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This paper reviews and assesses India's energy policy in the context of its commitment to achieve the target of net-zero carbon emissions by 2070. It emphasizes the central role of green electrification, particularly through the expansion of solar power capacity. It discusses policies outside the energy sector that need to be part of a strategy of achieving this target, including the use of information technology, infrastructure development, and transportation. Furthermore, it examines possible policy options for accelerating the target date to 2050, especially with the use of carbon capture to manage the transition from the current heavy use of coal. The paper also discusses the possible financial and growth implications of various strategy options, arguing that feasible external financing commitments can allow India to achieve net-zero goals without sacrificing economic growth. [ABSTRACT FROM AUTHOR]

Despite great efforts in facing climate change challenges—especially by the UN Paris Agreement, the 2030 Agenda for Sustainable Development, and companion documents (Sendai Framework for Disaster Risk Reduction and the New Urban Agenda)—generally speaking, current policies on climate change and Disaster Risk Reduction at both national and international levels have not yet been centrally positioned in respective plans for heritage, and cultural heritage still does not have a central role in such policies. The main aim of this paper is to explore the culture/cultural heritage's complex interrelationship with climate change by delving into critical issues/gaps and recommendatory encounters of heritage framework in climate change framework and vice versa at the international level and an example in India. Accordingly, this paper showcases a type of Indian Water Infrastructure Heritage; Stepwells, traditional underground water management systems in arid western India which, unfortunately, with modernization, lost their original function and hence, nowadays, most are abandoned. Thus, by the situational analysis of such an Indian urban-scale type of heritage, this paper concludes with critical reflections on the necessity of the systemic relationship among sustainability, conservation, and development, especially in practice and the need to recall the notion of sustainability again. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau is a unique global natural geographical unit with a high altitude and fragile ecology, where land cover change has been affecting its regional ecological security and sustainable development. The plateau covers nine countries with different variations in climate change and human activities, which cause significant spatial variations in its land cover change. This paper uses land cover data to reveal the spatiotemporal characteristics and multi-country differences in land cover change on the Qinghai–Tibet Plateau from 1992 to 2020 by applying spatiotemporal characteristic analysis and mapping methods. The results show that grassland (65.70%), bare land (15.56%), and woodland (10.25%) are the main types of land cover on the plateau, accounting for 91.51% of the total area. The interconversion of bare land and grassland was dominant in 1992–2020, with an area share of 67.83%. The turning point year of grassland change occurred in 2015. The grassland area increased by 6312 km2 in 1992–2015, while it decreased by 14,646 km2 in the plateau in 2015–2020. The areas of woodland, cropland, and water increased by 2.77%, 5.85%, and 7.57%, respectively, and the area of built-up land increased from 299.17 km2 to 1206.29 km2. Overall, a warming and wetting trend of the climate in the Qinghai–Tibet Plateau has driven the expansion of natural vegetation and water in the central plateau within China, with its natural vegetation area increasing by 0.11%. However, the development of regional warming and drying caused local grassland degradation, where Kyrgyzstan and India within the Qinghai–Tibet Plateau experienced the most prominent vegetation degradation. Human activities are relatively frequent in the Qinghai–Tibet Plateau within China and India, causing higher growth rates of built-up land and cropland than in other countries. The establishment of reserves and effective forest management policies have led to significant increases in woodland areas in China and Nepal within the plateau, while weak forest management and limited investment in forest conservation have led to high rates of deforestation in India and Myanmar. Accelerated temperature rises and regional differences in precipitation are the main drivers of large-scale land cover change on the plateau and differences in human activities and land use policies are responsible for the dramatic and diverse localized land cover change. [ABSTRACT FROM AUTHOR]

The year 2022 has served as a recall for the impact that climate change has in the South Asian region, which is one of the most vulnerable regions to climate shock. With a paucity of climate-based and geospatial observational studies in South Asia, this paper (i) links power sectors and carbon dioxide emissions, (ii) maps nitrogen dioxide density across three countries (Pakistan, India, and Bangladesh), (iii) understands electricity generation trends and projects weather changes through 2100. We monitored data monitored between 1995 and 2021. The following databases were used: the International Energy Agency, the World Bank, the UN Food and Agricultural Organization. Raw data was obtained for climate indicators, which were entered into Microsoft Excel. Geospatial trends were generated in the ArcGIS geostatistical tool by adopting the ordinary kriging method to interpolate and create continuous surfaces depicting the concentration of nitrogen dioxide in the three countries. We found increased usage of coal and fossil fuels in three countries (Pakistan, India, and Bangladesh). Both were significant contributors to carbon dioxide emissions. The geographic localities in South Asia were densely clouded with nitrogen dioxide as reported with the tropospheric column mapping. There are expected to be increased days with a heat index >35 °C, and consecutive dry days from 2020 and 2100. We also found increased chances of flooding in certain regions across the three countries. This study monitored climate change indicators and projects between 1995 and 2100. Lastly, we make recommendations to improve the relationship of the environment and living beings.

The Himalayan region is a fragile high mountain landscape where the population experiences acute vulnerability within a complex coupled human-natural system due to environmental, social, and economic linkages. The lack of significant regional and spatial knowledge of multi-faceted vulnerabilities hinders any potential recommendations to address these vulnerabilities. We systematically reviewed the literature to recommend mitigation interventions based on the region's socio-economic and ecological vulnerability research to date. We applied the PRISMA (Preferred Reporting of Items for Systematic Review and Meta-Analysis) criteria to search for results from four comprehensive databases. For our assessment, we compiled a final sample ( n = 59) of vulnerability research papers to examine the vulnerability types, spatial variation, assessment methodology, and significant drivers of change. Our study represented all Himalayan countries, namely, India, Nepal, Pakistan, China, and Bhutan. More than half of the vulnerability studies were conducted in the central Himalayan region, a quarter in the western Himalayas, and a few in the eastern Himalayas. Our review revealed that the primary drivers of change were climate change, land use/land cover, and glacial lake formation. The vulnerability assessments in the Himalayan region primarily used social science methods as compared to natural science methods. While the vulnerability studies seldom assessed mitigation interventions, our analysis identified fourteen recommendations. The recommended interventions mainly included policy interventions, livelihood improvement, and adaptation measures. This study emphasized that sustainable development requires cross-sectoral interventions to manage existing resources and mitigate the confronting vulnerabilities of the region.

