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":"4 3","pages":""},"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":"14 6","pages":""},"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":"89 4","pages":""},"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}
Hadis Sadeghi, S. Shobairi, A. Shamsipour, Hosein Mohammadi, Mostafa Karimi, Ebrahim Amiri, Saeid Soufizadeh
Climate has a significant effect on social and economic activities, and currently is a major problem, especially in agricultural yields. This study used two types of climatic and agricultural data. To simulate the climate for the next 30 years (2021-2050) from daily temperature and precipitation data for the base period 1986-2015, Reanalysis Atmospheric Data (NCEP) as observational predictors data and CanESM2 Atmospheric General Circulation Model data with two scenarios RCP 2.6 and RCP 8.5 were used as large-scale predictors. The data is related to the Rasht Rice Research Center field experiments. The results abstained from simulations showed that in future climate conditions, the average temperature would be 0.7 to 0.9°C, and precipitation would be 20 to 70 mm in the study area based on both emission scenarios compared to the base period (1986-2015) increases. The effect of climate change on the rice yield on the planting date of June 5, especially in the eastern parts of the region, is unfavourable in the future. At the regional level, in all planting dates, the length of the rice growth period in the future period (2021-2050) will decrease by 2 to 4 days compared to the base period. The planting date treatment of 5 May with a density level of 50 plants per square meter, a nitrogen fertiliser level of 195 kg per hectare with an intermittent irrigation regime (8-day cycle) is the most suitable adaptation strategy to reduce the negative effects of climate change and increase rice yield in the entire surface of the coastal area in the Caspian Sea.
{"title":"Effects of Climate Change on Rice Yield in Northern Areas of Iran: Humidity as a Large Variability of Climate","authors":"Hadis Sadeghi, S. Shobairi, A. Shamsipour, Hosein Mohammadi, Mostafa Karimi, Ebrahim Amiri, Saeid Soufizadeh","doi":"10.3233/jcc230029","DOIUrl":"https://doi.org/10.3233/jcc230029","url":null,"abstract":"Climate has a significant effect on social and economic activities, and currently is a major problem, especially in agricultural yields. This study used two types of climatic and agricultural data. To simulate the climate for the next 30 years (2021-2050) from daily temperature and precipitation data for the base period 1986-2015, Reanalysis Atmospheric Data (NCEP) as observational predictors data and CanESM2 Atmospheric General Circulation Model data with two scenarios RCP 2.6 and RCP 8.5 were used as large-scale predictors. The data is related to the Rasht Rice Research Center field experiments. The results abstained from simulations showed that in future climate conditions, the average temperature would be 0.7 to 0.9°C, and precipitation would be 20 to 70 mm in the study area based on both emission scenarios compared to the base period (1986-2015) increases. The effect of climate change on the rice yield on the planting date of June 5, especially in the eastern parts of the region, is unfavourable in the future. At the regional level, in all planting dates, the length of the rice growth period in the future period (2021-2050) will decrease by 2 to 4 days compared to the base period. The planting date treatment of 5 May with a density level of 50 plants per square meter, a nitrogen fertiliser level of 195 kg per hectare with an intermittent irrigation regime (8-day cycle) is the most suitable adaptation strategy to reduce the negative effects of climate change and increase rice yield in the entire surface of the coastal area in the Caspian Sea.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"24 5","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138979930","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}
J. Hemalatha, V. Vivek, M. Sekar, M.K. Kavitha Devi
The foremost challenge of rainfall forecasting is the intensity of rainfall in some particular stations. The unpredictable rainfall volume owing to the climate transformation can root cause for either overflow or dryness in the reservoir. In this article, we coin a novel model to predict the monthly rainfall by using an Ensemble Radial basis function Network and a One-Dimensional Deep Convolutional Neural Network algorithm. In the first step, nine climatological parameters, which are highly related to monthly rainfall disparity, are given as input for an ensemble model. In the second step, a hybrid approach is proposed and compared with Bayesian Linear Regression (BLR) and Decision Forest Regression (DFR). Experimental results show that the ensemble approach yields good results in seizing the multifaceted association among causal variables and also it extracted the most relevant hidden features of hydro meteorological rainfall system.
