Rajat Agrawal, Suraj Kumar Singh, S. Kanga, Bhartendu Sajan, Gowhar Meraj, Pankaj Kumar
This study utilises a comprehensive, multi-layered approach to assess flooding susceptibility in a specific area, integrating diverse environmental datasets such as JRC Global Surface Water, Landsat 8 images, and SRTM elevation data. Employing the GEE FMA, a powerful tool leveraging Google Earth Engine capabilities, the analysis covers water occurrence, permanent water, elevation, distance to water, topographic hazard score, and vegetation indices (NDVI and NDWI). The Water Occurrence layer establishes a foundational understanding of water-body distribution’s correlation with flood vulnerability, while Permanent Water refines this understanding. Distance to Water measures proximity for targeted risk evaluation, and Elevation identifies vulnerable regions based on topography. The GEE FMA synthesises these layers into a Flood Hazard Susceptibility map, categorising vulnerability into Very Low, Low, Medium, High, and Very High. This nuanced understanding is crucial for prioritising interventions. The GEE FMA’s rapid processing speed makes it an invaluable tool for short-term decision support in flood hazard disaster management, offering insights for informed decision-making and resilient infrastructure development. The Topographic Hazard Score provides information on how topography influences flood risk, while the Wetness Hazard Score categorises moisture conditions for identifying flood-prone locations. Decision-makers rely on these values for quick and precise flood susceptibility assessments. In an era of climate uncertainties and urbanisation, the GEE FMA emerges as a reliable tool for decision-making, mitigating flood impacts, and developing effective flood risk management strategies.
{"title":"Advancing Flood Risk Assessment through Integrated Hazard Mapping: A Google Earth Engine-Based Approach for Comprehensive Scientific Analysis and Decision Support","authors":"Rajat Agrawal, Suraj Kumar Singh, S. Kanga, Bhartendu Sajan, Gowhar Meraj, Pankaj Kumar","doi":"10.3233/jcc240007","DOIUrl":"https://doi.org/10.3233/jcc240007","url":null,"abstract":"This study utilises a comprehensive, multi-layered approach to assess flooding susceptibility in a specific area, integrating diverse environmental datasets such as JRC Global Surface Water, Landsat 8 images, and SRTM elevation data. Employing the GEE FMA, a powerful tool leveraging Google Earth Engine capabilities, the analysis covers water occurrence, permanent water, elevation, distance to water, topographic hazard score, and vegetation indices (NDVI and NDWI). The Water Occurrence layer establishes a foundational understanding of water-body distribution’s correlation with flood vulnerability, while Permanent Water refines this understanding. Distance to Water measures proximity for targeted risk evaluation, and Elevation identifies vulnerable regions based on topography. The GEE FMA synthesises these layers into a Flood Hazard Susceptibility map, categorising vulnerability into Very Low, Low, Medium, High, and Very High. This nuanced understanding is crucial for prioritising interventions. The GEE FMA’s rapid processing speed makes it an invaluable tool for short-term decision support in flood hazard disaster management, offering insights for informed decision-making and resilient infrastructure development. The Topographic Hazard Score provides information on how topography influences flood risk, while the Wetness Hazard Score categorises moisture conditions for identifying flood-prone locations. Decision-makers rely on these values for quick and precise flood susceptibility assessments. In an era of climate uncertainties and urbanisation, the GEE FMA emerges as a reliable tool for decision-making, mitigating flood impacts, and developing effective flood risk management strategies.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140225714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nguyen Phuoc Cong, Tran Van Hung, Bui Thi Bich Lien, D. V. Duy, Pankaj Kumar, T. Ty
Can Tho City is located in the middle of the Mekong Delta, where the effects of climate change have been and will continue to be considerable. According to climate change predictions, the city is one of five regions that could be affected. In this study, we conducted analysis of trends of Tmax and Tmin over 39 years using monthly temperature in Can Tho City. We employed a Box plot, Mann–Kendall test, and Sequential Trend Analysis (SMK). Tmax and Tmin increased for all 12 months from 1984 to 2022, with Sen’s slopes of 0.45°C/decade and 0.29°C/decade, respectively. Although Tmin shows a slower rate of increase than Tmax, the increase in Tmin indicates that the temperature in Can Tho has risen.
