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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Muhammad Shafeeque; Arfan Arshad; Ahmed Elbeltagi; Abid Sarwar; +4 Authors

    Les mesures strictes de confinement ont non seulement contribué à freiner la propagation de l'infection à COVID-19, mais ont également amélioré les conditions environnementales dans le monde entier. L'objectif principal de la présente étude était d'étudier les co-bénéfices du confinement de la COVID-19 sur l'atmosphère et le système écologique aquatique dans le cadre d'activités anthropiques restreintes en Asie du Sud. Les données de télédétection (a) des émissions de NO2 de l'instrument de surveillance de l'ozone (OMI), (b) de la profondeur optique des aérosols (AOD) du spectroradiomètre d'imagerie à résolution modérée (MODIS) et (c) de la chlorophylle (Chl-a) et des données de turbidité de MODIS-Aqua Level-3 au cours de janvier-octobre (2020) ont été analysées pour évaluer les changements dans la pollution de l'air et de l'eau par rapport aux cinq dernières années (2015–2019). Les interactions entre la pollution de l'air et de l'eau ont également été étudiées en utilisant le ruissellement terrestre et les précipitations en 2019 et 2020 à une échelle mensuelle pour enquêter sur les événements anormaux, qui pourraient affecter la charge d'azote dans les régions côtières. Les résultats ont révélé une baisse considérable de la pollution de l'air et de l'eau (réduction de 30 à 40 % des émissions de NO2, de 45 % de l'AOD, de 50 % de la concentration de chl-a sur les côtes et de 29 % de la turbidité) en Asie du Sud. Le taux de réduction des émissions de NO2 a été le plus élevé à Lahore (32 %), New Delhi (31 %), Ahmadabad (29 %), Karachi (26 %), Hyderabad (24 %) et Chennai (17 %) pendant la période de confinement strict d'avril à juin 2020. Une corrélation positive entre l'AOD et les émissions de NO2 (0,23-0,50) implique qu'une diminution de l'AOD est attribuée à une réduction du NO2. Il a été observé que pendant le confinement strict, la turbidité a diminué de 29 %, 11 %, 16 % et 17 % le long des régions côtières de Karachi, Mumbai, Calcutta et Dhaka, respectivement, tandis qu'une augmentation de 5 à 6 % de la turbidité a été observée sur les Madras au cours de la même période. Les résultats soulignent l'importance de la réduction des émissions d'azote en raison de l'arrêt de la consommation de combustibles fossiles et de leurs relations avec la réduction de la pollution de l'air et de l'eau. Il est conclu que l'environnement atmosphérique et hydrosphérique peut être amélioré en mettant en œuvre des restrictions intelligentes sur la consommation de combustibles fossiles avec un effet minimum sur la socio-économie dans la région. Des contraintes intelligentes sur l'utilisation des combustibles fossiles sont recommandées pour contrôler la pollution de l'air et de l'eau même après la reprise des activités sociales et économiques. Las estrictas medidas de confinamiento no solo contribuyeron a frenar la propagación de la infección por COVID-19, sino que también mejoraron las condiciones ambientales en todo el mundo. El objetivo principal del estudio actual fue investigar los beneficios colaterales del confinamiento por COVID-19 en la atmósfera y el sistema ecológico acuático bajo actividades antropogénicas restringidas en el sur de Asia. Los datos de teledetección (a) emisiones de NO2 del Instrumento de Monitoreo de Ozono (OMI), (b) Profundidad Óptica de Aerosol (AOD) del Espectrorradiómetro de Imágenes de Resolución Moderada (MODIS) y (c) clorofila (Chl-a) y datos de turbidez de MODIS-Aqua Nivel-3 durante enero-octubre (2020) se analizaron para evaluar los cambios en la contaminación del aire y el agua en comparación con los últimos cinco años (2015–2019). Las interacciones entre la contaminación del aire y del agua también se investigaron utilizando la escorrentía y las precipitaciones terrestres en 2019 y 2020 a escala mensual para investigar los eventos anómalos, que podrían afectar la carga de N en las regiones costeras. Los resultados revelaron una caída considerable en la contaminación del aire y el agua (reducción del 30–40% en las emisiones de NO2, 45% en AOD, disminución del 50% en la concentración costera de Chl-a y disminución del 29% en la turbidez) en el sur de Asia. La tasa de reducción de las emisiones de NO2 fue la más alta para Lahore (32%), Nueva Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%) y Chennai (17%) durante el estricto período de confinamiento de abril a junio de 2020. Una correlación positiva entre AOD y las emisiones de NO2 (0.23-0.50) implica que una disminución en AOD se atribuye a una reducción en NO2. Se observó que durante el confinamiento estricto, la turbidez ha disminuido en un 29%, 11%, 16% y 17% a lo largo de las regiones costeras de Karachi, Mumbai, Calcuta y Dhaka, respectivamente, mientras que se observó un aumento del 5–6% en la turbidez en Madras durante el mismo período. Los hallazgos enfatizan la importancia de reducir las emisiones de N debido a la interrupción del consumo de combustibles fósiles y sus relaciones con la reducción de la contaminación del aire y el agua. Se concluye que el ambiente atmosférico e hidrosférico puede mejorarse mediante la implementación de restricciones inteligentes en el consumo de combustibles fósiles con un efecto mínimo en la socioeconómica de la región. Se recomiendan restricciones inteligentes en el uso de combustibles fósiles para controlar la contaminación del aire y del agua incluso después de que las actividades sociales y económicas reanuden el escenario habitual. The strict lockdown measures not only contributed to curbing the spread of COVID-19 infection, but also improved the environmental conditions worldwide. The main goal of the current study was to investigate the co-benefits of COVID-19 lockdown on the atmosphere and aquatic ecological system under restricted anthropogenic activities in South Asia. The remote sensing data (a) NO2 emissions from the Ozone Monitoring Instrument (OMI), (b) Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and (c) chlorophyll (Chl-a) and turbidity data from MODIS-Aqua Level-3 during Jan–Oct (2020) were analyzed to assess the changes in air and water pollution compared to the last five years (2015–2019). The interactions between the air and water pollution were also investigated using overland runoff and precipitation in 2019 and 2020 at a monthly scale to investigate the anomalous events, which could affect the N loading to coastal regions. The results revealed a considerable drop in the air and water pollution (30–40% reduction in NO2 emissions, 45% in AOD, 50% decline in coastal Chl-a concentration, and 29% decline in turbidity) over South Asia. The rate of reduction in NO2 emissions was found the highest for Lahore (32%), New Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%), and Chennai (17%) during the strict lockdown period from Apr–Jun, 2020. A positive correlation between AOD and NO2 emissions (0.23–0.50) implies that a decrease in AOD is attributed to a reduction in NO2. It was observed that during strict lockdown, the turbidity has decreased by 29%, 11%, 16%, and 17% along the coastal regions of Karachi, Mumbai, Calcutta, and Dhaka, respectively, while a 5–6% increase in turbidity was seen over the Madras during the same period. The findings stress the importance of reduced N emissions due to halted fossil fuel consumption and their relationships with the reduced air and water pollution. It is concluded that the atmospheric and hydrospheric environment can be improved by implementing smart restrictions on fossil fuel consumption with a minimum effect on socioeconomics in the region. Smart constraints on fossil fuel usage are recommended to control air and water pollution even after the social and economic activities resume business-as-usual scenario. لم تساهم إجراءات الإغلاق الصارمة في الحد من انتشار عدوى COVID -19 فحسب، بل أدت أيضًا إلى تحسين الظروف البيئية في جميع أنحاء العالم. كان الهدف الرئيسي من الدراسة الحالية هو التحقيق في الفوائد المشتركة لإغلاق COVID -19 على الغلاف الجوي والنظام البيئي المائي في ظل الأنشطة البشرية المقيدة في جنوب آسيا. تم تحليل بيانات الاستشعار عن بعد (أ) انبعاثات ثاني أكسيد النيتروجين من جهاز مراقبة الأوزون (OMI)، (ب) العمق البصري للهباء الجوي (AOD) من مقياس الطيف التصويري متوسط الدقة (MODIS)، و (ج) بيانات الكلوروفيل (Chl - a) والتعكر من MODIS - Aqua Level -3 خلال الفترة من يناير إلى أكتوبر (2020) لتقييم التغيرات في تلوث الهواء والماء مقارنة بالسنوات الخمس الماضية (2015–2019). كما تم التحقيق في التفاعلات بين تلوث الهواء والمياه باستخدام الجريان السطحي وهطول الأمطار في عامي 2019 و 2020 على نطاق شهري للتحقيق في الأحداث الشاذة، والتي يمكن أن تؤثر على تحميل N إلى المناطق الساحلية. كشفت النتائج عن انخفاض كبير في تلوث الهواء والماء (انخفاض بنسبة 30-40 ٪ في انبعاثات ثاني أكسيد النيتروجين، و 45 ٪ في AOD، وانخفاض بنسبة 50 ٪ في تركيز Chl - a الساحلي، وانخفاض بنسبة 29 ٪ في التعكر) فوق جنوب آسيا. وجد أن معدل الانخفاض في انبعاثات ثاني أكسيد النيتروجين هو الأعلى في لاهور (32 ٪) ونيودلهي (31 ٪) وأحمد أباد (29 ٪) وكراتشي (26 ٪) وحيدر أباد (24 ٪) وتشيناي (17 ٪) خلال فترة الإغلاق الصارمة من أبريل إلى يونيو 2020. تشير العلاقة الإيجابية بين انبعاثات أكسيد النيتروجين وثاني أكسيد النيتروجين (0.23-0.50) إلى أن انخفاض أكسيد النيتروجين يعزى إلى انخفاض ثاني أكسيد النيتروجين. لوحظ أنه خلال الإغلاق الصارم، انخفض التعكر بنسبة 29 ٪ و 11 ٪ و 16 ٪ و 17 ٪ على طول المناطق الساحلية في كراتشي ومومباي وكلكتا ودكا، على التوالي، في حين لوحظت زيادة بنسبة 5-6 ٪ في التعكر فوق مدراس خلال نفس الفترة. وتشدد النتائج على أهمية خفض انبعاثات النيتروجين بسبب وقف استهلاك الوقود الأحفوري وعلاقاتها بانخفاض تلوث الهواء والماء. وخلص إلى أنه يمكن تحسين البيئة الجوية والمائية من خلال تنفيذ قيود ذكية على استهلاك الوقود الأحفوري بأقل تأثير على الاقتصاد الاجتماعي في المنطقة. يوصى بالقيود الذكية على استخدام الوقود الأحفوري للسيطرة على تلوث الهواء والماء حتى بعد استئناف الأنشطة الاجتماعية والاقتصادية لسيناريو العمل كالمعتاد.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Geomatics, Natural H...arrow_drop_down
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    Geomatics, Natural Hazards & Risk
    Article . 2021 . Peer-reviewed
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    Geomatics, Natural Hazards & Risk
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Geomatics, Natural H...arrow_drop_down
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      Geomatics, Natural Hazards & Risk
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      https://dx.doi.org/10.60692/e5...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Muhammad Shafeeque; Arfan Arshad; Ahmed Elbeltagi; Abid Sarwar; +4 Authors