{"title":"Improving Rainfall Forecasting via Radial Basis Function and Deep Convolutional Neural Networks Integration","authors":"J. Hemalatha, V. Vivek, M. Sekar, M.K. Kavitha Devi","doi":"10.3233/jcc230030","DOIUrl":"https://doi.org/10.3233/jcc230030","url":null,"abstract":"The foremost challenge of rainfall forecasting is the intensity of rainfall in some particular stations. The unpredictable rainfall volume owing to the climate transformation can root cause for either overflow or dryness in the reservoir. In this article, we coin a novel model to predict the monthly rainfall by using an Ensemble Radial basis function Network and a One-Dimensional Deep Convolutional Neural Network algorithm. In the first step, nine climatological parameters, which are highly related to monthly rainfall disparity, are given as input for an ensemble model. In the second step, a hybrid approach is proposed and compared with Bayesian Linear Regression (BLR) and Decision Forest Regression (DFR). Experimental results show that the ensemble approach yields good results in seizing the multifaceted association among causal variables and also it extracted the most relevant hidden features of hydro meteorological rainfall system.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"26 10","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138980011","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 Ngan Sau River basin, which is situated in Ha Tinh Province of Vietnam, experiences flooding during the rainy season, resulting in significant loss of property and human life. This research aimed to investigate the impact of climate change and land-use variation on flood losses. The study began by simulating the heavy rainfall events in August 2007 using the Weather Research and Forecast model with an ensemble method. Future rainfall was examined through numerical simulation based on pseudo-global warming constructed using six CMIP5 models (MIROC-ESM, MRI-CGM3, GISS-E2-H, HadGEM2-ES, HadGEM2-ES, and CNRM-CM5), and the variation in land-use was obtained from local authorities. Inundations caused by rainfall in 2007 and rainfall in the future were determined by the rainfall-runoff-inundation model. Finally, based on flood maps, land-use, and flood depth-damage functions, the economic losses were computed. The results of the average flood economic loss were $380 million in CTL, whereas the local authorities report an estimated loss of over $300 million. Under the impact of climate change and land-use variation, economic losses ranged from $380 million to $526 million in six CMIP5 models. The result of INMCM4 showed the highest value of $526 million, the results of MRI-CGM3, GISS-E2-H, HadGEM2-ES, and CNRM-CM5 fluctuated around $500 million, and the MIROC-ESM recorded the lowest at $380 million. The damage maps showed that the losses would be highest in urban areas, followed by forest areas, and lowest in agricultural areas. This information is essential for decision-makers to improve solutions for preventing economic losses caused by floods.
{"title":"Assessment of Flood Economic Losses Under Climate Change: A Case Study in the Ngan Sau River Basin, Ha Tinh Province and Vietnam","authors":"Tran Quoc Lap","doi":"10.3233/jcc230028","DOIUrl":"https://doi.org/10.3233/jcc230028","url":null,"abstract":"The Ngan Sau River basin, which is situated in Ha Tinh Province of Vietnam, experiences flooding during the rainy season, resulting in significant loss of property and human life. This research aimed to investigate the impact of climate change and land-use variation on flood losses. The study began by simulating the heavy rainfall events in August 2007 using the Weather Research and Forecast model with an ensemble method. Future rainfall was examined through numerical simulation based on pseudo-global warming constructed using six CMIP5 models (MIROC-ESM, MRI-CGM3, GISS-E2-H, HadGEM2-ES, HadGEM2-ES, and CNRM-CM5), and the variation in land-use was obtained from local authorities. Inundations caused by rainfall in 2007 and rainfall in the future were determined by the rainfall-runoff-inundation model. Finally, based on flood maps, land-use, and flood depth-damage functions, the economic losses were computed. The results of the average flood economic loss were $380 million in CTL, whereas the local authorities report an estimated loss of over $300 million. Under the impact of climate change and land-use variation, economic losses ranged from $380 million to $526 million in six CMIP5 models. The result of INMCM4 showed the highest value of $526 million, the results of MRI-CGM3, GISS-E2-H, HadGEM2-ES, and CNRM-CM5 fluctuated around $500 million, and the MIROC-ESM recorded the lowest at $380 million. The damage maps showed that the losses would be highest in urban areas, followed by forest areas, and lowest in agricultural areas. This information is essential for decision-makers to improve solutions for preventing economic losses caused by floods.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"2 4","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138981028","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 cumulative effects of seasonal Earth processes in different places and times in the atmosphere, hydrosphere, and cryosphere essentially and inevitably shape global climate conditions. Therefore, the article investigates the possibilities for modelling the periodicity of the observable seasonal climate processes. The starting assumption of the study is that the seasonal climate processes are representable by two-phase linear periodic models based on observed data. A numerical algorithm elaborated in the sequel makes it possible to accumulate the seasonal effects of two successively progressive and regressive process phases of periodic climate changes in time. The model first tackles the reported seasonal growth of the atmospheric CO2 concentration. Next, it considers the observed seasonal cryospheric melting and freezing processes of the Antarctica and Greenland ice sheets and of the Arctic sea ice. It also elaborates on the reported seasonal sea level rise. Finally, the article summarises the interactions of periodic climate processes and the global climate conditions in time scale. The reports on global temperature rise are only on an annual basis. The article also emphasises the importance of control over the seasonal worsening and recovery scenarios for more appropriate projections of climate policies to 2100.