{"title":"Trend Analysis of Maximum and Minimum Temperature in Can Tho City, Viet Nam","authors":"Nguyen Phuoc Cong, Tran Van Hung, Bui Thi Bich Lien, D. V. Duy, Pankaj Kumar, T. Ty","doi":"10.3233/jcc240002","DOIUrl":"https://doi.org/10.3233/jcc240002","url":null,"abstract":"Can Tho City is located in the middle of the Mekong Delta, where the effects of climate change have been and will continue to be considerable. According to climate change predictions, the city is one of five regions that could be affected. In this study, we conducted analysis of trends of Tmax and Tmin over 39 years using monthly temperature in Can Tho City. We employed a Box plot, Mann–Kendall test, and Sequential Trend Analysis (SMK). Tmax and Tmin increased for all 12 months from 1984 to 2022, with Sen’s slopes of 0.45°C/decade and 0.29°C/decade, respectively. Although Tmin shows a slower rate of increase than Tmax, the increase in Tmin indicates that the temperature in Can Tho has risen.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140226807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Harsh Taneja, Rohan Verma, Prabhdeep Singh, Kiran Deep Singh
Innovative solutions are necessary for efficient monitoring and mitigation techniques as climate change increases the frequency and severity of natural catastrophes. In this study, we investigate how Cloud Internet of Things (IoT) might help mitigate climate-related calamities. Through the use of cloud computing and sensor networks, Cloud IoT facilitates the capture, processing, and distribution of data in near-real time. This strategy promotes catastrophe planning, response, and recovery by offering early warnings, predictive insights, and simplified communication. The article emphasises the cumulative influence of Cloud IoT components such as sensor networks, data analytics, decision support systems, and remote control in the context of disaster management. Cloud IoT is useful in real-world scenarios, such as the tracking of floods in Bangladesh and the identification of wildfires in California. These cases show how the technology may prevent injuries and preserve property through early warnings and well-coordinated responses. Despite its potential, it faces obstacles including ensuring the safety of data and dealing with issues related to the necessary infrastructure. In conclusion, including Cloud IoT in disaster management provides a cost-effective, scalable, and efficient solution, greatly contributing to constructing resilient communities and creating a sustainable future in the face of climate-induced natural catastrophes.
{"title":"Monitoring and Mitigating Climate-Induced Natural Disasters with Cloud IoT","authors":"Harsh Taneja, Rohan Verma, Prabhdeep Singh, Kiran Deep Singh","doi":"10.3233/jcc240008","DOIUrl":"https://doi.org/10.3233/jcc240008","url":null,"abstract":"Innovative solutions are necessary for efficient monitoring and mitigation techniques as climate change increases the frequency and severity of natural catastrophes. In this study, we investigate how Cloud Internet of Things (IoT) might help mitigate climate-related calamities. Through the use of cloud computing and sensor networks, Cloud IoT facilitates the capture, processing, and distribution of data in near-real time. This strategy promotes catastrophe planning, response, and recovery by offering early warnings, predictive insights, and simplified communication. The article emphasises the cumulative influence of Cloud IoT components such as sensor networks, data analytics, decision support systems, and remote control in the context of disaster management. Cloud IoT is useful in real-world scenarios, such as the tracking of floods in Bangladesh and the identification of wildfires in California. These cases show how the technology may prevent injuries and preserve property through early warnings and well-coordinated responses. Despite its potential, it faces obstacles including ensuring the safety of data and dealing with issues related to the necessary infrastructure. In conclusion, including Cloud IoT in disaster management provides a cost-effective, scalable, and efficient solution, greatly contributing to constructing resilient communities and creating a sustainable future in the face of climate-induced natural catastrophes.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140227311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate change is having a detrimental effect on the environment’s natural equilibrium. The population that depends on agriculture is suffering from rising temperatures, sporadic droughts and famines, unpredictable dry spells, and irregular rains. Deploying Climate Smart Agriculture (CSA) is a terrific strategy to cut greenhouse gas emissions and boost crop output for food security and climate change adaptation. The primary objective of this study is to provide an organized appraisal of current advancements in the field of climate-smart agriculture. For this study, the Scopus database was used to analyze 157 papers that were published between 2013 and 2022. However, the use of climate-smart agriculture technology that considers local knowledge is still quite low in developing countries. Therefore, raising the importance of indigenous knowledge in the context of climate change could aid smallholder agricultural groups in their adaptation. Improving adaptability, developing capacity, and fusing indigenous knowledge with climate-smart agricultural practices may all be necessary to increase a community’s effective resilience to climate change.