Simple Summary: Authentic species-level identification is key to many fields of entomology, especially insect pest management and biosecurity. Bamboo, known as "Poor Man's Timber" and "Green Gold", is one of the fastest growing plants on earth. Bamboo and food grain crops (rice and wheat, for example) belong to the same family (Poaceae), so there is a chance of host shift because of global climate change and extensive cultivation. In the present study, the colour polymorphism of the bamboo-feeding leafhopper Mukaria splendida is highlighted, along with additional geographical distribution records. The integration of the morpho-molecular data confirmed that all the colour morphs belonged to the same species, M. splendida. The leafhopper species, Mukaria splendida Distant, is economically important due to itsstatus as a pest on bamboo and was recently reported to bea vector for phytoplasmal disease. Morphological identification is often difficult and requires a high level of taxonomic expertise, with misidentifications causing problematic false-positive/negative results. In this paper, colour polymorphism was recorded in the bamboo-feedingleafhopper M. splendida (Distant, 1908), which is a major insect pest in the bamboo ecosystem based on explorations conducted in different locations of India. Ten morphs were identified for each sex of M. splendida Distant based on the colour pattern on the pronotum and forewings. However, in view of the economic importance of the species, the morphological studies were integrated with the molecular data for the accurate identification of the species. The morphological characteristics and sequence results of the amplified product of the mitochondrial cytochrome oxidase subunit I (mtCOI) gene confirmed that all the morphs were M. splendida and the pairwise distance matrix showed a negligible genetic distance in the COI mtDNA gene. Simulated future predictions, along with detailed notes on the colour polymorphic forms with illustrations, and additional distribution records as well as thebiology of M. splendida were discussed in light of the available literature, all of which will aid the authentic identification of this species. [ABSTRACT FROM AUTHOR]

Antibiotic resistance is a pressing global, one health and planetary health challenge. Links between climate change, antibiotic use, and the emergence of antibiotic resistance have been well documented, but less attention has been given to the impact(s) of earth systems on specific bacterial livestock diseases at a more granular level. Understanding the precise impacts of climate change on livestock health—and in turn the use of antibiotics to address that ill-health—is important in providing an evidence base from which to tackle such impacts and to develop practical, implementable, and locally acceptable solutions within and beyond current antibiotic stewardship programs. In this paper, we set out the case for better integration of earth scientists and their specific disciplinary skill set (specifically, problem-solving with incomplete/fragmentary data; the ability to work across four dimensions and at the interface between the present and deep/geological time) into planetary health research. Then, using a case study from our own research, we discuss a methodology that makes use of risk mapping, a common methodology in earth science but less frequently used in health science, to map disease risk against changing climatic conditions at a granular level. The aim of this exercise is to argue that, by enabling livestock farmers, veterinarians, and animal health observatories to better predict future disease risk and risk impacts based on predicted future climate conditions, earth science can help to provide an evidence base from which to influence policy and develop mitigations. Our example—of climate conditions' impact on livestock health in Karnataka, India—clearly evidences the benefit of integrating earth scientists into planetary health research. [ABSTRACT FROM AUTHOR]

Effective management of water resources is crucial for sustainable development in any region. When considering computer-aided analysis for resource management, geospatial technology, i.e., the use of remote sensing (RS) combined with Geographic Information Systems (GIS) proves to be highly valuable. Geospatial technology is more cost-effective and requires less labor compared to ground-based surveys, making it highly suitable for a wide range of agricultural applications. Effectively utilizing the timely, accurate, and objective data provided by RS technologies presents a crucial challenge in the field of water resource management. Satellite-based RS measurements offer consistent information on agricultural and hydrological conditions across extensive land areas. In this study, we carried out a detailed analysis focused on addressing agricultural water management issues in India through the application of RS and GIS technologies. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we systematically reviewed published research articles, providing a comprehensive and detailed analysis. This study aims to explore the use of RS and GIS technologies in crucial agricultural water management practices with the goal of enhancing their effectiveness and efficiency. This study primarily examines the current use of geospatial technology in Indian agricultural water management and sustainability. We revealed that considerable research has primarily used multispectral Landsat series data. Cutting-edge technologies like Sentinel, Unmanned Aerial Vehicles (UAVs), and hyperspectral technology have not been fully investigated for the assessment and monitoring of water resources. Integrating RS and GIS allows for consistent agricultural monitoring, offering valuable recommendations for effective management. [ABSTRACT FROM AUTHOR]

This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India. [ABSTRACT FROM AUTHOR]

Participatory approaches within development programs involving common-pool resources are intended to revive a community's role in managing these resources. Certainly, to ensure the successful and equitable use of such resources, community participation is essential. However, in many cases, attempts at applying a participatory approach often fail to genuinely engage all subgroups within a community due to assumptions of homogeneity and a lack of understanding of the deep socio-political divisions between people. As a result, development programs can be plagued by these pre-existing power relations, potentially resulting in tokenistic community participation and the continuation of elite capture of natural resources to the same extent or worse than before a development program has begun. This in turn can negatively impact good governance and the fair distribution of a common pool resource. This paper explores the use of participatory approaches in water projects, assessing to what degree power relationships impact water management programs. Using a qualitative approach, the paper identifies key challenges of participatory water governance through case studies from Turkey, India, and Sri Lanka, exploring: lack of social trust, elite capture of participatory processes, power heterogeneity and imbalances at the micro-level, and a lack of inclusive participation in decision-making. Based on the analysis of these case studies, this paper argues that it is essential for participatory development interventions to understand socio-political power relations within a community—an inherently complex and contested space. The so-called "exit strategy" of a community project play a key role to decide the project sustainability that grants the "community ownership" of the project. Such an understanding can bring about greater success in development interventions attempting to address water-related issues. [ABSTRACT FROM AUTHOR]

This paper presents findings from a process aimed at identifying the climate linkages of non-climate focused environment and development projects in India. Findings from four case studies based on workshops using participatory systems thinking are summarized. These climate adjacencies are documented as systems stories using the tools of systems thinking—behavior over time graphs and causal loop diagrams. These place-based stories highlight how the environment and development projects have linkages with climate change mitigation and adaptation. An attempt has been made to convert one of the systems stories into a computable simulation model using system dynamics modelling. A small concept model has been created thus and used to perform simulation runs. Four scenarios have been generated and the results discussed. Our learning from converting feedback maps into stock-flow models is presented. The insights generated from interpreting the feedback maps and simulation results are also presented. These insights are then compared and the benefits of simulation evaluated. The paper highlights the need to document climate linkages of non-climate-focused development projects and the benefit of converting systems stories into simulation models for developing operational insights. The important role such methods can play in developing capacities for enhancing climate action is also discussed. [ABSTRACT FROM AUTHOR]

This study aimed to utilize hybrid physics-based models that allow for a comprehensive evaluation of how solar–meteorological variables influence the fraction of absorbed photosynthetically active radiation (FAPAR). By integrating both physical and statistical approaches, these models provided a novel perspective on understanding the complex relationship between solar radiation and FAPAR dynamics. The integration of URE and CLC in studying ecosystem efficiency in the nations of China and India is crucial, owing to their interdependent nature. To achieve this, the coupled model intercomparison project phase 6 (CMIP6) was utilized, which involved interpolating data from the most recent five GCMs from the six-phase CMIP6. By integrating advanced modeling techniques with observational data, this innovative approach enabled a holistic assessment of the intricate connections between urban development, climate dynamics, and the productivity of surrounding ecosystems in these regions. The reported decline in FAPAR productivity in China and India highlights the growing concern over the impact of climate change on the health and resilience of vegetation. China experienced negative changes of −1.425, −0.414, and −0.018, while India reported negative changes of −2.463, 2.199, and 2.915 under different scenarios. Interestingly, despite these variations, both countries observed similar tidal variations in their seasonal bases, suggesting a consistent pattern in the fluctuations of vegetation productivity throughout the year. The authors of this study collected and analyzed extensive data on CLC and URE in order to investigate their impact on FAPAR fluctuations in China and India. The higher impact of URE compared to CLC in terms of effective contributions suggests that URE plays a crucial role in shaping the atmospheric physics of both China, accounting for 45.26%, and India, registering 33.95%. Conversely, the effects of CLC and PAR residual factor (PRF) were more pronounced in India compared to China, with impacts of 8.21% and 53.03% compared to 4.21% and 46.70%, respectively. [ABSTRACT FROM AUTHOR]