    Les mesures strictes de confinement ont non seulement contribué à freiner la propagation de l'infection à COVID-19, mais ont également amélioré les conditions environnementales dans le monde entier. L'objectif principal de la présente étude était d'étudier les co-bénéfices du confinement de la COVID-19 sur l'atmosphère et le système écologique aquatique dans le cadre d'activités anthropiques restreintes en Asie du Sud. Les données de télédétection (a) des émissions de NO2 de l'instrument de surveillance de l'ozone (OMI), (b) de la profondeur optique des aérosols (AOD) du spectroradiomètre d'imagerie à résolution modérée (MODIS) et (c) de la chlorophylle (Chl-a) et des données de turbidité de MODIS-Aqua Level-3 au cours de janvier-octobre (2020) ont été analysées pour évaluer les changements dans la pollution de l'air et de l'eau par rapport aux cinq dernières années (2015–2019). Les interactions entre la pollution de l'air et de l'eau ont également été étudiées en utilisant le ruissellement terrestre et les précipitations en 2019 et 2020 à une échelle mensuelle pour enquêter sur les événements anormaux, qui pourraient affecter la charge d'azote dans les régions côtières. Les résultats ont révélé une baisse considérable de la pollution de l'air et de l'eau (réduction de 30 à 40 % des émissions de NO2, de 45 % de l'AOD, de 50 % de la concentration de chl-a sur les côtes et de 29 % de la turbidité) en Asie du Sud. Le taux de réduction des émissions de NO2 a été le plus élevé à Lahore (32 %), New Delhi (31 %), Ahmadabad (29 %), Karachi (26 %), Hyderabad (24 %) et Chennai (17 %) pendant la période de confinement strict d'avril à juin 2020. Une corrélation positive entre l'AOD et les émissions de NO2 (0,23-0,50) implique qu'une diminution de l'AOD est attribuée à une réduction du NO2. Il a été observé que pendant le confinement strict, la turbidité a diminué de 29 %, 11 %, 16 % et 17 % le long des régions côtières de Karachi, Mumbai, Calcutta et Dhaka, respectivement, tandis qu'une augmentation de 5 à 6 % de la turbidité a été observée sur les Madras au cours de la même période. Les résultats soulignent l'importance de la réduction des émissions d'azote en raison de l'arrêt de la consommation de combustibles fossiles et de leurs relations avec la réduction de la pollution de l'air et de l'eau. Il est conclu que l'environnement atmosphérique et hydrosphérique peut être amélioré en mettant en œuvre des restrictions intelligentes sur la consommation de combustibles fossiles avec un effet minimum sur la socio-économie dans la région. Des contraintes intelligentes sur l'utilisation des combustibles fossiles sont recommandées pour contrôler la pollution de l'air et de l'eau même après la reprise des activités sociales et économiques. Las estrictas medidas de confinamiento no solo contribuyeron a frenar la propagación de la infección por COVID-19, sino que también mejoraron las condiciones ambientales en todo el mundo. El objetivo principal del estudio actual fue investigar los beneficios colaterales del confinamiento por COVID-19 en la atmósfera y el sistema ecológico acuático bajo actividades antropogénicas restringidas en el sur de Asia. Los datos de teledetección (a) emisiones de NO2 del Instrumento de Monitoreo de Ozono (OMI), (b) Profundidad Óptica de Aerosol (AOD) del Espectrorradiómetro de Imágenes de Resolución Moderada (MODIS) y (c) clorofila (Chl-a) y datos de turbidez de MODIS-Aqua Nivel-3 durante enero-octubre (2020) se analizaron para evaluar los cambios en la contaminación del aire y el agua en comparación con los últimos cinco años (2015–2019). Las interacciones entre la contaminación del aire y del agua también se investigaron utilizando la escorrentía y las precipitaciones terrestres en 2019 y 2020 a escala mensual para investigar los eventos anómalos, que podrían afectar la carga de N en las regiones costeras. Los resultados revelaron una caída considerable en la contaminación del aire y el agua (reducción del 30–40% en las emisiones de NO2, 45% en AOD, disminución del 50% en la concentración costera de Chl-a y disminución del 29% en la turbidez) en el sur de Asia. La tasa de reducción de las emisiones de NO2 fue la más alta para Lahore (32%), Nueva Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%) y Chennai (17%) durante el estricto período de confinamiento de abril a junio de 2020. Una correlación positiva entre AOD y las emisiones de NO2 (0.23-0.50) implica que una disminución en AOD se atribuye a una reducción en NO2. Se observó que durante el confinamiento estricto, la turbidez ha disminuido en un 29%, 11%, 16% y 17% a lo largo de las regiones costeras de Karachi, Mumbai, Calcuta y Dhaka, respectivamente, mientras que se observó un aumento del 5–6% en la turbidez en Madras durante el mismo período. Los hallazgos enfatizan la importancia de reducir las emisiones de N debido a la interrupción del consumo de combustibles fósiles y sus relaciones con la reducción de la contaminación del aire y el agua. Se concluye que el ambiente atmosférico e hidrosférico puede mejorarse mediante la implementación de restricciones inteligentes en el consumo de combustibles fósiles con un efecto mínimo en la socioeconómica de la región. Se recomiendan restricciones inteligentes en el uso de combustibles fósiles para controlar la contaminación del aire y del agua incluso después de que las actividades sociales y económicas reanuden el escenario habitual. The strict lockdown measures not only contributed to curbing the spread of COVID-19 infection, but also improved the environmental conditions worldwide. The main goal of the current study was to investigate the co-benefits of COVID-19 lockdown on the atmosphere and aquatic ecological system under restricted anthropogenic activities in South Asia. The remote sensing data (a) NO2 emissions from the Ozone Monitoring Instrument (OMI), (b) Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and (c) chlorophyll (Chl-a) and turbidity data from MODIS-Aqua Level-3 during Jan–Oct (2020) were analyzed to assess the changes in air and water pollution compared to the last five years (2015–2019). The interactions between the air and water pollution were also investigated using overland runoff and precipitation in 2019 and 2020 at a monthly scale to investigate the anomalous events, which could affect the N loading to coastal regions. The results revealed a considerable drop in the air and water pollution (30–40% reduction in NO2 emissions, 45% in AOD, 50% decline in coastal Chl-a concentration, and 29% decline in turbidity) over South Asia. The rate of reduction in NO2 emissions was found the highest for Lahore (32%), New Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%), and Chennai (17%) during the strict lockdown period from Apr–Jun, 2020. A positive correlation between AOD and NO2 emissions (0.23–0.50) implies that a decrease in AOD is attributed to a reduction in NO2. It was observed that during strict lockdown, the turbidity has decreased by 29%, 11%, 16%, and 17% along the coastal regions of Karachi, Mumbai, Calcutta, and Dhaka, respectively, while a 5–6% increase in turbidity was seen over the Madras during the same period. The findings stress the importance of reduced N emissions due to halted fossil fuel consumption and their relationships with the reduced air and water pollution. It is concluded that the atmospheric and hydrospheric environment can be improved by implementing smart restrictions on fossil fuel consumption with a minimum effect on socioeconomics in the region. Smart constraints on fossil fuel usage are recommended to control air and water pollution even after the social and economic activities resume business-as-usual scenario. لم تساهم إجراءات الإغلاق الصارمة في الحد من انتشار عدوى COVID -19 فحسب، بل أدت أيضًا إلى تحسين الظروف البيئية في جميع أنحاء العالم. كان الهدف الرئيسي من الدراسة الحالية هو التحقيق في الفوائد المشتركة لإغلاق COVID -19 على الغلاف الجوي والنظام البيئي المائي في ظل الأنشطة البشرية المقيدة في جنوب آسيا. تم تحليل بيانات الاستشعار عن بعد (أ) انبعاثات ثاني أكسيد النيتروجين من جهاز مراقبة الأوزون (OMI)، (ب) العمق البصري للهباء الجوي (AOD) من مقياس الطيف التصويري متوسط الدقة (MODIS)، و (ج) بيانات الكلوروفيل (Chl - a) والتعكر من MODIS - Aqua Level -3 خلال الفترة من يناير إلى أكتوبر (2020) لتقييم التغيرات في تلوث الهواء والماء مقارنة بالسنوات الخمس الماضية (2015–2019). كما تم التحقيق في التفاعلات بين تلوث الهواء والمياه باستخدام الجريان السطحي وهطول الأمطار في عامي 2019 و 2020 على نطاق شهري للتحقيق في الأحداث الشاذة، والتي يمكن أن تؤثر على تحميل N إلى المناطق الساحلية. كشفت النتائج عن انخفاض كبير في تلوث الهواء والماء (انخفاض بنسبة 30-40 ٪ في انبعاثات ثاني أكسيد النيتروجين، و 45 ٪ في AOD، وانخفاض بنسبة 50 ٪ في تركيز Chl - a الساحلي، وانخفاض بنسبة 29 ٪ في التعكر) فوق جنوب آسيا. وجد أن معدل الانخفاض في انبعاثات ثاني أكسيد النيتروجين هو الأعلى في لاهور (32 ٪) ونيودلهي (31 ٪) وأحمد أباد (29 ٪) وكراتشي (26 ٪) وحيدر أباد (24 ٪) وتشيناي (17 ٪) خلال فترة الإغلاق الصارمة من أبريل إلى يونيو 2020. تشير العلاقة الإيجابية بين انبعاثات أكسيد النيتروجين وثاني أكسيد النيتروجين (0.23-0.50) إلى أن انخفاض أكسيد النيتروجين يعزى إلى انخفاض ثاني أكسيد النيتروجين. لوحظ أنه خلال الإغلاق الصارم، انخفض التعكر بنسبة 29 ٪ و 11 ٪ و 16 ٪ و 17 ٪ على طول المناطق الساحلية في كراتشي ومومباي وكلكتا ودكا، على التوالي، في حين لوحظت زيادة بنسبة 5-6 ٪ في التعكر فوق مدراس خلال نفس الفترة. وتشدد النتائج على أهمية خفض انبعاثات النيتروجين بسبب وقف استهلاك الوقود الأحفوري وعلاقاتها بانخفاض تلوث الهواء والماء. وخلص إلى أنه يمكن تحسين البيئة الجوية والمائية من خلال تنفيذ قيود ذكية على استهلاك الوقود الأحفوري بأقل تأثير على الاقتصاد الاجتماعي في المنطقة. يوصى بالقيود الذكية على استخدام الوقود الأحفوري للسيطرة على تلوث الهواء والماء حتى بعد استئناف الأنشطة الاجتماعية والاقتصادية لسيناريو العمل كالمعتاد.

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    Authors: Abu Reza Md. Towfiqul Islam; Irtifa Alam Nabila; Md. Hasanuzzaman; Md. Bozlar Rahman; +5 Authors

    En raison des variations climatiques évidentes et de la contribution significative à la production alimentaire nationale, le Bangladesh est une région d'examen des conséquences climatiques pour la production de riz (Oryza Sativa). Cette étude vise à explorer la variabilité des variables climatiques (par exemple, les variations de la température moyenne, des précipitations, de l'humidité relative et de la durée d'ensoleillement) avec les rendements en riz (par exemple, les variétés de riz Aus, Aman et Boro) dans le nord-ouest du Bangladesh. Le test de Mann–Kendall modifié, l'estimateur de pente de Theil–Sen et la modélisation par régression linéaire multiple (MLR) ont été utilisés pour estimer l'association entre ces facteurs. L'hétéroskédasticité et l'erreur standard constante d'autocorrélation (HAC) et la technique faisable des moindres carrés généralisés (FGLS) ont été adoptées pour mesurer le lien entre le climat et les cultures de riz à l'aide de l'ensemble de données au niveau régional pour 1976–2015. En outre, la variation spatio-temporelle des tendances du rendement du riz avec les variables climatiques a été cartographiée et évaluée par le coefficient de variation. Les résultats montrent que les tendances observées en matière de température et d'humidité ont été bénéfiques pour les rendements Aus et Aman, mais pas pour les rendements Boro. En revanche, les tendances observées en matière de précipitations et d'ensoleillement ont été négatives pour les trois saisons du riz. Les résultats du modèle MLR expliquent 67 %, 92 % et 83 % de la variabilité des rendements en riz Aus, Aman et Boro dans la région étudiée. Les résultats du modèle ont montré que l'humidité et les précipitations ont eu un impact négatif sur les cultures de riz Aus et Aman, tandis que la température et les précipitations ont une influence positive sur le rendement du riz Boro. En ce qui concerne les questions de changement climatique et la sauvegarde de la sécurité alimentaire au niveau régional, les autorités concernées devraient accorder une attention considérable à l'amélioration des variétés à haut rendement tolérantes à la chaleur et à la sécheresse contre les effets climatiques sur les variétés de riz Aus et Aman. Debido a las evidentes variaciones climáticas y a la importante contribución a la producción nacional de alimentos, Bangladesh es una región climáticamente crítica para examinar las consecuencias climáticas para la producción de cultivos de arroz (Oryza Sativa). Este estudio pretende explorar la variabilidad de las variables climáticas (por ejemplo, variaciones en la temperatura media, las precipitaciones, la humedad relativa y la duración del sol) con los rendimientos de arroz (por ejemplo, las variedades de arroz AUS, aman y Boro) en el noroeste de Bangladesh. La prueba de Mann–Kendall modificada, el estimador de pendiente de Theil–Sen y el modelado de regresión lineal múltiple (MLR) se utilizaron para estimar la asociación entre estos factores. Se adoptó la técnica de heterocedasticidad y error estándar constante de autocorrelación (hac) y mínimos cuadrados generalizados factibles (FGLS) para medir el nexo clima-arroz utilizando el conjunto de datos a nivel regional para 1976–2015. Además, se mapeó y evaluó la variación espaciotemporal de las tendencias de rendimiento del arroz con variables climáticas mediante el coeficiente de variación. Los resultados muestran que las tendencias observadas de temperatura y humedad fueron beneficiosas para los rendimientos de AUS y aman, pero no para los rendimientos de Boro. Por el contrario, las tendencias observadas de precipitaciones y sol fueron negativas para las tres temporadas de arroz. Los resultados del modelo MLR explicaron el 67%, 92% y 83% de la variabilidad en los rendimientos de arroz AUS, aman y Boro en la región de estudio. Los resultados del modelo mostraron que la humedad y las precipitaciones han afectado negativamente a los cultivos de arroz AUS y aman, mientras que la temperatura y las precipitaciones influyen positivamente en el rendimiento del arroz Boro. Con respecto a los problemas del cambio climático y la salvaguardia de la seguridad alimentaria a nivel regional, las autoridades competentes deben prestar una atención sustancial a la mejora de las variedades de alto rendimiento tolerantes al calor y la sequía frente a los efectos climáticos en las variedades de arroz AUS y aman. Because of evident climatic variations and significant contribution to national food production, Bangladesh is a climate extreme hotspot region of examination for climatic consequences for rice (Oryza Sativa) crop production. This study intends to explore the variability of climatic variables (e.g., variations in mean temperature, rainfall, relative humidity, and sunshine duration) with rice yields (e.g., Aus, Aman, and Boro rice varieties) in northwest Bangladesh. The modified Mann–Kendall test, Theil–Sen slope estimator, and multiple linear regression (MLR) modeling were used to estimate the association among these factors. Heteroskedasticity and autocorrelation constant standard error (HAC) and feasible generalized least square (FGLS) technique were adopted to measure the climate-rice crop nexus using the regional level dataset for 1976–2015. Furthermore, the spatiotemporal variation of rice yield trends with climatic variables was mapped and assessed by the coefficient of variation. The results show that observed temperature and humidity trends were beneficial for Aus and Aman yields but not Boro yields. In contrast, observed rainfall and sunshine trends were negative for all three rice seasons. The outcomes of the MLR model explained 67%, 92%, and 83% of the variability in Aus, Aman, and Boro rice yields in the study region. The model outcomes showed that humidity and rainfall have negatively affected Aus and Aman rice crops, while temperature and rainfall positively influence Boro rice yield. Regarding the climate change issues and safeguarding food safety at the regional level, the concerned authorities should provide substantial attention to improving heat and drought-tolerance high-yielding varieties against climate effects on Aus and Aman rice varieties. نظرًا للتغيرات المناخية الواضحة والمساهمة الكبيرة في الإنتاج الغذائي الوطني، تعد بنغلاديش منطقة ساخنة شديدة المناخ لفحص الآثار المناخية على إنتاج محاصيل الأرز (أوريزا ساتيفا). تهدف هذه الدراسة إلى استكشاف تقلب المتغيرات المناخية (على سبيل المثال، الاختلافات في متوسط درجة الحرارة وهطول الأمطار والرطوبة النسبية ومدة أشعة الشمس) مع غلة الأرز (على سبيل المثال، أصناف أرز أستراليا وأمان وبورو) في شمال غرب بنغلاديش. تم استخدام اختبار مان- كيندال المعدل، ومقدر ميل ثيل- سين، ونمذجة الانحدار الخطي المتعدد (MLR) لتقدير الارتباط بين هذه العوامل. تم اعتماد المرونة المتغايرة والخطأ المعياري الثابت للارتباط الذاتي (HAC) وتقنية المربعات الأقل عمومية (FGLS) لقياس العلاقة بين محاصيل المناخ والأرز باستخدام مجموعة البيانات على المستوى الإقليمي للفترة 1976–2015. علاوة على ذلك، تم تعيين وتقييم التباين المكاني والزماني لاتجاهات غلة الأرز مع المتغيرات المناخية من خلال معامل التباين. تظهر النتائج أن اتجاهات درجة الحرارة والرطوبة المرصودة كانت مفيدة لمحاصيل Aus و Aman ولكن ليس محاصيل Boro. على النقيض من ذلك، كانت اتجاهات هطول الأمطار وأشعة الشمس المرصودة سلبية لجميع مواسم الأرز الثلاثة. أوضحت نتائج نموذج MLR 67 ٪ و 92 ٪ و 83 ٪ من التباين في غلة أرز AUS و Aman و Boro في منطقة الدراسة. أظهرت نتائج النموذج أن الرطوبة وهطول الأمطار قد أثرت سلبًا على محاصيل الأرز في أستراليا وأمان، في حين أن درجة الحرارة وهطول الأمطار يؤثران بشكل إيجابي على غلة أرز بورو. فيما يتعلق بقضايا تغير المناخ وحماية سلامة الأغذية على المستوى الإقليمي، يجب على السلطات المعنية إيلاء اهتمام كبير لتحسين الأصناف عالية الغلة التي تتحمل الحرارة والجفاف ضد الآثار المناخية على أصناف أرز أستراليا وأمان.

