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India is an Agriculture based country and about 60% of the population depends on agriculture for their living. But there is a substantiable reduction in agricultural production has happened due to unstable climate conditions and global warming. Indian farmers are always lacking the support of advanced technologies for improving and maximizing their yield. If they get explicit information about soil type, nutrients, pH value, changes in climatic factors, previous year yield etc., they can optimize their work and yield. With the advancement of machine learning, big data analytics and cloud computing technologies, the climate and crop yield can be got predicted to the farmers. Prediction of yield in advance can help the farmers to take corrective decisions about fertilization, storage and marketing to increase their production and revenue. A huge number of studies have been conducted worldwide, on agriculture sector for the prediction of crop yield, plant diseases etc. This paper presents a brief study of different researches in India on crop yield prediction based on Machine Learning and deep learning. Most of the researchers used environmental parameters like temperature, rainfall and soil type as the main features for prediction. A number of machine learning algorithms are employed in this field and it is really a complex task to identify the best algorithm. The researchers tried to accurately predict the crop yield and thereby suggesting ways to improve production and efficient use of fertilizers. [ABSTRACT FROM AUTHOR]

India is a country of diversity. The primary occupation of the country is agriculture. In our country there is perfect weather conditions. There are significant challenges due to climatic changes that effects multiple sectors, which includes agriculture. According to food and agriculture organisation (FAO), the food production has to be increased by 70% by 2050 to meet food requirement of the population. The answer to this challenge is by introducing the new technology in the sector. In detailed introduction of IOT, UAVs and many technologies. Precision agriculture's tasks like smart spraying and aerial crop monitoring etc. Use of software development kit (SDKs) in UAVs will connect it to the mobile phones which makes farmer's ease of use. Introducing GPS in the UAV's makes discrete time broadcasts of its global coordinates, which also makes UAVs to fly at same altitude, autopilot, auto home return. By using sensors like collision avoidance sensors (CAS), gyroscope, accelerometer, magnetometer, barometer, range finder, helps the UAVs for anti-collision, balancing, determining speed, range respectively. By using thermal imaging camera, farmers can see which part of the field was affected by pests. By using the cameras farmers can monitor their crops, they can even survey their field. In this paper, we introduce the AI technology in the UAVs to help the farmers. Finally, we outline UAV based solutions for the challenges in precision agriculture. [ABSTRACT FROM AUTHOR]

The first mangrove forests appeared during the late cretaceous- Early tertiary period along Thethys Sea coasts. Since then, mangrove forests have faced and survived several catastrophic climate change events. The sea level is not and has not been constant. Studies carried out on mangrove peat prove mangroves extinction in various parts of the world due to abrupt sea-level rise. The response of mangrove in different geographic regions will depend on factors such as local rate of sea-level rise, coastal topography, and sediment supply rates. It is vital to understand mangrove floor dynamics to understand how mangroves will respond to rising sea-level. Rod surface elevation table is used worldwide to understand surface elevation or loss in wetlands. This paper deals with studying the work done using Rod Surface Elevation Table (RSET) technique to learn mangrove floor level changes worldwide. This literature review also reveals the gap in organised research studying mangrove surface elevation gain rates using RSET technique in India. [ABSTRACT FROM AUTHOR]

This paper mainly deals with the design and analysis of Agriculture data using Machine Learning (ML) techniques. Agriculture includes cultivating the soil and we can grow different types of crops. In India there are 28 states and 8 Union Territories. In each and every state people are farming and they are developing our agriculture in so many ways. Every state has its own farm for example: - Andhra Pradesh-Rice, Bazra, maize, ragi, pulses etc; the other name for agriculture is "Back Bone of India ". The sediment pressure is due to erosion and soil loss. Diffusion in nature occurs in the fine-grained sediments. Statistical analysis is being carried out for effective solution based on different parameters. This helps to get more information for farmers to make critical farming decisions. Researchers focused on agriculture and found an optimal option to increase production. Experimental data is analyzed and the production is optimized for agriculture such that it is more resilient to climatic change. [ABSTRACT FROM AUTHOR]

