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The present study provides an assessment of the distribution of key Non-Timber Forest Product species in India, namely Aegle marmelos (L.) Correa, Buchanania lanzan Spreng., Madhuca longifolia (J. Koenig ex L.) J. F. Macbr., Phyllanthus emblica L. and Terminalia bellirica (Gaertn.) Roxb. The suitable habitat was analyzed under current climate scenarios and subsequently, the future distribution (2050s and 2070s) was mapped under RCP 2.6 and 8.5 scenarios, along with the past distribution (mid-Holocene, ~ 6000 cal year BP) using the MaxEnt species distribution model. The distribution of all species is primarily driven by key bioclimatic factors, including annual precipitation (Bio_12), mean annual temperature (Bio_1), isothermality (Bio_3) and precipitation of the coldest quarter (Bio_19). The results indicate that the present distribution of these species is mainly centred in the Western Ghats regions, Central Highlands, North-eastern India and Siwalik hills. The current study suggests that under the future climate change, the suitable habitat for A. marmelos and T. bellirica is expected to increase while for B. lanzan, M. longifolia and P. emblica, it is projected to decline. A. marmelos and T. bellirica are anticipated to exhibit resilience to future climate changes and are expected to be minimally affected, while B. lanzan, M. longifolia and P. emblica are highly sensitive to high temperature and alteration in rainfall pattern expected under future climate changes. The projections of habitat suitability areas can be used as a valuable foundation for developing conservation and restoration strategies aimed at alleviating the climate change impacts on NTFP species., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Climate change and human activities have massively impacted the hydrological cycle. Thus, it is of the greatest concern to examine the effect of climate change on water management, especially at the regional level, to understand the possible future shifts in water supply and water-related crises and support regional water management. Fortunately, there is a high degree of ambiguity in determining the effect of climate change on water requirements. In this paper, the statistical downscaling (SDSM) model is applied to simulate the potential impact of climate on crop water requirements (CWR) by downscaling ET 0 in the region of Western Maharashtra, India, for the future periods, viz., the 2030s, 2050s, and 2080s, across three meteorological stations (Pune, Rahuri, and Solapur). Four crops, i.e., cotton, soybean, onion, and sugarcane, were selected during the analysis. The Penman-Monteith equation calculates reference crop evapotranspiration (ET 0 ). Furthermore, in conjunction with the crop coefficient (K c ) equation, it calculates crop evapotranspiration (ET c )/CWR. The predictor variables were extracted from the National Centre for Environmental Prediction (NCEP) reanalysis dataset for 1961-2000 and the HadCM3 for 1961-2099 under the H3A2 and H3B2 scenarios. The results indicated by SDSM profound good applicability in downscaling due to satisfactory performance during calibration and validation for all three stations. The projected ET 0 indicated an increase in mean annual ET 0 compared to the present condition during the 2030s, 2050s, and 2080s. The ET 0 would increase for all months (in summer, winter, and pre-monsoon seasons) and decrease from June to September (monsoon season). The estimated future CWR shows variation in the range for cotton (- 0.97 to 2.48%), soybean (- 2.09 to 1.63%), onion (0.49 to 4.62%), and sugarcane (0.05 to 2.86%). The significance of this research lies in its contribution to understanding the potential impacts of climate change at a regional level. This study provides valuable insights into the expected changes in water demand for key crops. The research also manifests implementing an identical methodology for downscaling other environmental parameters using a similar approach., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The rapidly changing climatic conditions are adversely impacting the Indian agricultural sector. Farmers are frequently seen adopting several adaptation measures, which are neither equally efficient nor mutually exclusive. Based on the primary data collected from 300 farming households of the Indian Eastern Himalayan foothills, the present study attempts to examine the efficiency of local farmers' adaptation by developing indices combining the feasibility, effectiveness, and sustainability of the adaptation measures with the scale of actual adoption. Further, by employing multiple linear regression, the study analyzes the internal (psychological) and external (physical and socio-economic) factors influencing higher scores of these indices. Results show that local farmers are well aware of climate change and are responding through implementing at least one and up to seven adaptation measures. Farmers preferred agroforestry, a shift from cereals to low water-intensive commercials, irrigation, and intensification of winter crops as the most efficient. There was, however, a misalignment between the perceived efficiency of adaptation measures and their scale of adoption. Farmers' perceptions of pest infestation, satisfaction with farming, soil characteristics, farm size, remittances, and access to credit were found to be positively and significantly influencing the adaptation indices, while open-mindedness toward changing farming practices and crop-raiding by elephants were found to be negatively and significantly associated with adaptation indices. Lastly, the study made relevant recommendations for improving farmers' efficiency in adopting appropriate adaptation measures and strengthening the "State Action Plan on Climate Change"., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the Godavari River basin. The Sacramento model provided initial streamflow estimates for Kanhargaon, Nowrangpur, and Wairagarh. This approach melded traditional hydrological modeling with advanced multi-layer perceptron (MLP) capabilities. When combined with parameters like lagged rainfall, lagged streamflow, potential evapotranspiration (PET), and temperature variations, these initial outputs were further refined using the Sac-MLP model. A comparison with Sacramento revealed the superior performance of the Sac-MLP model. For instance, during training, the Nash Sutcliffe efficiency (NSE) values for the Sac-MLP witnessed an improvement from 0.610 to 0.810 in Kanhargaon, 0.580 to 0.692 in Nowrangpur, and 0.675 to 0.849 in Wairagarh. The results of the testing further corroborated these findings, as evidenced by the increase in the NSE for Kanhargaon from 0.890 to 0.910. Additionally, Nowrangpur and Wairagarh experienced notable improvements, with their NSE values rising from 0.629 to 0.785 and 0.725 to 0.902, respectively. Projections based on EC-Earth3 data across various scenarios highlighted significant shifts in rainfall and temperature patterns, especially in the far future (2071-2100). Regarding the relative change in annual streamflow, Kanhargaon projections under SSP370 and SSP585 for the far future indicate increases of 584.38% and 662.74%. Similarly, Nowrangpur and Wairagarh are projected to see increases of 98.27% and 114.98%, and 81.68% and 108.08%, respectively. This study uses EC-Earth3 estimates to demonstrate the Sac-MLP model's accuracy and importance in climate change water resource planning. The unique method for region-specific hydrological analysis provides vital insights for sustainable water resource management. This research provides a deeper understanding of climate-induced hydrological changes and a robust modeling approach for accurate predictions in changing environmental conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R 2  = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Climate change crises and environmental imbalances have been a significant concern globally in recent times. The climatic changes give rise to various issues such as global warming, depletion of the ozone layer, deterioration of natural resources, soil erosion, deforestation, and more. Many international and national agreements and policies have been created to protect the environment, from the UNFCCC to the recent Paris Agreement, aiming to control rising environmental issues. However, developed and developing countries must achieve desirable results in combating climate change. Industrial and technological developments are critical reasons for environmental pollution and degradation. Progress is necessary for planned developing countries, but growth and expansions shall also consider ecological sustainability. Technology shall be novel in adapting to the changes, considering the effects it can produce on the environment. Green technology combines technology with the environment, also called environmental technology, clean technology, or sustainable technology. It is a combination of science and technology together to mitigate climatic changes and protect the environment. Green technology is the modern sustainable solution to pressing environmental concerns. India is one of the countries globally showing rapid green technology developments. The authors of this paper have tried to highlight the dire need to modify technological developments vis-a-vis environmental sustainability to protect the environment. The research paper delves into and understands the interface between clean technology’s importance and relevance for ecological sustainability and the role of patent law, particularly in dealing with issues of the environment. The paper shall also establish a harmonious relationship between patent law and its role in ensuring environmental sustainability. [ABSTRACT FROM AUTHOR]