{"title":"Interactions of Seasonal Earth Processes and Climate System","authors":"K. Ziha","doi":"10.3233/jcc230032","DOIUrl":"https://doi.org/10.3233/jcc230032","url":null,"abstract":"The cumulative effects of seasonal Earth processes in different places and times in the atmosphere, hydrosphere, and cryosphere essentially and inevitably shape global climate conditions. Therefore, the article investigates the possibilities for modelling the periodicity of the observable seasonal climate processes. The starting assumption of the study is that the seasonal climate processes are representable by two-phase linear periodic models based on observed data. A numerical algorithm elaborated in the sequel makes it possible to accumulate the seasonal effects of two successively progressive and regressive process phases of periodic climate changes in time. The model first tackles the reported seasonal growth of the atmospheric CO2 concentration. Next, it considers the observed seasonal cryospheric melting and freezing processes of the Antarctica and Greenland ice sheets and of the Arctic sea ice. It also elaborates on the reported seasonal sea level rise. Finally, the article summarises the interactions of periodic climate processes and the global climate conditions in time scale. The reports on global temperature rise are only on an annual basis. The article also emphasises the importance of control over the seasonal worsening and recovery scenarios for more appropriate projections of climate policies to 2100.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"70 8","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138979574","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}
When the river Yamuna leaves the National Capital Territory of Delhi, its situation further deteriorates. Despite accounting for only 1% of the river’s overall catchment area, this region is responsible for more than half of the pollutants discovered in the Yamuna. The river Yamuna, on the other hand, is Delhi’s only natural resource for maintaining all forms of life. The Yamuna River is currently experiencing a significant level of pollution problem, and in order to control pollution in the Yamuna River, continual analysis is essential. The Yamuna River is contaminated by the discharge of untreated municipal sewage and industrial effluent through seven major drains: Najafgarh, Yamunapur, Sen Nursing Home, Barathpula, Maharani Bagh, Kalkaji, and Tuglakabad. In terms of people and chemicals, continuous sampling takes time and money. The primary objective of this study is to analyse the wastewater samples collected by sub-drains and STP’s to predict the pollutant transportation in river Yamuna from Najafgarh Drain. The study focusses on the only pollutant, i.e., Biochemical Oxygen Demand from the starting point to after the confluence of Najafgarh Drain into river Yamuna. The prediction is to be done by using MATLAB software. This study would help to identify the main sources of sub-drains which are polluting Najafgarh Drain and eventually the river Yamuna. This shows how MATLAB may be used to calculate the pollution load caused by organic waste in the Yamuna River as it flows through Delhi, India’s National Capital Territory. The model numerically solves a series of differential equations to simulate the dissolved oxygen and biochemical oxygen demand parameters in two dimensions. MATLAB is an interactive programming language that may be used to develop algorithms, graphics, and user interfaces in other computer languages. MATLAB helps estimate future water quality using present data, which saves time, labour, and other costs associated with the continuous study. There are various software programmes available in the market for predicting river water quality, however, MATLAB GUI provides an accessible and convenient user interface (Graphical User Interface).
