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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]

The land, oceans, and atmosphere are tightly linked and form the most dynamic component of the climate system. Studies on terrestrial and ocean science enhance the understanding on the impacts of climate change. Across India and the world over, human-driven land use and climate changes are altering the structure, function, and extent of natural terrestrial ecosystems and in turn regional biogeochemical feedbacks. In this special issue, we present 29 manuscripts; those discuss wide-ranging aspects of terrestrial and oceanic characterization and dynamics. These contributions are based on selected presentations made at the 2nd International Workshop on Biodiversity and Climate Change (BDCC-2018) held on 24–27 February 2018 at the Indian Institute of Technology Kharagpur, India. The manuscripts are arranged in five sections such as Ecological Assessment, Plant Invasion, Carbon Dynamics, Ecosystem Characterization, and Ocean Dynamics. We realized that the utility of satellite remote sensing data has been emerging as a dominant trend in environmental monitoring and assessment studies in India. [ABSTRACT FROM AUTHOR]

The cement industry is undeniably critical for the global economy. However, they are also the largest energy consumers in the world. The clinker manufacturing process causes gaseous emissions like nitrogen oxides, sulfur dioxide, carbon dioxide and particulate matter. There is scope for various technologies to be used in the cement manufacturing process for reducing emissions and energy consumption. This paper presents an analysis of various emission reduction approaches using alternative techniques/raw materials, energy saving (thermal and electrical) methods, process optimization/modifications, carbon capture and storage. However, financial and technical challenges remain significant barriers against sustainability initiatives in the clinker manufacturing process. Practical and feasible methods were applied to reduce nitrogen oxides, carbon dioxide and particulate matter emissions during the clinker manufacturing process. This study also shows the application of pinch technology for more economical energy usage. This study was conducted in the premises of Emami Cement Limited, Balodabazar (Chhattisgarh State), India. [ABSTRACT FROM AUTHOR]

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]

Climate model, a complex numerical representation of the global climate system, has been developed to simulate current climate and used to project future climatic conditions. Simulated climatic variables from climate models often exhibit significant deviations from observations. In climate projections, different approaches were introduced to deal with systematic deviations and random model errors. This paper demonstrates the intercomparison of four bias correction approaches (linear scaling, delta change correction, distribution mapping, and variance scaling) underlying the assumptions of stationary output from climate models. Mean monthly temperatures derived from five global climate models were corrected by four bias correction approaches for five states of southern India. The suitability of correction approaches depends upon the climate models and regional framework. The applied approaches improve the mean values and other statistical properties. The results show that all four bias techniques significantly improved the simulated data, but distribution mapping and variance scaling were more effective in removing systematic model biases. [ABSTRACT FROM AUTHOR]

Fishers' local knowledge and their perceptions of climate change are increasingly recognized by researchers and international institutions. However, in India, limited regional studies are available to understand the fishers' local knowledge, and a crucial question which largely remained unaddressed has been how fishers perceive the relevance of their local knowledge systems in the face of climate change. Provided this background, this paper aims to explore the fishermen's local knowledge and their climate perceptions in the face of climate change. This paper has employed the data that were obtained by in-depth interviews and focus-group discussions with the small-scale fishermen of three highly vulnerable fishing villages of Nagapattinam district, Tamil Nadu. The marine fishers across this coast were the victims of the 2004 Indian Ocean Tsunami disaster, several major cyclones, and various weather and climate events for over the last four decades. Key results show (1) fishermen perceive multiple aberrations and anomalies in the weather and climate patterns for over the previous three to four decades, particularly after the 2004 Indian Ocean Tsunami disaster. (2) The next finding is contrary to the conventional understandings, in which we have found that the fishermen are increasingly felt and experienced that their local knowledge is no longer adequately relevant in the face of climate change. Thus, for promoting the adaptive capacity of fishers, this paper has suggested that fishermen's perceptions and their expectations should be appropriately recognized and there is a strong need to provide scientific assistance to the fishermen through proper channels to respond to climate change impacts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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]

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]

India is severely affected by the COVID-19 pandemic and is facing an unprecedented public health emergency. While the country's immediate measures focus on combating the coronavirus spread, it is important to investigate the impacts of the current crisis on India's renewable energy transition and air quality. India's economic slowdown is mainly compounded by the collapse of global oil prices and the erosion of global energy demand. A clean energy transition is a key step in enabling the integration of energy and climate. Millions in India are affected owing to fossil fuel pollution and the increasing climate heating that has led to inconceivable health impacts. This paper attempts to study the impact of COVID-19 on India's climate and renewable energy transitions through machine learning algorithms. India is observing a massive collapse in energy demand during the lockdown as its coal generation is suffering the worst part of the ongoing pandemic. During this current COVID-19 crisis, the renewable energy sector benefits from its competitive cost and the Indian government's must-run status to run generators based on renewable energy sources. In contrast to fossil fuel-based power plants, renewable energy sources are not exposed to the same supply chain disruptions in this current pandemic situation. India has the definite potential to surprise the global community and contribute to cost-effective decarbonization. Moreover, the country has a good chance of building more flexibility into the renewable energy sector to avoid an unstable future. [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]

