MAUSAM最新文献 - Book学术

Study of Annual Rainfall Patterns for North-Western Indian Himalayan Region 印度西北部喜马拉雅地区年降水模式研究

4区地球科学

MAUSAM Pub Date : 2025-09-27 DOI: 10.54302/mausam.v76i4.7109

Vineet Ahuja, Chhavi P. Pandey, Hemwati Nandan

{"title":"Study of Annual Rainfall Patterns for North-Western Indian Himalayan Region","authors":"Vineet Ahuja, Chhavi P. Pandey, Hemwati Nandan","doi":"10.54302/mausam.v76i4.7109","DOIUrl":"https://doi.org/10.54302/mausam.v76i4.7109","url":null,"abstract":"Climate change, though inevitable, requires localized understanding of its variability to enable effective adaptation strategies, particularly in vulnerable sectors such as agriculture. This study focuses on the North Western Himalayan (NWH) region of India, encompassing Jammu & Kashmir, Ladakh, Himachal Pradesh, and Uttarakhand-areas that have witnessed substantial climatic shifts, including a 1.6 °C temperature rise over the last century and increased frequency of extreme rainfall events. Using global datasets from the GPCC and the Precipitation Concentration Index (PCI) as a key analytical tool, this research investigates spatio-temporal rainfall variability from 1971 to 2020 across varying altitudes and climate zones of the NWH region. Findings indicate a strong irregularity in precipitation distribution, particularly in J&K and Ladakh, aligning with recorded extreme rainfall events (EREs) such as 1998 J&K cloudbursts and the 2013 Kedarnath floods. The PCI values calculated for these events (e.g., 19.10 for Kedarnath) underscore the role of rainfall irregularity in disaster occurrence. Despite the observed trends, ground-based data gaps and limited infrastructure, particularly in remote or geopolitically sensitive areas, hamper precise monitoring and disaster preparedness. This study emphasizes the urgent need for enhanced climate data collection, improved documentation of EREs, and the development of microclimate-specific adaptation strategies for effective climate resilience in the North Western Himalayan region.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"76 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147916805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Source characterisation of June 2023 Doda (Kashmir) earthquake 2023年6月多达（克什米尔）地震震源特征

4区地球科学

MAUSAM Pub Date : 2025-06-28 DOI: 10.54302/mausam.v76i3.6684

Sindu Kumari, Ambikapathy Ammani, DELNA JOY K., VISHWARANJAN OJHA, SANDEEP ARORA

{"title":"Source characterisation of June 2023 Doda (Kashmir) earthquake","authors":"Sindu Kumari, Ambikapathy Ammani, DELNA JOY K., VISHWARANJAN OJHA, SANDEEP ARORA","doi":"10.54302/mausam.v76i3.6684","DOIUrl":"https://doi.org/10.54302/mausam.v76i3.6684","url":null,"abstract":"On the 13th of June 2023, at 13:33:42 IST, an earthquake of magnitude Ml5.1 occurred in the Doda region of Jammu & Kashmir (J&K). The earthquake's epicenter was at coordinates 33.15 N and 75.89 E, with a shallow depth of 10 km. This seismic event unfolded within the geological context of the Himalayan orogeny, which has taken shape as a consequence of the collision between the Indian plate and the Eurasian plate. The Himalayan region, characterized by the intricate dynamics of these tectonic collisions, harbours numerous significant regional and local fault systems. A substantial portion of these fault lines remains active, continually generating seismic activity throughout the Himalayan region and its adjacent areas. Despite causing minor structural damage to a few buildings in the source region, this particular earthquake was well-documented and was accurately located by the Indian National Seismic Network, which is operated by the National Centre for Seismology (NCS), Ministry of Earth Sciences (MoES). Notably, the NCS-MoES maintains three Seismological observatories in Jammu & Kashmir (specifically in Jammu, Srinagar, and Udhampur), along with two additional Seismological observatories in Ladakh (in Hanley and Alchi). In the present study, we have harnessed waveform data collected from a network of 15 Seismological observatories managed by NCS-MoES, strategically positioned across J&K, Ladakh, and Himachal Pradesh. Our research endeavours to estimate the source characteristics including the precise determination of the earthquake's geographical location. Our analysis employed specialized software tools, SEISAN for epicenter localization and ISOLA for fault plane solution. Moreover, these derived seismic parameters served as foundational data for further analyses. Specifically, we leveraged these parameters to quantify the energy released and determine the source radius. These additional insights provided a comprehensive characterization of this earthquake and its implications.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"76 3","pages":"767-777"},"PeriodicalIF":0.0,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147899237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Temporal variations of Rainfall over Konkan & Goa during 1901-2020 1901-2020 年期间康坎和果阿降雨量的时间变化