In recent years, growing water insecurity in the Himalayan region has attracted new scientific research and fresh attention on policy. In this paper, we synthesize field research evidence from a sample of five Himalayan cities—three in Nepal and two in the western Indian Himalayas—on various forms of water insecurity and cities' responses to such challenges. We gathered evidence from a field research conducted in these cities between 2014 and 2018. We show how different types of Himalayan towns (mainly hilltop, foot hill, river side, touristic, and regional trading hub) are struggling to secure water for their residents and tourists, as well as for the wider urban economy. We found that even though the region receives significant amounts of precipitation in the form of snow and rainfall, it is facing increasing levels of water insecurity. Four of the five towns we studied are struggling to develop well-performing local institutions to manage water supply. Worse still, none of the cities have a robust system of water planning and governance to tackle the water challenges emerging from rapid urbanization and climate change. In the absence of a coordinated water planning agency, a complex mix of government, community, and private systems of water supply has emerged in the Himalayan towns across both Nepal and India. There is clearly a need for strengthening local governance capacity as well as down-scaling climate science to inform water planning at the city level. [ABSTRACT FROM AUTHOR]

This study estimates the radiative forcing by biomass burning and dust aerosols over the Indian subcontinent, with emphasis on the Indo-Gangetic Plains (IGP) during the period from January 2021 to April 2021, based on multiple satellite and reanalysis datasets. In this respect, we used retrievals from the Moderate Resolution Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) system, as well as reanalysis data from the Goddard Earth Observing System, version 5 (GEOS-5), the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), the Copernicus Atmosphere Monitoring Service (CAMS), and ERA-Interim. According to the MERRA-2 and the CAMS, the highest black carbon (BC) concentrations in January 2021 were 7–8 µg m−3, which were significantly lower than measurements performed in main cities along the IGP, such as Patiala, Delhi, and Kanpur. The meteorological data analysis accompanied by the CALIPSO lidar measurements showed that the vertical distribution of total attenuated backscatter (TAB) could reach altitudes of up to ~4–5 km and could be transported over the central Himalayan region. The spatial-averaged daily aerosol radiative forcing (ARF) values over the Indian subcontinent from January 2021 to April 2021 were found to range from −51.40 to −6.08 W m−2 (mean of −22.02 ± 9.19 W m−2), while on a monthly basis, the ARF values varied widely, from −146.24 to −1.63 W m−2 (mean of −45.56 ± 22.85 W m−2) over different parts of the study region. Furthermore, the spatial-averaged daily BC radiative forcing ranged from −2.23 to −0.35 (−1.01 ± 0.40 W m−2), while it varied from −15.29 to −0.31 W m−2 (−2.46 ± 2.32 W m−2) over different regions of southern Asia, indicating a rather small contribution to the total aerosol radiative effect and a large presence of highly scattering aerosols. Our findings highlight the importance of growing biomass burning, in light of recent climate change and the rapid decline in air quality over North India and the Indian Ocean. [ABSTRACT FROM AUTHOR]

Climate-induced changes in precipitation and temperature can have a profound impact on watershed hydrological regimes, ultimately affecting agricultural yields and the quantity and quality of surface water systems. In India, the majority of the watersheds are facing water quality and quantity issues due to changes in the precipitation and temperature, which requires assessment and adaptive measures. This study seeks to evaluate the effects of climate change on the water quality and quantity at a regional scale in the Nagavali and Vamsadhara watersheds of eastern India. The impact rainfall variations in the study watersheds were modeled using the Soil and Water Assessment Tool (SWAT) with bias-corrected, statistically downscaled models from Coupled Model Intercomparison Project-6 (CMIP-6) data for historical (1975–2014), near future (2022–2060), and far future (2061–2100) timeframes using three Shared Socioeconomic Pathways (SSP) scenarios. The range of projected changes in percentage of mean annual precipitation and mean temperature varies from 0 to 41.7% and 0.7 °C to 2.7 °C in the future climate, which indicates a warmer and wetter climate in the Nagavali and Vamsadhara watersheds. Under SSP245, the average monthly changes in precipitation range from a decrease of 4.6% to an increase of 25.5%, while the corresponding changes in streamflow and sediment yield range from −11.2% to 41.2% and −15.6% to 44.9%, respectively. Similarly, under SSP370, the average monthly change in precipitation ranges from −3.6% to 36.4%, while the corresponding changes in streamflow and sediment yield range from −21.53% to 77.71% and −28.6% to 129.8%. Under SSP585, the average monthly change in precipitation ranges from −2.5% to 60.5%, while the corresponding changes in streamflow and sediment yield range from −15.8% to 134.4% and −21% to 166.5%. In the Nagavali and Vamsadhara watersheds, historical simulations indicate that 2438 and 5120 sq. km of basin areas, respectively, were subjected to high soil erosion. In contrast, under the far future Cold-Wet SSP585 scenario, 7468 and 9426 sq. km of basin areas in the Nagavali and Vamsadhara watersheds, respectively, are projected to experience high soil erosion. These results indicate that increased rainfall in the future (compared to the present) will lead to higher streamflow and sediment yield in both watersheds. This could have negative impacts on soil properties, agricultural lands, and reservoir capacity. Therefore, it is important to implement soil and water management practices in these river basins to reduce sediment loadings and mitigate these negative impacts. [ABSTRACT FROM AUTHOR]

Children in developing countries such as India will experience severe consequences of climate change. Primary school students, in particular, are the most vulnerable to extreme weather conditions, such as heat waves intensifying due to climate change. This will adversely impair their development, well-being, and learning outcomes. However, significant research gaps exist in understanding and mitigating children's vulnerabilities. There is an urgent need for a deeper understanding of the impact of heat waves on children's health and well-being in India. Further, the discussion on the state of heat safety in Indian primary schools is limited. This study addresses these gaps by surveying 335 primary school teachers in seven Indian cities. The data gathered from the field survey offers a better understanding of classroom experiences and challenges encountered by children and teachers during heat waves. It underscores several aspects of students' vulnerability to heat exposure and its adverse impact on their health, such as absence from school, physical symptoms of heat distress, etc. Furthermore, it highlights the pressing need for classroom heat risk management in light of climate change and makes several policy prescriptions in primary schools. [ABSTRACT FROM AUTHOR]

We investigated rainfall patterns over India for the period from 1951 to 2010 and predicted changes for the next century (2051–2100) with an assumed 4K warming from large ensemble experiments (190 members). We focused on rainfall patterns during two periods of present-day climate (1951–1980 and 1981–2010) and their projected changes for the near and far future (2051–2080 and 2081–2110). Our analysis found that the northeastern region of India and some southern regions received higher rainfall during the period of 1951–2010, which is consistent with daily observations from the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE). In the warming climate, rainfall events in India are predicted to carry more precipitation, with the northeast and southern regions experiencing stronger rainfall events. The frequency and intensity of these events (with more than 20 mm of rainfall per day, on average) are also expected to increase. Overall, our study suggests that water-related disasters such as flooding and landslides could be much worse in India in the future due to climate warming. [ABSTRACT FROM AUTHOR]