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]

Tribal farmers in the Himalayas are vulnerable to climatic changes, as their rain-fed cultivation systems, practiced on steep, sloping terrain, are susceptible to changes in rainfall while at the same time being the primary means of livelihood. Soil and water conservation practices (SWCP) can improve the resilience of these cultivation systems to adverse climatic conditions. However, little is known about adaptation within these tribal farming communities. This is the first empirical study on the adaptation decisions of tribal farmers in the Himalayan uplands of Northeast India. Starting from the analysis of future climate risks, we surveyed 372 tribal farmers in Nagaland state to analyze perceived climate and environmental changes in relation to socio-demographic factors. We estimate current adoption rates of SWCP together with farmers' goals and values and employ a binary logit model (BLM) to quantify the influence of diverse factors on adaptation decisions. Our results show that increases in temperatures and crop diseases were the most perceived changes by tribal farmers. Climate projections indicate that precipitation amount and intensity, along with temperatures, will increase towards the end of the century, underlining the importance of SWCP. However, all considered SWCP were employed by less than half of the tribal farmers. Adoption probabilities for all practices were significantly increased when farmers participated in agricultural training. After that, participation in a civil society organization, livestock ownership, high-altitude locations, and perceived increases in droughts were found to increase adoption probabilities significantly, while socio-demographic factors were of only minor importance. If the most effective factor was employed to all farmers, average adoption rates of SWCP could at least double. Adoption decisions were mainly motivated by improving livelihoods, sustaining natural resources, reducing workload, and preserving cultural aspects of cultivation. This research contributes to understanding adaptation decisions of tribal farmers and quantifies the untapped potential for climate change adaptation of marginalized and climate-vulnerable farming communities in mountain regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Wetlands provide numerous ecological and economic services to mankind. The soils of wetlands are one of the largest sinks of carbon (C) among the terrestrial ecosystems and can play an important role in offsetting the emission of C as a greenhouse gas (GHG) to the atmosphere. India is bestowed with enriched wetland ecosystems that support diverse and unique habitats. The potential of the wetlands in terms of C capture and sequestration has not been quantified. Therefore, in the present paper, an assessment of C capture from different sources and its ultimate deposition in soils leading to sequestration has been done in three different types of wetlands, one created sewage-fed and two natural floodplain oxbow lakes, in the West Bengal state of India. Multiple seasonal sampling of water, macrophytes, and soil was done to assess the primary productivity, dissolved C, and deposition of C in soils of the wetlands in comparison to reference upland sites. All these wetlands are productive ecosystems as indicated by the physicochemical parameters of water and soil. The quantity of C accumulated up to 0.3 m depth in the oxbow lakes was to the tune of 144–166 Mg/ha, which was 3.43–4.78 times higher than that in the corresponding reference upland sites. In the sewage-fed wetland, the C accumulation estimated as 50 Mg/ha was 1.27 times higher than its corresponding upland site. So, the wetland ecosystems, particularly the floodplains, are highly efficient in accumulating C in their soils and thus can somewhat negate the GHG emission. [ABSTRACT FROM AUTHOR]

This paper aims to illustrate the crucial role of preserving, protecting and managing the environment by Indigenous Peoples in Japan and India. Traditional Knowledge has provided the ability to detect, understand and respond to environmental changes. However, modern science and applied technology often fall short of sustainable practices, acquired through 'centuries of local observation'. Our consumer-centric world has unravelled a sad situation that has contributed to an irretrievable climate crisis. Multilateral instruments, however, have come to the rescue. In this journey, Japan and India have shown the world some constructive initiatives with positive outcomes which could go a long way in achieving the UN-SDGs. [ABSTRACT FROM AUTHOR]

