VAIDHEKI M, Debkishore Gupta, Pradip Basak, Manoj Kanti Debnath, Satyajit Hembram, A. S.
Late blight is one of the most devastating diseases on potato the world over, including West Bengal, India. The economic and yield losses from outbreaks of potato late blight can be huge. In this article, application of statistical models such as autoregressive integrated moving average (ARIMA), autoregressive integrated moving average with exogenous variables (ARIMAX) in combination with machine learning models such as, neural network auto regression (NNAR), support vector regression (SVR) and classification and regression tree (CART) have been explored to predict the percentage disease index (PDI) of potato late blight in the northern part of West Bengal. Models were developed to predict PDI at 3- and 7-days interval using the weather variables viz., rainfall, maximum and minimum temperature, maximum and minimum relative humidity, and dew point temperature. Among the developed models, CART to predict PDI at 7 days interval was found to be the best fitted model on the basis of least RMSE, MAE and MAPE. The results of decision tree (CART) model showed that dew point temperature had a significant effect on PDI at 7 days interval and the incidence of potato late blight was high when dew point temperature was greater than 12 0C in the preceding week.
{"title":"Prediction of potato late blight disease incidence based on weather variables using statistical and machine learning models: A case study from West Bengal","authors":"VAIDHEKI M, Debkishore Gupta, Pradip Basak, Manoj Kanti Debnath, Satyajit Hembram, A. S.","doi":"10.54386/jam.v25i4.2272","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2272","url":null,"abstract":"Late blight is one of the most devastating diseases on potato the world over, including West Bengal, India. The economic and yield losses from outbreaks of potato late blight can be huge. In this article, application of statistical models such as autoregressive integrated moving average (ARIMA), autoregressive integrated moving average with exogenous variables (ARIMAX) in combination with machine learning models such as, neural network auto regression (NNAR), support vector regression (SVR) and classification and regression tree (CART) have been explored to predict the percentage disease index (PDI) of potato late blight in the northern part of West Bengal. Models were developed to predict PDI at 3- and 7-days interval using the weather variables viz., rainfall, maximum and minimum temperature, maximum and minimum relative humidity, and dew point temperature. Among the developed models, CART to predict PDI at 7 days interval was found to be the best fitted model on the basis of least RMSE, MAE and MAPE. The results of decision tree (CART) model showed that dew point temperature had a significant effect on PDI at 7 days interval and the incidence of potato late blight was high when dew point temperature was greater than 12 0C in the preceding week.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139202252","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}
Mohanasundaram Arumugam, K. K. Sharma, MOHAMMAD MONOBRULLAH, Jaipal Singh Choudhary, ACHINTYA PRAMANIK, NAASERAH ZEESHAN, MUNNA YADAV
Indian lac insect, Kerria lacca is a scale group beneficial insect which suffers by several natural enemies. The establishment of the relationship between the incidences of natural enemies on lac insects with weather variables is essential for formulating management strategies well in advance. The relationship between weather factors and the emergence of A. purpureus was studied from 2011–12 to 2020–21 on the rangeeni summer (baisakhi) lac crop. Correlation and regression analyses were done after pooling ten years data (2011-12 to 2020-21) during the critical lac growth period i.e. SMW 8 to SMW 20. The relative abundance of lac-associated fauna showed that three parasitoids ((Aprostocetus purpureus, Tachardiaephagus tachardiae, and Tyndarichus(=Parechthrodryinus) clavicornis)) and one predator (Eublemma amabilis) were abundant. Among them, A. purpureus recorded maximum percent infestation, which was 84% and 75% on ber and palas, respectively. Maximum number of A. purpureus was emerged during the sexual maturity period (8 to 20 SMW) of the summer lac crop. The incidence exhibited a significant negative correlation with maximum (Tmax) and minimum temperature (Tmin) and a significant positive correlation with morning and evening relative humidity (RH-II). Stepwise regression analysis showed Tmax and RH-II were the most important factors contributing to 68% variation in the incidence of A. purpureus on palas. The present study results indicated that environmental factors played a significant role in the incidence of parasitoids on lac insect.