Renewable energy has been an important component of India's energy planning process for quite some time, especially since India seeks to make significant contributions toward climate change mitigation and emerge as a responsible global powerhouse. Solar energy has rapidly emerged as a reliable, affordable and clean solution for meeting India's fast-growing energy demand and supply power to all. This, it is crucial for India to promote large-scale mega solar projects like solar parks in order to promote ecologically sustainable growth and to meet the challenges of climate change, with technology and investment flow from around the globe, is one of the National goals. Based on above object National Solar Mission was launched with the goal of 20 GW grid connected solar power by the year 2021-22. Further, Government of India has revised the target of Grid Connected Solar Power Projects from 20 GW by the year 2021-22 to 100 GW by the year 2021-22 under the Mission. This can be achieved through an integrated bid process including Make in India. The critical success factors including development of Solar Park in India and tariff trends are described in this article. India, with its large population and rapidly growing economy, needs access to clean, cheap and reliable sources of energy. India lies in the high solar insolation region, endowed with huge solar energy potential with most of the country having about 300 days of the sunshine per year with annual mean daily global solar radiation in the range of 4-6 kWh/m2/day. The solar park is a concentrated zone of the development of solar power generation projects and provides developers an area that is well characterized, with proper infrastructure and access to amenities and where the risk of the projects can be minimized. Solar Park also facilitates developers by reducing the number of required approvals. The most important benefit from the solar park for the private developer is a significant time saved. Solar power projects can be set up anywhere in the country, however, the scattering of solar power projects leads to higher project cost per MW and higher transmission losses. Individual projects of smaller capacity incur significant expenses in site development, drawing separate transmission lines to the nearest substation, procuring water and in the creation of other necessary infrastructure. It also takes a long time for project developers to acquire land, get a change of land use and various permissions, etc. which delays the project. The paper describes the concept of solar parks has indeed emerged as a powerful tool for the rapid development of solar power projects in India. Further, Assured availability of land and transmission infrastructure are the major benefits of the Solar Parks. The recent downward trends in solar tariff may be attributed to the factors like economies of scale, assured the availability of land and power evacuation systems under the Solar Parks also included. [ABSTRACT FROM AUTHOR]

Countries across the globe are looking for some alternative sources of energy to cope up the depletion of fossil fuels. These alternative sources also help in minimizing the impact of climate change. To help the impact of climate change and to support the more renewable and electrical vehicle penetration, policies are designed. These policies encourage more renewable energy integration and promote electric vehicles. Net metering is a policy by the virtue of which unconsumed energy is fed into the distribution network and is utilized by the nearby consumers, connected to the same distribution network. It permits the renewable energy power producers of small scale to store or bank their electricity at the time of over-production and sent back to the grid. This paper throws some light on different net metering models available in the literature. Policy and regulatory barriers are investigated in the survey across all the states in the country. A review is presented on net metering policies across all states of India. [ABSTRACT FROM AUTHOR]

Nobody on this planet is going to be untouched by the impacts of climate change. The ability to cope with climate change varies from region to region, resulting the difference among its effects on fragility. In this paper, we focus on figuring out how the climate change influences the state’s fragility. First, we build Multilevel Fuzzy Mathematic Appraisement Model to assess the grade of the fragility. Then we identify the climate change as an indirect indicator through studying and discussing. Furthermore, after conducting Multiple Linear Regression Models between quantified climate index and twelve factors, we select the indicators that is relevant to climate change to measure the effect of climate change. Then, apply our model to the countries we choose--Sudan and India. We figure out climate change will increase the fragility index by affecting the economy, brain drain and state legitimacy of Sudan, then we quantize the growth by the multiple liner regression equation. For India, we find that when the temperature raise 1.6°C or the fragility index reach 90, India will become fragile. Then we predict by Back-Propagation neural network, finding that it is hard for India to be fragile within 100 years. Additionally, we apply our model to China, finding that its fragility index decreased with its intervention by decreasing most indicator index. Besides, we measure the total cost of intervention by Markal―Macro Model, getting that the total cost takes up 4% of GDP. Finally, because the indicators affecting the fragility of the cities is different from these affecting states, we modified it by altering the indicators we considered to apply in a small “state”, so it could be effective for cities to reflect the climate change impact on fragility. [ABSTRACT FROM AUTHOR]

Diversification of land use in the cultivation of various crops provides an alternative way to moderate the climate risk. By choosing alternative crops that are resilient to various weather parameters, farmers can reduce the crop damage and achieve optimum output from their limited land resources. Apart from other adaptation measures, crop diversity can reflect farmers' response towards changing climate uncertainty. This paper tries to examine the changing climatic condition through spatio-temporal variation of two important weather variables (precipitation and temperature) in the largest North-East Indian state, Assam, since 1950. It is examined by the variation in crop diversification index. We have used (1) Herfindahl Index for measuring degree of diversification and (2) locational quotient for measuring the changes in the regional crop concentration. The results show that, in almost all the districts, crop specialization has been taking place slowly and that happened mostly in the last phase of our study. The hilly and backward districts recorded more diversification but towards lower value crops. It goes against the normal feature of crop diversification where farmers diversify in favour of high value crops. Employing ordinary least squares method and/or Fixed Effect model, irrigation is found to have significant impact on crop diversification; while the flood plain zones and hill zones are found to have better progress in this regard, which has been due to the survival necessity of poor farmers living the zone. Thus crop diversity does not reflect very significant response from the farmers' side towards changing weather factors (except rainfall) though they have significant impact on the productivity of various crops, and thus profitability. The study thus suggests the necessity for rapid and suitable diversification as alternative climate change mitigation in the long run. [ABSTRACT FROM AUTHOR]