Vertical integration, which creates strategic linkages between national and sub-national levels, is being promoted as important for climate change adaptation. Decentralisation, which transfers authority and responsibility to lower levels of organisation, serves a similar purpose and has been in place for a number of decades. Based on four case studies in semi-arid regions in Africa and India, this paper argues that vertical integration for climate change adaptation should reflect on lessons from decentralisation related to governing natural resources, particularly in the water sector. The paper focuses on participation and flexibility, two central components of climate change adaptation, and considers how decentralisation has enhanced or undermined these. The findings suggest that vertical integration for adaptation will be strengthened if a number of lessons are considered, namely (i) actively seek equitable representation from marginal and diverse local groups drawing on both formal and informal participation structures, (ii) assess and address capacity deficits that undermine flexibility and adaptive responses, especially within lower levels of government, and (iii) use hybrid modes of governance that include government, intermediaries and diverse local actors through both formal and informal institutions to improve bottom-up engagement. [ABSTRACT FROM AUTHOR]

The present paper investigates the impact of future scenarios for the past two storms (namely, Vardah and Madi). These two storms had a different intensity over Bay of Bengal, India. The recent study in this region shows that the influence of these Tropical Cyclones (TC) may be severe in future climatic conditions. Different future Representative concentration pathways (RCP) scenarios are investigated in this study. The combined sea level rise (SLR) and high wind intensity in future scenarios has been investigated in the present study for their influence on maximum water level (MWL), wave climate and coastal inundations. The coupled surge and wave models are used to analyze the influence of SLR and wind intensity for different RCPs. The variations of MWL and inundation extent with increase and decrease in wind increment for different RCPs of the TC's were reported. Overall, for the Far Future RCP 8.5 scenario, the relative percentage of difference (compared to the current scenario) in MWL has increased by 135% for TC Vardah and 180% for TC Madi. Further, the flood area for TC's Vardah and Madi will increase by 70% and 95% compared to the current scenario. Finally, the study reveals that the extreme wind intensity of the TC's in future scenarios plays a significant contribution of up to 50% in coastal inundations. [ABSTRACT FROM AUTHOR]

An effort is made to understand the role of El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events on the malaria transmission intensity over India during the period 1951–2020 (70 years) with the help of a realistically simulated dynamical malaria model. The results suggest that the La Nina years pose a greater threat of malaria disease, especially in the densely populated Indian states. During El Nino years, the malaria transmission intensity and distribution over India greatly reduce, except in the regions such as Orissa, Chhattisgarh, Jharkhand, Western Ghats, parts of Madhya Pradesh, and Andhra Pradesh. It is found that in the positive IOD years, the malaria transmission intensity increases (decreases) over the entire central Indian region and along coastal regions of Tamil Nadu and Kerala (southern peninsular states of India and northeast India). An almost opposite behavior is seen during the negative IOD years. The malaria transmission variability over India is becoming increasingly heterogeneous in recent decades during the El Nino and La Nina years as a result of global warming. The period of 1986–2020 witnessed a substantial decrease (increase) in the malaria transmission intensity during the positive (negative) IOD years, except for a few regions of India. The implications of the results presented in the paper linking the ENSO and IOD signals with the intensity and distribution of malaria over India in a warming world are enormous, especially for the densely populated Indian states. [ABSTRACT FROM AUTHOR]

This paper aims to assess the disparities in vulnerability to climate change among the rural and urban population by taking the case of Madhya Pradesh, the central state of India. Madhya Pradesh is highly exposed to climate change, as evident by the historical and projected changes in climatic parameters. The impacts of climate change vary as per the dependence of the population on natural resource-intensive sectors and the relative socioeconomic development. The higher disparities in population composition, livelihood, infrastructural access, and other socioeconomic characteristics among rural and urban populations can influence their relative vulnerability to climate change. In this context, this study tries to understand how the spatiotemporal pattern of vulnerability to climate change differs in the rural and urban areas in three decades (1991, 2001 and 2011), using two sub-indices viz. Composite Social Vulnerability Index (CSVI) and Climate Index (CI). The CSVI is a weighted average of the Socioeconomic Vulnerability Index and Infrastructural Vulnerability Index. The CSVI is a weighted average of the Socioeconomic Vulnerability Index and Infrastructural Vulnerability Index. The results indicate that rural areas possess more social vulnerability than urban areas and, thus, are more vulnerable to climate change. CSVI scores and score of its subindices have reduced over time for both rural and urban population. However, the overall climate vulnerability has slightly increased from 2001 to 2011 due to the increase in mean CI in 2011. The study points out more targeted interventions for livelihood diversification, education, and infrastructural facilities in rural areas, especially in tribal dominated districts, in the context of increased climate change exposure in recent decades. [ABSTRACT FROM AUTHOR]

The present research study aims to analyze flood frequency to relate flood magnitudes with corresponding return periods. These estimates are crucial for the development of flood-preventive hydrological infrastructures and flood plain zoning, etc. Basin-wide high intensity of rainfall and high discharge from the upper riparian region during monsoon months creates flooding in the middle and lower reaches of the Ghagra River basin. Therefore, the flood estimates for three gauging sites situated on the mainstream of the Ghagra River viz., Elginbridge, Ayodhya, and Turtipar, have been comprehended using the Gumbel distribution (Extreme Value Type I) method and the Log-Pearson Type III distribution method. Flood estimates are calculated for 1.01, 1.05, 1.11, 1.25, 2, 5, 10, 20, 50, 100, 200, and 500 years return periods considering flood time series of 50 years to reduce estimation uncertainty. The findings of flood frequency analysis (FFA) revealed that the probability of occurrence of the flood is more than 80% at all three sites because Ghagra River can carry around 7800 to 9000 m3/s of water discharge without posing a high risk of levee break. The upper and lower limits of discharge carrying capacity depend on the river's desiltation process. Hence, the flood occurs almost every year in the basin; its only variation is its severity. The rainfall-runoff relationship is estimated by integrating a simple linear model and for rainfall trend analysis Mann-Kendall is applied. Linear regression analysis-based rainfall-runoff relationship outcomes revealed a significant relationship with a positive correlation coefficient i.e., 0.2722 for Elginbridge, 0.39624 for Ayodhya, and 0.4844 for Turtipar gauging site in the monsoon season but other factors like a high amount of water discharge from dams in upper riparian regions, etc. are also responsible for flooding in the middle and lower reaches. The Mann-Kendall trend analysis shows a decrease in annual average rainfall and rainfall in the monsoon season. Discharge variability indicates the direct relationship between flood fury and changes in climatic patterns in recent decades. This paper identifies that future research is needed to better inform the policy planners who strive to design sustainable infrastructure. [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]