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      Theoretical and Applied Climatology
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      Theoretical and Applied Climatology
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    Authors: Abu Reza Md. Towfiqul Islam; Irtifa Alam Nabila; Md. Hasanuzzaman; Md. Bozlar Rahman; +5 Authors

    En raison des variations climatiques évidentes et de la contribution significative à la production alimentaire nationale, le Bangladesh est une région d'examen des conséquences climatiques pour la production de riz (Oryza Sativa). Cette étude vise à explorer la variabilité des variables climatiques (par exemple, les variations de la température moyenne, des précipitations, de l'humidité relative et de la durée d'ensoleillement) avec les rendements en riz (par exemple, les variétés de riz Aus, Aman et Boro) dans le nord-ouest du Bangladesh. Le test de Mann–Kendall modifié, l'estimateur de pente de Theil–Sen et la modélisation par régression linéaire multiple (MLR) ont été utilisés pour estimer l'association entre ces facteurs. L'hétéroskédasticité et l'erreur standard constante d'autocorrélation (HAC) et la technique faisable des moindres carrés généralisés (FGLS) ont été adoptées pour mesurer le lien entre le climat et les cultures de riz à l'aide de l'ensemble de données au niveau régional pour 1976–2015. En outre, la variation spatio-temporelle des tendances du rendement du riz avec les variables climatiques a été cartographiée et évaluée par le coefficient de variation. Les résultats montrent que les tendances observées en matière de température et d'humidité ont été bénéfiques pour les rendements Aus et Aman, mais pas pour les rendements Boro. En revanche, les tendances observées en matière de précipitations et d'ensoleillement ont été négatives pour les trois saisons du riz. Les résultats du modèle MLR expliquent 67 %, 92 % et 83 % de la variabilité des rendements en riz Aus, Aman et Boro dans la région étudiée. Les résultats du modèle ont montré que l'humidité et les précipitations ont eu un impact négatif sur les cultures de riz Aus et Aman, tandis que la température et les précipitations ont une influence positive sur le rendement du riz Boro. En ce qui concerne les questions de changement climatique et la sauvegarde de la sécurité alimentaire au niveau régional, les autorités concernées devraient accorder une attention considérable à l'amélioration des variétés à haut rendement tolérantes à la chaleur et à la sécheresse contre les effets climatiques sur les variétés de riz Aus et Aman. Debido a las evidentes variaciones climáticas y a la importante contribución a la producción nacional de alimentos, Bangladesh es una región climáticamente crítica para examinar las consecuencias climáticas para la producción de cultivos de arroz (Oryza Sativa). Este estudio pretende explorar la variabilidad de las variables climáticas (por ejemplo, variaciones en la temperatura media, las precipitaciones, la humedad relativa y la duración del sol) con los rendimientos de arroz (por ejemplo, las variedades de arroz AUS, aman y Boro) en el noroeste de Bangladesh. La prueba de Mann–Kendall modificada, el estimador de pendiente de Theil–Sen y el modelado de regresión lineal múltiple (MLR) se utilizaron para estimar la asociación entre estos factores. Se adoptó la técnica de heterocedasticidad y error estándar constante de autocorrelación (hac) y mínimos cuadrados generalizados factibles (FGLS) para medir el nexo clima-arroz utilizando el conjunto de datos a nivel regional para 1976–2015. Además, se mapeó y evaluó la variación espaciotemporal de las tendencias de rendimiento del arroz con variables climáticas mediante el coeficiente de variación. Los resultados muestran que las tendencias observadas de temperatura y humedad fueron beneficiosas para los rendimientos de AUS y aman, pero no para los rendimientos de Boro. Por el contrario, las tendencias observadas de precipitaciones y sol fueron negativas para las tres temporadas de arroz. Los resultados del modelo MLR explicaron el 67%, 92% y 83% de la variabilidad en los rendimientos de arroz AUS, aman y Boro en la región de estudio. Los resultados del modelo mostraron que la humedad y las precipitaciones han afectado negativamente a los cultivos de arroz AUS y aman, mientras que la temperatura y las precipitaciones influyen positivamente en el rendimiento del arroz Boro. Con respecto a los problemas del cambio climático y la salvaguardia de la seguridad alimentaria a nivel regional, las autoridades competentes deben prestar una atención sustancial a la mejora de las variedades de alto rendimiento tolerantes al calor y la sequía frente a los efectos climáticos en las variedades de arroz AUS y aman. Because of evident climatic variations and significant contribution to national food production, Bangladesh is a climate extreme hotspot region of examination for climatic consequences for rice (Oryza Sativa) crop production. This study intends to explore the variability of climatic variables (e.g., variations in mean temperature, rainfall, relative humidity, and sunshine duration) with rice yields (e.g., Aus, Aman, and Boro rice varieties) in northwest Bangladesh. The modified Mann–Kendall test, Theil–Sen slope estimator, and multiple linear regression (MLR) modeling were used to estimate the association among these factors. Heteroskedasticity and autocorrelation constant standard error (HAC) and feasible generalized least square (FGLS) technique were adopted to measure the climate-rice crop nexus using the regional level dataset for 1976–2015. Furthermore, the spatiotemporal variation of rice yield trends with climatic variables was mapped and assessed by the coefficient of variation. The results show that observed temperature and humidity trends were beneficial for Aus and Aman yields but not Boro yields. In contrast, observed rainfall and sunshine trends were negative for all three rice seasons. The outcomes of the MLR model explained 67%, 92%, and 83% of the variability in Aus, Aman, and Boro rice yields in the study region. The model outcomes showed that humidity and rainfall have negatively affected Aus and Aman rice crops, while temperature and rainfall positively influence Boro rice yield. Regarding the climate change issues and safeguarding food safety at the regional level, the concerned authorities should provide substantial attention to improving heat and drought-tolerance high-yielding varieties against climate effects on Aus and Aman rice varieties. نظرًا للتغيرات المناخية الواضحة والمساهمة الكبيرة في الإنتاج الغذائي الوطني، تعد بنغلاديش منطقة ساخنة شديدة المناخ لفحص الآثار المناخية على إنتاج محاصيل الأرز (أوريزا ساتيفا). تهدف هذه الدراسة إلى استكشاف تقلب المتغيرات المناخية (على سبيل المثال، الاختلافات في متوسط درجة الحرارة وهطول الأمطار والرطوبة النسبية ومدة أشعة الشمس) مع غلة الأرز (على سبيل المثال، أصناف أرز أستراليا وأمان وبورو) في شمال غرب بنغلاديش. تم استخدام اختبار مان- كيندال المعدل، ومقدر ميل ثيل- سين، ونمذجة الانحدار الخطي المتعدد (MLR) لتقدير الارتباط بين هذه العوامل. تم اعتماد المرونة المتغايرة والخطأ المعياري الثابت للارتباط الذاتي (HAC) وتقنية المربعات الأقل عمومية (FGLS) لقياس العلاقة بين محاصيل المناخ والأرز باستخدام مجموعة البيانات على المستوى الإقليمي للفترة 1976–2015. علاوة على ذلك، تم تعيين وتقييم التباين المكاني والزماني لاتجاهات غلة الأرز مع المتغيرات المناخية من خلال معامل التباين. تظهر النتائج أن اتجاهات درجة الحرارة والرطوبة المرصودة كانت مفيدة لمحاصيل Aus و Aman ولكن ليس محاصيل Boro. على النقيض من ذلك، كانت اتجاهات هطول الأمطار وأشعة الشمس المرصودة سلبية لجميع مواسم الأرز الثلاثة. أوضحت نتائج نموذج MLR 67 ٪ و 92 ٪ و 83 ٪ من التباين في غلة أرز AUS و Aman و Boro في منطقة الدراسة. أظهرت نتائج النموذج أن الرطوبة وهطول الأمطار قد أثرت سلبًا على محاصيل الأرز في أستراليا وأمان، في حين أن درجة الحرارة وهطول الأمطار يؤثران بشكل إيجابي على غلة أرز بورو. فيما يتعلق بقضايا تغير المناخ وحماية سلامة الأغذية على المستوى الإقليمي، يجب على السلطات المعنية إيلاء اهتمام كبير لتحسين الأصناف عالية الغلة التي تتحمل الحرارة والجفاف ضد الآثار المناخية على أصناف أرز أستراليا وأمان.

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    Authors: Rohitashw Kumar; Saika Manzoor; Dinesh Kumar Vishwakarma; Nadhir Al-Ansari; +5 Authors

    Under different climate change scenarios, the current study was planned to simulate runoff due to snowmelt in the Lidder River catchment in the Himalayan region. A basic degree-day model, the Snowmelt-Runoff Model (SRM), was utilized to assess the hydrological consequences of change in the climate. The performance of the SRM model during calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found to be 11.7, −10.1, −11.8, 1.96, and 8.6 in 2009–2014, respectively, while the respective R2 was 0.96, 0.92, 0.95, 0.90, and 0.94. The Dv and R2 values indicate that the simulated snowmelt runoff closely agrees with the observed values. The simulated findings were assessed under three different climate change scenarios: (a) an increase in precipitation by +20%, (b) a temperature rise of +2 °C, and (c) a temperature rise of +2 °C with a 20% increase in snow cover. In scenario (b), the simulated results showed that runoff increased by 53% in summer (April–September). In contrast, the projected increased discharge for scenarios (a) and (c) was 37% and 67%, respectively. The SRM efficiently forecasts future water supplies due to snowmelt runoff in high elevation, data-scarce mountain environments.

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    Authors: Rohitashw Kumar; Saika Manzoor; Dinesh Kumar Vishwakarma; Nadhir Al-Ansari; +5 Authors

    Under different climate change scenarios, the current study was planned to simulate runoff due to snowmelt in the Lidder River catchment in the Himalayan region. A basic degree-day model, the Snowmelt-Runoff Model (SRM), was utilized to assess the hydrological consequences of change in the climate. The performance of the SRM model during calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found to be 11.7, −10.1, −11.8, 1.96, and 8.6 in 2009–2014, respectively, while the respective R2 was 0.96, 0.92, 0.95, 0.90, and 0.94. The Dv and R2 values indicate that the simulated snowmelt runoff closely agrees with the observed values. The simulated findings were assessed under three different climate change scenarios: (a) an increase in precipitation by +20%, (b) a temperature rise of +2 °C, and (c) a temperature rise of +2 °C with a 20% increase in snow cover. In scenario (b), the simulated results showed that runoff increased by 53% in summer (April–September). In contrast, the projected increased discharge for scenarios (a) and (c) was 37% and 67%, respectively. The SRM efficiently forecasts future water supplies due to snowmelt runoff in high elevation, data-scarce mountain environments.

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    Authors: Yongguang Hu; Ali Raza; Neyha Rubab Syed; Siham Acharki; +5 Authors

    Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021). Landsat-based images of 30 m × 30 m spatial resolution were used to detect LULC changes, while NDVI dynamics were calculated using Modis Product MOD13Q1 (Tiles: h24 v5, h24 v6) at a resolution of 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering using the minimal distance center approach) was used to quantify the LULC changes in this research because of its straightforward approach that requires minimal human intervention. The accuracy assessment and the Kappa coefficient were calculated to assess the efficacy of results derived from LULC changes. Our findings revealed considerable changes in settlements, forests, and barren land in Southern Punjab. Compared to 2000, while forest cover had reduced by 31.03%, settlement had increased by 14.52% in 2021. Similarly, forest land had rapidly been converted into barren land. For example, barren land had increased by 12.87% in 2021 compared to 2000. The analysis showed that forests were reduced by 31.03%, while settlements and barren land increased by 14.52% and 12.87%, respectively, over the twenty year period in Southern Punjab. The forest area had decreased to 4.36% by 2021. It shows that 31.03% of forest land had been converted to urban land, barren ground, and farmland. Land that was formerly utilized for vegetation had been converted into urban land due to the expansion of infrastructure and the commercial sector in Southern Punjab. Consequently, proper monitoring of LULC changes is required. Furthermore, relevant agencies, governments, and policymakers must focus on land management development. Finally, the current study provides an overall scenario of how LULC trends are evolving over the study region, which aids in land use planning and management.

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    Authors: Yongguang Hu; Ali Raza; Neyha Rubab Syed; Siham Acharki; +5 Authors

    Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021). Landsat-based images of 30 m × 30 m spatial resolution were used to detect LULC changes, while NDVI dynamics were calculated using Modis Product MOD13Q1 (Tiles: h24 v5, h24 v6) at a resolution of 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering using the minimal distance center approach) was used to quantify the LULC changes in this research because of its straightforward approach that requires minimal human intervention. The accuracy assessment and the Kappa coefficient were calculated to assess the efficacy of results derived from LULC changes. Our findings revealed considerable changes in settlements, forests, and barren land in Southern Punjab. Compared to 2000, while forest cover had reduced by 31.03%, settlement had increased by 14.52% in 2021. Similarly, forest land had rapidly been converted into barren land. For example, barren land had increased by 12.87% in 2021 compared to 2000. The analysis showed that forests were reduced by 31.03%, while settlements and barren land increased by 14.52% and 12.87%, respectively, over the twenty year period in Southern Punjab. The forest area had decreased to 4.36% by 2021. It shows that 31.03% of forest land had been converted to urban land, barren ground, and farmland. Land that was formerly utilized for vegetation had been converted into urban land due to the expansion of infrastructure and the commercial sector in Southern Punjab. Consequently, proper monitoring of LULC changes is required. Furthermore, relevant agencies, governments, and policymakers must focus on land management development. Finally, the current study provides an overall scenario of how LULC trends are evolving over the study region, which aids in land use planning and management.