{"title":"Review on Climate Smart Agriculture Practice: A Global Perspective","authors":"Prabal Barua, Anisa Mitra","doi":"10.3233/jcc240003","DOIUrl":"https://doi.org/10.3233/jcc240003","url":null,"abstract":"Climate change is having a detrimental effect on the environment’s natural equilibrium. The population that depends on agriculture is suffering from rising temperatures, sporadic droughts and famines, unpredictable dry spells, and irregular rains. Deploying Climate Smart Agriculture (CSA) is a terrific strategy to cut greenhouse gas emissions and boost crop output for food security and climate change adaptation. The primary objective of this study is to provide an organized appraisal of current advancements in the field of climate-smart agriculture. For this study, the Scopus database was used to analyze 157 papers that were published between 2013 and 2022. However, the use of climate-smart agriculture technology that considers local knowledge is still quite low in developing countries. Therefore, raising the importance of indigenous knowledge in the context of climate change could aid smallholder agricultural groups in their adaptation. Improving adaptability, developing capacity, and fusing indigenous knowledge with climate-smart agricultural practices may all be necessary to increase a community’s effective resilience to climate change.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140224241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The unpredictable weather conditions due to climate change have resulted in significant changes in global weather patterns, affecting various sectors across the world; mostly the agriculture sector which got affected. This study focusses on the changing agricultural patterns caused by climate change and their severe effects on farmers’ livelihoods in the Kishanganj District of Bihar. The purpose of this study is to look at the dynamic interaction between changing weather patterns and agricultural practices and the socioeconomic implications for the local farming community. This study intends (1) to explore farmers’ perceptions and their experience of climate change towards agricultural practices, (2) to understand the adaptive techniques used by farmers in the Kishanganj district of Bihar in response to altering the agricultural patterns, (3) to assess the socioeconomic consequences of shifting agricultural patterns on farmers’ lives. Through a comprehensive literature review and primary data collection, including in-depth interviews with local farmers, to discover variations in agricultural patterns, changing weather patterns, and changes in farming practices adopted by the farmers in response to unpredictable weather conditions. From the findings of this study, it is revealed that the agricultural sector in Kishanganj is extremely vulnerable to unpredictable weather patterns, such as severe droughts, unseasonal rainfall, and temperature variations. The changing weather patterns have resulted in significant crop loss, which resulted in lower agricultural production, less income, and more debt for farmers’ families. The negative effects of weather-related disruptions extend beyond economic factors, affecting both farmers’ families and food security.
{"title":"Disruption in Agricultural Pattern Due to Unpredictable Weather Conditions and its Effect on Farmer’s Family of Kishanganj District of Bihar","authors":"Saifuddin Soz, Md. Shahid Raza","doi":"10.3233/jcc240005","DOIUrl":"https://doi.org/10.3233/jcc240005","url":null,"abstract":"The unpredictable weather conditions due to climate change have resulted in significant changes in global weather patterns, affecting various sectors across the world; mostly the agriculture sector which got affected. This study focusses on the changing agricultural patterns caused by climate change and their severe effects on farmers’ livelihoods in the Kishanganj District of Bihar. The purpose of this study is to look at the dynamic interaction between changing weather patterns and agricultural practices and the socioeconomic implications for the local farming community. This study intends (1) to explore farmers’ perceptions and their experience of climate change towards agricultural practices, (2) to understand the adaptive techniques used by farmers in the Kishanganj district of Bihar in response to altering the agricultural patterns, (3) to assess the socioeconomic consequences of shifting agricultural patterns on farmers’ lives. Through a comprehensive literature review and primary data collection, including in-depth interviews with local farmers, to discover variations in agricultural patterns, changing weather patterns, and changes in farming practices adopted by the farmers in response to unpredictable weather conditions. From the findings of this study, it is revealed that the agricultural sector in Kishanganj is extremely vulnerable to unpredictable weather patterns, such as severe droughts, unseasonal rainfall, and temperature variations. The changing weather patterns have resulted in significant crop loss, which resulted in lower agricultural production, less income, and more debt for farmers’ families. The negative effects of weather-related disruptions extend beyond economic factors, affecting both farmers’ families and food security.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140224831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The environment undergoes shifts across various timescales, yet presently, human intervention remains the primary solution provider and is likely to persist in this role for the next few centuries. While it is widely recognised that human-induced, or anthropogenic, climate change contributes to global warming, what is often underestimated are the direct impacts of heavy rainfall, droughts, and storms, incurring significant costs for both society and the environment. The expansion of human populations has led to the conversion of natural ecosystems for agricultural, industrial, and residential purposes, creating a demand for environmental inputs such as fresh water, fiber, and soil fertility. This heightened demand puts increased pressure on the capacity of natural ecosystems. Deforestation, expanding agriculture, illegal fishing and hunting, unplanned tourism, and pesticide pollution have collectively led to the progressive degradation of natural habitats. The consequence is a loss of biodiversity and the removal of forests, disrupting the food and shelter sources for wildlife residing in these ecosystems. Scientific research aims to comprehend the scale of biodiversity, and land use, and contribute to mitigating the impacts of land use changes.