In general, the impact of two different connected extreme events is noticed on the same duration and spatial area. However, the connected extreme events can have footprint over different temporal and spatial scales. Thus, this article analyses the connected extreme events over India using the spatio-temporal compounding technique to understand the impact at different temporal and spatial scales. This approach is applied to analyse the historical and future connected extreme events. In the present study, coincident heat waves and droughts (Event C1), coincident heat waves and extreme precipitation (Event C2) are considered as connected extreme events. The future events are investigated using the suitable global climate models (GCMs) projections under three climate change scenarios (Shared Socioeconomic Pathways (SSP) 2-4.5, SSP3-7.0, and SSP5-8.5). The suitable GCMs are identified with the help of compromise programming. Subsequently, the hotspot regions are identified applying the Regional Climate Change Index (RCCI) method. The outcomes from the study suggest that with increasing temporal compounding, the mean duration of extreme events also increases. Highest increase in mean duration is observed for Event C1 over PI (Peninsular India), WCI (West Central India), and some parts of CNI (Central Northeast India) regions. The regions with high magnitude of duration have low magnitude of occurrence. The duration of Event C1 is likely to increase with respect to climate change scenarios and temporal compounding, especially in the PI region and some parts of WCI. However, there is insignificant change in the duration of Event C2. The PI region identified as the most vulnerable region followed by WCI and HR regions. The highest percentage of area under the emerging hotspot category is noticed under SSP5-8.5 climate change scenario., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Accurate estimation of carbon cycle is a challenging task owing to the complexity and heterogeneity of ecosystems. Carbon Use Efficiency (CUE) is a metric to define the ability of vegetation to sequester carbon from the atmosphere. It is key to understand the carbon sink and source pathways of ecosystems. Here, we quantify CUE using remote sensing measurements to examine its variability, drivers and underlying mechanisms in India for the period 2000-2019, by applying the principal component analyses (PCA), multiple linear regression (MLR) and causal discovery. Our analysis shows that the forests in the hilly regions (HR) and northeast (NE), and croplands in the western areas of South India (SI) exhibit high (>0.6) CUE. The northwest (NW), Indo-Gangetic plain (IGP) and some areas in Central India (CI) show low (<0.3) CUE. In general, the water availability as soil moisture (SM) and precipitation (P) promote higher CUE, but higher temperature (T) and air organic carbon content (AOCC) reduce CUE. It is found that SM has the strongest relative influence (33%) on CUE, followed by P. Also, SM has a direct causal link with all drivers and CUE; reiterating its importance in driving vegetation carbon dynamics (VCD) for the cropland dominated India. The long-term analysis reveals that the low CUE regions in NW (moisture induced greening) and IGP (irrigation induced agricultural boom) have an increasing trend in productivity (greening). However, the high CUE regions in NE (deforestation and extreme events) and SI (warming induced moisture stress) exhibit a decreasing trend in productivity (browning), which is a great concern. Our study, therefore, provides new insights on the rate of carbon allocation and the need of proper planning for maintaining balance in the terrestrial carbon cycle. This is particularly important in the context of drafting policy decisions for the mitigation of climate change, food security and sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The rainfall over the Indian region, governed majorly by the monsoonal flow, is a point of research in the perspective of climate change. In this paper, we compute the change points in the rainfall series at every grid of the India Meteorological Department (IMD) daily gridded rainfall data for a period of 120 years (1901 to 2020). The map shows clearly demarcated regions indicating different zones, where the rainfall statistics have altered at different periods. It is observed that in a major part of central India, the shift in rainfall intensity is mainly associated with the time frame 1955-1965; in the Indo-Gangetic plain, the changes are found to be more recent (1990), while the latest changes (post 2000) are observed particularly for North Eastern region and some parts along the East Indian coast. The changeover years are significant at a 95% confidence level for most part of the Indian landmass. The causes may be surmised due to moisture transport from the Arabian Sea (Central India), the presence of aerosol (Gangetic Plain), and the possible revival of monsoon due to land-ocean gradient (Eastern coast and North East India). This is the first-ever study which provides a comprehensive daily rainfall change point map over India using 120 years of gridded station data., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

To meet the demand of the growing population, there exists pressure on food production. In this context, appropriate prediction of crop yield helps in agricultural production planning. Given the inability of the traditional linear models to provide satisfactory prediction performance, there is a need to develop a crop yield prediction model that is simple in complexity, accurate in prediction, and less time-consuming during training and validation phases. Keeping these objectives in view, the present paper focuses on building an adaptive, low complexity, and accurate nonlinear model for the prediction of crop yield. A time series dataset for the period 1991–2012 of Karnataka, a southwestern state of India, is used for yield prediction. An empirical nonlinear relation between crop yield and the four independent attributes has been obtained from the proposed ANN model. The independent attributes employed are total rainfall, the cumulative distribution of temperature, the proportion of irrigated land, and the average amount of fertilizer used. It is demonstrated that the developed model exhibits better prediction accuracy, less root mean square error in the range of 0.07–0.14, less mean square error in the range of 0.01–0.04, and mean absolute error in the range of 0.07–0.15 compared to its corresponding linear regression model. It is recommended that the proposed ANN model can also be applied to predict other agricultural products of the same or other geographical regions of the globe. [ABSTRACT FROM AUTHOR]