{"title":"Weather based forecasting model for emergence of Aprostocetus purpureus (Cameron) – a parasitoid of lac insect, Kerria lacca (Kerr)","authors":"Mohanasundaram Arumugam, K. K. Sharma, MOHAMMAD MONOBRULLAH, Jaipal Singh Choudhary, ACHINTYA PRAMANIK, NAASERAH ZEESHAN, MUNNA YADAV","doi":"10.54386/jam.v25i4.2345","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2345","url":null,"abstract":"Indian lac insect, Kerria lacca is a scale group beneficial insect which suffers by several natural enemies. The establishment of the relationship between the incidences of natural enemies on lac insects with weather variables is essential for formulating management strategies well in advance. The relationship between weather factors and the emergence of A. purpureus was studied from 2011–12 to 2020–21 on the rangeeni summer (baisakhi) lac crop. Correlation and regression analyses were done after pooling ten years data (2011-12 to 2020-21) during the critical lac growth period i.e. SMW 8 to SMW 20. The relative abundance of lac-associated fauna showed that three parasitoids ((Aprostocetus purpureus, Tachardiaephagus tachardiae, and Tyndarichus(=Parechthrodryinus) clavicornis)) and one predator (Eublemma amabilis) were abundant. Among them, A. purpureus recorded maximum percent infestation, which was 84% and 75% on ber and palas, respectively. Maximum number of A. purpureus was emerged during the sexual maturity period (8 to 20 SMW) of the summer lac crop. The incidence exhibited a significant negative correlation with maximum (Tmax) and minimum temperature (Tmin) and a significant positive correlation with morning and evening relative humidity (RH-II). Stepwise regression analysis showed Tmax and RH-II were the most important factors contributing to 68% variation in the incidence of A. purpureus on palas. The present study results indicated that environmental factors played a significant role in the incidence of parasitoids on lac insect.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139208810","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}
{"title":"Estimation of crop water requirement of tomato in Algeria using CROPWAT model","authors":"Abdelkader Boualem","doi":"10.54386/jam.v25i4.2376","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2376","url":null,"abstract":"","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":" 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139197567","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}
Pradipa Chinnasamy, Panneerselvam Shanmugam, G. Vellingiri, J. R, B. K., S. Vigneswaran
Assessing the pulse of an important legume crop, red gram (Cajanus cajan L.) of Tamil Nadu under changing climate and framing adaptation strategies were formulated using the DSSAT model. The assessment was done for the popular variety of red gram, viz., CO(RG)7 with August 1st as sowing date, under constant CO2 (380ppm) and CO2 enrichment. The adaptation strategies such as altering the sowing date and 25 per cent increment in nitrogenous fertilizer were carried out with CO2 enrichment conditions. The yield was found to be adversely affected by the warming scenario of the climate system without CO2 fertilization. With the incorporation of enriched CO2 data, the average yield increases until the end of the century, but with temporal and spatial variations. Among the different agro climatic zones of Tamil Nadu, highest yield was recorded in Western Zone and lowest in Southern Zone. There was no response to application of Nitrogenous fertilizer. July 15 sowing was identified to be the best sowing for the base as well as future period for CO(RG)7.