{"title":"Anthropocene: Human Activity Impact on the Climate and Environment","authors":"Parthvee R. Damor","doi":"10.3233/jcc240006","DOIUrl":"https://doi.org/10.3233/jcc240006","url":null,"abstract":"The environment undergoes shifts across various timescales, yet presently, human intervention remains the primary solution provider and is likely to persist in this role for the next few centuries. While it is widely recognised that human-induced, or anthropogenic, climate change contributes to global warming, what is often underestimated are the direct impacts of heavy rainfall, droughts, and storms, incurring significant costs for both society and the environment. The expansion of human populations has led to the conversion of natural ecosystems for agricultural, industrial, and residential purposes, creating a demand for environmental inputs such as fresh water, fiber, and soil fertility. This heightened demand puts increased pressure on the capacity of natural ecosystems. Deforestation, expanding agriculture, illegal fishing and hunting, unplanned tourism, and pesticide pollution have collectively led to the progressive degradation of natural habitats. The consequence is a loss of biodiversity and the removal of forests, disrupting the food and shelter sources for wildlife residing in these ecosystems. Scientific research aims to comprehend the scale of biodiversity, and land use, and contribute to mitigating the impacts of land use changes.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140227842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate models help us simulate and predict how the Earth’s climate is going to change in the future. Wind speed data is critical for developing and validating such models. However, in the real world, often owing to many factors such as station maintenance and sensor failures, a considerable amount of wind data goes missing. The Generative Adversarial Network (GAN) has been used to impute missing wind data, but the handling of unrealistic GAN output has remained largely unstudied. In this paper, we propose a novel hybrid approach that combines both the GAN and dual annealing algorithms to not only impute missing wind speed data but also counter unrealistic GAN outcomes. The hourly mean wind data has been collected from the National Centers for Environmental Information for four Indian stations, viz. Ahmedabad, Indore, Mangaluru and Mumbai. We compared the performance of the proposed approach with those of k-nn, soft imputation, and plain GAN-based approaches on mean, variance, standard deviation, kurtosis, skewness, and R-square. We found that our approach ranks number one based on the R-square value for all the considered stations. Our model consistently produces realistic results, unlike plain GAN. We observed that Mumbai has the lowest percentage of missing data (13.14%) and the highest R-square value (0.9999186451). However, Indore has the highest percentage of missing data (46.6463%) and the lowest R-square value (0.9046885604).