Climate change is a major concern the world over more so for a predominantly agrarian country like India. In this paper we analyze the time horizon dynamics of crop and climate variables at the regional level in India. We also analyze the co-movements of crop yields with temperature and rainfall to observe the coherence across heterogenous time horizons. We employ Bai-Perron structural break and Continuous wavelet transform methods on yearly data of seven crop yields and climate variables. Observed variables are analyzed from 1956 to 2010 for the un-divided state of Andhra Pradesh, India. Breakpoint analysis shows an increase of around 1.0° temperature with two observed break points. Rainfall depicts no systematic change with fluctuations being largely random. The framework of wavelets-based time–frequency analysis employed in this study captures climate and crop dynamics at heterogeneous time horizons, allowing one to study the impact of climate and crop yields at both short and longer time-horizons. Wavelet based coherence analysis exhibited significant co-movement between climatic and crop variables. Given shifts in climate patterns and subsequent shifts in co-movements across time horizons at the regional level, policy makers and crop scientists should design time specific and locally viable adaption and mitigation policies to tackle the impact of climate change on crops and livelihoods. [ABSTRACT FROM AUTHOR]

The paper contributes to the growing literature highlighting the significance of assessing risk and vulnerability, micro-level perceptions and adaptation decision-making in building resilience of farm communities to climate change in dryland region of India. To select a region for grassroots enquiry, spatial differential in risk to climate change was assessed in Rajasthan, using IPCC AR5 framework. Among the highly vulnerable and risky districts, Bikaner district was selected for elicitation of micro-level imperatives. Rising atmospheric temperature, inter-seasonal displacements of rainfall and recurrence of extreme events were perceived by the farmers resulting in resource degradation, production risks and erosion of households' socio-economic dynamics. As risk preventive measures, suitable adjustment in agricultural practices, natural resource management, shift to off-farm activities and other relief measures were adopted by the farmers. Farmer's choice of adaptation was influenced by several climatic, socio-economic and infrastructural & institutional factors in varying degree. Moreover, several financial, economic, infrastructural and informational bottlenecks to adaptations were reported during household survey and FGDs. The results suggest that capturing grassroots evidence is crucial for directing locally tailored adaptation strategies, along with the improving deficiencies in the developmental pathways for climate-resilient agriculture. [ABSTRACT FROM AUTHOR]

Biodiversity is continually transformed by a changing climate. Conditions change across the face of the planet at variable pace leading to rearrangements of biological associations. The carbon cycle and the water cycle, arguably the two most important large-scale processes for life on Earth; depend on biodiversity at genetic, species, and ecosystem levels and can yield feedbacks to climate change. India is no less affected through this feedback mechanism of climate change and had shown its cause and effect association in several studies. In this special issue we present 25 papers contributed by ca 90 authors from India and elsewhere those discuss wide-ranging aspects of biodiversity and climate change. These contributions are based on presentations made at the 2nd International Workshop on Biodiversity and Climate Change (BDCC-2018) held on 24–27-February 2018 at the Indian Institute of Technology Kharagpur, India. The papers are arranged in six sections: Plant (and lichen) Diversity and Climate; Plant Diversity Pattern and Environmental Heterogeneity; Forest Biomass and Carbon; Plant Diversity and Remote Sensing; Species Distribution Modelling; and Animal Diversity, Soil and Biotechnology. Included amongst the contributions are ones using a national database on plant diversity, describing vegetation carbon and biomass sequestration patterns, utilizing remote sensing to assess plant diversity proxies and conservation prioritization, employing species distribution models to analyze climate change scenarios, using acoustics indices for rapid assessment of biodiversity, addressing the soil micro-biome and environmental stress on medicinal plants. [ABSTRACT FROM AUTHOR]

Global warming is the average temperature of the earth's surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Designing of a sustainable forest policy is of extreme importance in our present world where the process of rapid economic growth is causing imbalance in the climatic cycles by denying ecosystems sufficient time for adaptation and the socioeconomic systems adequate opportunity for mitigation. In this paper, the forests are considered highly resilient natural resource that plays a major role in reducing the impact of global climate change through carbon sequestration, heat absorption, watershed protection, acid deposition, etc. This paper examines the prospect of sustainable forest management for an emerging economy like India, where forest coverage has gone up over the last three decades in spite of population growth, rapid urbanization, and fast economic growth. To assess the possibility of sustainable future growth in a globally congenial environment, the extent of ecological stress on Indian economy has been checked and pattern of public as well as private expenditure along with import and export of forestry and related products analyzed. The import of forestry-based products are increasing in terms of volume, value and unit prices throughout this period and the major importers of raw and semi-finished forestry-based inputs are the South and East Asian countries. From the perspective of material balance, the results of structural decomposition analysis reveal increasing dominance of economic growth over other effects indicating necessity of designing intervention to decouple potential future economic growth from forest resources to ensure long run sustainability. [ABSTRACT FROM AUTHOR]