Long-term experiments are essential in understanding the ecological consequences of global land use and climate change. Further, it is well established that longterm data sets are prerequisites for effective management of forest resources and biodiversity conservation. In view of this, the present study attempts to contribute to major global long-term ecological monitoring (LTEM) networks and the status of LTEM studies in India with a special focus on Indian Himalayan Region. Over the last 40 years, around 103 countries from the America, Europe, Africa, Asia and Australia have been engaged in LTEM studies on various aspects of biodiversity, monitoring and predicting climate change impacts in a range of ecosystems, including the mountains. The temporal distribution of past studies on the subject shows a gradual increasing pattern (3 papers in 1992) with a peak during 2021 (105 papers). The established LTEM networks across the globe provide a significant empirical basis for understanding ecosystem structure and dynamics. Literature indicates plenty of permanent monitoring plots from India, mostly from southern India, and their significant contribution to ecosystem understanding. Himalayan regions are important sites for monitoring biological and socio-ecological responses to environmental perturbations, including climate change. LTEM studies are lacking in the IHR; only a few sites have been established, mostly in alpine ecosystems. This review identifies research gaps, opportunities with respect to LTEM studies, and the possibilities for strengthening long-term research and observation in India in general and the Himalaya in particular. [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]

Potential changes in hydro-meteorological events have been causing mass damage to the economy and lives. Among several other factors, the progression of climate change over a long time is expected to cause non-stationarity in annual maximum rainfall. Understanding the characteristics of annual maximum rainfall series is crucial for coastal cities as they are highly vulnerable due to the greatly varying weather patterns. In this paper, we propose stationary and non-stationary methods to model the effect of non-stationarity on the differing duration of annual maximum rainfall and demonstrate the impacts on nine coastal cities spread across the Arabian Sea and Bay of Bengal stretch of India. The Bayesian inference parameter estimation technique was used. It was found that while stationary models often fit well for longer-duration rainfall, non-stationary models often best fit the short duration. [ABSTRACT FROM AUTHOR]

The transition of the Earth's climate from one zone to another is one of the major causes behind biodiversity loss, rural-urban migration, and increasing food crises. The rising rate of arid-humid zone transition due to climate change has been substantially visible in the last few decades. However, the precise quantification of the climate change-induced rainfall variation on the climate zone transition still remained a challenge. To solve the issue, the Representative Grid Location-Multivariate Adaptive Regression Spline (RGL-MARS) downscaling algorithm was coupled with the Koppen climate classification scheme to project future changes in various climate zones for the study area. It was observed that the performance of the model was better for the humid clusters compared to the arid clusters. It was noticed that, by the end of the 21 st century, the arid region would increase marginally and the humid region would rise by 24.28-36.09% for the western province of India. In contrast, the area of the semi-arid and semi-humid regions would decline for the study area. It was observed that there would be an extensive conversion of semi-humid to humid zone in the peripheral region of the Arabian sea due to the strengthening of land-sea thermal contrast caused by climate change. Similarly, semi-arid to arid zone conversion would also increase due to the inflow of dry air from the Arabian region. The current research would be helpful for the researchers and policymakers to take appropriate measures to reduce the rate of climate zone transition, thereby developing the socioeconomic status of the rural and urban populations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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 establishment, development and abandonment and/or destruction of ancient civilizations were catalytically controlled by geomorphic features such as lakes and rivers and the climate. This paper examined the possible influence of tectonism and climate on six habitations of the ancient Vaigai River Basin civilization in South India, using multiple proxies such as grain size, geochronology and geochemistry of the sedimentary archives. The tectonic setting of the basin changed between the active margin and passive margin; the discriminant diagrams suggested varying provenance and changing climatic conditions over the mid‐ and‐late Holocene. Tectonic activism and quiescence, base‐level change in the channel morphology led to the burial/marooning of the first habitation surface. Overall, arid conditions were punctuated with catastrophic flooding and peak discharge (flood) destroyed the second, third and fourth habitation sites. These flooding events were characterized by moderate weathering (CIA) and high values of Al, Fe and Rb/Sr and low Ca/Mg in the sediment records. The abandonment/destruction of the fifth habitation also occurred during an arid interval (droughts), possibly caused by weak monsoon. Along with the interactions between tectono‐climatic and fluvial geomorphic factors, the new results provided avenues to (a) check and recognize the archives for 8.2 and 4.2 ka‐like events in this part of the world, and (b) the utility of integrated analyses to constrain on the civilizational histories of the mankind. [ABSTRACT FROM AUTHOR]

Under global warming and climate change (CC), the vulnerable piece of land is India's Eastern-Himalayan-Region (EHR), where millions' livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perception of kiwifruit growers under EHR and the impact of CC on its cultivation. Perceived and scientific data were used for accurate decision-support information. The climatic variables of two locations were analyzed for trend using Mann–Kendall's test. Results suggested that the rainfall trend was found non-significant for both locations, but there was a negative trend during winter for Pasighat and during all seasons for Itanagar. Maximum temperature exhibited an increasing trend for annual, and minimum temperature showed an increasing trend across seasons for the Pasighat region. For the Itanagar region, the maximum temperature was found to have a significantly increasing trend in all seasons, while the minimum temperature showed an increasing trend during winter and annual seasons. Morning relative humidity showed an increasing trend for annual data for Pasighat, while annual evening relative humidity was significantly increased for Itanagar. The study shows that the indigenous farming communities were following shifting cultivation and diversifying their traditional agriculture to kiwifruit cultivation as an adaptation strategy. The community had a clear perception of CC trends and an inadequate perception of the impact on agriculture, therefore, engaging indigenous communities and other stakeholders to postulate a comprehensive adaptation and mitigation strategy for CC. [ABSTRACT FROM AUTHOR]

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.