气候模型可以帮助我们模拟和预测未来地球气候的变化。风速数据对于开发和验证此类模型至关重要。然而，在现实世界中，往往由于台站维护和传感器故障等多种因素，大量的风速数据会丢失。生成对抗网络（GAN）已被用于对缺失的风力数据进行补偿，但如何处理不真实的 GAN 输出在很大程度上仍未得到研究。在本文中，我们提出了一种新颖的混合方法，该方法结合了 GAN 算法和双退火算法，不仅能计算缺失的风速数据，还能处理不切实际的 GAN 结果。我们从国家环境信息中心收集了印度四个站点（艾哈迈达巴德、印多尔、曼加鲁鲁和孟买）的每小时平均风速数据。我们比较了拟议方法与 k-nn、软估算和基于 GAN 的普通方法在平均值、方差、标准差、峰度、偏斜度和 R 平方方面的性能。我们发现，在所有考虑的站点中，根据 R 平方值，我们的方法排名第一。与普通 GAN 不同的是，我们的模型始终能产生真实的结果。我们发现，孟买的数据缺失率最低（13.14%），R 方值最高（0.9999186451）。然而，印多尔的数据缺失率最高（46.6463%），R 方值最低（0.9046885604）。
{"title":"Synergising Simulated Annealing and Generative Adversarial Network for Enhanced Wind Data Imputation in Climate Change Modelling","authors":"Soumyabrata Bhattacharjee, Gaurav Kumar Gugliani","doi":"10.3233/jcc240004","DOIUrl":"https://doi.org/10.3233/jcc240004","url":null,"abstract":"Climate models help us simulate and predict how the Earth’s climate is going to change in the future. Wind speed data is critical for developing and validating such models. However, in the real world, often owing to many factors such as station maintenance and sensor failures, a considerable amount of wind data goes missing. The Generative Adversarial Network (GAN) has been used to impute missing wind data, but the handling of unrealistic GAN output has remained largely unstudied. In this paper, we propose a novel hybrid approach that combines both the GAN and dual annealing algorithms to not only impute missing wind speed data but also counter unrealistic GAN outcomes. The hourly mean wind data has been collected from the National Centers for Environmental Information for four Indian stations, viz. Ahmedabad, Indore, Mangaluru and Mumbai. We compared the performance of the proposed approach with those of k-nn, soft imputation, and plain GAN-based approaches on mean, variance, standard deviation, kurtosis, skewness, and R-square. We found that our approach ranks number one based on the R-square value for all the considered stations. Our model consistently produces realistic results, unlike plain GAN. We observed that Mumbai has the lowest percentage of missing data (13.14%) and the highest R-square value (0.9999186451). However, Indore has the highest percentage of missing data (46.6463%) and the lowest R-square value (0.9046885604).","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140225674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Kotlia, Manmohan Kukreti, Harish Bisht, Biswajit Palar, Martin Seiler, Marie-Josée Nadeauc, A. Singh, L.M. Joshi, Anupam Sharma, Rajkumar Kashyap, Pooja Chand, Kalpana Gururani, Abhishek Mehra
In this research, we conducted a detailed granulometric analysis of 9.5 m thick palaeolake succession, exposed at Bilaspur (Bhimtal) in the Kumaun Lesser Himalaya to reconstruct the palaeoenvironmental and palaeoclimatic conditions. We carried out statistical parameters of grain-size data (i.e., standard deviation, kurtosis, and skewness, bivariate plots), and end member modelling analysis (EMMA) and our study reveal sediment’s unimodal and bimodal nature, deposited via fluvial action under low to high energy environmental conditions since the origin of the lake. Some parts of the deposit show poorly sorted and mixed character (leptokurtic to platykurtic) of sediments, indicating that the sediments were primarily transported from the proximal area of the lake basin under low-energy environmental conditions. The finely skewed and poorly sorted sediments show different modes of grain size distribution, which are attributed to fluctuations in the hydrodynamic conditions of the lake. The arid climatic conditions prevailed in the valley from ca. 42 to 40 ka BP, followed by warm and moist conditions from ca. 40 to 39 ka BP. The arid conditions under the low rainfall regime were experienced by the valley from ca. 39 to 30 ka BP, while it exercised another episode of moist and warmer conditions from ca. 30 to 24 ka BP. Further, the end-Member Modelling Analysis (EMMA) shows four end members (EM1-EM4) with different climatic conditions during the deposition, e.g., clay to fine silt-size particles reflecting higher lake levels under warm-wet climatic conditions, coarse silt fraction representing moderate energy conditions, and fine to coarse sand fractions indicating shallow lake-level conditions in the arid climatic conditions as well higher energy flow. The interpretation of energy conditions in the lake and catchment area by using various methods reveals different palaeoenvironmental conditions during the sediment deposition.