IF 0.6 4区地球科学

MAUSAM Pub Date : 2024-01-01 DOI: 10.54302/mausam.v75i1.803

Dr Neeti Singh, T. C S, Gajendra Kumar, A. S H, Dinesh Sankhala

引用次数: 0

Identifying source apportionment of atmospheric particulate matter and gaseous pollutants using receptor models : A case study of Bengaluru, India 利用受体模型确定大气颗粒物和气体污染物的来源分配：印度班加罗尔案例研究

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.6080

H. N. Sowmya, Channabasavaraj Wollur, G. P. Shivashankara, H. K. Ramaraju

{"title":"Identifying source apportionment of atmospheric particulate matter and gaseous pollutants using receptor models : A case study of Bengaluru, India","authors":"H. N. Sowmya, Channabasavaraj Wollur, G. P. Shivashankara, H. K. Ramaraju","doi":"10.54302/mausam.v75i1.6080","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.6080","url":null,"abstract":"The data of Particulate matter PMs (PM2.5, PM10) and Gaseous Pollutants such as carbon monoxide (CO), methane (CH4), oxides of nitrogen (NOx: NO and NO2), non-methane hydrocarbons (NMHCs), sulfur dioxide (SO2), along with ammonia (NH3) at five different locations across Bengaluru from 1st January, 2017 to 20th March, 2018 were collected. The primary objective of this research work is to identify the sources of atmospheric particulate matter and gaseous pollutants using receptor models in Bengaluru, India. To execute this, receptor models, namely Conditional Bivariate Probability Function (CBPF) and Concentrated Weighted Trajectory (CWT) Analysis, are applied. Conditional Bivariate Probability Function (CBPF) shows that, annually, the maximum concentrations of PMs over receptor sites were detected during low wind speed (< 2 knots) along the north-east direction specifying that the long-range transport does not play an essential role in the transportation of higher concentrations of PM and their primary source region may be localized. Concentrated Weighted Trajectory (CWT) analysis shows that, seasonally, the highest air mass contribution of about 37% was noticed in summer, whereas the lowest was in the post-monsoon season (13%). The significant contribution of PM2.5 transported from long distances was during monsoon, and in the case of PM10, it was in summer. The study suggests that the long-range transport of PMs and gaseous Pollutants was not vital and was observed to be localized.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":" 946","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analytical concentration of pollutants with deposition using wind speed as power and logarithmic law 利用风速作为动力和对数定律分析污染物的沉积浓度

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.5899

K. Essa, S. Etman, M. El-Otaify, M. Embaby

引用次数: 0

Policy Interventions to Address Urban Water Problems of highly urbanised area due to Climate Change 解决气候变化导致的高度城市化地区城市用水问题的政策干预措施