Clean energy transition via utilizing biomass resources has been projected as an important climate change mitigation strategy. A vital characteristic of biomass is its localized nature; therefore, bioenergy utilization should follow decentralized planning. Agrarian countries like India can take benefit of its large agricultural biomass waste pool to produce clean renewable energy. However, prior knowledge of spatio-temporal distribution, competing uses, and biomass characteristics are necessary for successful bioenergy planning. This paper assesses biomass resource and its power generation potential at different agro-climatic zone levels in the state of Rajasthan, India considering crop residue biomass (25 different crop residues from 14 crops) and livestock manure (from cattle, buffalo, and poultry). Uncertainties associated with the availability of biomass and the power generation potential are assessed for each agro-climatic zone under different scenarios. Greenhouse gases (GHGs) emissions from biomass-based power generations are also estimated and compared with biomass-equivalent coal power plants. It is observed that the annual biomass power potential of Rajasthan is 3056 MW (2496 MW from crop residues and 560 MW from livestock manure). Scenario analysis suggests that the potential varies from 2445 to 6045 MW under different biomass availability and power plant operating conditions. Annual GHGs emissions due to biomass power generation is 5053 kt CO 2 eq. Replacing coal-based power with biomass power would result in annual GHGs savings of 11412 kt CO 2 eq. The paper also discusses various carriers and barriers viz. logistics, institutional, financial and technical in setting up decentralized bioenergy plants. Outcomes of the present study are expected to assist renewable energy planners in India., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Tropical inland capture fisheries are susceptible to a series of vulnerabilities such as habitat destruction, biodiversity loss, pollution, overfishing, invasive species and anthropogenic climate change. A comprehensive review of the impact of climatic uncertainties on Indian inland fisheries has not been adequately attempted yet. Recent approaches emphasizing ecosystem-based management in a regional context, specific to inland fisheries for combating climatic changes, have not been reported to date. The paper presents a critical bibliometric review of the climatic vulnerabilities faced by Indian inland fishery resources and various adaptive and mitigation strategies put forward by the country for the sustainability of the resources. In this communication, a systematic review of the impact of climate change and other stressors on various inland ecosystems of the subcontinent and the ecosystem-based management strategies adopted in India is presented and discussed. [ABSTRACT FROM AUTHOR]

Occurrences of extreme events, especially floods, have become more frequent and severe in the recent past due to the global impacts of climate change. In this context, possibilities for generating a near‐accurate streamflow forecast at higher lead times, which could be utilized for developing a reliable flood warning system to minimize the effects of extreme events, are highly important. This paper aims to investigate the potential of a novel hybrid modeling framework that couples the random forest algorithm, particle filter, and the HBV model for improving the overall accuracy of forecasts at higher lead times through the dynamic error correction schematic. The new framework simulates an ensemble of streamflow for estimating uncertainty associated with the predictions and is applied across two snow‐fed Himalayan rivers: the Beas River in India and the Sunkoshi River in Nepal. Several statistical indices along with graphical performance indicators were used for assessing the accuracy of the model performance and associated uncertainty. The modeling framework achieved the Nash Sutcliffe Efficiency of 0.94 and 0.98 in calibration and 0.95 and 0.99 in validation for the Beas and Sunkoshi river basin respectively for a 7‐day ahead forecast. Thus, the proposed framework can be considered as a promising tool having reasonably good performance in forecasting streamflow at a higher lead time. Key Points: Hybrid hydrological model integrates process‐based model with machine learning algorithm through data assimilation techniqueDynamic error correction framework capable of improving the streamflow forecast at longer lead time is proposedOverall the developed framework improves the forecast accuracy along with quantifying the model prediction uncertainty [ABSTRACT FROM AUTHOR]

While the Global North is historically responsible for the majority of greenhouse gas emissions in the atmosphere, Newly Industrializing Countries (NICs) are expected to overtake developed country emissions in the coming years. At the same time, NICs are climbing the ladder of the global economy, increasing their competitiveness on the global stage and catching up with technological competencies of developed economies. Against this background, this paper explores innovation and collaboration in Climate Change Mitigation Technologies (CCMTs) in NICs. The research question is whether the propensity to innovate and diffuse CCMTs is impacted by technological collaboration with two highly developed countries, Germany and The United States. The sample of NICs includes the BRICS (Brazil, Russia, India, China, South Africa) plus Israel, Mexico, and Turkey, in a panel from 1995 to 2015. The empirical results suggest that collaboration with both Germany and the U.S. is highly significant for domestic CCMT innovation in NICs. These findings are important because, stepping beyond the literature on the merits and drawbacks of global climate governance tools such as the Clean Development Mechanism (CDM) and related UNFCCC processes, they show that collaboration for climate and environmental technologies could become a key tool to significantly improve the chances to stay in line with the Paris Climate Agreement. Finally, the policy advice for NICs and developing countries is to, above all else, focus on incubating strong technological innovation systems, including strengthening domestic Intellectual Property Rights (IPR), as well as to enhance technological collaboration with developed countries., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The ever-growing impacts of climate change such as extreme heat, more frequent heavy precipitation events, intensifying tropical revolving storms, and sea level rise continue to pose major threats to India's critical maritime infrastructure. As the country moves towards its ambition of becoming a leading Blue Economy of the world, a wide range of initiatives have been taken by the central and state governments to expand the maritime sector with a specific focus on the transport sector. However, there is little emphasis being paid on protecting the existing and planned seaport infrastructure against the deleterious impacts of climate change. None of the major ports in India have a dedicated climate action strategy and climate adaptation finds no mention in the policy documents pertaining to the maritime transport sector. In this context, this paper aims to highlight the need for a comprehensive, holistic and dynamic climate change adaptation strategy for India's port infrastructure including support infrastructure and supply chains. The adaptation strategy, at the individual ports' level and the national level, must be preceded by rigorous risk assessment studies to identify and prioritise the major challenges arising from climate change at the local level. The paper draws upon international best practices in climate risk assessments and adaptation measures to provide a way forward for Indian ports. [ABSTRACT FROM AUTHOR]