{"title":"Modelling adaptation strategies towards climate smart red gram production in Tamil Nadu","authors":"Pradipa Chinnasamy, Panneerselvam Shanmugam, G. Vellingiri, J. R, B. K., S. Vigneswaran","doi":"10.54386/jam.v25i4.2280","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2280","url":null,"abstract":"Assessing the pulse of an important legume crop, red gram (Cajanus cajan L.) of Tamil Nadu under changing climate and framing adaptation strategies were formulated using the DSSAT model. The assessment was done for the popular variety of red gram, viz., CO(RG)7 with August 1st as sowing date, under constant CO2 (380ppm) and CO2 enrichment. The adaptation strategies such as altering the sowing date and 25 per cent increment in nitrogenous fertilizer were carried out with CO2 enrichment conditions. The yield was found to be adversely affected by the warming scenario of the climate system without CO2 fertilization. With the incorporation of enriched CO2 data, the average yield increases until the end of the century, but with temporal and spatial variations. Among the different agro climatic zones of Tamil Nadu, highest yield was recorded in Western Zone and lowest in Southern Zone. There was no response to application of Nitrogenous fertilizer. July 15 sowing was identified to be the best sowing for the base as well as future period for CO(RG)7.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139201294","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}
Shravani Sanyal, B. Chakrabarti, A. Bhatia, S. N. Kumar, T. Purakayastha, Dinesh Kumar, Pragati Pramanik, S. Kannojiya, A. Sharma, V. Kumar
An experiment was undertaken during rabi season of 2020-2021 and 2021-2022 at experimental field of Division of Environmental Science, ICAR-Indian Agriculture Research Institute (IARI), New Delhi inside Open Top Chambers (OTCs) to study the growth and physiological response of aestivum (HD 3226) and durum wheat (HI 8627) varieties to elevated temperature and CO2 concentration. Results showed that days to maturity hastened under elevated temperature condition. Photosynthesis rate, leaf area index and tiller number of wheat varieties reduced in elevated temperature treatment while elevated CO2 concentration of 550 ppm was able to partially compensate the reduction. In aestivum variety of wheat, transpiration rate significantly reduced in elevated CO2 plus high temperature interaction treatment than ambient while transpiration rate of durum variety remained unaffected. The negative effect of elevated temperature on aboveground biomass was more in aestivum variety than durum variety. Elevated CO2 concentration compensated reduction in aboveground biomass by 5.9% in HD 3226 (aestivum) and by 3.6% in HI 8627 (durum) varieties under elevated temperature condition. Hence elevated CO2 concentration will be able to partially compensate reduced crop growth in both aestivum and durum wheat varieties under high temperature condition.
{"title":"Response of aestivum and durum wheat varieties to elevated CO2 and temperature under OTC condition","authors":"Shravani Sanyal, B. Chakrabarti, A. Bhatia, S. N. Kumar, T. Purakayastha, Dinesh Kumar, Pragati Pramanik, S. Kannojiya, A. Sharma, V. Kumar","doi":"10.54386/jam.v25i4.2366","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2366","url":null,"abstract":"An experiment was undertaken during rabi season of 2020-2021 and 2021-2022 at experimental field of Division of Environmental Science, ICAR-Indian Agriculture Research Institute (IARI), New Delhi inside Open Top Chambers (OTCs) to study the growth and physiological response of aestivum (HD 3226) and durum wheat (HI 8627) varieties to elevated temperature and CO2 concentration. Results showed that days to maturity hastened under elevated temperature condition. Photosynthesis rate, leaf area index and tiller number of wheat varieties reduced in elevated temperature treatment while elevated CO2 concentration of 550 ppm was able to partially compensate the reduction. In aestivum variety of wheat, transpiration rate significantly reduced in elevated CO2 plus high temperature interaction treatment than ambient while transpiration rate of durum variety remained unaffected. The negative effect of elevated temperature on aboveground biomass was more in aestivum variety than durum variety. Elevated CO2 concentration compensated reduction in aboveground biomass by 5.9% in HD 3226 (aestivum) and by 3.6% in HI 8627 (durum) varieties under elevated temperature condition. Hence elevated CO2 concentration will be able to partially compensate reduced crop growth in both aestivum and durum wheat varieties under high temperature condition.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"136 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139202894","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}
R. Verma, Apurba Das, P. R. Narzary, Sanjib Sharma
Black pepper (Piper nigrum L.) production faces several challenges due to various diseases, with anthracnose being the most significant. It is caused by Colletotrichum gloeosporioides (Penz.) Penz. and Sacc., a fungal plant pathogen that leads to severe infections in black pepper plants, both in nurseries and in the field. The occurrence of anthracnose disease is highly influenced by weather conditions. Epidemiological studies were conducted at Assam Agricultural University, Jorhat, Assam from 2019 to 2021 to determine the impact of weather factors such as temperature, rainfall, rainy days, and relative humidity on anthracnose incidence in seven different black pepper varieties. Upon analyzing the recorded data, it was found that rainfall, minimum temperature, rainy days, and morning relative humidity are the most significant contributors to disease occurrence. However, the role of maximum temperature, evening relative humidity, and bright sunshine hours was statistically non-significant. Data from 2019 and 2020 were further analyzed using stepwise multiple regression to estimate anthracnose incidence in individual black pepper varieties. These regression models were subsequently validated using data of 2021. The root mean square error values varied between 0.0001 and 0.0011, indicating that the models are acceptable.