{"title":"Palaeoenvironmental and Palaeoclimatic Conditions in the Bhimtal Valley, Kumaun Lesser Himalaya, Between 40 and 24 ka Using Granulometric Analysis","authors":"B. Kotlia, Manmohan Kukreti, Harish Bisht, Biswajit Palar, Martin Seiler, Marie-Josée Nadeauc, A. Singh, L.M. Joshi, Anupam Sharma, Rajkumar Kashyap, Pooja Chand, Kalpana Gururani, Abhishek Mehra","doi":"10.3233/jcc230027","DOIUrl":"https://doi.org/10.3233/jcc230027","url":null,"abstract":"In this research, we conducted a detailed granulometric analysis of 9.5 m thick palaeolake succession, exposed at Bilaspur (Bhimtal) in the Kumaun Lesser Himalaya to reconstruct the palaeoenvironmental and palaeoclimatic conditions. We carried out statistical parameters of grain-size data (i.e., standard deviation, kurtosis, and skewness, bivariate plots), and end member modelling analysis (EMMA) and our study reveal sediment’s unimodal and bimodal nature, deposited via fluvial action under low to high energy environmental conditions since the origin of the lake. Some parts of the deposit show poorly sorted and mixed character (leptokurtic to platykurtic) of sediments, indicating that the sediments were primarily transported from the proximal area of the lake basin under low-energy environmental conditions. The finely skewed and poorly sorted sediments show different modes of grain size distribution, which are attributed to fluctuations in the hydrodynamic conditions of the lake. The arid climatic conditions prevailed in the valley from ca. 42 to 40 ka BP, followed by warm and moist conditions from ca. 40 to 39 ka BP. The arid conditions under the low rainfall regime were experienced by the valley from ca. 39 to 30 ka BP, while it exercised another episode of moist and warmer conditions from ca. 30 to 24 ka BP. Further, the end-Member Modelling Analysis (EMMA) shows four end members (EM1-EM4) with different climatic conditions during the deposition, e.g., clay to fine silt-size particles reflecting higher lake levels under warm-wet climatic conditions, coarse silt fraction representing moderate energy conditions, and fine to coarse sand fractions indicating shallow lake-level conditions in the arid climatic conditions as well higher energy flow. The interpretation of energy conditions in the lake and catchment area by using various methods reveals different palaeoenvironmental conditions during the sediment deposition.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138980350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Agulhas Current (AC) had been quite variable during the Quaternary Period, which not only impacted the Agulhas Leakage (AL) but also caused changes in the AMOC. To study the changes in the strength of AC, planktic foraminiferal census count and stable oxygen isotope data from the IODP Hole U-1474A were generated for the last 1.2 million years (My). We recorded significant variations in the abundance of climate-sensitive species, which were grouped according to their ecological preference as warm tropical-subtropical Agulhas Fauna (AF), temperate-subpolar Southern Ocean Fauna (SOF), stable oxygen isotope records and the Subtropical Front (STF) Index. The correlation of these records suggests that the strength of AC reduced during seven intervals during the last 1.2 My, in response to cooling climate, which led to the northward shift of STF. The studied interval was divided into three periods of MPT, MPT-MBE and post-MBE events. The AC was strongest after the Mid-Brunhes Event (0.43 Ma) as compared to the Mid-Pleistocene Transition (MPT) and post-MPT to MBE intervals.
{"title":"Reduction in the Strength of Agulhas Current During Quaternary: Planktic Foraminiferal Records for 1.2 Million Years from IODP Hole U-1474A","authors":"Vikram Pratap Singh, Shivani Pathak, Rahul Dwivedi","doi":"10.3233/jcc230031","DOIUrl":"https://doi.org/10.3233/jcc230031","url":null,"abstract":"The Agulhas Current (AC) had been quite variable during the Quaternary Period, which not only impacted the Agulhas Leakage (AL) but also caused changes in the AMOC. To study the changes in the strength of AC, planktic foraminiferal census count and stable oxygen isotope data from the IODP Hole U-1474A were generated for the last 1.2 million years (My). We recorded significant variations in the abundance of climate-sensitive species, which were grouped according to their ecological preference as warm tropical-subtropical Agulhas Fauna (AF), temperate-subpolar Southern Ocean Fauna (SOF), stable oxygen isotope records and the Subtropical Front (STF) Index. The correlation of these records suggests that the strength of AC reduced during seven intervals during the last 1.2 My, in response to cooling climate, which led to the northward shift of STF. The studied interval was divided into three periods of MPT, MPT-MBE and post-MBE events. The AC was strongest after the Mid-Brunhes Event (0.43 Ma) as compared to the Mid-Pleistocene Transition (MPT) and post-MPT to MBE intervals.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138978911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shaheen Manna, Sayantika Mukherjee, Dipanwita Das, Amrita Saha