{"title":"Modelling of Pollutant Transport in Yamuna River from the Najafgarh Drain, NCT Delhi Using Matlab Software","authors":"S.K Singh, Priyanka Negi, Karan Arora, Monika","doi":"10.3233/jcc230023","DOIUrl":"https://doi.org/10.3233/jcc230023","url":null,"abstract":"When the river Yamuna leaves the National Capital Territory of Delhi, its situation further deteriorates. Despite accounting for only 1% of the river’s overall catchment area, this region is responsible for more than half of the pollutants discovered in the Yamuna. The river Yamuna, on the other hand, is Delhi’s only natural resource for maintaining all forms of life. The Yamuna River is currently experiencing a significant level of pollution problem, and in order to control pollution in the Yamuna River, continual analysis is essential. The Yamuna River is contaminated by the discharge of untreated municipal sewage and industrial effluent through seven major drains: Najafgarh, Yamunapur, Sen Nursing Home, Barathpula, Maharani Bagh, Kalkaji, and Tuglakabad. In terms of people and chemicals, continuous sampling takes time and money. The primary objective of this study is to analyse the wastewater samples collected by sub-drains and STP’s to predict the pollutant transportation in river Yamuna from Najafgarh Drain. The study focusses on the only pollutant, i.e., Biochemical Oxygen Demand from the starting point to after the confluence of Najafgarh Drain into river Yamuna. The prediction is to be done by using MATLAB software. This study would help to identify the main sources of sub-drains which are polluting Najafgarh Drain and eventually the river Yamuna. This shows how MATLAB may be used to calculate the pollution load caused by organic waste in the Yamuna River as it flows through Delhi, India’s National Capital Territory. The model numerically solves a series of differential equations to simulate the dissolved oxygen and biochemical oxygen demand parameters in two dimensions. MATLAB is an interactive programming language that may be used to develop algorithms, graphics, and user interfaces in other computer languages. MATLAB helps estimate future water quality using present data, which saves time, labour, and other costs associated with the continuous study. There are various software programmes available in the market for predicting river water quality, however, MATLAB GUI provides an accessible and convenient user interface (Graphical User Interface).","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"245 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80581700","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}
Fiona Bassy William, P. M. Viswanathan, Anshuman Mishra
Trend analysis is frequently utilised to identify the changes in meteorological and hydrologic time series data, such as rainfall and temperature. The variations in the intensity, rainfall pattern and temperature have gradually changed globally. Hence, in this study, an attempt was made to analyse the decadal rainfall and surface air temperature data to understand the microclimatic variations in the Miri coastal region of NW Borneo. A data series of records for daily total rainfall amount and daily surface temperature of 11 years from 2010 to 2021 was studied and analysed. In addition, representative rainwater and groundwater samples were collected and analysed for hydrochemical parameters and oxygen and hydrogen isotopes. A detailed literature review was carried out on rainfall patterns in Malaysia, which was used for the comparative study. Interpretation of results shows that the northeast monsoon (NEM) contributed a higher total rainfall rate with lower daily mean surface air temperature over the years compared to the southwest monsoon (SWM). The recorded data for rainfall amounts in SWM for the month of May, July, August and September were higher, particularly for the years 2010 and 2020. During NEM, a higher rainfall amount was recorded in the month of January for several years. February month has always been among the driest month in NEM, and September has been the wettest month throughout the year during SWM. The isotopic values of rainwater indicate a similar moisture source to the regional precipitation trend. Groundwater isotopes reveal the low water-rock ratio of retrograde exchange between water and primary silicate minerals in the aquifer. The moisture source of the precipitation was contributed from both oceanic and continent, affecting the rainfall intensity in this region. This study is a crucial outcome to determine the potential impacts of microclimatic variations on the rainfall patterns in the Miri coastal region.