{"title":"Influence of weather parameters on Anthracnose in black pepper (Piper nigrum L.) in the upper Brahmaputra valley zone of Assam","authors":"R. Verma, Apurba Das, P. R. Narzary, Sanjib Sharma","doi":"10.54386/jam.v25i4.2408","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2408","url":null,"abstract":"Black pepper (Piper nigrum L.) production faces several challenges due to various diseases, with anthracnose being the most significant. It is caused by Colletotrichum gloeosporioides (Penz.) Penz. and Sacc., a fungal plant pathogen that leads to severe infections in black pepper plants, both in nurseries and in the field. The occurrence of anthracnose disease is highly influenced by weather conditions. Epidemiological studies were conducted at Assam Agricultural University, Jorhat, Assam from 2019 to 2021 to determine the impact of weather factors such as temperature, rainfall, rainy days, and relative humidity on anthracnose incidence in seven different black pepper varieties. Upon analyzing the recorded data, it was found that rainfall, minimum temperature, rainy days, and morning relative humidity are the most significant contributors to disease occurrence. However, the role of maximum temperature, evening relative humidity, and bright sunshine hours was statistically non-significant. Data from 2019 and 2020 were further analyzed using stepwise multiple regression to estimate anthracnose incidence in individual black pepper varieties. These regression models were subsequently validated using data of 2021. The root mean square error values varied between 0.0001 and 0.0011, indicating that the models are acceptable.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139199906","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}
Abishek Murugesan, R. Dave, Amit Kushwaha, Dharmendra Kumar Pandey, Koushik Saha
Surface soil moisture has vital role in water energy balance, climate change and agriculture mainly for crop water requirements and irrigation scheduling. Microwave remote sensing with its unique characteristics of high penetration and sensitivity towards dielectric constant, has enabled the researchers to explore various techniques for soil moisture estimation. With the launch of Sentinel-1 (A&B) Synthetic Aperture Radar (SAR) satellites, the hindrance in accessing high spatial and temporal resolution data is eliminated. The current study focuses on surface soil moisture estimation for bare agricultural fields in the semi-arid region. Field soil moisture up to 5 cm depth using HydraGo Probe sensor and surface roughness synchronizing with satellite pass dates were collected from total 102 locations spanning four dates. Volumetric and sensor-based soil moisture are well correlated with R2 = 0.85. The Modified Dubois Model (MDM) was applied to obtain the relative permittivity of the soil for the backscattering coefficient (σ◦) for VV polarization, which is used as one of the inputs in universal Topp’s model for soil moisture calculation. Model derived soil moisture is well correlated with ground-based soil moisture for the entire range of the soil moisture (0.02-0.18 m3m-3) with R2 = 0.85 and RMSE=0.005. The entire soil moisture was categorized in three soil moisture ranges to evaluate the sensitivity. The highest correlation was observed for 0.06-0.1 m3m-3 with R2 = 0.73 and RMSE=0.003 followed by 0.015-0.6 m3m-3 with R2 = 0.81 and RMSE=0.001 and 0.11-0.18 m3m-3 with R2 = 0.48 and RMSE=0.019 which is significantly low. Performance accuracy of MDM is encouraging for bare soil moisture estimation for even the lower range of surface soil moisture.