Cement is a basic requirement of today's society and is the only thing that humans consume more volume than water, but cement manufacturing is the most energy- and emission-intensive process. Hence, the cement industry is currently under pressure to reduce greenhouse gases (GHGs) emissions. Climate change mitigation strategies implemented in the industry leads to GHGs reduction, climate risks, pollutants, and another adverse impact on the environment. In order to implement climate change mitigation strategies in the cement industry, a careful analysis of barriers that hinder the emission reduction must be taken. However, most existing research on the barriers to mitigation measures is focused on developed countries. Among the most important emerging economies, India, the second-largest producer and consumer of cement, faces challenges to implement emission reduction measures. To bridge this gap, this paper identifies and evaluates the barriers and solutions to overcome these barriers in the context of India. This study employs a three-phase methodology based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify barriers and solutions to overcome these barriers to climate change mitigation strategies adoption in Indian cement industry. Fuzzy AHP is employed to prioritize these barriers, and to rank solutions of these barriers, Fuzzy TOPSIS is employed. Ten Indian cement manufacturing industry is taken to illustrate the proposed three-phase methodology. Finally, the result of the analysis offers an effective decision support tool to the Indian cement industry to eliminate and overcome barriers to mitigation strategies adoption and build their green image in the market. [ABSTRACT FROM AUTHOR]

The aim of this paper is to understand the historical and future climate change situation using 15 extreme precipitation indices in the Pare watershed of Arunachal Pradesh, India. Historical period (1981–2019) and future period (2021–2050) precipitation data are used to compute extreme precipitation indices in RClimDex software. The Pare watershed was divided into 13 subwatersheds; however, the results of the study showed no significant spatial variation. This study found that majority of the precipitation extreme indices are showing decreasing trends during the historical period and most of them are statistically insignificant at 95% confidence level. Only three indices such as SDII, CWD and MRI are found significant at 0.05 level in the Pare watershed. Though not significant, the annual precipitation amount in the Pare watershed was found decreasing at the rate of 3.3 mm per year during the study period. The trend analysis over the whole watershed indicated significant decreasing trends for CWD and MRI while indicating significant increasing trend for SDII. The representative concentration pathway (RCP) 4.5 and 8.5 projected the extreme precipitation indices in a very similar way. The results of the trend analysis under RCP 8.5 showed significant decreasing trend only at SW10 for the index-moderate rainfall index (MRI). Various cases of RX1DAY and RX5DAY not falling during the months of monsoon were observed in both the historical and future periods. The percentage departures of the monsoon from its annual total had increased in RCP 4.5 and RCP 8.5 scenarios as compared to the historical periods. The results of this climatic investigation suggest that the precipitation regime in the study area had been accompanied and also expected by overall reduction in precipitation amount, milder rainfall events, reduction in monsoon (June–September) rainfall and drier climatic conditions. With the prevalent historical scenario and future projected scenarios of the extreme precipitation indices, the water resource potential in the study area is expected to be greatly reduced, for which the authors seek the attention of various stakeholders in water and allied sectors to come together and discuss on the construction of water conservation structures so that agricultural activities can be expanded and remain sustainable. [ABSTRACT FROM AUTHOR]

Global warming is a biggest issue around the world. In this research paper, the temporal and spatial trend analysis of seasonal and annual rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat state of India has been analysed using the data of 11 rain gauge stations installed in Bhogavo watershed. Linear regression, Mann–Kendall Test, Sen's slope test and innovative trend analysis methods are used to carry out monthly and annual rainfall trend analysis. In addition to the rainfall analysis, a number of rainy days change in magnitude as a percentage of mean rainfall have also been analysed using linear regression and Sen's slope method, respectively. The IDW method is used to develop a spatial distribution of annual and seasonal rainfall trend over the study area. From the results, it is concluded that annual rainfall shown increasing (positive) trend at nine stations out of 11 stations. The highest value of change in magnitude of trend as a percentage of mean monthly rainfall has been obtained in the month of July, attributing increasing trend at Sayla station and lowest value magnitude of trend as a percentage of mean rainfall in the monthly rainfall has been obtained in the month of August, attributing decreasing trend at Bavla station. [ABSTRACT FROM AUTHOR]

Globally, agriculture is recognized as a highly vulnerable sector to climate change and risks from climatic aberrations pose an imminent danger to the food security and sustainability of livelihoods. To bring robustness in climate adaptation planning, evaluation of resilience across homogenous regions is essential for developing and scaling suitable location-need-context specific interventions and policies that build the resilience of the agricultural system. In this paper, we present an analysis and discussion of multi-scalar and multi-indicator assessment, by profiling resilience across agro-climatic zones of India, based on the development of a Climate-Resilient Agriculture Index embracing environmental, technological, socio-economic, and institutional and infrastructural dimension. A total of 26 indicators, spread across these four dimensions, were employed to purport inter- and intra-agro-climatic zone differentials in the level of resilience. Among the zones, it was found that West Coast Plains & Ghats and Tans-Gangetic Plains had the highest degree of resilience to manage climate risks. Most of the districts lying within Eastern Himalayan Region, Middle Gangetic Plains, Eastern Plateau & Hills, and Western Dry Region had a lower degree of resilience. The study places greater emphasis on deciphering region-specific drivers and barriers to resilience at a further disaggregated scale for improving rural well-beings. It is construed that devising action plans emphasizing awareness, preservation of natural resources, diversification, building physical infrastructure, strengthening of grass-root institutions, and mainstreaming climate adaptation in the developmental policy is crucial for climate-resilient pathways. [ABSTRACT FROM AUTHOR]