Atmospherics aerosols play a vital role in the field of study of Earth's radiation budget and their impact on climate change. The present study was carried out for the study of variation of aerosol characteristics during pre-monsoon season 2011 at different locations, (a) Jaipur (26.900 N, 75.900E), (b) Kanpur (26.40 N, 80.40 E) and (c) Gandhi College, Ballia (25.8° N, 84.2°E) over Indo Gangetic Basin (IGB) using AERONET level 1.5 data. Various interesting results are discussed in present paper in terms of aerosol optical and radiative properties. [ABSTRACT FROM AUTHOR]

This paper is an attempt to understand Indian Solar Photovoltaic technological innovation system. Solar energy is one of the key solutions for energy security that holds a significant place to bridge the demand-supply gap of energy and consider a more sustainable form of energy among various renewable energy sources. At the same time, it is also one of low-carbon technologies, which aim to enhance the country's economic development. In this study, we adopt technological innovation system framework to understand the main drivers and barriers and to see the future directions pertaining to Solar Photovoltaic technological innovation system in the country. Methodologically, the study relies on both primary and secondary data. We found that entrepreneurial activities function embraces a fairly accumulated technological innovation system that performs a dynamic result. However, the least accumulated in the system is associated with resource mobilisation. Inconsistent regulations, less interaction in networks, disconnected competitive entities, unpredictable behaviour of the government and the lack of funding are the key barriers of Indian Photovoltaic industry development. [ABSTRACT FROM AUTHOR]

India continues to struggle with the combined effects of water stress alongside poor access to water and sanitation. However, data-driven infrastructure planning is helping to bring a more integrated, sustainable approach to water management and the provision of water, sanitation and hygiene in rural areas. Working with non-governmental organisations in Chhattisgarh and Madhya Pradesh, a project was undertaken to introduce consistent digital data collection, analysis and sharing processes for water resources and water demand data. Key outputs from the project included a toolkit and mobile application, the wider adoption of which could transform rural water access. [ABSTRACT FROM AUTHOR]

The project Comparing Climate Change Policy Networks has teams in 15 countries conducting equivalent data collection on media framing of climate change as well as networks of coalition-building among engaged organizations. This paper reports on the first phase of the project, comparing how the national news media frame climate change in China, India, the US, Japan, South Korea, Taiwan, Brazil, the UK and Sweden. [ABSTRACT FROM AUTHOR]

When based on the zones of available water in storage, hedging has traditionally used a single hedged zone and a constant rationing ratio for constraining supply during droughts. Given the usual seasonality of reservoir inflows, it is also possible that hedging could feature multiple hedged zones and temporally varying rationing ratios but very few studies addressing this have been reported especially in relation to adaptation to projected climate change. This study developed and tested Genetic Algorithms (GA) optimised zone-based operating policies of various configurations using data for the Pong reservoir, Himachal Pradesh, India. The results show that hedging does lessen vulnerability, which dropped from ≥60% without hedging to below 25% with the single stage hedging. More complex hedging policies, e.g. two stage and/or temporally varying rationing ratios only produced marginal improvements in performance. All this shows that water hedging policies do not have to be overly complex to effectively offset reservoir vulnerability caused by water shortage resulting from e.g. projected climate change. [ABSTRACT FROM AUTHOR]

Developing countries like India are increasingly under pressure to sign a binding emissions treaty to avert catastrophic climatic change. However, developing countries have argued that any international agreement should be based on historic responsibility, and per-capita emissions, with developed countries taking the primary responsibility to mitigate, and fund adaptation measures in other countries. Recently, India has shifted its position in international negotiations to indicate it may be willing to sign binding mitigation agreement in future, and domestically renewed its commitment to renewable energy through the Prime Minister's eight National Action Plans, and establishing Indian Network for Climate Change Assessment. This grounded theory study investigated the evolution of climate change discourse in India by analyzing 25 interviews of Indian climate policy elites, including scientists, energy policy experts, top government officials, and other NGO organizational members working actively in the field. Our analysis suggests that India's increasing vulnerability to climate change, taken together with concerns about domestic energy security, and the international aspirations of Indian government, have set the stage for a substantial shift in Indian climate change discourse, with broader implications for environmental governance, and sustainable development imperative. [ABSTRACT FROM AUTHOR]

The retail sector in India is experiencing a shift from an industry dominated by small grocers serving the needs of local markets to one characterized by chain retailers. The conditions of resistance by small retailers against retail liberalization however, are very much affected by the global climate and local particularities, amidst the changing nature of governance. The study employed Williams' (1989) 'militant particularisms' and Foucault's (1991) concept of governmentality to conceptualize the narratives of resistance by the small retailers in a traditional market in India. The Aminabad Market in a metro city in northern India provided a unique opportunity to do ethnography of ongoing resistance against chain retailing. The study explores the protests and militant particularisms that are constituted in 'local' market conditions. To this purpose, the study examines small retailers' participation, their resistance narratives, and the conditions preventing the universalizaton of resistance. ..PAT.-Unpublished Manuscript [ABSTRACT FROM AUTHOR]