In all global challenges such as climate change, pandemic, nuclear proliferation etc, scientific and technological cooperation is playing a vital role in addressing these multilateral problems. Recent years have witnessed the formidable presence of science, technology and innovation in international relations. In pursuant to this, Science Diplomacy is gaining remarkable attention in international relations and solving global problems. The EIR Of orum in European Union, e-ASIA JRP in South East Asia, African Scientific Institute in Africa and the Arctic Council in the Arctic region have promoted science diplomacy among the member countries while addressing the emerging global challenges. However, these efforts of scientific diplomacy and a comprehensive multilateral mechanism is a distant reality in South Asia. Despite the incongruities, India has taken up several steps - from launching the SAARC satellite to facilitating COVID Vaccine - to promote its science diplomacy in recent years. With the increasing GDP, India's R&D budget took a parallel upsurge from mere Rs. 5000 crore in 1995-96 to Rs. 1, 23,847.71 crore in 2018-19. However, its engagement in south asia raises more skepticism and denouncement. In this context, the present paper intended to analyse the evolution, nature and extent of science diplomacy in South Asia. Further, the paper aims to highlight India's science diplomacy programme in South Asia given its unique political settings and geostrategic implication in shaping South Asian cooperation. [ABSTRACT FROM AUTHOR]

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]

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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]

Air pollution is a growing concern in India, and its adverse health effects are well documented. Climate change is likely to exacerbate this problem by altering weather patterns and increasing the frequency and severity of extreme events. This paper examines the potential impact of climate change on ambient air pollution in India and its implications for policy design. Our analysis reveals that pollution in India is highly sensitive to variation in weather, particularly in the densely populated Indus-Gangetic Plain. Using our estimated relationship between weather and pollution, we predict that changing weather patterns will increase average PM2.5 concentrations by 3.1 µg/m3, leading to a loss of 364 million years of life expectancy. To address this challenge, we propose an emissions fee calibrated to be highest in regions most vulnerable to persistently high levels of pollution and most sensitive to future deterioration in air quality due to climate change. [ABSTRACT FROM AUTHOR]

India's economy is rooted in agriculture, and the majority of the farmers, being smallholders, are highly exposed to the adversities associated with climate change. It has been argued by several researchers that perceiving climate change is a pre-condition for the adoption of adaptation strategies to reduce vulnerabilities. In this regard, studies are limited to explore the question 'is the perceptions of changing climate primarily motivate the smallholders to take adaptation actions?' In this nexus, the present paper seeks to understand the linkages between smallholders' climate change perception and the changes in their farming practices. The study was conducted in the seven villages of Sub-Himalayan West Bengal, India, using participatory rural appraisal (PRA) tools. Key results show, (1) respondents perceived increased warming and decreased precipitation in accordance with the scientific analysis; (2) abundance of groundwater, misconceptions and lack of awareness shaped respondents' agricultural risk perception, and despite decreasing precipitation, water management appeared less risky (3) incorporation of irrigation, diversification towards high valued and high yielding crops, as well as farm mechanizations were the major changes in the farming practices; and, (4) except water management, rest of the changes were not necessarily made to adapt with climate change instead to increase crop yield and profit. It is noticed that the changes in farming practices perhaps made the farmers unconsciously adapted to climate change. Still, a prolonged continuation of some of those practices may lead to maladaptation. In this regard, we have given direction towards necessary policy formulation and future research to achieve sustainability. [ABSTRACT FROM AUTHOR]

This article examines the structural aspects of climate vulnerabilities in the context of monsoon failures. The paper is based on a unique household survey, conducted in Tamil Nadu, India. The study uses a rural differentiation framework to interrogate unequal vulnerabilities to monsoon failures, based on measures such as Gini coefficients and Lorenz curves of monetary losses. Results show that negative consequences of climate change in general, and monsoon failures in particular, intensify pre-existing socio-economic disparities. When the rural differentiation theory is applied in a broader sense, the analysis shows that landed and farming households have greater exposure and losses. When we move beyond these aggregate categories, the revelation is that households with pre-existing disadvantages such as marginal landholders, subsistence farmers and agricultural workers are more vulnerable., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988-2016) using the maximum likelihood algorithm and the long-term LU (2016-2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006-2040), mid-future (2041-2070), and far-future (2071-2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The impacts of anthropogenic activities on the earth atmosphere and its systems have been engaging attention planners, governments and politicians worldwide. The countries across the world are engaged in working out the impacts and associated variability's to the projected climate change. In the twentieth century many recent studies show changes in rainfall patterns of India as well as changes in weather conditions climate changes, decrease in rainfall duration and rainfall amount and increase in rainfall intensity paper describe Climate Change Impact Studies on Rain Madhya Pradesh, India. The rainfall data collected for a period of 1901 to 2019from the District Land Record Department of Chhatarpur and Indian Meteorological Department, New Delhi (IMD). The results historical rainfall records of Chhatarpur district have been analysis using statistical and Mann Results are also discussed for the future climate change scenario in rainfall variability of thearea. [ABSTRACT FROM AUTHOR]