{"title":"Surface soil moisture estimation in bare agricultural soil using modified Dubois model for Sentinel-1 C-band SAR data","authors":"Abishek Murugesan, R. Dave, Amit Kushwaha, Dharmendra Kumar Pandey, Koushik Saha","doi":"10.54386/jam.v25i4.2303","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2303","url":null,"abstract":"Surface soil moisture has vital role in water energy balance, climate change and agriculture mainly for crop water requirements and irrigation scheduling. Microwave remote sensing with its unique characteristics of high penetration and sensitivity towards dielectric constant, has enabled the researchers to explore various techniques for soil moisture estimation. With the launch of Sentinel-1 (A&B) Synthetic Aperture Radar (SAR) satellites, the hindrance in accessing high spatial and temporal resolution data is eliminated. The current study focuses on surface soil moisture estimation for bare agricultural fields in the semi-arid region. Field soil moisture up to 5 cm depth using HydraGo Probe sensor and surface roughness synchronizing with satellite pass dates were collected from total 102 locations spanning four dates. Volumetric and sensor-based soil moisture are well correlated with R2 = 0.85. The Modified Dubois Model (MDM) was applied to obtain the relative permittivity of the soil for the backscattering coefficient (σ◦) for VV polarization, which is used as one of the inputs in universal Topp’s model for soil moisture calculation. Model derived soil moisture is well correlated with ground-based soil moisture for the entire range of the soil moisture (0.02-0.18 m3m-3) with R2 = 0.85 and RMSE=0.005. The entire soil moisture was categorized in three soil moisture ranges to evaluate the sensitivity. The highest correlation was observed for 0.06-0.1 m3m-3 with R2 = 0.73 and RMSE=0.003 followed by 0.015-0.6 m3m-3 with R2 = 0.81 and RMSE=0.001 and 0.11-0.18 m3m-3 with R2 = 0.48 and RMSE=0.019 which is significantly low. Performance accuracy of MDM is encouraging for bare soil moisture estimation for even the lower range of surface soil moisture.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200348","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 monsoon on the Indian subcontinent remains a seasonal occurrence that all inhabitants of the subcontinent desire. Modern scientific knowledge of methods of rain forecasting has originated recently. However, traditional indigenous wisdom is peculiar to our country. In the past, India had a magnificent scientific and technical legacy. Even today, it is common that village astrologers (pandits) are right in a surprisingly high percentage of their rain predictions. Scientists and local traditional farmers have a long history of astronomical research and treatises that predict rainfall. They use different methods to forecast rainfall conditions based on numerous panchangs, almanac bio-indicators (Bhoum method), non-bio-indicators (Antariksh method), and predict the likely behavior of climate in the planting season. Rainfall forecasting also aids in the planning of operations by agriculturists, builders, water supply engineers, and others. All mortals from the subcontinent have looked at it from their own perspective, and it continues to be the subject of intense multi-dimensional engagement. The monsoon has provided a means of life for numerous civilizations while also shaping the drainages and palaeo-geography of the subcontinent. The objective of this article is to document some indigenous knowledge for forecasting climate and environmental dynamics towards community resilience.