The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today's 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a "no-regret option" in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits. [ABSTRACT FROM AUTHOR]

This paper examines climate change adaptation and gender issues through an application of a feminist intersectional approach. This approach permits the identification of diverse adaptation responses arising from the existence of multiple and fragmented dimensions of identity (including gender) that intersect with power relations to shape situation-specific interactions between farmers and ecosystems. Based on results from contrasting research cases in Bihar and Uttarakhand, India, this paper demonstrates, inter alia, that there are geographically determined gendered preferences and adoption strategies regarding adaptation options and that these are influenced by the socio-ecological context and institutional dynamics. Intersecting identities, such as caste, wealth, age and gender, influence decisions and reveal power dynamics and negotiation within the household and the community, as well as barriers to adaptation among groups. Overall, the findings suggest that a feminist intersectional approach does appear to be useful and worth further exploration in the context of climate change adaptation. In particular, future research could benefit from more emphasis on a nuanced analysis of the intra-gender differences that shape adaptive capacity to climate change. [ABSTRACT FROM AUTHOR]

Climate change poses major challenges to agricultural systems in drought prone regions of the world especially in the areas with high poverty, lack of irrigation facilities and low productivity. Towards this it is essential to understand the climate change perceptions, adaptation practices and barriers to effective adaptation at household and community level. This paper using household surveys and focus group discussions in one of the drought prone areas of Odisha in India, explores various aspects of perception on climate change and barriers to adaptation. It also analyses the accuracy of perceptions based on rainfall data from nearest meteorological stations. The study reinforces the argument by earlier studies that the perception by people simply cannot be wrong because they may have a just a low correlation with underlying meteorological data. Results suggest that farmers increasingly perceive the changes in the rainfall and temperature patterns. However, when compared with the trend in actual rainfall data, perceptions on rainfall are found to more closely align with the results from the nearest station as compared to the station farther from it. Analysis revealed that seasonal rainfall variability has a profound influence on the farmers' perceptions on climate change and drought in the study region. Farmers' are still dependent on the traditional forecasting system because of the lack of access to modern climate forecasting and tailored information for agricultural practice. Although farmers in the study region are already adapting to the changing climate, the study finds that while lack of access to water and irrigation, information on climate change adaptation and early warning systems are major barriers to adaptation at the household level lack of government intervention, lack of knowledge on drought resistant crops and varieties and lack of renovation of water bodies and irrigation were mentioned as the major barriers at the community level. Findings from the paper argue for better adaptation planning at the local level incorporating local level perceptions and barriers to adaptation. In such areas local level planning can be crucial in enhancing the adaptive capacity of the farmers. [ABSTRACT FROM AUTHOR]

The floodplain wetlands in different regional settings vary with time and space in terms of function and geomorphological diversity. In recent decades, these eco-sensitive waterbodies have been exposed to a wide range of anthropogenic threats and climatic changes. Therefore, assessment of these ecological and environmental threats is prerequisite to understand the state of ecosystem and to develop a sustainable management strategy for conservation of wetland biodiversity and fisheries enhancement. This paper discusses the region-specific pattern of trophic state index (TSI) of the 27 floodplain wetlands in West Bengal, India. Carlson TSI and Lamparelli TSI methods were used to determine a better approach based on historical and continuous dataset and to delineate the interrelationship among historical climatic variability for sustainable management of the resources. The study revealed that agro-climatic divisions do not unveil any significant impact on the TSI calculated using Carlson TSI as well as Lamparelli TSI method. The TSI scores for the two methods were significantly different (p < 0.01) for different zones based on wetland habitat types. The TSI scores revealed most of the wetlands to be in mesotrophic state. Principal component analysis (PCA) indicated that TSI scores were having similar pattern of variation with rainfall and water temperature. The present study also conveys fundamental information on ecological status based on the trophic state, which will aid to develop region-specific strategies for sustainable fisheries enhancement. [ABSTRACT FROM AUTHOR]

Assessment of climate and land use changes impact including extreme events on the sediment yield is vital for water and power stressed countries. Mangla Reservoir is the second-largest reservoir in Pakistan, and its capacity is being reduced due to rapid sedimentation and will be threatened under climate and land use changes. This paper discusses the consequences of climate and land use change on sediment yield at Mangla Dam using General Circulation Models (GCMs), Land Change Modeler (LCM), Soil and Water Assessment Tool (SWAT) model after calibration and validation. Results show that over the historical period temperature is observed to increase by 0.10oC/decade and forest cover is observed to reduce to the level of only 16% in 2007. Nevertheless, owing to the forest conservation policy, the forest cover raised back to 27% in 2012. Anticipated land use maps by using LCM of 2025, 2050 and 2100 showed that the forest cover will be 33%, 39.2%, and, 53.7%, respectively. All seven GCMs projected the increase in temperature and five GCMs projected an increase in precipitation, however, two GCMs projected a decrease in precipitation. Owing to climate change, land use change and combined impact of climate and land use change on annual sediment yield (2011-2100) may vary from -42.9% to 39.4%, 0% to -27.3% and, -73% to 39.4%, respectively. Under climate change scenarios projected sediment yield is mainly linked with extreme events and is expected to increase with the increase in extreme events. Under land use change scenarios projected sediment yield is mainly linked with the forest cover and is expected to decrease with the increase in forest cover. The results of this study are beneficial for planners, watershed managers and policymakers to mitigate the impacts of climate and land use changes to enhance reservoir life by reducing the sediment yield. [ABSTRACT FROM AUTHOR]