Groundwater is the second largest store of freshwater in the world. The sustainability of the ecosystem is largely dependent on groundwater availability, and groundwater has already been under tremendous pressure to fulfill human needs owing to anthropogenic activities around various parts of the world. The footprints of human activities can be witnessed in terms of looming climate change, water pollution, and changes in available water resources. This paper provides a comprehensive view of the linkage between groundwater, climate system, and anthropogenic activities, with a focus on the Indian region. The significant prior works addressing the groundwater-induced response on the climatic system and the impacts of climate on groundwater through natural and human-instigated processes are reviewed. The condition of groundwater quality in India with respect to various physicochemical, heavy metal and biological contamination is discussed. The utility of remote sensing and GIS in groundwater-related studies is discussed, focusing on Gravity Recovery and Climate Experiment (GRACE) applications over the Indian region. GRACE-based estimates of terrestrial water storage have been instrumental in numerous groundwater studies in recent times. Based on the literature review, the sustainable practices adopted for optimum utilization of groundwater for different purposes and the possible groundwater-based adaptation strategies for climate change are also enunciated. [ABSTRACT FROM AUTHOR]

This paper examines the EIA process and its effectiveness in addressing the impacts of a 190 km long national highway project along the Karnataka coast. We analyse the quality and relevance of the environmental clearance conditions established by the Ministry of Environment, Forest, and Climate Change (MoEF&CC) and discusses their potential implications. The findings underline that most of the conditions that pertained to the prevention of pollution, restoration of mangroves, and protection of biodiversity lacked a scientific basis and specific information required for effective implementation. The MoEF&CC also overlooked the social impact of the project and underplayed its own role in ensuring fair compensation to project affected communities for the loss of their land and other livelihoods. The paper concludes by promulgating a long list of irrelevant and ineffective environmental conditions that represent greenwashing because it could misguide affected communities and other stakeholders by creating the impression the state is exercising due diligence in protecting the environment. [ABSTRACT FROM AUTHOR]

Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

Irrigation is an important adaptation strategy to cope with climate change which reduces vulnerability to water stress and improves crop productivity to feed millions. There is evidence of crop yield stagnation in many developing countries, and irrigation efficiency is claimed to increase crop productivity. Therefore, this paper uses data envelopment analysis to evaluate the farmer's productivity through technical efficiency (TE), i.e., the relationship between resource inputs and outputs of 513 paddy farmers in Eastern India. The results show that the farms are, on average operating at 14% TE, leaving a considerable scope to improve up to 86% to reach the optimal level. A significant difference is observed between irrigated and rain-fed paddy farmers, such that10% of the irrigated farms achieved efficiency scores over 40% and only 2% of rain-fed farms achieved the same. The tobit and beta fit regression models are estimated to find out the factors that influence the TE. Both surface water and groundwater sources of irrigation are used as predictors, along with other socio-demographic factors. Access to surface water irrigation is identified to be a significant determinant of farm efficiency, however, surface water irrigation, such as canal irrigation, is accessible only to farmers living on plain land. Farmers living on highlands need to explore other sources of irrigation practices, such as drip and sprinkler, that can increase TE and farm productivity. Therefore, this paper calls for government intervention to provide extensive training and facilities for these micro-irrigation practices. • Data Envelopment analysis was estimated to derive the paddy efficiency among the tribal villages of eastern India. • The DEA estimates show that average Technical efficiency in the study region is much below the national average. • Irrigated farmers are more efficient than the rain-fed farmers. Surface irrigation is the dominate factor. • Rain-fed paddy cultivators' farm efficiency would improve by 6.5%, if they had irrigated. • Semi-mountainous regions with little access to surface irrigation must explore micro-irrigation practices such as drips and sprinklers. [ABSTRACT FROM AUTHOR]

Electric vehicles are promoted in large numbers by government of India to reduce environmental pollution and climatic change. Major anxieties while introducing electrical vehicles is their driving range and initial cost. Enough number of normal, medium and fast charging stations and battery swapping stations are to be planned and installed for smooth conveyance of electrical vehicles. This paper deals with a normal charging station implemented at a workspace. A solar power plant is used as the major source of electrical energy. An alternate connection to the station storage battery is used for importing/exporting the electrical power at times of deficient/excess solar power generation. The performance of the system is verified with MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

To combat the effects of climate change and meet the need for clean energy, the global power sector, over the past few decades, has been undergoing a major transformation for which all possible renewable energy sources are currently being utilized. To achieve sustainable growth, India, like many other countries, is also in the process of energy transition, aiming to shift to renewable energy-based power generation. In this transition, research in Ocean Renewable Energy (ORE) technologies is rising to rapid prominence. This study examines the state of ORE research in India and compares it with global research activities in this field using a graph-theoretical framework for collaboration co-authorship networks in ORE using bibliometric data on published scholarly articles indexed in two well-known electronic databases covering two 10-year windows: 1999-2008 and 2009-2018, inclusive. A strategic analysis of a number of metrics characterizing the networks’ large-scale structures reveals that the Indian network is highly fragmented, resulting in a singular dearth of large-scale connections for Indian ORE researchers. We recommend effective research policies to improve knowledge generation and dissemination in ORE research collaboration in India (and many other countries in similar situations), based on our findings for Indian networks and pertinent parallels with global ORE. With growing concerns about sustainable energy utilization, our study has policy implications for pressing issues of energy demands in the country. [ABSTRACT FROM AUTHOR]