India is the world’s second-largest producer of fish, where the state of West Bengal is leading in fish production. The Sundarbans, located in the southern part of India’s West Bengal state, is a UNESCO-designated world heritage site. The Indian Sundarbans is a tide-dominated region in the southern part of deltaic West Bengal, and is home to 4.43 million people. Even though it is traversed by numerous creeks and rivulets and receives a significant amount of precipitation during the monsoon season, freshwater is a scarce resource in the Sundarbans. During the dry season, there is a lack of fresh water above and below the ground, increasing siltation results in shallower channels, high salinity of the water and soil, and congestion in drainage making it difficult for people to make a living. During the dry season, most blocks experience water scarcity as a result of the ever-increasing population’s demand for water. According to this study, Sundarbans’ current annual domestic and drinking water demands are 105.1 mcm and 8.08 mcm, respectively. By combining the area under various crops and their lifecycle water requirements, the water demand for agriculture has been calculated to be 2782.83 mcm. The rainfall-runoff modelling aims to get a general idea of how much fresh water is available each year through surface runoff. It has also been estimated how much water is available from different sources in each block. It is estimated that deep and shallow bore wells contribute approximately 400 mcm, whereas surface water sources like tanks and canals contribute approximately 50 mcm. The communities that live in the Sundarbans eco-region benefit greatly from aquaculture’s contribution to their socio-economic development. For the sustainable development of aquaculture in the Sundarbans Delta, strong technical, financial and extension services from government organisations and research institutions are urgently required to meet these obstacles. Additionally, this study emphasises that roof-top rainwater harvesting in this region has the potential to supply 45 mcm more water, which could be used to partially satisfy the region’s domestic water demand. Future major policy options for meeting the Sundarbans ecoregion’s water demand include large-scale rainwater harvesting, rejuvenation and reconnection of disconnected river channels, artificial recharge of shallow aquifers to lower their salinity, and de-salination of shallow groundwater.
{"title":"Sustainable Management of Aquaculture and Water Footprint Analysis in Sunderban","authors":"Shaheen Manna, Sayantika Mukherjee, Dipanwita Das, Amrita Saha","doi":"10.3233/jcc230033","DOIUrl":"https://doi.org/10.3233/jcc230033","url":null,"abstract":"India is the world’s second-largest producer of fish, where the state of West Bengal is leading in fish production. The Sundarbans, located in the southern part of India’s West Bengal state, is a UNESCO-designated world heritage site. The Indian Sundarbans is a tide-dominated region in the southern part of deltaic West Bengal, and is home to 4.43 million people. Even though it is traversed by numerous creeks and rivulets and receives a significant amount of precipitation during the monsoon season, freshwater is a scarce resource in the Sundarbans. During the dry season, there is a lack of fresh water above and below the ground, increasing siltation results in shallower channels, high salinity of the water and soil, and congestion in drainage making it difficult for people to make a living. During the dry season, most blocks experience water scarcity as a result of the ever-increasing population’s demand for water. According to this study, Sundarbans’ current annual domestic and drinking water demands are 105.1 mcm and 8.08 mcm, respectively. By combining the area under various crops and their lifecycle water requirements, the water demand for agriculture has been calculated to be 2782.83 mcm. The rainfall-runoff modelling aims to get a general idea of how much fresh water is available each year through surface runoff. It has also been estimated how much water is available from different sources in each block. It is estimated that deep and shallow bore wells contribute approximately 400 mcm, whereas surface water sources like tanks and canals contribute approximately 50 mcm. The communities that live in the Sundarbans eco-region benefit greatly from aquaculture’s contribution to their socio-economic development. For the sustainable development of aquaculture in the Sundarbans Delta, strong technical, financial and extension services from government organisations and research institutions are urgently required to meet these obstacles. Additionally, this study emphasises that roof-top rainwater harvesting in this region has the potential to supply 45 mcm more water, which could be used to partially satisfy the region’s domestic water demand. Future major policy options for meeting the Sundarbans ecoregion’s water demand include large-scale rainwater harvesting, rejuvenation and reconnection of disconnected river channels, artificial recharge of shallow aquifers to lower their salinity, and de-salination of shallow groundwater.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138978577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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