{"title":"Microclimatic Variation in Miri Region (NW Borneo): Inference from Rainfall and Temperature Trends, Isotopic Signature and Air Mass Movement","authors":"Fiona Bassy William, P. M. Viswanathan, Anshuman Mishra","doi":"10.3233/jcc230024","DOIUrl":"https://doi.org/10.3233/jcc230024","url":null,"abstract":"Trend analysis is frequently utilised to identify the changes in meteorological and hydrologic time series data, such as rainfall and temperature. The variations in the intensity, rainfall pattern and temperature have gradually changed globally. Hence, in this study, an attempt was made to analyse the decadal rainfall and surface air temperature data to understand the microclimatic variations in the Miri coastal region of NW Borneo. A data series of records for daily total rainfall amount and daily surface temperature of 11 years from 2010 to 2021 was studied and analysed. In addition, representative rainwater and groundwater samples were collected and analysed for hydrochemical parameters and oxygen and hydrogen isotopes. A detailed literature review was carried out on rainfall patterns in Malaysia, which was used for the comparative study. Interpretation of results shows that the northeast monsoon (NEM) contributed a higher total rainfall rate with lower daily mean surface air temperature over the years compared to the southwest monsoon (SWM). The recorded data for rainfall amounts in SWM for the month of May, July, August and September were higher, particularly for the years 2010 and 2020. During NEM, a higher rainfall amount was recorded in the month of January for several years. February month has always been among the driest month in NEM, and September has been the wettest month throughout the year during SWM. The isotopic values of rainwater indicate a similar moisture source to the regional precipitation trend. Groundwater isotopes reveal the low water-rock ratio of retrograde exchange between water and primary silicate minerals in the aquifer. The moisture source of the precipitation was contributed from both oceanic and continent, affecting the rainfall intensity in this region. This study is a crucial outcome to determine the potential impacts of microclimatic variations on the rainfall patterns in the Miri coastal region.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"122 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85693817","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 a pressing issue that is affecting the lives and livelihoods of millions of people across the world. This study investigates the trend analysis and spatial-temporal variations of temperature and precipitation on a monthly, seasonal, and annual basis in Rajasthan state, India, over the past 40 years (1981-2020). The trend analysis of temperature and precipitation were analysed using the Mann-Kendall test at the confidence level of 95%. The magnitude (slope) was determined by using Theil-Sen’s slope test. The results of the analysis revealed significant positive and negative trends of temperature and precipitation observed on a monthly, seasonal, and annual basis in all the 33 districts of Rajasthan state. The summer season experienced the maximum average temperature, while the winter season had the minimum. The study also found that the northern and western parts of Rajasthan experience “Mawat” rain during the winter due to cyclones happening in the Mediterranean Sea during that season. The annual average temperature and precipitation were observed to be maximum in the southern part and minimum in the northern and western parts of the state. The findings of this study provide valuable information for the future management of water resources and the likely impact of activities on the hydrologic cycle and natural resources in Rajasthan state.
{"title":"Investigating Variations and Trend Analysis for Temperature and Precipitation as a Result of Climate Change in Rajasthan, India","authors":"Vratika Porwal, Mahendra Pratap Choudhary","doi":"10.3233/jcc230022","DOIUrl":"https://doi.org/10.3233/jcc230022","url":null,"abstract":"Climate change is a pressing issue that is affecting the lives and livelihoods of millions of people across the world. This study investigates the trend analysis and spatial-temporal variations of temperature and precipitation on a monthly, seasonal, and annual basis in Rajasthan state, India, over the past 40 years (1981-2020). The trend analysis of temperature and precipitation were analysed using the Mann-Kendall test at the confidence level of 95%. The magnitude (slope) was determined by using Theil-Sen’s slope test. The results of the analysis revealed significant positive and negative trends of temperature and precipitation observed on a monthly, seasonal, and annual basis in all the 33 districts of Rajasthan state. The summer season experienced the maximum average temperature, while the winter season had the minimum. The study also found that the northern and western parts of Rajasthan experience “Mawat” rain during the winter due to cyclones happening in the Mediterranean Sea during that season. The annual average temperature and precipitation were observed to be maximum in the southern part and minimum in the northern and western parts of the state. The findings of this study provide valuable information for the future management of water resources and the likely impact of activities on the hydrologic cycle and natural resources in Rajasthan state.","PeriodicalId":43177,"journal":{"name":"Journal of Climate Change","volume":"10 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88132356","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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