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    Authors: Abhay M. Varade; Kanak N. Moharir; S. F. R. Khadri; Chaitanya B. Pande; +5 Authors

    In India the demand of sustainable energy is growing at a fragmented level. The demand of rural electrification and economic growth requires high production of energy. Hence, the use of renewable energy may help to mitigate air pollution, and allow specific regenerative agriculture, waste, and forest biomass for producing the energy and achieving sustainable development goals. In the current work, we have selected a district of Maharashtra state of India as a case study and mapped the different land cover categories, and their estimated biomass. Based on this we have prepared the biomass thematic maps for the study area. These biomass maps have been prepared in the GIS environment and they displayed the biomass of crops, forests, and wastelands. The studied district has huge potential for agricultural biomass and can act as biofuel and biomass economies. These maps may play a crucial role in upgrading biomass sites focused on generating power from plants in the district Akola of Maharashtra, India.

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    Authors: Abhay M. Varade; Kanak N. Moharir; S. F. R. Khadri; Chaitanya B. Pande; +5 Authors

    In India the demand of sustainable energy is growing at a fragmented level. The demand of rural electrification and economic growth requires high production of energy. Hence, the use of renewable energy may help to mitigate air pollution, and allow specific regenerative agriculture, waste, and forest biomass for producing the energy and achieving sustainable development goals. In the current work, we have selected a district of Maharashtra state of India as a case study and mapped the different land cover categories, and their estimated biomass. Based on this we have prepared the biomass thematic maps for the study area. These biomass maps have been prepared in the GIS environment and they displayed the biomass of crops, forests, and wastelands. The studied district has huge potential for agricultural biomass and can act as biofuel and biomass economies. These maps may play a crucial role in upgrading biomass sites focused on generating power from plants in the district Akola of Maharashtra, India.

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    Authors: Elsayed Ahmed Elsadek; Ke Zhang; Yousef Alhaj Hamoud; Ahmed Mousa; +6 Authors

    Climate change directly affects crop yields, which would cause more future food security crises. Ensemble global climate models (GCMs) combined with crop growth models are an effective method to project such impacts. In the current study, five criteria were used to pick out ten GCMs. Three types of efficiency criteria, namely root-mean-squared error (RMSE), Pearson’s correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and bias (BISA) between predicted and observed temperature and precipitation, were used to evaluate and select the better-performing of the GCMs for the baseline period (1981–2010). Then, AquaCrop-GIS, driven by the downscaled projected climate data from the selected GCMs, was used to predict rice yields in the Nile River Delta (NRD) region under two Shared Socioeconomic Pathways (SSP) scenarios (SSP2–4.5 and SSP5–8.5) and four prediction periods (2021–2099). Four statistical indicators, namely, prediction error (Pe), normalized RMSE (RMSEn), index of agreement (Dindex), and coefficient of determination (R2), were used to evaluate the performance of AquaCrop-GIS. Our results showed that five GCMs, including the BCC-CSM2-MR, CMCC-ESM2, INM-CM5–0, MRI-ESM2–0, and UKESM1–0-LL, had better performances in simulating temperature and precipitation (0.81 ≤ RMSE ≤ 4.77, 0.30 ≤ NSE ≤ 0.97, and 0.57 ≤ R ≤ 0.99). In addition, AquaCrop-GIS showed excellent accuracy in simulating rice yields and predicted that, without CO2 effects, rice yields would increase by 2.19% and 4.23% under SSP2–4.5 and by 0.72% and 0.30% under SSP5–8.5 during the 2030s and 2050s, respectively. However, in the 2070s and 2090s, rice yields would decline by 7.20% and 9.0% under SSP2–4.5 and by 23.34% and 34.24% under SSP5–8.5 during the 2070s and 2090s, respectively. With CO2 effects, rice yields would rise by 14.49%, 24.97%, 15.96%, and 16.93% under SSP2–4.5 and by 14.33%, 26.22%, 8.06%, and 1.61% under SSP5–8.5 during the 2030s, 2050s, 2070s, and 2090s, respectively. Regardless of uncertainties and limitations, our findings are beneficial for farmers and policymakers to develop appropriate management strategies to improve rice yields in Egypt.

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    Agricultural Water Management
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      Agricultural Water Management
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    Authors: Elsayed Ahmed Elsadek; Ke Zhang; Yousef Alhaj Hamoud; Ahmed Mousa; +6 Authors

    Climate change directly affects crop yields, which would cause more future food security crises. Ensemble global climate models (GCMs) combined with crop growth models are an effective method to project such impacts. In the current study, five criteria were used to pick out ten GCMs. Three types of efficiency criteria, namely root-mean-squared error (RMSE), Pearson’s correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and bias (BISA) between predicted and observed temperature and precipitation, were used to evaluate and select the better-performing of the GCMs for the baseline period (1981–2010). Then, AquaCrop-GIS, driven by the downscaled projected climate data from the selected GCMs, was used to predict rice yields in the Nile River Delta (NRD) region under two Shared Socioeconomic Pathways (SSP) scenarios (SSP2–4.5 and SSP5–8.5) and four prediction periods (2021–2099). Four statistical indicators, namely, prediction error (Pe), normalized RMSE (RMSEn), index of agreement (Dindex), and coefficient of determination (R2), were used to evaluate the performance of AquaCrop-GIS. Our results showed that five GCMs, including the BCC-CSM2-MR, CMCC-ESM2, INM-CM5–0, MRI-ESM2–0, and UKESM1–0-LL, had better performances in simulating temperature and precipitation (0.81 ≤ RMSE ≤ 4.77, 0.30 ≤ NSE ≤ 0.97, and 0.57 ≤ R ≤ 0.99). In addition, AquaCrop-GIS showed excellent accuracy in simulating rice yields and predicted that, without CO2 effects, rice yields would increase by 2.19% and 4.23% under SSP2–4.5 and by 0.72% and 0.30% under SSP5–8.5 during the 2030s and 2050s, respectively. However, in the 2070s and 2090s, rice yields would decline by 7.20% and 9.0% under SSP2–4.5 and by 23.34% and 34.24% under SSP5–8.5 during the 2070s and 2090s, respectively. With CO2 effects, rice yields would rise by 14.49%, 24.97%, 15.96%, and 16.93% under SSP2–4.5 and by 14.33%, 26.22%, 8.06%, and 1.61% under SSP5–8.5 during the 2030s, 2050s, 2070s, and 2090s, respectively. Regardless of uncertainties and limitations, our findings are beneficial for farmers and policymakers to develop appropriate management strategies to improve rice yields in Egypt.

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    Agricultural Water Management
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    Authors: Muhammad Tayyab Sohail; Zaira Manzoor; Muhsan Ehsan; Nadhir Al-Ansari; +8 Authors

    Rapid urbanization, coupled with land use land cover changes (LULC), has caused stress on freshwater resources around the globe. As in the case of Islamabad, the capital of Pakistan, the population has increased significantly, creating a deficit of natural resources and affecting the environment adversely. Therefore, the purpose of this study is to examine the effects of urbanization and LULC on the decline of the static water table in Islamabad. It also seeks to analyze water policy issues in order to achieve sustainable water resource development. The excessive pumping of the existing groundwater has exceeded the safe limit, which is justified by the constantly growing population. However, the changes in the LULC of the study area have turned many green pastures into barren land. Our research data were obtained from the Capital Development Authority (CDA), Pakistan Meteorological Department (PMD), and Landsat Satellite images. After analyzing PMD and CDA data for the last 20 years (2000–2020), the results were interpreted using Arc GIS. It has been observed that the Normalized Difference Vegetation Index (NDVI) value increases as the Land Surface Temperature (LST) decreases. Therefore, the overall observation is a decreasing trend in Islamabad temperatures due to the increased vegetation in the study area during the period of 2000–2020. It was observed that there has been a considerable drop in water levels due to over-pumping in a few areas. It is primarily associated with the increasing population of the capital in the last 2 decades. This study uses a survey to explore the potential locations for check dams to enhance and recharge the groundwater aquifers in the capital, Islamabad. It suggests catchment areas throughout the Margalla Hills along with different localities, such as Rumli Village, Trail 5, and Shahdara.

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    Frontiers in Environmental Science
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    Authors: Muhammad Tayyab Sohail; Zaira Manzoor; Muhsan Ehsan; Nadhir Al-Ansari; +8 Authors

    Rapid urbanization, coupled with land use land cover changes (LULC), has caused stress on freshwater resources around the globe. As in the case of Islamabad, the capital of Pakistan, the population has increased significantly, creating a deficit of natural resources and affecting the environment adversely. Therefore, the purpose of this study is to examine the effects of urbanization and LULC on the decline of the static water table in Islamabad. It also seeks to analyze water policy issues in order to achieve sustainable water resource development. The excessive pumping of the existing groundwater has exceeded the safe limit, which is justified by the constantly growing population. However, the changes in the LULC of the study area have turned many green pastures into barren land. Our research data were obtained from the Capital Development Authority (CDA), Pakistan Meteorological Department (PMD), and Landsat Satellite images. After analyzing PMD and CDA data for the last 20 years (2000–2020), the results were interpreted using Arc GIS. It has been observed that the Normalized Difference Vegetation Index (NDVI) value increases as the Land Surface Temperature (LST) decreases. Therefore, the overall observation is a decreasing trend in Islamabad temperatures due to the increased vegetation in the study area during the period of 2000–2020. It was observed that there has been a considerable drop in water levels due to over-pumping in a few areas. It is primarily associated with the increasing population of the capital in the last 2 decades. This study uses a survey to explore the potential locations for check dams to enhance and recharge the groundwater aquifers in the capital, Islamabad. It suggests catchment areas throughout the Margalla Hills along with different localities, such as Rumli Village, Trail 5, and Shahdara.

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    Frontiers in Environmental Science
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      https://dx.doi.org/10.60692/f3...
      Other literature type . 2023
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      https://dx.doi.org/10.60692/0v...
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    Authors: Endre Harsányi; Bashar Bashir; Gafar Almhamad; Omar Hijazi; +6 Authors

    Climate mitigation and adaptation planning (CMAP) has recently been implemented across the EU-28 to reduce GHG emissions (CO2, CH4, N2O). Thus, the aim of this study was to provide an overview of GHG emissions from the agricultural sector in the EU-28 from 1990 to 2019, and cluster the EU-28 countries regarding their total GHG emissions. The results emphasize the positive impact of CMAP through a negative trend of the total GHG emissions (−2653.01 thousand tons/year, p < 0.05). Despite the positive and not significant trend of the total CO2 emissions, both CH4 and N2O exhibited a negative and significant trend. At the country scale, Italy, the United Kingdom, and the Netherlands showed the highest reduction in total GHG emissions, by −282.61thousand tons/year (p < 0.05), −266.40 thousand tons/year (p < 0.05), and −262.91 thousand tons/year (p < 0.05), respectively. The output of the multivariate analysis approach indicates changes in the pattern of GHG emissions between 1990 and 2019, where CO2 emissions decreased in the case of Poland and Czechia. The output of this study highlights the positive impact of CMAP, adopted by EU countries, in minimizing GHG emissions. Despite some fluctuations in CO2 emissions, strategies for attaining carbon neutrality in the agricultural sector, across the European Union, should be pursued.

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    Energies
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      Energies
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    Authors: Endre Harsányi; Bashar Bashir; Gafar Almhamad; Omar Hijazi; +6 Authors

    Climate mitigation and adaptation planning (CMAP) has recently been implemented across the EU-28 to reduce GHG emissions (CO2, CH4, N2O). Thus, the aim of this study was to provide an overview of GHG emissions from the agricultural sector in the EU-28 from 1990 to 2019, and cluster the EU-28 countries regarding their total GHG emissions. The results emphasize the positive impact of CMAP through a negative trend of the total GHG emissions (−2653.01 thousand tons/year, p < 0.05). Despite the positive and not significant trend of the total CO2 emissions, both CH4 and N2O exhibited a negative and significant trend. At the country scale, Italy, the United Kingdom, and the Netherlands showed the highest reduction in total GHG emissions, by −282.61thousand tons/year (p < 0.05), −266.40 thousand tons/year (p < 0.05), and −262.91 thousand tons/year (p < 0.05), respectively. The output of the multivariate analysis approach indicates changes in the pattern of GHG emissions between 1990 and 2019, where CO2 emissions decreased in the case of Poland and Czechia. The output of this study highlights the positive impact of CMAP, adopted by EU countries, in minimizing GHG emissions. Despite some fluctuations in CO2 emissions, strategies for attaining carbon neutrality in the agricultural sector, across the European Union, should be pursued.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
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    Energies
    Article . 2021 . Peer-reviewed
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    Energies
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    Energies
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      Energies
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Ismail, Abd-Elaty; N L, Kushwaha; Mark E, Grismer; Ahmed, Elbeltagi; +1 Authors

    Sustainable management of natural water resources and food security in the face of changing climate conditions is critical to the livelihood of coastal communities. Increasing inundation and saltwater intrusion (SWI) will likely adversely affect agricultural production and the associated beach access for tourism. This study uses an integrated surface-ground water model to introduce a new approach for retardation of SWI that consists of placing aquifer fill materials along the existing shoreline using Coastal Land Reclamation (CLR). The modeling results suggest that the artificial aquifer materials could be designed to decrease SWI by increasing the infiltration area of coastal precipitation, collecting runoffs from the catchment area, and applying treated wastewater or desalinated brackish water-using coastal wave energy to reduce water treatment costs. The SEAWAT model was applied to verify that it correctly addressed Henry's problem and then applied to the Biscayne aquifer, Florida, USA. In this study, to better inform Coastal Aquifer Management (CAM), we developed four modeling scenarios, namely, Physical Surface Barriers (PSB), including the artificial aquifer widths, permeability, and side slopes and recharge. In the base case scenario without artificial aquifer placement, results show that seawater levels would increase aquifer salinity and displace large amounts of presently available fresh groundwater. More specifically, for the Biscayne aquifer, approximately 0.50% of available fresh groundwater will be lost (that is, 41,192 m3) per km of the width of the aquifer considering the increasing seawater level. Furthermore, the results suggest that placing the PSB aquifer with a smaller permeability of <100 m per day at a width of approximately 615 m increases the available fresh groundwater by approximately 45.20 and 43.90% per km of shoreline, respectively. Similarly, decreasing the slope on the aquifer-ocean side and increasing the aquifer recharge will increase freshwater availability by about 43.90 and 44.50% per km of the aquifer. Finally, placing an aquifer fill along the shallow shoreline increases net revenues to the coastal community through increased agricultural production and possibly tourism that offset fill placement and water treatment costs. This study is useful for integrated management of coastal zones by delaying aquifer salinity, protecting fresh groundwater bodies, increasing agricultural lands, supporting surface water supplies by harvesting rainfall and flash flooding, and desalinating saline water using wave energy. Also, the feasibility of freshwater storage and costs for CAM is achieved in this study.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao The Science of The T...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    The Science of The Total Environment
    Article . 2022 . Peer-reviewed
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      The Science of The Total Environment
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    Authors: Ismail, Abd-Elaty; N L, Kushwaha; Mark E, Grismer; Ahmed, Elbeltagi; +1 Authors