Hydrological reaction to climate change anticipates water cycle alterations. To ensure long-term water availability and accessibility, it is essential to develop sustainable water management strategies and better hydrological models that can simulate peak flow. These efforts will aid in water resource planning, management, and climate change mitigation. This study develops and compares Sacramento, Australian Water Balance Model (AWBM), TANK, and SIMHYD conceptual models to simulate daily streamflow at Rajegaon station of the Pranhita subbasin in the Godavari basin of India. The study uses daily Indian Meteorological Department (IMD) gridded rainfall and temperature datasets. For 1987–2019, 70% of the models were calibrated and 30% validated. Pearson correlation (CC), Nash Sutcliffe efficiency (NSE), Root mean square error (RMSE), and coefficient of determination (CD) between the observed and simulated streamflow to evaluate model efficacy. The best conceptual (Sacramento) model selected to forecast future streamflow for the SSP126, SSP245, SSP370, and SSP585 scenarios for the near (2021–2040), middle (2041–2070), and far future (2071–2100) using EC-Earth3 data was resampled and bias-corrected using distribution mapping. In the far future, the SSP585 scenario had the most significant relative rainfall change (55.02%) and absolute rise in the annual mean temperature (3.29 °C). In the middle and far future, the 95th percentile of monthly streamflow in the wettest July is anticipated to rise 40.09% to 127.06% and 73.90% to 215.13%. SSP370 and SSP585 scenarios predicted the largest streamflow increases in all three time periods. In the near, middle, and far future, the SSP585 scenario projects yearly relative streamflow changes of 72.49%, 93.80%, and 150.76%. Overall, the findings emphasize the importance of considering the potential impacts of future scenarios on water resources to develop effective and sustainable water management practices. [ABSTRACT FROM AUTHOR]

Given the interdependence of climate change (CLC) and urban expansion (URE) on ecosystem productivity in China and India, hybrid physics-based models were fitted in this study to evaluate the effects of these variables on photosynthetically active radiation (PAR). This was accomplished by interpolating the most recent five general circulation models (GCMs) from coupled model intercomparison project phase 6 (CMIP6) into the CMIP6 multi-ensemble model. The potential of PAR is projected to increase by 0.001 to 2.077% in China and by 0.002 to 6.737% in India, on a seasonal and annual basis, if the warming is kept at 1.5 °C from now until the end of this century. The effects of CLC and URE on the changes in PAR in China and India were investigated, and URE had a greater impact than CLC when compared to effective contributions, with 49.47% for China and 28.41% for India in the entire case scenario. In contrast, CLC and PAR residual factor (PRF) have a greater impact in India than in China, with effects of 13.79% and 57.79% compared to 0.89% and 49.64%, respectively. Preferences for exotic, high-productivity plant species, irrigation, CO2 fertilization, and nitrogen deposition are suggested as measures for replenishing PAR in both countries. [ABSTRACT FROM AUTHOR]

Inappropriate agricultural practices consume more input energy and emit higher greenhouse gases (GHGs) which cause global warming and climate change, thereby threatening environmental sustainability. To identify energy and carbon-efficient varieties and nutrient management practices, the present study was undertaken during the kharif season of 2018 and 2019 in a split-plot design with three varieties of fodder maize (African Tall, J-1006 and P-3396) and four nutrient management practices such as N0: Absolute control, N1: 100% recommended dose of fertilizers (RDF), N2: 75% RDF + plant growth promoting rhizobacteria (PGPR) + Panchagavya spray and N3: 50% RDF + 25% farmyard manure (FYM) + PGPR + Panchagavya spray). Results indicated that variety J-1006 and applying 75% RDF + PGPR + Panchagavya spray produced significantly higher dry fodder yield. Among the varieties, J-1006 recorded the highest total energy output (224,123 MJ ha−1), net energy (211,280 MJ ha−1), energy use efficiency (17.64), energy productivity (0.98 kg MJ−1), energy profitability (16.64), and lowest specific energy (1.03 MJ ha−1). Regarding nutrient management, 75% RDF + PGPR + Panchagavya spray fetched the highest total energy output (229,470 MJ ha−1) and net energy (215,482 MJ ha−1). However, energy use efficiency, energy productivity, and energy profitability were significantly higher with integrated nutrient management (N2 and N3) over 100% RDF. Concerning the carbon estimation, J-1006 resulted in a significantly higher carbon output (5479 kg CE ha−1), net carbon gain (5029 kg CE ha−1), carbon efficiency (12.46), carbon sustainability index (11.46), and significantly lower carbon footprint per unit yield (CFy) (131.3 kg CO2-e Mg−1). For nutrient management, the application of 75% RDF + PGPR + Panchagavya spray showed significantly higher carbon output (5609 kg CE ha−1) and net carbon gain (5112 kg CE ha−1). However, significantly higher carbon efficiency, carbon sustainability index, and lower CFy were reported with integrated nutrient management over 100% RDF. Overall, selecting the J-1006 variety and applying 75% RDF + PGPR + Panchagavya spray for fodder maize cultivation could be the most productive in terms of dry fodder production, energy, and carbon efficiency approach. [ABSTRACT FROM AUTHOR]

Policymakers and environmental scientists have proposed numerous measures toward achieving a sustainable environment. Some of these measures include the efficient use of energy and a clean energy transition. This study empirically investigates the role of non-renewable energy efficiency and renewable energy utilization in driving environmental sustainability in India over the period from 1965 to 2018. Using the approach of the Dynamic Autoregressive Distributed Lag (DyARDL) simulations, the empirical evidence shows that non-renewable energy efficiency and renewable energy utilization promote environmental sustainability through an increase in the load capacity factor. The effects of financial development and trade impede environmental sustainability through a decrease in the load capacity factor. The results further show that the relationship between income and load capacity factor is characterized by an inverted U-shape. This suggests that the load capability curve (LCC) hypothesis is not valid for India. Given the overall findings of this study, it is suggested that policymakers should promote energy efficiency and renewable energy technologies as the ultimate policy measure to mitigate the accumulation of CO2 emissions and other significant climatic changes in India. [ABSTRACT FROM AUTHOR]

This study was carried out in the Tarai region of Uttarakhand, India to estimate the carbon stock and sequestration potential of Dalbergia latifolia and Melia composita plantations of different ages (4 and 6 years old). A total of 14 regression equations using one variable, dbh (diameter at breast height), were primarily selected for both of the tree species component-wise. Tree density was 880 and 960 individuals ha−1 in D. latifolia and M. composita monoplantations, respectively. These equations were statistically significant (p < 0.01, p < 0.05) at 95% confidence interval. The total biomass of trees, shrubs, and herbs at the different-aged plantations varied from 68.86 to 145.14 Mg ha−1, 1.29 to 2.41 Mg ha−1, and 1.14 to 3.68 Mg ha−1, respectively. Among the studied plantations, the maximum total biomass of 145.14 Mg ha−1 was recorded at the M. composita plantation (7 years old), resulting in the maximum carbon stock of 68.94 Mg C ha−1. Total NPP ranged from 5.6 Mg ha−1yr−1 to 16.01 Mg ha−1yr−1 for both plantations of different ages. The carbon sequestration in the M. composita 7-year-old plantation was 7.6 Mg Cha−1yr−1. Quantified carbon sequestration among different tree components must be considered for tree-level inventories for carbon trading schemes when determining the long-term carbon pools under the Paris agreement. [ABSTRACT FROM AUTHOR]