It is important to estimate a high-resolution spatiotemporal distribution of temperature rise under climate change for effective adaptation and mitigation planning. This paper studies the threshold crossing time (TCT) for eight Indian warming targets (IWTs) between 1.5 and 5 °C based on regional climate models (RCMs) participating in The Coordinated Regional Downscaling Experiment (CORDEX)—South Asia project. To evaluate the performance of CORDEX experiments in simulating the near-surface mean temperature, the model performance index (MPI) is used which represents that the CanESM experiment performs best for simulating Tmean over India. All India average Tmean projected by the multi-model ensemble (MME) represents that 1.5 °C TCT is about 2033 ± 3 and 2028 ± 3 in RCP4.5 and RCP8.5 scenarios, respectively. During the twenty-first century, Indian subcontinent can experience five IWTs (1.5–3.5 °C) under RCP4.5 and all eight under scenario RCP8.5. The fastest warming region in India is the western Himalayan region (North India) and north-west region (Indian Thar Desert). [ABSTRACT FROM AUTHOR]

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India. [ABSTRACT FROM AUTHOR]

Adaptation to environmental change, including biodiversity change, is both a new imperative in the face of global climate change and the oldest problem in human history. Humans have evolved a wide range of adaptation strategies in response to localised environmental changes, which have contributed strongly to both biological and cultural diversity. The evolving set of locally driven, 'bottom-up' responses to environmental change is collectively termed 'autonomous adaptation,' while its obverse, 'planned adaptation,' refers to 'top-down' (from without, e.g. State-driven) responses. After reviewing the dominant vulnerability, risk, and pathway approaches to adaptation, this paper applies an alternative framework for understanding human adaptation processes and responding more robustly to future adaptation needs. This adaptation processes-to-pathways framework is then deployed to consider human responses to biodiversity change caused by an aggressive 'invasive' plant, Lantana camara L., in several agri-forest communities of southern India. The results show that a variety of adaptation processes are developing to make Lantana less disruptive and more useable—from avoidance through mobility strategies to utilizing the plant for economic diversification. However, there is currently no clear synergy or policy support to connect them to a successful long-term adaptation pathway. These results are evaluated in relation to broader trends in adaptation analysis and governance to suggest ways of improving our understanding and support for human adaptation to biodiversity change at the household, community, and regional livelisystem levels, especially in societies highly dependent on local biodiversity for their livelihoods. [ABSTRACT FROM AUTHOR]

While much of the literature on future food consumption in India in the decades ahead focuses on cereals, this paper presents estimates of potato demand to the year 2030 according to three different scenarios. Estimated increases in total food demand for potato range from 20 to 30 million metric tonnes and from 5.5 to 15 kg capita−1 year−1, with modest, if any, increases in foreign trade. These estimates highlight the potato's growing importance in Indian diets as food consumption patterns continue to evolve while maintaining their traditional roots. They also call for a series of public and private initiatives to facilitate the realization of the potato's potential future contribution to food consumption and nutrition in India. These include renewed support for research and development as relates to improved technologies for the potato sector both on and off the farm. It also involves opportunities for industry to combine market-driven innovations to achieve commercial success with benefits for growers, consumers and the environment as well. [ABSTRACT FROM AUTHOR]

This paper attempts to assess the vulnerability to climate change of human communities in selected mouzas of Sagar Island, South 24 Parganas District of India. A primary household survey has been conducted to collect data on socio-demographic profile, livelihood strategy, health, food, water, social network, natural disaster and climate variation indicators, were selected for Livelihood Vulnerability Index (LVI) and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) analyses to measure and compare the vulnerability of mouzas (administrative unit) currently suffering from frequent flooding, coastal erosion and embankment breaching on an annual basis. Secondary data collected from the Indian Meteorological Department, the Water Resources Information System of India and the Global Sea Level Observing System have been used to identify dynamics of climate change by employing statistical and Geographic Information System (GIS) techniques. A GPS survey has been conducted to identify locations of embankment breaching, and satellite images obtained from the National Aeronautics and Space Administration and U.S. Geological Survey (NASA USGS) Government website have been applied to shoreline and land use change detection, using a supervised maximum likelihood classification. The results indicate that the study area has experienced increasing temperature, changing precipitation patterns, rise in sea level, higher storm surges, shoreline change, constant land loss, embankment breaching and changing land use, which have had impact on vulnerability, particularly of poorer people. The LVI (0.48 to 0.68) and LVI-IPCC (0.04 to 0.14) scores suggest that the populations of Dhablat, Bankimnagar, Sumatinagar, Muri Ganga and Sibpur mouzas are highly vulnerable (LVI scores of 0.60 to 0.68 and LVI-IPCC scores of 0.11 to 0.14) to climate change both because the communities are more exposed to it, and because poor access to food, health facilities and water makes them extremely sensitive to it and lowers their adaptive capacity. The findings of this study could be crucial to framing further development and adaptation strategies relating to climate change, and to safeguarding the estuarine ecosystem and the vulnerable population. [ABSTRACT FROM AUTHOR]