    Sustainable management of natural water resources and food security in the face of changing climate conditions is critical to the livelihood of coastal communities. Increasing inundation and saltwater intrusion (SWI) will likely adversely affect agricultural production and the associated beach access for tourism. This study uses an integrated surface-ground water model to introduce a new approach for retardation of SWI that consists of placing aquifer fill materials along the existing shoreline using Coastal Land Reclamation (CLR). The modeling results suggest that the artificial aquifer materials could be designed to decrease SWI by increasing the infiltration area of coastal precipitation, collecting runoffs from the catchment area, and applying treated wastewater or desalinated brackish water-using coastal wave energy to reduce water treatment costs. The SEAWAT model was applied to verify that it correctly addressed Henry's problem and then applied to the Biscayne aquifer, Florida, USA. In this study, to better inform Coastal Aquifer Management (CAM), we developed four modeling scenarios, namely, Physical Surface Barriers (PSB), including the artificial aquifer widths, permeability, and side slopes and recharge. In the base case scenario without artificial aquifer placement, results show that seawater levels would increase aquifer salinity and displace large amounts of presently available fresh groundwater. More specifically, for the Biscayne aquifer, approximately 0.50% of available fresh groundwater will be lost (that is, 41,192 m3) per km of the width of the aquifer considering the increasing seawater level. Furthermore, the results suggest that placing the PSB aquifer with a smaller permeability of <100 m per day at a width of approximately 615 m increases the available fresh groundwater by approximately 45.20 and 43.90% per km of shoreline, respectively. Similarly, decreasing the slope on the aquifer-ocean side and increasing the aquifer recharge will increase freshwater availability by about 43.90 and 44.50% per km of the aquifer. Finally, placing an aquifer fill along the shallow shoreline increases net revenues to the coastal community through increased agricultural production and possibly tourism that offset fill placement and water treatment costs. This study is useful for integrated management of coastal zones by delaying aquifer salinity, protecting fresh groundwater bodies, increasing agricultural lands, supporting surface water supplies by harvesting rainfall and flash flooding, and desalinating saline water using wave energy. Also, the feasibility of freshwater storage and costs for CAM is achieved in this study.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao The Science of The T...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    The Science of The Total Environment
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      The Science of The Total Environment
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    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Muhammad Shafeeque; Arfan Arshad; Ahmed Elbeltagi; Abid Sarwar; +4 Authors

    Les mesures strictes de confinement ont non seulement contribué à freiner la propagation de l'infection à COVID-19, mais ont également amélioré les conditions environnementales dans le monde entier. L'objectif principal de la présente étude était d'étudier les co-bénéfices du confinement de la COVID-19 sur l'atmosphère et le système écologique aquatique dans le cadre d'activités anthropiques restreintes en Asie du Sud. Les données de télédétection (a) des émissions de NO2 de l'instrument de surveillance de l'ozone (OMI), (b) de la profondeur optique des aérosols (AOD) du spectroradiomètre d'imagerie à résolution modérée (MODIS) et (c) de la chlorophylle (Chl-a) et des données de turbidité de MODIS-Aqua Level-3 au cours de janvier-octobre (2020) ont été analysées pour évaluer les changements dans la pollution de l'air et de l'eau par rapport aux cinq dernières années (2015–2019). Les interactions entre la pollution de l'air et de l'eau ont également été étudiées en utilisant le ruissellement terrestre et les précipitations en 2019 et 2020 à une échelle mensuelle pour enquêter sur les événements anormaux, qui pourraient affecter la charge d'azote dans les régions côtières. Les résultats ont révélé une baisse considérable de la pollution de l'air et de l'eau (réduction de 30 à 40 % des émissions de NO2, de 45 % de l'AOD, de 50 % de la concentration de chl-a sur les côtes et de 29 % de la turbidité) en Asie du Sud. Le taux de réduction des émissions de NO2 a été le plus élevé à Lahore (32 %), New Delhi (31 %), Ahmadabad (29 %), Karachi (26 %), Hyderabad (24 %) et Chennai (17 %) pendant la période de confinement strict d'avril à juin 2020. Une corrélation positive entre l'AOD et les émissions de NO2 (0,23-0,50) implique qu'une diminution de l'AOD est attribuée à une réduction du NO2. Il a été observé que pendant le confinement strict, la turbidité a diminué de 29 %, 11 %, 16 % et 17 % le long des régions côtières de Karachi, Mumbai, Calcutta et Dhaka, respectivement, tandis qu'une augmentation de 5 à 6 % de la turbidité a été observée sur les Madras au cours de la même période. Les résultats soulignent l'importance de la réduction des émissions d'azote en raison de l'arrêt de la consommation de combustibles fossiles et de leurs relations avec la réduction de la pollution de l'air et de l'eau. Il est conclu que l'environnement atmosphérique et hydrosphérique peut être amélioré en mettant en œuvre des restrictions intelligentes sur la consommation de combustibles fossiles avec un effet minimum sur la socio-économie dans la région. Des contraintes intelligentes sur l'utilisation des combustibles fossiles sont recommandées pour contrôler la pollution de l'air et de l'eau même après la reprise des activités sociales et économiques. Las estrictas medidas de confinamiento no solo contribuyeron a frenar la propagación de la infección por COVID-19, sino que también mejoraron las condiciones ambientales en todo el mundo. El objetivo principal del estudio actual fue investigar los beneficios colaterales del confinamiento por COVID-19 en la atmósfera y el sistema ecológico acuático bajo actividades antropogénicas restringidas en el sur de Asia. Los datos de teledetección (a) emisiones de NO2 del Instrumento de Monitoreo de Ozono (OMI), (b) Profundidad Óptica de Aerosol (AOD) del Espectrorradiómetro de Imágenes de Resolución Moderada (MODIS) y (c) clorofila (Chl-a) y datos de turbidez de MODIS-Aqua Nivel-3 durante enero-octubre (2020) se analizaron para evaluar los cambios en la contaminación del aire y el agua en comparación con los últimos cinco años (2015–2019). Las interacciones entre la contaminación del aire y del agua también se investigaron utilizando la escorrentía y las precipitaciones terrestres en 2019 y 2020 a escala mensual para investigar los eventos anómalos, que podrían afectar la carga de N en las regiones costeras. Los resultados revelaron una caída considerable en la contaminación del aire y el agua (reducción del 30–40% en las emisiones de NO2, 45% en AOD, disminución del 50% en la concentración costera de Chl-a y disminución del 29% en la turbidez) en el sur de Asia. La tasa de reducción de las emisiones de NO2 fue la más alta para Lahore (32%), Nueva Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%) y Chennai (17%) durante el estricto período de confinamiento de abril a junio de 2020. Una correlación positiva entre AOD y las emisiones de NO2 (0.23-0.50) implica que una disminución en AOD se atribuye a una reducción en NO2. Se observó que durante el confinamiento estricto, la turbidez ha disminuido en un 29%, 11%, 16% y 17% a lo largo de las regiones costeras de Karachi, Mumbai, Calcuta y Dhaka, respectivamente, mientras que se observó un aumento del 5–6% en la turbidez en Madras durante el mismo período. Los hallazgos enfatizan la importancia de reducir las emisiones de N debido a la interrupción del consumo de combustibles fósiles y sus relaciones con la reducción de la contaminación del aire y el agua. Se concluye que el ambiente atmosférico e hidrosférico puede mejorarse mediante la implementación de restricciones inteligentes en el consumo de combustibles fósiles con un efecto mínimo en la socioeconómica de la región. Se recomiendan restricciones inteligentes en el uso de combustibles fósiles para controlar la contaminación del aire y del agua incluso después de que las actividades sociales y económicas reanuden el escenario habitual. The strict lockdown measures not only contributed to curbing the spread of COVID-19 infection, but also improved the environmental conditions worldwide. The main goal of the current study was to investigate the co-benefits of COVID-19 lockdown on the atmosphere and aquatic ecological system under restricted anthropogenic activities in South Asia. The remote sensing data (a) NO2 emissions from the Ozone Monitoring Instrument (OMI), (b) Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and (c) chlorophyll (Chl-a) and turbidity data from MODIS-Aqua Level-3 during Jan–Oct (2020) were analyzed to assess the changes in air and water pollution compared to the last five years (2015–2019). The interactions between the air and water pollution were also investigated using overland runoff and precipitation in 2019 and 2020 at a monthly scale to investigate the anomalous events, which could affect the N loading to coastal regions. The results revealed a considerable drop in the air and water pollution (30–40% reduction in NO2 emissions, 45% in AOD, 50% decline in coastal Chl-a concentration, and 29% decline in turbidity) over South Asia. The rate of reduction in NO2 emissions was found the highest for Lahore (32%), New Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%), and Chennai (17%) during the strict lockdown period from Apr–Jun, 2020. A positive correlation between AOD and NO2 emissions (0.23–0.50) implies that a decrease in AOD is attributed to a reduction in NO2. It was observed that during strict lockdown, the turbidity has decreased by 29%, 11%, 16%, and 17% along the coastal regions of Karachi, Mumbai, Calcutta, and Dhaka, respectively, while a 5–6% increase in turbidity was seen over the Madras during the same period. The findings stress the importance of reduced N emissions due to halted fossil fuel consumption and their relationships with the reduced air and water pollution. It is concluded that the atmospheric and hydrospheric environment can be improved by implementing smart restrictions on fossil fuel consumption with a minimum effect on socioeconomics in the region. Smart constraints on fossil fuel usage are recommended to control air and water pollution even after the social and economic activities resume business-as-usual scenario. لم تساهم إجراءات الإغلاق الصارمة في الحد من انتشار عدوى COVID -19 فحسب، بل أدت أيضًا إلى تحسين الظروف البيئية في جميع أنحاء العالم. كان الهدف الرئيسي من الدراسة الحالية هو التحقيق في الفوائد المشتركة لإغلاق COVID -19 على الغلاف الجوي والنظام البيئي المائي في ظل الأنشطة البشرية المقيدة في جنوب آسيا. تم تحليل بيانات الاستشعار عن بعد (أ) انبعاثات ثاني أكسيد النيتروجين من جهاز مراقبة الأوزون (OMI)، (ب) العمق البصري للهباء الجوي (AOD) من مقياس الطيف التصويري متوسط الدقة (MODIS)، و (ج) بيانات الكلوروفيل (Chl - a) والتعكر من MODIS - Aqua Level -3 خلال الفترة من يناير إلى أكتوبر (2020) لتقييم التغيرات في تلوث الهواء والماء مقارنة بالسنوات الخمس الماضية (2015–2019). كما تم التحقيق في التفاعلات بين تلوث الهواء والمياه باستخدام الجريان السطحي وهطول الأمطار في عامي 2019 و 2020 على نطاق شهري للتحقيق في الأحداث الشاذة، والتي يمكن أن تؤثر على تحميل N إلى المناطق الساحلية. كشفت النتائج عن انخفاض كبير في تلوث الهواء والماء (انخفاض بنسبة 30-40 ٪ في انبعاثات ثاني أكسيد النيتروجين، و 45 ٪ في AOD، وانخفاض بنسبة 50 ٪ في تركيز Chl - a الساحلي، وانخفاض بنسبة 29 ٪ في التعكر) فوق جنوب آسيا. وجد أن معدل الانخفاض في انبعاثات ثاني أكسيد النيتروجين هو الأعلى في لاهور (32 ٪) ونيودلهي (31 ٪) وأحمد أباد (29 ٪) وكراتشي (26 ٪) وحيدر أباد (24 ٪) وتشيناي (17 ٪) خلال فترة الإغلاق الصارمة من أبريل إلى يونيو 2020. تشير العلاقة الإيجابية بين انبعاثات أكسيد النيتروجين وثاني أكسيد النيتروجين (0.23-0.50) إلى أن انخفاض أكسيد النيتروجين يعزى إلى انخفاض ثاني أكسيد النيتروجين. لوحظ أنه خلال الإغلاق الصارم، انخفض التعكر بنسبة 29 ٪ و 11 ٪ و 16 ٪ و 17 ٪ على طول المناطق الساحلية في كراتشي ومومباي وكلكتا ودكا، على التوالي، في حين لوحظت زيادة بنسبة 5-6 ٪ في التعكر فوق مدراس خلال نفس الفترة. وتشدد النتائج على أهمية خفض انبعاثات النيتروجين بسبب وقف استهلاك الوقود الأحفوري وعلاقاتها بانخفاض تلوث الهواء والماء. وخلص إلى أنه يمكن تحسين البيئة الجوية والمائية من خلال تنفيذ قيود ذكية على استهلاك الوقود الأحفوري بأقل تأثير على الاقتصاد الاجتماعي في المنطقة. يوصى بالقيود الذكية على استخدام الوقود الأحفوري للسيطرة على تلوث الهواء والماء حتى بعد استئناف الأنشطة الاجتماعية والاقتصادية لسيناريو العمل كالمعتاد.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Muhammad Shafeeque; Arfan Arshad; Ahmed Elbeltagi; Abid Sarwar; +4 Authors