Climate change, land degradation, and desertification lead to the loss of carbon present in the soil and plants. The carbon dioxide (CO2) concentration in the atmosphere has reached 412 ppm. This is a rise of 47% since the start of the industrial period, when the concentration was close to 280 ppm. Therefore, the sequestration of carbon from the atmosphere to earth is the need of the hour. Many scientists have suggested agroforestry as a potent instrument for climate change mitigation as well as to fetch lucrative benefits. The Indian government is also promulgating tree-based systems for increasing tree cover up to 33% of the total geographical area to mitigate climate change. Therefore, the expansion of the commercial agroforestry system of fast-growing tree species producing higher biomass could be a sustainable and ecologically benign technique to sequester carbon, increase green cover, and improve the financial status of farmers. This review highlights the commercial agroforestry systems, biomass and carbon sequestration potential, and case studies of poplar and eucalyptus. The species such as poplar (Populus deltoides), nilgiri (Eucalyptus spp.), subabul (Leucaena leucocephala), tree of heaven (Ailanthus excelsa), willow (Salix spp.), malabar neem (Melia dubia), cadamba (Neolamarckia cadamba), and white teak (Gmelina arborea) are the suitable tree species for carbon sequestration under agroforestry. Among these species, poplar and eucalyptus are major agroforestry tree species that have been adopted by millions of farmers in India since the 1990s. Indo-Gangetic plains are considered the birthplace of commercial or industrial agroforestry, as poplar and eucalyptus are widely planted. This review reports that poplar and eucalyptus have the potential to sequester carbon stock of 212.7 Mg C ha−1 and 237.2 Mg C ha−1, respectively. Further, the net carbon sequestration rate in poplar and eucalyptus was 10.3 and 12.7 Mg C ha−1 yr−1, respectively. In conclusion, the commercial agroforestry system was very successful in the Indo-Gangetic regions of the country but needs further expansion with suitable compatible crops in different parts of the country. [ABSTRACT FROM AUTHOR]

The maintenance of people's lifestyle against global climate change, exhaustion of groundwater, depletion of minerals, and water scarcity has instigated the recycling and reuse of water from unlikely sources. This situation has motivated researchers to develop effective technologies for treating wastewater, enabling its reuse. Water security has been ensured in myriad, highly populated regions through large-scale centralized treatment facilities. The development and implementation of small-scale, renewable-energy-based, decentralized, on-site treatment methodologies ensure water sustainability in rural areas, where centralized treatment facilities are impractical for application. This review article focuses on the recently reported low-cost purification techniques for recycling wastewater generated by single and community-based households in sparsely populated areas. Here we propose treatment technologies for efficient waste management that can be easily integrated in the upcoming years to the lavatories built under the Swachh Bharat Mission (SBM), a momentous cleanliness campaign that has been successfully implemented by the Government of India (GOI). Specifically, we suggest an electrochemical (EC) method to treat the supernatant of the Blackwater (BW) to produce purified non-potable water for reuse in diverse purposes. The EC technique does not require external chemicals for treatment and can be powered by sustainable technologies (like solar panels), thus reducing the treatment cost. Subsequently, vermicomposting, microwave, biogas, and phycoremediation methods are considered to treat the solid sludge to produce value-added products such as enriched organic fertilizer for agriculture and biofuel. The above methods also ensure the satisfactory reduction in Biochemical Oxygen Demand (BOD) (>85%) and Chemical Oxygen Demand (COD) (81–91%) and the complete removal of pathogens and other harmful pollutants. Finally, the novel treatment techniques discussed here are not only limited to rural areas of India but can be implemented in any rural area of the world. [ABSTRACT FROM AUTHOR]

Climate change is often linked with record-breaking heavy or poor rainfall events, unprecedented storms, extreme day and night time temperatures, etc. It may have a marked impact on climate-sensitive sectors and associated livelihoods. Block-level weather forecasting is a new-fangled dimension of agrometeorological services (AAS) in the country and is getting popularized as a climate-smart farming strategy. Studies on the economic impact of these microlevel advisories are uncommon. Agromet advisory services (AAS) play a critical role as an early warning service and preparedness among the maize farmers in the Parambikulam–Aliyar Basin, as this area still needs to widen and deepen its AWS network to reach the village level. In this article, the responses of the maize farmers of Parambikulam–Aliyar Basin on AAS were analyzed. AAS were provided to early and late Rabi farmers during the year 2020–2022. An automatic weather station was installed at the farmers' field to understand the real-time weather. Forecast data from the India Meteorological Department (IMD) were used to provide agromet advisory services. Therefore, the present study deserves special focus. Social media and other ICT tools were used for AAS dissemination purposes. A crop simulation model (CSM), DSSAT4.7cereal maize, was used for assessing maize yield in the present scenario and under the elevated GHGs scenario under climate change. Our findings suggest that the AAS significantly supported the farmers in sustaining production. The AAS were helpful for the farmers during the dry spells in the late samba (2021–2022) to provide critical irrigation and during heavy rainfall events at the events of harvest during early and late Rabi (2021–22). Published research articles on the verification of weather forecasts from South India are scanty. This article also tries to understand the reliability of forecasts. Findings from the verification suggest that rainfall represented a fairly good forecast for the season, though erratic, with an accuracy score or HI score of 0.77 and an HK score of 0.60, and the probability of detection (PoD) of hits was found to be 0.91. Verification shows that the forecasted relative humidity observed showed a fairly good correlation, with an R2 value of 0.52. These findings suggest that enhancing model forecast accuracy can enhance the reliability and utility of AAS as a climate-smart adaptation option. This study recommends that AAS can act as a valuable input to alleviate the impacts of hydrometeorological disasters on maize crop production in the basin. There is a huge demand for quality weather forecasts with respect to accuracy, resolution, and lead time, which is increasing across the country. Externally funded research studies such as ours are an added advantage to bridge the gap in AAS dissemination to a great extent. [ABSTRACT FROM AUTHOR]

The cold desert ecosystem of the north-western Himalaya in India's is considered to be the most vulnerable region to climate change. In this region, Juniperus macropoda Boisser grows across an altitudinal gradient and is highly sensitive to biotic, physiographic, and climatic factors. Keeping this in view, the present study aimed at ascertaining the response of Juniperus macropoda to changing climatic conditions. To achieve the target of the study, the area (elevation ranges from 3525 to 4150 m asl) was divided into thirteen elevation ranges in the cold desert of Lahaul valley (Himachal Pradesh). The NDVI change detection map from 1994–2017 revealed an increase in the area under the vegetation in the NDVI range of 0–0.15 (240%) and 0.15–0.30 (32%), which indicated the emergence of grasses and new recruits in the area. An increase in the minimum and maximum temperature during monsoon and post-monsoon season correlated positively with the emergence of the recruits in a significant manner. Furthermore, a decline in rainfall during the monsoon period was also recorded which bears a significant positive correlation with the establishment of recruits. However, the increase in the precipitation during winter resulted in a positive effect on the emergence of recruits. The biophysical parameters, like average height, diameter as well as the average age of the dominant trees showed a declining trend with the elevation. However, the age histogram revealed that the majority of the establishment occurred around 1900 and between 1975–2010. The tree ring analysis of J. macropoda revealed that the species is shifting upward at a rate of 3.91 m year−1. Besides this, the area is experiencing the impact of climate change resulting in an increase in the area under vegetation and migration towards the higher elevation, and many species of lichens were also found to invade the bare rock. [ABSTRACT FROM AUTHOR]