Impacts of global warming and local scale urbanization on precipitation are evident from observations; hence both must be considered in future projections of urban precipitation. Dynamic regional models at a fine spatial resolution can capture the signature of urbanization on precipitation, however simulations for multiple decades are computationally expensive. In contrast, statistical regional models are computationally inexpensive but incapable of assessing the impacts of urbanization due to the stationary relationship between predictors and predictand. This paper aims to develop a unique modelling framework with a demonstration for Mumbai, India, where future urbanization is projected using a Markov Chain Cellular Automata approach, long term projections with climate change impacts are performed using statistical downscaling and urban impacts are simulated with a dynamic regional model for limited number of years covering different precipitation characteristics. The evaluation of the statistical downscaling methodology over historical time period reveals large underestimation of the extreme rainfall, which is improved effectively by applying another regression model, for extreme days. The limited runs of dynamic downscaling models with different stages of urbanization for Mumbai, India, reveal spatially non uniform changes in precipitation, occurring primarily at the higher quantiles. The statistical and dynamical outputs are further integrated using quantile transformation for precipitation projection in Mumbai during 2050s. The projections show dominant impacts of urbanization compared to those from large scale changing patterns. The uniqueness of this computationally efficient framework lies in an integration of global and local factors for precipitation projections through a conjugal statistical–dynamical approach. [ABSTRACT FROM AUTHOR]

The global incidence of very intense cyclones has increased in recent decades with climate projections signaling that this trend will intensify. To what degree can vulnerability to extreme weather events be mitigated by access to a rural livelihoods program, particularly with regard to the impacts on women? This paper addresses this question through a natural experiment arising from two independent but overlapping sources of variation: exposure to a devastating cyclone that occurred in the Bay of Bengal region of India and the staggered rollout of a rural livelihoods intervention. Comparisons from household surveys across communities more or less exposed to the storm before and after the introduction of the program reveal that the storm led to significant reductions in overall household expenditure, and that these reductions were indeed the largest for women, adding to the emerging evidence for the frequently-posed hypothesis that women bear the brunt of the effects of disasters on overall household consumption. Participation in the livelihoods program mitigated some of the reductions in household nonfood expenditure and women's consumption, but not on food expenditure. These results from a densely populated region whose topography makes it particularly vulnerable to storms can inform future policy approaches and aid in modeling the impact of these policies on the effects of climate change. [ABSTRACT FROM AUTHOR]

India's position on climate change negotiations is likely to have far reaching implications for the success of global climate cooperation. Since the beginning of negotiations, the principle of equity and common but differentiated responsibilities (CBDR) remained the centerpiece of India's stand. The stand started to evolve at the 15th Conference of Parties to the United Nations Framework Convention on Climate Change at Copenhagen in 2009, when India accepted voluntary commitments to reduce emission intensity. Though India still swears by CBDR, status of the principle in the negotiations has become doubtful after the Durban Climate Conference in 2011 committed all parties to take emission targets. This paper traces major transition points in India's negotiating position over the years and provides a descriptive context of its climate-related concerns. It analyzes the interview responses of 15 top scientists, experts, and negotiators to build upon core areas of climate change issues in India, its future role, and position in negotiations. Interviewees, in general, were in favor of protecting the carbon space for the poor who had very low emissions. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions in China and India have been increasing rapidly over the last decade. Scenario studies can provide insight into expected future trends and the emission reduction potential in these regions. The scenarios show that growing population, gross domestic product, and energy demand are likely to lead to a further increase in emissions. At the same time, a decreasing emission intensity would still allow to create decarbonization scenarios in line with the requirements for reaching a maximal warming of 2 °C. There is, however, a wide range of assumptions across these studies. Based on the literature review, this paper observes that key assumptions in scenarios developed by national institutes in China and India differ from those presented by international studies or modeling teams. We explore how this-and other factors like data availability-may influence the interpretation of the scenarios and how international and national modeling groups could learn from each other. Our main recommendation is for more extensive collaboration between national and international research groups, so that national and international scenario studies can be compared in more detail in order to support international negotiations. [ABSTRACT FROM AUTHOR]

Given the general notion that dynamical downscaling leads to added accuracy in both historical simulations as well as climate change projections, this paper investigates its validity over India using historical data (1975-2005) from the CORDEX models and their driving global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5), and comparing them against observed temperature and rainfall. We find that downscaling invariably leads to an improvement in the spatial pattern of surface air temperature, but compared to the driving GCMs, the errors in magnitude after downscaling are even worse in some cases. In regard to JJAS rainfall simulations, the CMIP5 driving GCMs are found to be superior to their dynamically downscaled counterparts both in terms of spatial patterns as well as magnitude of errors. Both CMIP5 driving GCMs as well as the CORDEX models underestimate rainfall during JJAS; however, negative bias in CORDEX models is worse. Unlike the driving CMIP5 GCMs, their dynamically downscaled counterparts simulate an early onset followed by a slow and late withdrawal of the Indian summer monsoon rainfall. The frequency of occurrence of rainfall intensities is simulated well by both sets of models in the lower intensity regime (0-20 mm/day); however, for higher intensities, the driving CMIP5 GCMs underestimate whereas the CORDEX models overestimate. [ABSTRACT FROM AUTHOR]