    Les mesures strictes de confinement ont non seulement contribué à freiner la propagation de l'infection à COVID-19, mais ont également amélioré les conditions environnementales dans le monde entier. L'objectif principal de la présente étude était d'étudier les co-bénéfices du confinement de la COVID-19 sur l'atmosphère et le système écologique aquatique dans le cadre d'activités anthropiques restreintes en Asie du Sud. Les données de télédétection (a) des émissions de NO2 de l'instrument de surveillance de l'ozone (OMI), (b) de la profondeur optique des aérosols (AOD) du spectroradiomètre d'imagerie à résolution modérée (MODIS) et (c) de la chlorophylle (Chl-a) et des données de turbidité de MODIS-Aqua Level-3 au cours de janvier-octobre (2020) ont été analysées pour évaluer les changements dans la pollution de l'air et de l'eau par rapport aux cinq dernières années (2015–2019). Les interactions entre la pollution de l'air et de l'eau ont également été étudiées en utilisant le ruissellement terrestre et les précipitations en 2019 et 2020 à une échelle mensuelle pour enquêter sur les événements anormaux, qui pourraient affecter la charge d'azote dans les régions côtières. Les résultats ont révélé une baisse considérable de la pollution de l'air et de l'eau (réduction de 30 à 40 % des émissions de NO2, de 45 % de l'AOD, de 50 % de la concentration de chl-a sur les côtes et de 29 % de la turbidité) en Asie du Sud. Le taux de réduction des émissions de NO2 a été le plus élevé à Lahore (32 %), New Delhi (31 %), Ahmadabad (29 %), Karachi (26 %), Hyderabad (24 %) et Chennai (17 %) pendant la période de confinement strict d'avril à juin 2020. Une corrélation positive entre l'AOD et les émissions de NO2 (0,23-0,50) implique qu'une diminution de l'AOD est attribuée à une réduction du NO2. Il a été observé que pendant le confinement strict, la turbidité a diminué de 29 %, 11 %, 16 % et 17 % le long des régions côtières de Karachi, Mumbai, Calcutta et Dhaka, respectivement, tandis qu'une augmentation de 5 à 6 % de la turbidité a été observée sur les Madras au cours de la même période. Les résultats soulignent l'importance de la réduction des émissions d'azote en raison de l'arrêt de la consommation de combustibles fossiles et de leurs relations avec la réduction de la pollution de l'air et de l'eau. Il est conclu que l'environnement atmosphérique et hydrosphérique peut être amélioré en mettant en œuvre des restrictions intelligentes sur la consommation de combustibles fossiles avec un effet minimum sur la socio-économie dans la région. Des contraintes intelligentes sur l'utilisation des combustibles fossiles sont recommandées pour contrôler la pollution de l'air et de l'eau même après la reprise des activités sociales et économiques. Las estrictas medidas de confinamiento no solo contribuyeron a frenar la propagación de la infección por COVID-19, sino que también mejoraron las condiciones ambientales en todo el mundo. El objetivo principal del estudio actual fue investigar los beneficios colaterales del confinamiento por COVID-19 en la atmósfera y el sistema ecológico acuático bajo actividades antropogénicas restringidas en el sur de Asia. Los datos de teledetección (a) emisiones de NO2 del Instrumento de Monitoreo de Ozono (OMI), (b) Profundidad Óptica de Aerosol (AOD) del Espectrorradiómetro de Imágenes de Resolución Moderada (MODIS) y (c) clorofila (Chl-a) y datos de turbidez de MODIS-Aqua Nivel-3 durante enero-octubre (2020) se analizaron para evaluar los cambios en la contaminación del aire y el agua en comparación con los últimos cinco años (2015–2019). Las interacciones entre la contaminación del aire y del agua también se investigaron utilizando la escorrentía y las precipitaciones terrestres en 2019 y 2020 a escala mensual para investigar los eventos anómalos, que podrían afectar la carga de N en las regiones costeras. Los resultados revelaron una caída considerable en la contaminación del aire y el agua (reducción del 30–40% en las emisiones de NO2, 45% en AOD, disminución del 50% en la concentración costera de Chl-a y disminución del 29% en la turbidez) en el sur de Asia. La tasa de reducción de las emisiones de NO2 fue la más alta para Lahore (32%), Nueva Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%) y Chennai (17%) durante el estricto período de confinamiento de abril a junio de 2020. Una correlación positiva entre AOD y las emisiones de NO2 (0.23-0.50) implica que una disminución en AOD se atribuye a una reducción en NO2. Se observó que durante el confinamiento estricto, la turbidez ha disminuido en un 29%, 11%, 16% y 17% a lo largo de las regiones costeras de Karachi, Mumbai, Calcuta y Dhaka, respectivamente, mientras que se observó un aumento del 5–6% en la turbidez en Madras durante el mismo período. Los hallazgos enfatizan la importancia de reducir las emisiones de N debido a la interrupción del consumo de combustibles fósiles y sus relaciones con la reducción de la contaminación del aire y el agua. Se concluye que el ambiente atmosférico e hidrosférico puede mejorarse mediante la implementación de restricciones inteligentes en el consumo de combustibles fósiles con un efecto mínimo en la socioeconómica de la región. Se recomiendan restricciones inteligentes en el uso de combustibles fósiles para controlar la contaminación del aire y del agua incluso después de que las actividades sociales y económicas reanuden el escenario habitual. The strict lockdown measures not only contributed to curbing the spread of COVID-19 infection, but also improved the environmental conditions worldwide. The main goal of the current study was to investigate the co-benefits of COVID-19 lockdown on the atmosphere and aquatic ecological system under restricted anthropogenic activities in South Asia. The remote sensing data (a) NO2 emissions from the Ozone Monitoring Instrument (OMI), (b) Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and (c) chlorophyll (Chl-a) and turbidity data from MODIS-Aqua Level-3 during Jan–Oct (2020) were analyzed to assess the changes in air and water pollution compared to the last five years (2015–2019). The interactions between the air and water pollution were also investigated using overland runoff and precipitation in 2019 and 2020 at a monthly scale to investigate the anomalous events, which could affect the N loading to coastal regions. The results revealed a considerable drop in the air and water pollution (30–40% reduction in NO2 emissions, 45% in AOD, 50% decline in coastal Chl-a concentration, and 29% decline in turbidity) over South Asia. The rate of reduction in NO2 emissions was found the highest for Lahore (32%), New Delhi (31%), Ahmadabad (29%), Karachi (26%), Hyderabad (24%), and Chennai (17%) during the strict lockdown period from Apr–Jun, 2020. A positive correlation between AOD and NO2 emissions (0.23–0.50) implies that a decrease in AOD is attributed to a reduction in NO2. It was observed that during strict lockdown, the turbidity has decreased by 29%, 11%, 16%, and 17% along the coastal regions of Karachi, Mumbai, Calcutta, and Dhaka, respectively, while a 5–6% increase in turbidity was seen over the Madras during the same period. The findings stress the importance of reduced N emissions due to halted fossil fuel consumption and their relationships with the reduced air and water pollution. It is concluded that the atmospheric and hydrospheric environment can be improved by implementing smart restrictions on fossil fuel consumption with a minimum effect on socioeconomics in the region. Smart constraints on fossil fuel usage are recommended to control air and water pollution even after the social and economic activities resume business-as-usual scenario. لم تساهم إجراءات الإغلاق الصارمة في الحد من انتشار عدوى COVID -19 فحسب، بل أدت أيضًا إلى تحسين الظروف البيئية في جميع أنحاء العالم. كان الهدف الرئيسي من الدراسة الحالية هو التحقيق في الفوائد المشتركة لإغلاق COVID -19 على الغلاف الجوي والنظام البيئي المائي في ظل الأنشطة البشرية المقيدة في جنوب آسيا. تم تحليل بيانات الاستشعار عن بعد (أ) انبعاثات ثاني أكسيد النيتروجين من جهاز مراقبة الأوزون (OMI)، (ب) العمق البصري للهباء الجوي (AOD) من مقياس الطيف التصويري متوسط الدقة (MODIS)، و (ج) بيانات الكلوروفيل (Chl - a) والتعكر من MODIS - Aqua Level -3 خلال الفترة من يناير إلى أكتوبر (2020) لتقييم التغيرات في تلوث الهواء والماء مقارنة بالسنوات الخمس الماضية (2015–2019). كما تم التحقيق في التفاعلات بين تلوث الهواء والمياه باستخدام الجريان السطحي وهطول الأمطار في عامي 2019 و 2020 على نطاق شهري للتحقيق في الأحداث الشاذة، والتي يمكن أن تؤثر على تحميل N إلى المناطق الساحلية. كشفت النتائج عن انخفاض كبير في تلوث الهواء والماء (انخفاض بنسبة 30-40 ٪ في انبعاثات ثاني أكسيد النيتروجين، و 45 ٪ في AOD، وانخفاض بنسبة 50 ٪ في تركيز Chl - a الساحلي، وانخفاض بنسبة 29 ٪ في التعكر) فوق جنوب آسيا. وجد أن معدل الانخفاض في انبعاثات ثاني أكسيد النيتروجين هو الأعلى في لاهور (32 ٪) ونيودلهي (31 ٪) وأحمد أباد (29 ٪) وكراتشي (26 ٪) وحيدر أباد (24 ٪) وتشيناي (17 ٪) خلال فترة الإغلاق الصارمة من أبريل إلى يونيو 2020. تشير العلاقة الإيجابية بين انبعاثات أكسيد النيتروجين وثاني أكسيد النيتروجين (0.23-0.50) إلى أن انخفاض أكسيد النيتروجين يعزى إلى انخفاض ثاني أكسيد النيتروجين. لوحظ أنه خلال الإغلاق الصارم، انخفض التعكر بنسبة 29 ٪ و 11 ٪ و 16 ٪ و 17 ٪ على طول المناطق الساحلية في كراتشي ومومباي وكلكتا ودكا، على التوالي، في حين لوحظت زيادة بنسبة 5-6 ٪ في التعكر فوق مدراس خلال نفس الفترة. وتشدد النتائج على أهمية خفض انبعاثات النيتروجين بسبب وقف استهلاك الوقود الأحفوري وعلاقاتها بانخفاض تلوث الهواء والماء. وخلص إلى أنه يمكن تحسين البيئة الجوية والمائية من خلال تنفيذ قيود ذكية على استهلاك الوقود الأحفوري بأقل تأثير على الاقتصاد الاجتماعي في المنطقة. يوصى بالقيود الذكية على استخدام الوقود الأحفوري للسيطرة على تلوث الهواء والماء حتى بعد استئناف الأنشطة الاجتماعية والاقتصادية لسيناريو العمل كالمعتاد.

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    Geomatics, Natural Hazards &amp; Risk
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    Authors: Abu Reza Md. Towfiqul Islam; Irtifa Alam Nabila; Md. Hasanuzzaman; Md. Bozlar Rahman; +5 Authors

    En raison des variations climatiques évidentes et de la contribution significative à la production alimentaire nationale, le Bangladesh est une région d'examen des conséquences climatiques pour la production de riz (Oryza Sativa). Cette étude vise à explorer la variabilité des variables climatiques (par exemple, les variations de la température moyenne, des précipitations, de l'humidité relative et de la durée d'ensoleillement) avec les rendements en riz (par exemple, les variétés de riz Aus, Aman et Boro) dans le nord-ouest du Bangladesh. Le test de Mann–Kendall modifié, l'estimateur de pente de Theil–Sen et la modélisation par régression linéaire multiple (MLR) ont été utilisés pour estimer l'association entre ces facteurs. L'hétéroskédasticité et l'erreur standard constante d'autocorrélation (HAC) et la technique faisable des moindres carrés généralisés (FGLS) ont été adoptées pour mesurer le lien entre le climat et les cultures de riz à l'aide de l'ensemble de données au niveau régional pour 1976–2015. En outre, la variation spatio-temporelle des tendances du rendement du riz avec les variables climatiques a été cartographiée et évaluée par le coefficient de variation. Les résultats montrent que les tendances observées en matière de température et d'humidité ont été bénéfiques pour les rendements Aus et Aman, mais pas pour les rendements Boro. En revanche, les tendances observées en matière de précipitations et d'ensoleillement ont été négatives pour les trois saisons du riz. Les résultats du modèle MLR expliquent 67 %, 92 % et 83 % de la variabilité des rendements en riz Aus, Aman et Boro dans la région étudiée. Les résultats du modèle ont montré que l'humidité et les précipitations ont eu un impact négatif sur les cultures de riz Aus et Aman, tandis que la température et les précipitations ont une influence positive sur le rendement du riz Boro. En ce qui concerne les questions de changement climatique et la sauvegarde de la sécurité alimentaire au niveau régional, les autorités concernées devraient accorder une attention considérable à l'amélioration des variétés à haut rendement tolérantes à la chaleur et à la sécheresse contre les effets climatiques sur les variétés de riz Aus et Aman. Debido a las evidentes variaciones climáticas y a la importante contribución a la producción nacional de alimentos, Bangladesh es una región climáticamente crítica para examinar las consecuencias climáticas para la producción de cultivos de arroz (Oryza Sativa). Este estudio pretende explorar la variabilidad de las variables climáticas (por ejemplo, variaciones en la temperatura media, las precipitaciones, la humedad relativa y la duración del sol) con los rendimientos de arroz (por ejemplo, las variedades de arroz AUS, aman y Boro) en el noroeste de Bangladesh. La prueba de Mann–Kendall modificada, el estimador de pendiente de Theil–Sen y el modelado de regresión lineal múltiple (MLR) se utilizaron para estimar la asociación entre estos factores. Se adoptó la técnica de heterocedasticidad y error estándar constante de autocorrelación (hac) y mínimos cuadrados generalizados factibles (FGLS) para medir el nexo clima-arroz utilizando el conjunto de datos a nivel regional para 1976–2015. Además, se mapeó y evaluó la variación espaciotemporal de las tendencias de rendimiento del arroz con variables climáticas mediante el coeficiente de variación. Los resultados muestran que las tendencias observadas de temperatura y humedad fueron beneficiosas para los rendimientos de AUS y aman, pero no para los rendimientos de Boro. Por el contrario, las tendencias observadas de precipitaciones y sol fueron negativas para las tres temporadas de arroz. Los resultados del modelo MLR explicaron el 67%, 92% y 83% de la variabilidad en los rendimientos de arroz AUS, aman y Boro en la región de estudio. Los resultados del modelo mostraron que la humedad y las precipitaciones han afectado negativamente a los cultivos de arroz AUS y aman, mientras que la temperatura y las precipitaciones influyen positivamente en el rendimiento del arroz Boro. Con respecto a los problemas del cambio climático y la salvaguardia de la seguridad alimentaria a nivel regional, las autoridades competentes deben prestar una atención sustancial a la mejora de las variedades de alto rendimiento tolerantes al calor y la sequía frente a los efectos climáticos en las variedades de arroz AUS y aman. Because of evident climatic variations and significant contribution to national food production, Bangladesh is a climate extreme hotspot region of examination for climatic consequences for rice (Oryza Sativa) crop production. This study intends to explore the variability of climatic variables (e.g., variations in mean temperature, rainfall, relative humidity, and sunshine duration) with rice yields (e.g., Aus, Aman, and Boro rice varieties) in northwest Bangladesh. The modified Mann–Kendall test, Theil–Sen slope estimator, and multiple linear regression (MLR) modeling were used to estimate the association among these factors. Heteroskedasticity and autocorrelation constant standard error (HAC) and feasible generalized least square (FGLS) technique were adopted to measure the climate-rice crop nexus using the regional level dataset for 1976–2015. Furthermore, the spatiotemporal variation of rice yield trends with climatic variables was mapped and assessed by the coefficient of variation. The results show that observed temperature and humidity trends were beneficial for Aus and Aman yields but not Boro yields. In contrast, observed rainfall and sunshine trends were negative for all three rice seasons. The outcomes of the MLR model explained 67%, 92%, and 83% of the variability in Aus, Aman, and Boro rice yields in the study region. The model outcomes showed that humidity and rainfall have negatively affected Aus and Aman rice crops, while temperature and rainfall positively influence Boro rice yield. Regarding the climate change issues and safeguarding food safety at the regional level, the concerned authorities should provide substantial attention to improving heat and drought-tolerance high-yielding varieties against climate effects on Aus and Aman rice varieties. نظرًا للتغيرات المناخية الواضحة والمساهمة الكبيرة في الإنتاج الغذائي الوطني، تعد بنغلاديش منطقة ساخنة شديدة المناخ لفحص الآثار المناخية على إنتاج محاصيل الأرز (أوريزا ساتيفا). تهدف هذه الدراسة إلى استكشاف تقلب المتغيرات المناخية (على سبيل المثال، الاختلافات في متوسط درجة الحرارة وهطول الأمطار والرطوبة النسبية ومدة أشعة الشمس) مع غلة الأرز (على سبيل المثال، أصناف أرز أستراليا وأمان وبورو) في شمال غرب بنغلاديش. تم استخدام اختبار مان- كيندال المعدل، ومقدر ميل ثيل- سين، ونمذجة الانحدار الخطي المتعدد (MLR) لتقدير الارتباط بين هذه العوامل. تم اعتماد المرونة المتغايرة والخطأ المعياري الثابت للارتباط الذاتي (HAC) وتقنية المربعات الأقل عمومية (FGLS) لقياس العلاقة بين محاصيل المناخ والأرز باستخدام مجموعة البيانات على المستوى الإقليمي للفترة 1976–2015. علاوة على ذلك، تم تعيين وتقييم التباين المكاني والزماني لاتجاهات غلة الأرز مع المتغيرات المناخية من خلال معامل التباين. تظهر النتائج أن اتجاهات درجة الحرارة والرطوبة المرصودة كانت مفيدة لمحاصيل Aus و Aman ولكن ليس محاصيل Boro. على النقيض من ذلك، كانت اتجاهات هطول الأمطار وأشعة الشمس المرصودة سلبية لجميع مواسم الأرز الثلاثة. أوضحت نتائج نموذج MLR 67 ٪ و 92 ٪ و 83 ٪ من التباين في غلة أرز AUS و Aman و Boro في منطقة الدراسة. أظهرت نتائج النموذج أن الرطوبة وهطول الأمطار قد أثرت سلبًا على محاصيل الأرز في أستراليا وأمان، في حين أن درجة الحرارة وهطول الأمطار يؤثران بشكل إيجابي على غلة أرز بورو. فيما يتعلق بقضايا تغير المناخ وحماية سلامة الأغذية على المستوى الإقليمي، يجب على السلطات المعنية إيلاء اهتمام كبير لتحسين الأصناف عالية الغلة التي تتحمل الحرارة والجفاف ضد الآثار المناخية على أصناف أرز أستراليا وأمان.