The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the subdistrict level and aggregated to monthly, annual, seasonal rainfall totals, and the number of rainy days. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. NonParametric Mann–Kendall test and Spearman's rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen's slope method. For the data influenced by serial correlation, various modified versions of Mann–Kendall tests (pre-whitening, trend-free pre-whitening, bias-corrected pre-whitening, and two variants of variance correction approaches) were applied. A significant increasing summer rainfall trend is observed in six out of 27 stations. Significant decreasing trends are observed at two stations during the southwest monsoon season and at two stations during the northeast monsoon season. To identify the trend change points in the time series, distribution−free cumulative sum test, and sequential Mann–Kendall tests were applied. Two open−source library packages were developed in R language namely, "modifiedmk" and "trendchange" to implement the statistical tests mentioned in this paper. The study results benefit water resource management, drought mitigation, socio−economic development, and sustainable agricultural planning in the region. [ABSTRACT FROM AUTHOR]

Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers' perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers' perceptions about climate change, and farmers' adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers' perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change. [ABSTRACT FROM AUTHOR]

Research characterising the effects of future climate change on the marine environment remains heavily focussed on that of temperate regions and organisms. Furthermore, little is known of these effects on the early life stages of many marine species. Tropical regions are already experiencing an increase in sea surface temperature and decrease in sea surface salinity, conditions favoured by pathogenic bacteria such as Vibrio spp. The early life stages of crabs are known to be particularly vulnerable to both the direct physiological effects of climate change and exposure to harmful microorganisms, yet there are limited data on these effects on juveniles of many tropical crustacean species. This study assessed the metabolic responses of mud crab (Scylla serrata) juveniles to warming and/or freshening in the presence or absence of pathogenic bacteria in southwest India. Juvenile crabs were exposed to either ambient (28 °C/30 PSU) or one of three projected climate change regimes (28 °C/20 PSU (freshening), 32 °C/30 PSU (warming), 32 °C/20 PSU (warming + freshening)) for 10 days, in either the presence or absence of the pathogenic bacteria Vibrio parahaemolyticus. Results show that simulated climate change conditions, especially freshening, caused a significant increase in oxygen consumption rates (MO2), and that these were further increased when juveniles were exposed to V. parahaemolyticus. These results suggest that the effects of future climate change conditions could have significant implications for the conservation of wild stocks and commercial farming of this species in South Asia. [ABSTRACT FROM AUTHOR]

Semi-Arid Tropical (SAT) regions are influenced by climate change impacts affecting the rainfed crops in their productivity and production. Water Footprint (WF) assessment for rainfed crops on watershed scale is critical for water resource planning, development, efficient crop planning, and, better water use efficiency. A semi-arid tropical watershed was selected in lower Krishna river basin having a 4700 ha area in Telangana, India. Soil and Water Assessment Tool (SWAT) was used to estimate the water balance components of watershed like runoff, potential evapotranspiration, percolation, and effective rainfall for base period (1994 to 2013) and different climate change scenarios of Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 for the time periods of 2020, 2050 and 2080. Green and blue WF of rainfed crops viz., maize, sorghum, groundnut, redgram and cotton were performed by considering rainfed, and two critical irrigations (CI) of 30 mm and 50 mm. It indicated that the effective rainfall (ER) is less than crop evapo-transpiration (ET) during crop growing period under different RCPs, time periods, and base period. The green WF under rainfed condition over different RCPs and time periods had decreasing trend for all crops. The study suggested that in the rainfed agro-ecosystems, the blue WF can significantly reduce the total WF by enhancing the productivity through critical irrigation management using on farm water resources developed through rainwater harvesting structures. The maximum significant reduction in WF over the base period was observed 13–16% under rainfed, 30–32% with 30 mm CI and 40–42% with 50 mm CI by 2080. Development of crop varieties particularly in oilseeds and pulses which have less WF and higher yields for unit of water consumed could be a solution for improving overall WF in the watersheds of SAT regions. [ABSTRACT FROM AUTHOR]

River-floodplains support a significant number of small-scale capture fisheries despite having undergone degradation due to human modification of river flows by dams, pollution, and climate change. River fish production is underpinned by the annual flood-pulse and associated environmental changes that act as cues for spawning and dispersal for most species. However, studies on fish stock declines have focused more on overfishing than on hydroclimatic variability. Therefore, understanding how changes in flood-pulse variability influence fishing effort and yields is critical to inform adaptive fisheries' management. We investigated hydroclimatic factors driving flood-pulse variability and fish catch–effort dynamics in India's Ganga River over two decades (2000–2020). We compiled fishers' narratives of changing fish catches through semi-structured interviews to compare them with our observed trends. Flood amplitude showed increasing variability, longer duration, and earlier rise timings, linked to La Niña and El Niño phases. Catches per unit effort were correlated with total yield and effort but did not decline as fishers thought, despite overall declines in yield over time. Hydroclimatic variability was a more significant driver of changing yields than local fishing pressure. Rising uncertainty in fisheries' production, in response to increasing flood-pulse variability and altered flows in the Gangetic Plains, may be affecting fishing behaviour and underlying resource conflicts. [ABSTRACT FROM AUTHOR]

Worldwide, consumption of resources such as water, energy and food continues to rise exponentially despite environmental and climatic change related challenges. Centralized sewerage systems continue to be implemented worldwide despite being very water and energy intensive, and although this is not always the best option for regions facing water scarcity. Deploying the Water-Energy-Food (WEF) Nexus approach, particularly through alternative technology options that can support decentralized water reclamation with integrated resource recovery, can enable resource conservation and more effective management of the WEF security Nexus for local governments with limited capacities. However, a certain pattern of "business as usual" infrastructure development and investment linked to infrastructure shaming continuously reinforces implementation of centralized sewerage systems, thereby hampering deployment of alternative technology options. This study uses two typical case study towns, Shaxi in China and Leh in India, to describe this pattern. The study finds that alternative technology approaches were in place in both towns. Yet after international consulting companies got involved, centralized sewerage systems were implemented despite limited water availability and large segments of the population not having flush toilets. This study discusses management of the WEF security Nexus implications thereof in the context of cities worldwide and a systemic socio-technical transition to a circular economy. [ABSTRACT FROM AUTHOR]

