepalli (location 6).  

Figures 6.7, 6.8, and 6.9 depict the maximum of daily maximum 2-m air temperature for March, April, and May months. The period after the PV installation showed ~1oC lower Maximum temperature in May month (figure 6.5) at all locations, including Solar PV locations (loc 2), after 2019. There are no significant variations in 2-m air temperature during post installation period compared to before 2019 (F-test, p>0.05).

Higher air temperature at location 3 (away from solar PV by ~60Km) during summer months further highlights that presence of the large PV may not be the reason for changes in ambient temperature. The study confirms that PV panels do not significantly influence the ambient temperature. Nevertheless, there has been an increasing temperature trend in recent years at all locations, irrespective of the presence or absence of PV plants.

Bhadla Solar Park

The Bhadla solar park is located in the semiarid to the arid region. Carried out analyses of location-wise and year-wise temporal variation of 2-m Air Temperature at PV region and 5 km buffer in Bhadla (Rajasthan) PV Solar Park and presented in Figure 6.10 (and 6.11), Figure 6.12 (and 6.13) and Figure 6.14 (and 6.15) for April, May and June months respectively. It illustrates that there is no significant change in the 2-m air temperature during the summer months at Bhadla (Rajasthan) power plant and also in buffer region during post-installation compared to the period before installing PV solar plant. Figure 6.16, 6.17, and 6.18 depict the maximum daily, maximum 2-m Air temperature for April, May, and June months at Bhadla PV and the surrounding area, which further highlights that there are no significant variations in temperature (i) at PV locations and buffer regions, and (ii) during post installation period compared with the air temperatures of pre-installation period.

During the summer months of 2015 to 2018 (pre-installation period), there was an increase in the daily maximum 2-m air temperature, which dropped in 2019 to an average 43.6 0C from 45.2 0C (2018). However, after a further drop in 2020, 2-m air temperature showed an increasing trend in April. 2-m air temperature is 0.50C lower in 2022 (post-installation) than in 2018 (pore-installation), at all locations, including the PV-installed region (0.4 0C lower in 2022 than in 2018). There are significant variations in 2-m air temperature during the post-installation period compared to the pre-installation period (F-test, P<0.05) though there are minor fluctuating trends.

During May, daily maximum temperature shows an increasing trend from 2015 (pre-installation) to 2022(post-installation), and there has been a significant increase in 2016 compared to all years. The ambient temperature increased at PV location by 1.5 0C from 2015 to 2018, which decreased by 10C in 2021 and raised by 10C in 2022 compared to air temperatures of the pre-installation period.

Cooling in the air temperature ~1.50C was observed from June of 2018 to 2022 and 0.50C increase in 2019. There is no significant (F-test, P<0.05) variations in temperatures of June month during post installation period compared with the pre-installation period. Location 1, near the desert or part of the desert, shows the maximum temperature during April, May and June from 2015 to 2022.

Air temperature at the PV installed region and buffer region in the different climatic regimes doesn't follow any particular pattern. Although the assessment of air temperature at PV solar parks and buffer regions highlights of cooling effect of PV plants during April and June months in Bhadla, and May month in Pavagada. There is a slight increase during March and April in Pavagada, and May in Bhadla, but variations are not significant compared to the land feature other than solar panels. 

Figure 6.10 (and 6.11). Location wise and year wise temporal variation of 2-m Air Temperature for April at Bhadla (Rajasthan)PV region and 5 km buffer. Note: Green box indicates the location were PV plant is installed. Dotted line bifurcate years as pre/post PV panel installation year.

Figure 6.12 (and 6.13). Location wise and year wise temporal variation in the 2-m Air Temperature for May at Bhadla (Rajasthan) PV region and 5 km buffer. Note: Green box indicates the location were PV plant is installed. Dotted line bifurcate years as pre/post PV panel installation year.

Figure 6.14 (and 6.15). Location wise and year wise temporal variation in the 2-m Air Temperature for June at Bhadla (Rajasthan)PV and 5 km buffer.

Note: Green box indicates the location were PV plant is installed and Dotted line bifurcate years as pre/post PV panel installation year.

  

Pre-Installation
2015	2016	2017	2018
Post-Installation
2019	2020	2021	2022

Figure 6.16. maximum daily maximum 2m Air temperature for April at Bhadla PV plant and buffer region

 

Pre-Installation
2015	2016	2017	2018
Post-Installation
2019	2020	2021	2022

Figure 6.17. maximum daily maximum 2-m Air temperature for May at Bhadla PV and Surrounding area

 

Pre-Installation
2015	2016	2017	2018
Post-Installation
2019	2020	2021	2022

Figure 6.18. maximum daily maximum 2-m Air temperature for June at Bhadla PV and the Surrounding area

 

Challenges of Solar Energy

• Weather – Dependent. Although solar energy can still be collected during cloudy and rainy days, the efficiency of the solar system drops.
• Solar energy storage is expensive.
• Uses a lot of space.
• Associated with pollution
• Environmental impacts

Opportunities of Solar Energy

Socio- Economic

• Boost the local, rural Industries
• Acceleration of electrification in rural area
• 24/7 electricity for the Industries
• Energy independency
• Job opportunities

Environmental positive impacts

• Reduction of the emissions of the greenhouse gases
• Absence of any air emissions or waste products during their operation
• Reclamation of degraded land
• Reduction of the required transmission lines of the electricity grids

 

Conclusion

Study shows that nearly 58% of the country receives annual average Global insolation of 5 kWh/m2/day with 4.16 to 5.04 kWh/kWp (Rajasthan) Photovoltaic Power Potential. LST and 2-m Air temperature during the pre and post-installation period at Bhadhla and Pavagada reveals, there is no significant variations, cooling effect observed in the LST, no variation in air temperature because of PV plant. 6475ha (~16000 acres) of land identified for the solar plant in Rajasthan without disturbing the ecology and biodiversity of the region.