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.5398

Chetan R. Patel, R. Singhal

{"title":"Policy Interventions to Address Urban Water Problems of highly urbanised area due to Climate Change","authors":"Chetan R. Patel, R. Singhal","doi":"10.54302/mausam.v75i1.5398","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.5398","url":null,"abstract":"In this research firstly, the rainfall pattern of Ahmedabad and Surat, the fast-growing urban areas of Gujarat state of India have been studied and compared. It is detected that what makes Surat city more prone to floods. Then, analysis for rainfall shift in Surat over the last three decades has been carried out. It is interesting to observe that the rainfall pattern of Surat is following the local calendar, i.e. Indian calendar rather Gregorian calendar. This relation of rainfall pattern with Indian calendar shows that the prediction and the climatic condition responsible for rain is following the local calendar based on the planetary position. For the Water Sensitive Urban Design, four different wards in Surat Municipal Corporation (SMC) named Adajan, Piplod, Anjana and Pandesara are studied. These wards are selected based on land use, having the highest area in commercial, residential, industrial and institutional in total SMC area. For each ward, the previous and impervious area is calculated, and the runoff is determined. Planning interventions for water sensitive urban design at a building level, street level and ward level have been given for the study area. The study will be definitely helpful for the decision-makers to prepare a policy to follow the local calendar to operate the monsoon protocol and to manage water resource infrastructure, including the planning of harvesting activities.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"119 35","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Synoptic Analogue Model for Quantitative Precipitation Forecast over Cauvery basin, India 开发用于印度考弗里盆地定量降水预报的综合模拟模型

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.5099

R. M, Dr. Geeta Agnihotri

{"title":"Development of Synoptic Analogue Model for Quantitative Precipitation Forecast over Cauvery basin, India","authors":"R. M, Dr. Geeta Agnihotri","doi":"10.54302/mausam.v75i1.5099","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.5099","url":null,"abstract":"Daily Average Areal Precipitation (AAP) data of South West Monsoon Season for 2012 to 2020 in respect of sub-basins of Cauvery river basin were collected alongwith synoptic systems causing rainfall in the sub-basins. Five synoptic systems namely Depression/Deep Depression, low/well marked low(WML) pressure area, Upper air cyclonic circulations(UAC), off-shore trough(OST)/OST with embedded cyclonic circulations, east-west shear zone are considered in the study. Rainfall(AAP) caused by these systems considered are 11-25mm, 26-50mm, 51-100mm and > 100mm. Number of days for which these systems caused rainfall under each range was computed. The rainfall range with highest frequency for the particular system is taken as Synoptic Analogue Model. OST/OST with embedded cyclonic circulation has contributed significantly to rainfall in all the sub-basins. Depression/Deep Depression over Rayalaseema, Tamil Nadu and Pondicherry, South Interior Karnataka or North Interior Karnataka provides > 50mm rainfall in Harangi basin. Depression/Deep Depression over Rayalaseema, Tamil Nadu and Pondicherry, South Interior Karnataka or North Interior Karnataka provides > 50mm rainfall in Harangi basin. Low/Well Marked Low over Telangana provides > 50mm rainfall in Hemavathy basin. Upper Air Cyclonic circulation(UAC) over Rayalaseema provides > 50mm rainfall in Kabini basin. UAC over Rayalaseema, South East Bay of Bengal or West Central Bay of Bengal off Coastal Andhra Pradesh leads to >100 mm rain in Harangi. UAC over Coastal Karnataka and North Interior Karnataka or OST from Konkan Goa/Maharashtra to Karnataka leads to >100 mm rain in Upper Vaigai. Key words- Aerial Average Precipitation, QPF, Cauvery river basin, Synoptic Analogue Model","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":" 443","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139137109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mitigation and risk management of climate change in crop cultivation through the adoption of Agromet Advisory Bulletin (AAB) in NICRA adopted villages in Punjab 通过在旁遮普邦 NICRA 采纳的村庄采用农业气象咨询公告 (AAB)，在作物种植中减缓气候变化并进行风险管理