In the Indian monsoon region, frequent cloud cover in the rainy season results in less valid satellite observations during the vegetation growth period, making it difficult to extract land surface phenology (LSP). Even worse, many valid but humid observations were misidentified as clouds in the MODIS cloud mask, causing severe gaps in the LSP product. Using a refined cloud detection approach to separate clear-sky and cloudy observations, this study found that potentially valid observations during the vegetation growth period could be identified. Furthermore, the varied vegetation growth trajectories cannot be well-fitted by a global curve-fitting approach, but can be modelled by using the locally adjusted cubic-spline capping approach, which performed well for any seasonal patterns. Applying this approach, the start of growing season (SOS) was determined with 9.18% of vegetation growth amplitude between the maximum and minimum NDVI to generate the SOS product (2000-2016). The valid percentage of this regional product largely increased from 29.30% to 69.76% compared with the MCD12Q2 product, and its reliability was approximate to that of deciduous broadleaf forest in North America and Europe. This product could serve as a basis for understanding the response of terrestrial ecosystems to the changing Indian monsoon. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the climate- and human-induced impacts on two contrasting river basins in India, specifically, the Ganges and the Godavari. Monthly discharge simulations from global hydrological models (GHMs), run with and without human influence using CMIP5 projections under the framework of the Inter-Sectoral Impact Model Intercomparison Project, are utilized to address the scientific questions related to the quantification of the future impacts of climate change and the historical impacts of human activities on these river basins. The five state-of-the-art GHMs were considered and subsequently used to evaluate the human and climate change impacts on river discharges (seasonal mean discharge and extreme flows) during the pre-monsoon, monsoon, and post-monsoon seasons under the RCP2.6 and RCP8.5 emission scenarios. Results showed that human impacts during the baseline period on long-term seasonal discharge in the Ganges and Godavari River basins for the pre-monsoon season are around 40% and 23%, respectively, and these impacts are stronger than the future climate change impact in the pre-monsoon season for the Ganges basin, whereas, for the Godavari basin, the same pattern is observed with some exceptions. The human impact in the course of the historical period on the pre-monsoon flows of both the Ganges and the Godavari are more significant than on the monsoon and post-monsoon flows. In the near future (2010–39) time slice, the impact of climate change on the streamflow of the Ganges is highest for the post-monsoon season (13.4%) under RCP 8.5 as compared to other seasons. For Godavari, in the near-future period, this impact is highest for the pre-monsoon season (18.2%) under RCP 2.6. Climate-induced changes in both of the basins during both the monsoon and post-monsoon seasons is observed to have a higher impact on future flows than direct human impact-induced changes to flow during the current period. High flows (31.4% and 19.9%) and low flows (51.2% and 36.8%) gain greater influence due to anthropogenic actions in the time of the pre-monsoon season compared to other times of year for the Ganges and Godavari basins, respectively. High flows for the Ganges during the near future time slice are most affected in the monsoon season (15.8%) under RCP 8.5 and, in the case of the Godavari, in the pre-monsoon season (18.4%) under the RCP 2.6 scenario. Low flows of the Ganges during the near-future period are most affected during the monsoon season (22.3%) and for the Godavari, low flows are affected most for the post-monsoon season (22.1%) under RCP 2.6. Uncertainty in the streamflow estimates is more pronounced for the Godavari basin compared to the Ganges basin. The findings of this study enhance our understanding of the natural and human-influenced flow regimes in these river basins, which helps the formation of future strategies, especially for inter-state and transboundary river management. [ABSTRACT FROM AUTHOR]

Increasing energy demand in buildings with a 40% global share and 30% greenhouse gas emissions has accounted for climate change and a consequent crisis encouraging improvement of building energy efficiency to achieve the combined benefit of energy, economy, and environment. For an efficient system, the optimization of different design control strategies such as building space load, occupancy, lighting, and HVAC becomes inevitable. Therefore, interdisciplinary teamwork of developers, designers, architects, and consumers to deliver a high-performance building becomes essential. This review aims to endorse the importance of Building Performance Simulation in the pre-design phase along with the challenges faced during its adaptation to implementation. A morphology chart is structured to showcase the improvement in Building Energy Efficiency by implementing Building Performance Simulation for different building energy systems and by implementing various energy efficiency strategies to achieve the 3E benefit. As a developing nation, India still lacks mass application of Building Performance Simulation tools for improving Building Energy Efficiency due to improper channelizing or implementation; thus, this framework will enable the designers, architects, researchers to contemplate variable building energy optimization scenarios. [ABSTRACT FROM AUTHOR]

The change in future climate will have a prominent impact on crop production and water requirement. Crop production is directly related to climatic variables. Temperature, solar radiation, wind, precipitation, CO2 concentration and other climatic variables dictate crop yield. This study, based on long-term historical data, investigates the patterns and changes in climatic variables (precipitation, temperature, and solar radiation) that would most significantly affect the future crop production in many parts of the world, and especially in India, where most farmers depend on rainfall for rice production. Statistical analyses—box and whisker plot, mean absolute error, Taylor diagram, double mass curve, Mann–Kendall trend test, and projected climate change—were used to assess the significance of the climatic factors for the purpose of agricultural modeling. Large variability in precipitation may cause the flash floods and affect the farming, and at the same time, increase in temperature from baseline period will lead to high water requirement by crops, and may cause drought if rainfall does not occur. Decrease in solar radiation will affect crop growth and development, and thus, would hamper the crop production. The results of this study would be useful in identifying the negative issues arising from climate change in future agricultural practices in Bihar, India. Furthermore, the results can also help in developing management strategies to combat the climate change impact on crop production. [ABSTRACT FROM AUTHOR]

The Himalayas have become synonymous with the hydropower developments for larger electricity demands of India's energy sector. In the Himachal Himalayas though, there are only three large storage dams with more than 1000 megawatts (hereafter MW) capacity that have very serious environmental issues. However, hundreds of small runoff-river hydropower plants across the Himachal Himalayas are a serious threat to the river regimes and Himalayan biota. There are 965 identified hydropower projects (hereafter HPPs) having a potential capacity of 27,436 MW in the Himachal Pradesh as of December 2019 as per the Directorate of Energy of the state. Out of the 965 identified, 216 are commissioned, including less than 5 MW plants, with an installed capacity of 10,596 MW, and were operational by December 2019. Only 58 projects are under construction among the identified with an installed capacity of 2351 MW, 640 projects are in various stages of clearance and investigation with an installed capacity 9260 MW, 30 projects are to be allotted with 1304 MW installed capacity, and merely four projects are disputed/cancelled with installed capacity of 50.50 MW. The large number of HPPs are sanctioned without proper consideration of negative environmental and geohazard impacts on the Himalayan terrestrial biota. In this work, our focus was on the hydropower and climate change impact on the Himalayan river regimes of the Chenab, the Ravi, the Beas, the Satluj, and the Yamuna river basins. We analyzed basin-wise rainfall, temperature, and soil moisture data from 1955 to 2019 to see the trend by applying the Mann–Kendall test, the linear regression model, and Sen's slope test. A basin-wise hazard zonation map has been drawn to assess the disaster vulnerability, and 12 hydropower sites have been covered through the primary survey for first-hand information of local perceptions and responses owing to hydropower plants. [ABSTRACT FROM AUTHOR]

Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future. [ABSTRACT FROM AUTHOR]