{"title":"Ancient science of weather forecasting in India with special reference to rainfall prediction","authors":"Vidyadhar B. Vaidya, Vyas Pandey, Suvarna Dhabale","doi":"10.54386/jam.v25i4.2422","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2422","url":null,"abstract":"The monsoon on the Indian subcontinent remains a seasonal occurrence that all inhabitants of the subcontinent desire. Modern scientific knowledge of methods of rain forecasting has originated recently. However, traditional indigenous wisdom is peculiar to our country. In the past, India had a magnificent scientific and technical legacy. Even today, it is common that village astrologers (pandits) are right in a surprisingly high percentage of their rain predictions. Scientists and local traditional farmers have a long history of astronomical research and treatises that predict rainfall. They use different methods to forecast rainfall conditions based on numerous panchangs, almanac bio-indicators (Bhoum method), non-bio-indicators (Antariksh method), and predict the likely behavior of climate in the planting season. Rainfall forecasting also aids in the planning of operations by agriculturists, builders, water supply engineers, and others. All mortals from the subcontinent have looked at it from their own perspective, and it continues to be the subject of intense multi-dimensional engagement. The monsoon has provided a means of life for numerous civilizations while also shaping the drainages and palaeo-geography of the subcontinent. The objective of this article is to document some indigenous knowledge for forecasting climate and environmental dynamics towards community resilience.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"126 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139197102","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}
Mostafa Abd EL-HAMEED Mohamed, Mohammed M. A. Hwehy, F. Moursy, Attia M. El-Tantawi
The interaction between thermal discomfort and air pollution poses significant challenges for human health and environmental well-being. When there is a high level of air pollution, it can worsen thermal discomfort by trapping heat in the atmosphere. This paper aims to study this interaction in arid megacities during different weather events. Weather data and air pollution were utilized to evaluate air quality, thermal discomfort levels, their impact, and their relationship at three separate sites (Qaha, Naser City, and 6th of October City). The ambient air quality is determined by measuring the levels of particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2). The work included a statistical analysis of the discomfort index (DI) and the air quality index (AQI) for each city and their linkage with the weather. The air quality evaluation revealed that a significant portion of the population in Qaha frequently experienced discomfort and were exposed to unhealthy levels of air pollution. The results show that most of the population in all three cities experience discomfort at least some of the time with varying degrees. In Qaha, 28.97% of the population experiences no discomfort, while 25.41% experiences severe stress. In Nasr City, 32.15% of the population experiences no discomfort, while 20.21% experiences severe stress. The 6th of October City, 33.76% of the population experienced no discomfort, while 16.65% experienced severe stress. Noted that certain months, specifically June to September, are associated with higher levels of discomfort, affecting more than 50% of the population. Seasonal variations in discomfort can be due to a range of factors, including weather, climate, and environmental conditions. The temporal variation in discomfort reflects the challenges people face when transitioning from colder to hotter seasons.
{"title":"The synergy of ambient air quality and thermal discomfort: A case study of Greater Cairo, Egypt","authors":"Mostafa Abd EL-HAMEED Mohamed, Mohammed M. A. Hwehy, F. Moursy, Attia M. El-Tantawi","doi":"10.54386/jam.v25i4.2309","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2309","url":null,"abstract":"The interaction between thermal discomfort and air pollution poses significant challenges for human health and environmental well-being. When there is a high level of air pollution, it can worsen thermal discomfort by trapping heat in the atmosphere. This paper aims to study this interaction in arid megacities during different weather events. Weather data and air pollution were utilized to evaluate air quality, thermal discomfort levels, their impact, and their relationship at three separate sites (Qaha, Naser City, and 6th of October City). The ambient air quality is determined by measuring the levels of particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2). The work included a statistical analysis of the discomfort index (DI) and the air quality index (AQI) for each city and their linkage with the weather. The air quality evaluation revealed that a significant portion of the population in Qaha frequently experienced discomfort and were exposed to unhealthy levels of air pollution. The results show that most of the population in all three cities experience discomfort at least some of the time with varying degrees. In Qaha, 28.97% of the population experiences no discomfort, while 25.41% experiences severe stress. In Nasr City, 32.15% of the population experiences no discomfort, while 20.21% experiences severe stress. The 6th of October City, 33.76% of the population experienced no discomfort, while 16.65% experienced severe stress. Noted that certain months, specifically June to September, are associated with higher levels of discomfort, affecting more than 50% of the population. Seasonal variations in discomfort can be due to a range of factors, including weather, climate, and environmental conditions. The temporal variation in discomfort reflects the challenges people face when transitioning from colder to hotter seasons.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"30 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139205876","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}