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.6140

P. Kaur, S. S. Sandhu, Abhishek Dhir

{"title":"Mitigation and risk management of climate change in crop cultivation through the adoption of Agromet Advisory Bulletin (AAB) in NICRA adopted villages in Punjab","authors":"P. Kaur, S. S. Sandhu, Abhishek Dhir","doi":"10.54302/mausam.v75i1.6140","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.6140","url":null,"abstract":"Crop production is a direct output of manageable (agronomic) and unmanageable (weather) inputs. A farmer can cut down losses in crop production due to aberrant weather conditions by following weather forecast. India Meteorological Department is providing weather forecast on eight weather parameters at district and block level. Under All India Coordinated Research Project on Agrometeorology-National Innovations in Climate Resilient Agriculture, an Agromet Advisory Bulletin (AAB) is prepared by using this forecast for coming five days and disseminated to farmers. To evaluate the impact of AAB in three selected villages Badoshe Kalan and Bauranga Zer (district Fatehgarh Sahib) and Rampur Fasse (district Rupnagar) a survey from 110 farmers was conducted. Amongst the 110 farmer, 70 were marginal/small farmers (landholding <2.0ha) and 40 were medium farmers (landholding 2-10ha) who adopted the information given in AAB in crop cultivation. The analysis revealed that by following AAB in rice and wheat crops 65-93% farmers benefitted by managing biotic stresses, 65-85% farmers by irrigation management, 75-78% farmers by adjusting sowing and 62-65% farmers by nutrient management. The farmers who scheduled irrigations to their crop by adopting AAB in rice-wheat cropping system reduced ~34.2 metric tonnes of CO2 emissions by preventing wasteful burning of diesel. The adopters of AAB in rice and wheat crop were able to harness an average yield increase of 2.25-3.75q/ha and 1.75-4.50 q/ha, respectively and save nearly Rs 4100 to 7000/ha and Rs 3200-9200/ha, respectively with lesser expenditure. Hence, AAB can help boost crop productivity as well as help reduce carbon footprints and make agriculture an eco-friendly and profitable venture.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"62 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139132605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Shifts in wetness pattern and periodicity across Tripura state in north east India 印度东北部特里普拉邦各地潮湿模式和周期的变化

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.4536

Saurav Saha, Gulav Singh Yadav, Dhiman Daschaudhuri, Mrinmoy Datta, Debasish Chakraborty, Sandip Sadhu, Bappa Das, Samik Chowdhury, V. Dayal, Anup Das, Basant Kandpal, Ingudam Shakuntala

引用次数: 0

Comparative analysis of SMLR, ANN, Elastic net and LASSO based models for rice crop yield prediction in Uttarakhand 基于 SMLR、ANN、弹性网和 LASSO 模型的北阿坎德邦水稻作物产量预测比较分析

IF 0.6 4区地球科学

MAUSAM Pub Date : 2023-12-31 DOI: 10.54302/mausam.v75i1.3576

P. Setiya, A. Nain, Anurag Satpathi

{"title":"Comparative analysis of SMLR, ANN, Elastic net and LASSO based models for rice crop yield prediction in Uttarakhand","authors":"P. Setiya, A. Nain, Anurag Satpathi","doi":"10.54302/mausam.v75i1.3576","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.3576","url":null,"abstract":"The study was aimed to develop the yield forecast model for rice crop yield. Four different techniques i.e. Stepwise Multiple Linear Regression (SMLR), Artificial Neural Network (ANN), Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net (ELNET)were used to build the prediction models. Dataset of meteorological data and crop yield data of 15 years have been used to develop the forecast models. The developed models were also validated on the dataset of three years. The assessment of the developed models wasdone by using root mean square error (RMSE),normalized root mean square error (nRMSE),Mean Absolute Error (MAE) and on the basis of coefficient of determination (R2). The experimental analysis suggested that the performance for Artificial Neural Network (R2=0.99, RMSE=0.07, nRMSE=2.20, MAE=0.06) is better as compared to SMLR(R2=0.97, RMSE=0.08, nRMSE=2.34, MAE=0.05), LASSO (R2=0.62, RMSE=0.26, nRMSE=7.81, MAE=0.24) and ELNET (R2=0.54, RMSE=0.38, nRMSE=11.41, MAE=0.37) for the predictionof rice crop yield for Udham Singh Nagar (USN) district of Uttarakhand. Therefore, for the prediction of rice yield, ANN technique can be well utilised for Udham Singh Nagar district of Uttarakhand.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"117 44","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0