The Narmada river basin is a highly regulated catchment in central India, supporting a population of over 16 million people. In such extensively modified hydrological systems, the influence of anthropogenic alterations is often underrepresented or excluded entirely by large-scale hydrological models. The Global Water Availability Assessment (GWAVA) model is applied to the Upper Narmada, with all major dams, water abstractions and irrigation command areas included, which allows for the development of a holistic methodology for the assessment of water resources in the basin. The model is driven with 17 Global Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to assess the impact of climate change on water resources in the basin for the period 2031–2060. The study finds that the hydrological regime within the basin is likely to intensify over the next half-century as a result of future climate change, causing long-term increases in monsoon season flow across the Upper Narmada. Climate is expected to have little impact on dry season flows, in comparison to water demand intensification over the same period, which may lead to increased water stress in parts of the basin. [ABSTRACT FROM AUTHOR]

This study evaluated the potential distribution of the potato tuber moth. This species severely impacts global potato production, especially in China and India, which have the world's largest potato production. We developed two indices considering host plant availability and production in addition to climatic suitability, which was simulated using the CLIMEX model. Thus, three different indices were used to project potential distribution of the potato tuber moth under a climate change scenario: (1) climatic suitability (ecoclimatic index (EI)) (EIM), (2) climatic suitability combined with host plant availability (EIN1), and (3) climatic suitability combined with host plant production (EIN2). Under the current climate, EIM was high in southern India and central to southern China, while EIN1 and EIN2 were approximately 38% and 20% lower than EIM, respectively. Under the Special Report on Emissions Scenario A1B, the potato tuber moth would probably not occur in India, but its distribution could be extended to the north, reaching N47°. The areas with the highest climatic suitability by potato tuber moth based on three indices were Sichuan and Karnataka in response to climate change. These areas require adequate pest control, such as prevention of spread through transport of potato seed or by using cold storage facilities. [ABSTRACT FROM AUTHOR]

Ocean wave energy is one of the cleanest renewable energy sources around the globe, but wave energy varies widely from place to place and from time to time. The long-term variability of wave power at 20 locations in the Indian shelf seas from 1979 to 2018 is described here using the European Centre for Medium-Range Weather Forecasts recently released ERA5 reanalysis hourly data. The variability is calculated on a yearly and monthly basis for the locations based on the coefficient of variation. The annual average wave power varied from 2.3 (at location 16 in the western Bay of Bengal) to 11 kW/m (at location 2 in the northeastern Arabian Sea). Along the western shelf seas, the maximum value of wave power is during the southwest monsoon period and along the east coast, it is during the tropical cyclone period. The standard deviation in wave power is more than the mean value at locations along the northern shelf seas of India, indicating a large variability in wave power in an annual cycle. The west coast locations are shown to have a slightly higher increasing trend with an average of 0.024 kW/m per year, while the increasing trend in wave power of east coast locations is with an average of 0.015 kW/m per year. The study also examines the variation in wave power from deep to shallow water at 2 locations using the wave characteristics obtained from the numerical model SWAN. The electric power output from a few wave energy converters are calculated for all the locations and found that the southernmost locations have a steady and higher percentage of power production. [ABSTRACT FROM AUTHOR]

China and India are not only the two most populous nations on Earth, they are also two of the most rapidly growing economies. Historically, economic and social development have been subsidized by cheap and abundant fossil-fuels. Climate change from fossil-fuel emissions has resulted in the need to reduce fossil-fuel emissions in order to avoid catastrophic warming. If climate goals are achieved, China and India will have been the first major economies to develop via renewable energy sources. In this article, we examine the factors of projected population growth, available fossil-fuel reserves, and renewable energy installations required to develop scenarios in which both China and India may increase per capita energy consumption while remaining on trach to meet ambitious climate goals. Here, we show that China and India will have to expand their renewable energy infrastructure at unprecedented rates in order to support both population growth and development goals. In the larger scope of the literature, we recommend community-based approaches to microgrid and cookstove development in both China and India. [ABSTRACT FROM AUTHOR]

The Shaksgam Valley, located on the north side of the Karakoram Mountains of western China, is situated in the transition zone between the Indian monsoon system and dry arid climate zones. Previous studies have reported abnormal behaviors of the glaciers in this region compared to the global trend of glacier retreat, so the region is of special interest for glacier-climatological studies. For this purpose, long-term monitoring of glaciers in this region is necessary to obtain a better understanding of the relationships between glacier changes and local climate variations. However, accurate historical and up-to-date glacier inventory data for the region are currently unavailable. For this reason, this study conducted glacier inventories for the years 1970, 1980, 1990, 2000 and 2014 (i.e., a ~10-year interval) using multi-temporal remote sensing imagery. The remote sensing data used included Corona KH-4A/B (1965–1971), Hexagon KH-9 (1980), Landsat Thematic Mapper (TM) (1990/1993), Landsat Enhanced Thematic Mapper Plus (ETM+) (2000/2001), and Landsat Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) (2014/2015) multispectral satellite images, as well as digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM), DEMs generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images (2005–2014), and Advanced Land Observing Satellite (ALOS) World 3D 30 m mesh (AW3D30). In the year 2014, a total of 173 glaciers (including 121 debris-free glaciers) (>0.5 km2), covering an area of 1478 ± 34 km2 (area of debris-free glaciers: 295 ± 7 km2) were mapped. The multi-temporal glacier inventory results indicated that total glacier area change between 1970–2014 was not significant. However, individual glacier changes showed significant variability. Comparisons of the changes in glacier terminus position indicated that 55 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) between 1970–2014, and 74 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) during the most recent period (2000–2014). Notably, small glaciers showed higher sensitivity to climate changes, and the glaciers located in the western part of the study site were exhibiting glacier area expansion compared to other parts of the Shaksgam Valley. Finally, regression analyses indicated that topographic parameters were not the main driver of glacier changes. On the contrary, local climate variability could explain the complex behavior of glaciers in this region. [ABSTRACT FROM AUTHOR]

In this study, a linear scaling method, precipitation extended linear scaling (PELS), is proposed to correct precipitation simulated by GCMs. In this method, monthly scaling factors were extended to daily scaling factors (DSFs) to improve the daily variation in precipitation. In addition, DSFs were also checked for outliers and smoothed with a smoothing filter to reduce the effect of noisy DSFs before correcting the GCM’s precipitation. This method was evaluated using the observed precipitation of 21 climate stations and five GCMs in the Jhelum River basin, Pakistan and India, for the period of 1986–2000 and also compared with the original linear scaling (OLS) method. The evaluation results showed substantial improvement in the corrected GCM precipitation, especially in case of mean and standard deviation values. Although PELS and OLS showed comparable results, the overall performance of PELS was better than OLS. After Evaluation, PELS was applied to the future precipitation from five GCMs for the period of 2041–2070 under RCP8.5 and RCP2.6 in the Jhelum basin, and the future changes in precipitation were calculated with respect to 1971–2000. According to average all GCMs, annual precipitation was projected to decrease by 4% and 6% in the basin under RCP8.5 and RCP2.6, respectively. Although two seasons, spring and fall, showed some increasing precipitation, the monsoon season showed severe decrease in precipitation, with 22% (RCP8.5) and 29% (RCP2.6), and even more reduction in July and August, up to 34% (RCP8.5) and 36% (RCP2.6). This means if the climate of the world follows the RCP8.5 and RCP2.6, then there will be a severe reduction in precipitation in the Jhelum basin during peak months. It was also observed that decline in precipitation was higher under RCP2.6 than RCP8.5. [ABSTRACT FROM AUTHOR]