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    Authors: Abu Reza Md. Towfiqul Islam; Irtifa Alam Nabila; Md. Hasanuzzaman; Md. Bozlar Rahman; +5 Authors

    En raison des variations climatiques évidentes et de la contribution significative à la production alimentaire nationale, le Bangladesh est une région d'examen des conséquences climatiques pour la production de riz (Oryza Sativa). Cette étude vise à explorer la variabilité des variables climatiques (par exemple, les variations de la température moyenne, des précipitations, de l'humidité relative et de la durée d'ensoleillement) avec les rendements en riz (par exemple, les variétés de riz Aus, Aman et Boro) dans le nord-ouest du Bangladesh. Le test de Mann–Kendall modifié, l'estimateur de pente de Theil–Sen et la modélisation par régression linéaire multiple (MLR) ont été utilisés pour estimer l'association entre ces facteurs. L'hétéroskédasticité et l'erreur standard constante d'autocorrélation (HAC) et la technique faisable des moindres carrés généralisés (FGLS) ont été adoptées pour mesurer le lien entre le climat et les cultures de riz à l'aide de l'ensemble de données au niveau régional pour 1976–2015. En outre, la variation spatio-temporelle des tendances du rendement du riz avec les variables climatiques a été cartographiée et évaluée par le coefficient de variation. Les résultats montrent que les tendances observées en matière de température et d'humidité ont été bénéfiques pour les rendements Aus et Aman, mais pas pour les rendements Boro. En revanche, les tendances observées en matière de précipitations et d'ensoleillement ont été négatives pour les trois saisons du riz. Les résultats du modèle MLR expliquent 67 %, 92 % et 83 % de la variabilité des rendements en riz Aus, Aman et Boro dans la région étudiée. Les résultats du modèle ont montré que l'humidité et les précipitations ont eu un impact négatif sur les cultures de riz Aus et Aman, tandis que la température et les précipitations ont une influence positive sur le rendement du riz Boro. En ce qui concerne les questions de changement climatique et la sauvegarde de la sécurité alimentaire au niveau régional, les autorités concernées devraient accorder une attention considérable à l'amélioration des variétés à haut rendement tolérantes à la chaleur et à la sécheresse contre les effets climatiques sur les variétés de riz Aus et Aman. Debido a las evidentes variaciones climáticas y a la importante contribución a la producción nacional de alimentos, Bangladesh es una región climáticamente crítica para examinar las consecuencias climáticas para la producción de cultivos de arroz (Oryza Sativa). Este estudio pretende explorar la variabilidad de las variables climáticas (por ejemplo, variaciones en la temperatura media, las precipitaciones, la humedad relativa y la duración del sol) con los rendimientos de arroz (por ejemplo, las variedades de arroz AUS, aman y Boro) en el noroeste de Bangladesh. La prueba de Mann–Kendall modificada, el estimador de pendiente de Theil–Sen y el modelado de regresión lineal múltiple (MLR) se utilizaron para estimar la asociación entre estos factores. Se adoptó la técnica de heterocedasticidad y error estándar constante de autocorrelación (hac) y mínimos cuadrados generalizados factibles (FGLS) para medir el nexo clima-arroz utilizando el conjunto de datos a nivel regional para 1976–2015. Además, se mapeó y evaluó la variación espaciotemporal de las tendencias de rendimiento del arroz con variables climáticas mediante el coeficiente de variación. Los resultados muestran que las tendencias observadas de temperatura y humedad fueron beneficiosas para los rendimientos de AUS y aman, pero no para los rendimientos de Boro. Por el contrario, las tendencias observadas de precipitaciones y sol fueron negativas para las tres temporadas de arroz. Los resultados del modelo MLR explicaron el 67%, 92% y 83% de la variabilidad en los rendimientos de arroz AUS, aman y Boro en la región de estudio. Los resultados del modelo mostraron que la humedad y las precipitaciones han afectado negativamente a los cultivos de arroz AUS y aman, mientras que la temperatura y las precipitaciones influyen positivamente en el rendimiento del arroz Boro. Con respecto a los problemas del cambio climático y la salvaguardia de la seguridad alimentaria a nivel regional, las autoridades competentes deben prestar una atención sustancial a la mejora de las variedades de alto rendimiento tolerantes al calor y la sequía frente a los efectos climáticos en las variedades de arroz AUS y aman. Because of evident climatic variations and significant contribution to national food production, Bangladesh is a climate extreme hotspot region of examination for climatic consequences for rice (Oryza Sativa) crop production. This study intends to explore the variability of climatic variables (e.g., variations in mean temperature, rainfall, relative humidity, and sunshine duration) with rice yields (e.g., Aus, Aman, and Boro rice varieties) in northwest Bangladesh. The modified Mann–Kendall test, Theil–Sen slope estimator, and multiple linear regression (MLR) modeling were used to estimate the association among these factors. Heteroskedasticity and autocorrelation constant standard error (HAC) and feasible generalized least square (FGLS) technique were adopted to measure the climate-rice crop nexus using the regional level dataset for 1976–2015. Furthermore, the spatiotemporal variation of rice yield trends with climatic variables was mapped and assessed by the coefficient of variation. The results show that observed temperature and humidity trends were beneficial for Aus and Aman yields but not Boro yields. In contrast, observed rainfall and sunshine trends were negative for all three rice seasons. The outcomes of the MLR model explained 67%, 92%, and 83% of the variability in Aus, Aman, and Boro rice yields in the study region. The model outcomes showed that humidity and rainfall have negatively affected Aus and Aman rice crops, while temperature and rainfall positively influence Boro rice yield. Regarding the climate change issues and safeguarding food safety at the regional level, the concerned authorities should provide substantial attention to improving heat and drought-tolerance high-yielding varieties against climate effects on Aus and Aman rice varieties. نظرًا للتغيرات المناخية الواضحة والمساهمة الكبيرة في الإنتاج الغذائي الوطني، تعد بنغلاديش منطقة ساخنة شديدة المناخ لفحص الآثار المناخية على إنتاج محاصيل الأرز (أوريزا ساتيفا). تهدف هذه الدراسة إلى استكشاف تقلب المتغيرات المناخية (على سبيل المثال، الاختلافات في متوسط درجة الحرارة وهطول الأمطار والرطوبة النسبية ومدة أشعة الشمس) مع غلة الأرز (على سبيل المثال، أصناف أرز أستراليا وأمان وبورو) في شمال غرب بنغلاديش. تم استخدام اختبار مان- كيندال المعدل، ومقدر ميل ثيل- سين، ونمذجة الانحدار الخطي المتعدد (MLR) لتقدير الارتباط بين هذه العوامل. تم اعتماد المرونة المتغايرة والخطأ المعياري الثابت للارتباط الذاتي (HAC) وتقنية المربعات الأقل عمومية (FGLS) لقياس العلاقة بين محاصيل المناخ والأرز باستخدام مجموعة البيانات على المستوى الإقليمي للفترة 1976–2015. علاوة على ذلك، تم تعيين وتقييم التباين المكاني والزماني لاتجاهات غلة الأرز مع المتغيرات المناخية من خلال معامل التباين. تظهر النتائج أن اتجاهات درجة الحرارة والرطوبة المرصودة كانت مفيدة لمحاصيل Aus و Aman ولكن ليس محاصيل Boro. على النقيض من ذلك، كانت اتجاهات هطول الأمطار وأشعة الشمس المرصودة سلبية لجميع مواسم الأرز الثلاثة. أوضحت نتائج نموذج MLR 67 ٪ و 92 ٪ و 83 ٪ من التباين في غلة أرز AUS و Aman و Boro في منطقة الدراسة. أظهرت نتائج النموذج أن الرطوبة وهطول الأمطار قد أثرت سلبًا على محاصيل الأرز في أستراليا وأمان، في حين أن درجة الحرارة وهطول الأمطار يؤثران بشكل إيجابي على غلة أرز بورو. فيما يتعلق بقضايا تغير المناخ وحماية سلامة الأغذية على المستوى الإقليمي، يجب على السلطات المعنية إيلاء اهتمام كبير لتحسين الأصناف عالية الغلة التي تتحمل الحرارة والجفاف ضد الآثار المناخية على أصناف أرز أستراليا وأمان.

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    Authors: Rohitashw Kumar; Saika Manzoor; Dinesh Kumar Vishwakarma; Nadhir Al-Ansari; +5 Authors

    Under different climate change scenarios, the current study was planned to simulate runoff due to snowmelt in the Lidder River catchment in the Himalayan region. A basic degree-day model, the Snowmelt-Runoff Model (SRM), was utilized to assess the hydrological consequences of change in the climate. The performance of the SRM model during calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found to be 11.7, −10.1, −11.8, 1.96, and 8.6 in 2009–2014, respectively, while the respective R2 was 0.96, 0.92, 0.95, 0.90, and 0.94. The Dv and R2 values indicate that the simulated snowmelt runoff closely agrees with the observed values. The simulated findings were assessed under three different climate change scenarios: (a) an increase in precipitation by +20%, (b) a temperature rise of +2 °C, and (c) a temperature rise of +2 °C with a 20% increase in snow cover. In scenario (b), the simulated results showed that runoff increased by 53% in summer (April–September). In contrast, the projected increased discharge for scenarios (a) and (c) was 37% and 67%, respectively. The SRM efficiently forecasts future water supplies due to snowmelt runoff in high elevation, data-scarce mountain environments.

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    Authors: Rohitashw Kumar; Saika Manzoor; Dinesh Kumar Vishwakarma; Nadhir Al-Ansari; +5 Authors

    Under different climate change scenarios, the current study was planned to simulate runoff due to snowmelt in the Lidder River catchment in the Himalayan region. A basic degree-day model, the Snowmelt-Runoff Model (SRM), was utilized to assess the hydrological consequences of change in the climate. The performance of the SRM model during calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found to be 11.7, −10.1, −11.8, 1.96, and 8.6 in 2009–2014, respectively, while the respective R2 was 0.96, 0.92, 0.95, 0.90, and 0.94. The Dv and R2 values indicate that the simulated snowmelt runoff closely agrees with the observed values. The simulated findings were assessed under three different climate change scenarios: (a) an increase in precipitation by +20%, (b) a temperature rise of +2 °C, and (c) a temperature rise of +2 °C with a 20% increase in snow cover. In scenario (b), the simulated results showed that runoff increased by 53% in summer (April–September). In contrast, the projected increased discharge for scenarios (a) and (c) was 37% and 67%, respectively. The SRM efficiently forecasts future water supplies due to snowmelt runoff in high elevation, data-scarce mountain environments.