In the context of climate change, countries all over the world are making numerous efforts to transition to a bio-based economy from a fossil fuel-based economy. This paper looks at the motivations and policy initiatives in India that drive the transition to a bio-based economy. This article focusses on the bioenergy sector and the comparative analysis of the historical developments in the biofuels domain leading to the biofuel policies of 2009 and 2018. As a potential contributor to bio-based economy by ensuring energy self-reliance, clean energy and increasing farmers income, this article analyses the shifts in the policies, the technical trajectories. It examines the opportunities and challenges in developing and harnessing the advanced biofuels and the initiatives taken in recent years in this regard. It points out that there are many challenges and highlights the importance of engaging with stakeholders in development of policy. Considering the opportunities, the issues that could arise and the potential and need for biofuels for energy security and to fulfil other objectives, it makes some suggestions for policy makers. [ABSTRACT FROM AUTHOR]

Introduction: With increasing demand for food and changing environmental conditions, a better understanding of the factors impacting wheat yield is essential for ensuring food security and sustainable agriculture. By analyzing the effect of multiple factors on wheat yield, the presented research provides novel insights into the potential impacts of climate change on wheat production in India. In the present study, datasets consisting of countrywide environmental and agronomic factors and wheat yield were collected. In addition, the study also analyzes the effect of information demand of farmers on production. Methodology: The study employs a regional analysis approach by dividing the country into five zonal clusters: Northern Hills, Central India, Indo-Gangetic Plains, North-Eastern India, and Peninsular India. Correlation and Principal Component Analysis (PCA) were performed to uncover the month-wise key factors affecting wheat yield in each zone. Furthermore, four Machine Learning/Deep Learning-based models, including XGBoost, Multi-layer Perceptron (MLP), Gated Recurrent Unit (GRU), and 1-D Convolutional Neural Network (CNN), were developed to estimate wheat yield. This study estimated partial derivatives for all factors using Newton's Quotient Technique, a numerical method-based approach. Results: The analysis focused on applying this technique to the best-performing wheat yield estimation model, which was the GRU-based model (with RMSE and MAE of 0.60 t/ha and 0.46 t/ha, respectively). Discussion: In the later sections of the article, multiple policy recommendations are communicated based on the extracted insights. The results of the presented research help inform decision-making regarding the development of strategies and policies to mitigate the impacts of climate change on wheat production in India. [ABSTRACT FROM AUTHOR]

India is one of the rapidly urbanizing major economies in the developing world. As it embarks on its urban transition, many small tier-2 cities are already experiencing a large-scale transformation. This study examines the effects of surface urban heat island intensity (SUHI) effect from 2001 to 2020 on a tropical coastal urban complex, Bhubaneswar and Cuttack, a rapidly expanding tier-2 twin city in the Eastern Indian region. Our study reveals a clear discernible annual nighttime SUHI for both Bhubaneswar and Cuttack (0.75 ± 0.08 and 1.22 ± 0.07 °C) with a growth rate of 0.18 ± 0.07 and 0.13 ± 0.07 °C/decade, respectively. Surprisingly, the annual daytime SUHI is weakening for Bhubaneswar. Both night and daytime SUHI showed substantial seasonality with a clear asymmetry during the day and night. Daytime urban cool island effect was observed for Cuttack with Bhubaneswar reporting weak SUHI for daytime during dry seasons. Around the periphery of the cities, the diurnal temperature range (DTR) was found to be the highest. Furthermore, A decrease of 2 °C in the DTR has been reported over the past two decades. The urbanization effect on the local thermal climate of both cities is seen beyond the physical urban limits. Such changes, even in tier-2 cities, have significant potential to modulate local climate and underscore the need for detailed studies in the rapidly urbanizing cities of India and the world to enable disaster resilience, climate-proofing, and sustainability. [ABSTRACT FROM AUTHOR]

The increasing concentrations of greenhouse gas emissions in the atmosphere along with the increasing temperatures exacerbate the situation, making it one of the major issues for food security. This research aims to explore the effects of climate change on food production in India. More specifically, this study investigates the impact of temperature, rainfall, CO2, methane, and N2O emissions and energy use on food production using a time spanning from 1990 to 2019 and explores the major critical factors impacting food production in India. The study used autoregressive distributed (ARDL) estimates for long-run and short-run cointegration. The empirical results demonstrated that energy use, rainfall, and methane emissions improve food productivity, whereas temperature and N2O emissions undermine food production in the long run and short run. However, the results revealed that CO2 emissions do not affect food production. Additionally, we used the dynamic ordinal least squared approach to verify the robustness of ARDL results. The results also demonstrate that N2O emissions and temperature are critical determinants of food production, indicating that a rise in temperature and N2O emissions significantly reduces food production in India. On the other hand, the findings show that methane emissions and rainfall significantly increase food production with a coefficient of 0.19 and 0.059, respectively. The most important adaptation strategies that should be considered due to climate change are reducing greenhouse gas emissions, expanding renewable energy investment, and adopting new technologies to combat environmental challenges. [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]

Uttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs. Plain Language Summary: Uttar Pradesh is the most populated state in India, with most of the population working in the agriculture sector and having a low income. The state's vulnerability to climate change is high due to inadequate infrastructure and heavy dependence on agriculture. Rice is a crucial crop for the state, but this study shows that climate change will decrease rice yields in the future, especially for irrigated rice, due to higher temperatures and shorter growing seasons. While rainfed rice yields may increase in some regions due to increased rainfall, rice production is expected to decline overall. Key Points: Rice yield (combining irrigated and rainfed) in Uttar Pradesh, India, is projected to decrease in the future for SSP2‐4.5 and SSP5‐8.5With a projected increase in rainfall, rainfed rice yield increases in rainfall deficit zones, and irrigation decreases under both shared socioeconomic pathwaysPlanting in the early season could reduce the amount of yield loss for irrigated rice [ABSTRACT FROM AUTHOR]