Urbanisation and climate change can have adverse effects on the streamflow and water balance components in river basins. This study focuses on the understanding of different hydrologic responses to climate change between urban and rural basins. The comprehensive semi-distributed hydrologic model, SWAT (Soil and Water Assessment Tool), is used to evaluate how the streamflow and water balance components vary under future climate change on Bharalu (urban basin) and Basistha (rural basin) River basins near the Brahmaputra River in India based on precipitation, temperature and geospatial data. Based on data collected in 1990-2012, it is found that 98.78% of the water yield generated for the urban Bharalu River basin is by surface runoff, comparing to 75% of that for the rural Basistha basin. Comparison of various hydrologic processes (e.g. precipitation, discharge, water yield, surface runoff, actual evapotranspiration and potential evapotranspiration) based on predicted climate change scenarios is evaluated. The urban Bharalu basin shows a decrease in streamflow, water yield, surface runoff, actual evapotranspiration in contrast to the rural Basistha basin, for the 2050s and 2090s decades. The average annual discharge will increase a maximum 1.43 and 2.20 m3/s from the base period for representative concentration pathways (RCPs) such as 2.6 and 8.5 pathways in Basistha River and it will decrease a maximum 0.67 and 0.46 m3/s for Bharalu River, respectively. This paper also discusses the influence of sensitive parameters on hydrologic processes, future issues and challenges in the rural and urban basins. [ABSTRACT FROM AUTHOR]

Climate change adds another dimension of challenges to the growth and sustainability of Indian agriculture. The growing exposure to livelihood shocks from climate variability/change and limited resource base of the rural community to adapt has reinforced the need to mainstream climate adaptation planning into developmental landscape. However, a better understanding of micro-level perceptions is imperative for effective and informed planning at the macro-level. In this paper, the grass-root level perspectives on climate change impacts and adaptation decisions were elicited at farm level in the Moga district of Punjab and Mahbubnagar district of Telangana, India. The farmers opined that the climatic variability impacts more than the long-term climate change. They observed change in the quantum, onset and distribution of rainfall, rise in minimum as well as maximum temperature levels, decline in crop yield and ground water depletion. The key socio-economic effects of climate change included decline in farm income, farm unemployment, rural migration and increased indebtedness among farmers. In order to cope with climate variability and change thereon, farmers resorted to adaptation strategies such as use of crop varieties of suitable duration, water conservation techniques, crop insurance and participation in non-farm activities and employment guarantee schemes. Farmers’ adaptation to changing climate was constrained by several technological, socio-economic and institutional barriers. These include limited knowledge on the costs-benefits of adaptation, lack of access to and knowledge of adaptation technologies, lack of financial resources and limited information on weather. Besides, lack of access to input markets, inadequate farm labour and smaller farm size were the other constraints. Further, on the basis of the grass-root elicitation a ‘Need-Based Adaptation’ planning incorporating farmers’ perceptions on climate change impacts, constraints in the adoption of adaptation strategies and plausible adaptation options were linked with the most suitable ongoing programmatic interventions of the Government of India. The study concluded that micro-level needs and constraints for various adaptation strategies and interventions should be an integral part of the programme development, implementation and evaluation in the entire developmental paradigm. [ABSTRACT FROM AUTHOR]

Floodplain wetlands of India are biologically rich sensitive ecosystem that support unique aquatic biodiversity and play vital role in providing livelihood and nutritional security to a large section of the population of the country. Besides contributing to the environmental sustainability through Carbon sequestration, flood plain wetlands also serve as source for harvesting flood and rain water. Covering around 5.5 Lakh ha area, the flood plain wetlands of India are one of the major sources for fish production of the country, offering vast potential for capture as well as culture based fisheries. Degradation and shrinkage of the floodplain wetlands have been recorded due to several natural and anthropogenic reasons. In addition to that, the change in the climatic condition may have a far more devastating impact on these natural resources. Substantial change in climate with increasing temperature trend (0.60 °C during last 112 years) as well as changing pattern and intensity of rainfall have been reported in India. It is projected that extreme climate changes may have profound impact on wetlands, mediated through several direct or indirect pathways. Attention is urgently required at different levels for conservation and revamping of these resources along with coping up and mitigation strategies to address the impending challenges. However, there is dearth of scientific information specific to the flood plain wetlands of India. This paper reviews the present status and importance of the flood plain wetlands of India with special reference to impact of climate change along with coping-up and mitigation measures. [ABSTRACT FROM AUTHOR]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [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]

This paper examines the relationship between local institutions and adaptation to climate variability in four semi-arid villages in India. Based on a qualitative survey, it draws attention to the constraints that farming households face, the role of institutions, and the implications for their capacities to adapt. Using an institutional framework, the study examines the role of local institutions in facilitating community adaptation to perceived climate variability. It was found that at the institutional and community level farmers rely on government schemes that provide social safety nets and the private sector such as moneylenders as sources of adaptation options regarding access to credit. Serious constraints emerged, however, in terms of adaptation to what may be a more challenging future. These constraints were further explored by means of grounded theory. The lack of collective feeling and action has hindered bargaining for better market prices and the development of alternate livelihood options. The need for better financial inclusion and access to more formal systems of finance is necessary to increase the overall adaptive capacity of households. During crisis situations or climatic shocks, the absence of these systems means the sale of household assets and resources especially among small and landless groups of farmers. Overall, rural households perceive that public, civic, and private institutions play a significant role in shielding them against the adverse effects of climate variability. The perceived importance of different institutions is, however, different across different categories of farmers, women, and labourers. [ABSTRACT FROM AUTHOR]