A detailed review was done on the past studies conducted by the researchers on climate change and variability, particularly for the Indian conditions having a typical monsoon climate. The short-term droughts (flash droughts) occurring due to the prolonged dry spells, heat waves, soil moisture deficits, which are caused due to the climate variability were also investigated. Accurate prediction techniques used for flash drought (FD), assessment of its impact on agriculture and farmers’ income as well as appropriate coping strategies recommended by different researchers to minimize the losses in crop yield and farmers’ income were analyzed. The total loss in crop yield was found to increase with increase in land size; however, per acre loss was higher for smaller holdings. It was observed that the resource crunch small and marginal farmers particularly belonging to SC/ST were worst sufferers due to their inability to adopt appropriate coping strategies such as: crop insurance, short duration climate resilient cultivars, low-interest loans from financial institutions etc. It was inferred that the FD needs special attention particularly for the state of Odisha, where a majority of the population are engaged in agriculture and its allied activities. Agriculture accounts for around 30 per cent of the net state domestic product (NSDP). Investigations of the past studies revealed that the western Odisha regions are most vulnerable to climate change and variability and to the FD caused by the climate variability. The small and marginal tribal farmers of western Odisha whose sole source of income is from agriculture, with low affordability, are worst affected. To cope with these natural calamities, they need to adopt coping strategies namely, going for a variety of sources of income, cultivation of short-duration climate resilient varieties, in-situ rainwater conservation and use for life-saving irrigation, crop insurance, and low interest loans as well as low-cost post-harvest techniques for the perishable crop produce etc.
{"title":"Flash drought in Odisha- prediction, impact assessment, coping strategies: Current status and future strategies","authors":"R. K. Panda, U. C. Mohanty, S. Dash, Curie Parhi","doi":"10.54386/jam.v25i4.2450","DOIUrl":"https://doi.org/10.54386/jam.v25i4.2450","url":null,"abstract":"A detailed review was done on the past studies conducted by the researchers on climate change and variability, particularly for the Indian conditions having a typical monsoon climate. The short-term droughts (flash droughts) occurring due to the prolonged dry spells, heat waves, soil moisture deficits, which are caused due to the climate variability were also investigated. Accurate prediction techniques used for flash drought (FD), assessment of its impact on agriculture and farmers’ income as well as appropriate coping strategies recommended by different researchers to minimize the losses in crop yield and farmers’ income were analyzed. The total loss in crop yield was found to increase with increase in land size; however, per acre loss was higher for smaller holdings. It was observed that the resource crunch small and marginal farmers particularly belonging to SC/ST were worst sufferers due to their inability to adopt appropriate coping strategies such as: crop insurance, short duration climate resilient cultivars, low-interest loans from financial institutions etc. It was inferred that the FD needs special attention particularly for the state of Odisha, where a majority of the population are engaged in agriculture and its allied activities. Agriculture accounts for around 30 per cent of the net state domestic product (NSDP). Investigations of the past studies revealed that the western Odisha regions are most vulnerable to climate change and variability and to the FD caused by the climate variability. The small and marginal tribal farmers of western Odisha whose sole source of income is from agriculture, with low affordability, are worst affected. To cope with these natural calamities, they need to adopt coping strategies namely, going for a variety of sources of income, cultivation of short-duration climate resilient varieties, in-situ rainwater conservation and use for life-saving irrigation, crop insurance, and low interest loans as well as low-cost post-harvest techniques for the perishable crop produce etc.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"127 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139197342","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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