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    Authors: Yongguang Hu; Ali Raza; Neyha Rubab Syed; Siham Acharki; +5 Authors

    Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021). Landsat-based images of 30 m × 30 m spatial resolution were used to detect LULC changes, while NDVI dynamics were calculated using Modis Product MOD13Q1 (Tiles: h24 v5, h24 v6) at a resolution of 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering using the minimal distance center approach) was used to quantify the LULC changes in this research because of its straightforward approach that requires minimal human intervention. The accuracy assessment and the Kappa coefficient were calculated to assess the efficacy of results derived from LULC changes. Our findings revealed considerable changes in settlements, forests, and barren land in Southern Punjab. Compared to 2000, while forest cover had reduced by 31.03%, settlement had increased by 14.52% in 2021. Similarly, forest land had rapidly been converted into barren land. For example, barren land had increased by 12.87% in 2021 compared to 2000. The analysis showed that forests were reduced by 31.03%, while settlements and barren land increased by 14.52% and 12.87%, respectively, over the twenty year period in Southern Punjab. The forest area had decreased to 4.36% by 2021. It shows that 31.03% of forest land had been converted to urban land, barren ground, and farmland. Land that was formerly utilized for vegetation had been converted into urban land due to the expansion of infrastructure and the commercial sector in Southern Punjab. Consequently, proper monitoring of LULC changes is required. Furthermore, relevant agencies, governments, and policymakers must focus on land management development. Finally, the current study provides an overall scenario of how LULC trends are evolving over the study region, which aids in land use planning and management.

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    Sustainability
    Article . 2023 . Peer-reviewed
    License: CC BY
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    Sustainability
    Article . 2023
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      Sustainability
      Article . 2023 . Peer-reviewed
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    Authors: Yongguang Hu; Ali Raza; Neyha Rubab Syed; Siham Acharki; +5 Authors

    Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021). Landsat-based images of 30 m × 30 m spatial resolution were used to detect LULC changes, while NDVI dynamics were calculated using Modis Product MOD13Q1 (Tiles: h24 v5, h24 v6) at a resolution of 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering using the minimal distance center approach) was used to quantify the LULC changes in this research because of its straightforward approach that requires minimal human intervention. The accuracy assessment and the Kappa coefficient were calculated to assess the efficacy of results derived from LULC changes. Our findings revealed considerable changes in settlements, forests, and barren land in Southern Punjab. Compared to 2000, while forest cover had reduced by 31.03%, settlement had increased by 14.52% in 2021. Similarly, forest land had rapidly been converted into barren land. For example, barren land had increased by 12.87% in 2021 compared to 2000. The analysis showed that forests were reduced by 31.03%, while settlements and barren land increased by 14.52% and 12.87%, respectively, over the twenty year period in Southern Punjab. The forest area had decreased to 4.36% by 2021. It shows that 31.03% of forest land had been converted to urban land, barren ground, and farmland. Land that was formerly utilized for vegetation had been converted into urban land due to the expansion of infrastructure and the commercial sector in Southern Punjab. Consequently, proper monitoring of LULC changes is required. Furthermore, relevant agencies, governments, and policymakers must focus on land management development. Finally, the current study provides an overall scenario of how LULC trends are evolving over the study region, which aids in land use planning and management.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sustainabilityarrow_drop_down
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    Sustainability
    Article . 2023 . Peer-reviewed
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    Sustainability
    Article . 2023
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      Sustainability
      Article . 2023 . Peer-reviewed
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      Sustainability
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    Authors: Abhay M. Varade; Kanak N. Moharir; S. F. R. Khadri; Chaitanya B. Pande; +5 Authors

    In India the demand of sustainable energy is growing at a fragmented level. The demand of rural electrification and economic growth requires high production of energy. Hence, the use of renewable energy may help to mitigate air pollution, and allow specific regenerative agriculture, waste, and forest biomass for producing the energy and achieving sustainable development goals. In the current work, we have selected a district of Maharashtra state of India as a case study and mapped the different land cover categories, and their estimated biomass. Based on this we have prepared the biomass thematic maps for the study area. These biomass maps have been prepared in the GIS environment and they displayed the biomass of crops, forests, and wastelands. The studied district has huge potential for agricultural biomass and can act as biofuel and biomass economies. These maps may play a crucial role in upgrading biomass sites focused on generating power from plants in the district Akola of Maharashtra, India.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of the Saudi...arrow_drop_down
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    Journal of the Saudi Society of Agricultural Sciences
    Article . 2021 . Peer-reviewed
    License: CC BY NC ND
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      Journal of the Saudi Society of Agricultural Sciences
      Article . 2021 . Peer-reviewed
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    Authors: Abhay M. Varade; Kanak N. Moharir; S. F. R. Khadri; Chaitanya B. Pande; +5 Authors

    In India the demand of sustainable energy is growing at a fragmented level. The demand of rural electrification and economic growth requires high production of energy. Hence, the use of renewable energy may help to mitigate air pollution, and allow specific regenerative agriculture, waste, and forest biomass for producing the energy and achieving sustainable development goals. In the current work, we have selected a district of Maharashtra state of India as a case study and mapped the different land cover categories, and their estimated biomass. Based on this we have prepared the biomass thematic maps for the study area. These biomass maps have been prepared in the GIS environment and they displayed the biomass of crops, forests, and wastelands. The studied district has huge potential for agricultural biomass and can act as biofuel and biomass economies. These maps may play a crucial role in upgrading biomass sites focused on generating power from plants in the district Akola of Maharashtra, India.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of the Saudi...arrow_drop_down
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    Journal of the Saudi Society of Agricultural Sciences
    Article . 2021 . Peer-reviewed
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      Journal of the Saudi Society of Agricultural Sciences
      Article . 2021 . Peer-reviewed
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    Authors: Elsayed Ahmed Elsadek; Ke Zhang; Yousef Alhaj Hamoud; Ahmed Mousa; +6 Authors

    Climate change directly affects crop yields, which would cause more future food security crises. Ensemble global climate models (GCMs) combined with crop growth models are an effective method to project such impacts. In the current study, five criteria were used to pick out ten GCMs. Three types of efficiency criteria, namely root-mean-squared error (RMSE), Pearson’s correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and bias (BISA) between predicted and observed temperature and precipitation, were used to evaluate and select the better-performing of the GCMs for the baseline period (1981–2010). Then, AquaCrop-GIS, driven by the downscaled projected climate data from the selected GCMs, was used to predict rice yields in the Nile River Delta (NRD) region under two Shared Socioeconomic Pathways (SSP) scenarios (SSP2–4.5 and SSP5–8.5) and four prediction periods (2021–2099). Four statistical indicators, namely, prediction error (Pe), normalized RMSE (RMSEn), index of agreement (Dindex), and coefficient of determination (R2), were used to evaluate the performance of AquaCrop-GIS. Our results showed that five GCMs, including the BCC-CSM2-MR, CMCC-ESM2, INM-CM5–0, MRI-ESM2–0, and UKESM1–0-LL, had better performances in simulating temperature and precipitation (0.81 ≤ RMSE ≤ 4.77, 0.30 ≤ NSE ≤ 0.97, and 0.57 ≤ R ≤ 0.99). In addition, AquaCrop-GIS showed excellent accuracy in simulating rice yields and predicted that, without CO2 effects, rice yields would increase by 2.19% and 4.23% under SSP2–4.5 and by 0.72% and 0.30% under SSP5–8.5 during the 2030s and 2050s, respectively. However, in the 2070s and 2090s, rice yields would decline by 7.20% and 9.0% under SSP2–4.5 and by 23.34% and 34.24% under SSP5–8.5 during the 2070s and 2090s, respectively. With CO2 effects, rice yields would rise by 14.49%, 24.97%, 15.96%, and 16.93% under SSP2–4.5 and by 14.33%, 26.22%, 8.06%, and 1.61% under SSP5–8.5 during the 2030s, 2050s, 2070s, and 2090s, respectively. Regardless of uncertainties and limitations, our findings are beneficial for farmers and policymakers to develop appropriate management strategies to improve rice yields in Egypt.

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    Agricultural Water Management
    Article . 2024 . Peer-reviewed
    License: CC BY NC
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    Agricultural Water Management
    Article . 2024
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      Agricultural Water Management
      Article . 2024 . Peer-reviewed
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      Agricultural Water Management
      Article . 2024
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    Authors: Elsayed Ahmed Elsadek; Ke Zhang; Yousef Alhaj Hamoud; Ahmed Mousa; +6 Authors

    Climate change directly affects crop yields, which would cause more future food security crises. Ensemble global climate models (GCMs) combined with crop growth models are an effective method to project such impacts. In the current study, five criteria were used to pick out ten GCMs. Three types of efficiency criteria, namely root-mean-squared error (RMSE), Pearson’s correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and bias (BISA) between predicted and observed temperature and precipitation, were used to evaluate and select the better-performing of the GCMs for the baseline period (1981–2010). Then, AquaCrop-GIS, driven by the downscaled projected climate data from the selected GCMs, was used to predict rice yields in the Nile River Delta (NRD) region under two Shared Socioeconomic Pathways (SSP) scenarios (SSP2–4.5 and SSP5–8.5) and four prediction periods (2021–2099). Four statistical indicators, namely, prediction error (Pe), normalized RMSE (RMSEn), index of agreement (Dindex), and coefficient of determination (R2), were used to evaluate the performance of AquaCrop-GIS. Our results showed that five GCMs, including the BCC-CSM2-MR, CMCC-ESM2, INM-CM5–0, MRI-ESM2–0, and UKESM1–0-LL, had better performances in simulating temperature and precipitation (0.81 ≤ RMSE ≤ 4.77, 0.30 ≤ NSE ≤ 0.97, and 0.57 ≤ R ≤ 0.99). In addition, AquaCrop-GIS showed excellent accuracy in simulating rice yields and predicted that, without CO2 effects, rice yields would increase by 2.19% and 4.23% under SSP2–4.5 and by 0.72% and 0.30% under SSP5–8.5 during the 2030s and 2050s, respectively. However, in the 2070s and 2090s, rice yields would decline by 7.20% and 9.0% under SSP2–4.5 and by 23.34% and 34.24% under SSP5–8.5 during the 2070s and 2090s, respectively. With CO2 effects, rice yields would rise by 14.49%, 24.97%, 15.96%, and 16.93% under SSP2–4.5 and by 14.33%, 26.22%, 8.06%, and 1.61% under SSP5–8.5 during the 2030s, 2050s, 2070s, and 2090s, respectively. Regardless of uncertainties and limitations, our findings are beneficial for farmers and policymakers to develop appropriate management strategies to improve rice yields in Egypt.

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    Agricultural Water Management
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    Agricultural Water Management
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    Authors: Muhammad Tayyab Sohail; Zaira Manzoor; Muhsan Ehsan; Nadhir Al-Ansari; +8 Authors

    Rapid urbanization, coupled with land use land cover changes (LULC), has caused stress on freshwater resources around the globe. As in the case of Islamabad, the capital of Pakistan, the population has increased significantly, creating a deficit of natural resources and affecting the environment adversely. Therefore, the purpose of this study is to examine the effects of urbanization and LULC on the decline of the static water table in Islamabad. It also seeks to analyze water policy issues in order to achieve sustainable water resource development. The excessive pumping of the existing groundwater has exceeded the safe limit, which is justified by the constantly growing population. However, the changes in the LULC of the study area have turned many green pastures into barren land. Our research data were obtained from the Capital Development Authority (CDA), Pakistan Meteorological Department (PMD), and Landsat Satellite images. After analyzing PMD and CDA data for the last 20 years (2000–2020), the results were interpreted using Arc GIS. It has been observed that the Normalized Difference Vegetation Index (NDVI) value increases as the Land Surface Temperature (LST) decreases. Therefore, the overall observation is a decreasing trend in Islamabad temperatures due to the increased vegetation in the study area during the period of 2000–2020. It was observed that there has been a considerable drop in water levels due to over-pumping in a few areas. It is primarily associated with the increasing population of the capital in the last 2 decades. This study uses a survey to explore the potential locations for check dams to enhance and recharge the groundwater aquifers in the capital, Islamabad. It suggests catchment areas throughout the Margalla Hills along with different localities, such as Rumli Village, Trail 5, and Shahdara.

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    Frontiers in Environmental Science
    Article . 2023 . Peer-reviewed
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    Authors: Muhammad Tayyab Sohail; Zaira Manzoor; Muhsan Ehsan; Nadhir Al-Ansari; +8 Authors

    Rapid urbanization, coupled with land use land cover changes (LULC), has caused stress on freshwater resources around the globe. As in the case of Islamabad, the capital of Pakistan, the population has increased significantly, creating a deficit of natural resources and affecting the environment adversely. Therefore, the purpose of this study is to examine the effects of urbanization and LULC on the decline of the static water table in Islamabad. It also seeks to analyze water policy issues in order to achieve sustainable water resource development. The excessive pumping of the existing groundwater has exceeded the safe limit, which is justified by the constantly growing population. However, the changes in the LULC of the study area have turned many green pastures into barren land. Our research data were obtained from the Capital Development Authority (CDA), Pakistan Meteorological Department (PMD), and Landsat Satellite images. After analyzing PMD and CDA data for the last 20 years (2000–2020), the results were interpreted using Arc GIS. It has been observed that the Normalized Difference Vegetation Index (NDVI) value increases as the Land Surface Temperature (LST) decreases. Therefore, the overall observation is a decreasing trend in Islamabad temperatures due to the increased vegetation in the study area during the period of 2000–2020. It was observed that there has been a considerable drop in water levels due to over-pumping in a few areas. It is primarily associated with the increasing population of the capital in the last 2 decades. This study uses a survey to explore the potential locations for check dams to enhance and recharge the groundwater aquifers in the capital, Islamabad. It suggests catchment areas throughout the Margalla Hills along with different localities, such as Rumli Village, Trail 5, and Shahdara.

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    Frontiers in Environmental Science
    Article . 2023 . Peer-reviewed
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      Frontiers in Environmental Science
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    Authors: Endre Harsányi; Bashar Bashir; Gafar Almhamad; Omar Hijazi; +6 Authors

    Climate mitigation and adaptation planning (CMAP) has recently been implemented across the EU-28 to reduce GHG emissions (CO2, CH4, N2O). Thus, the aim of this study was to provide an overview of GHG emissions from the agricultural sector in the EU-28 from 1990 to 2019, and cluster the EU-28 countries regarding their total GHG emissions. The results emphasize the positive impact of CMAP through a negative trend of the total GHG emissions (−2653.01 thousand tons/year, p < 0.05). Despite the positive and not significant trend of the total CO2 emissions, both CH4 and N2O exhibited a negative and significant trend. At the country scale, Italy, the United Kingdom, and the Netherlands showed the highest reduction in total GHG emissions, by −282.61thousand tons/year (p < 0.05), −266.40 thousand tons/year (p < 0.05), and −262.91 thousand tons/year (p < 0.05), respectively. The output of the multivariate analysis approach indicates changes in the pattern of GHG emissions between 1990 and 2019, where CO2 emissions decreased in the case of Poland and Czechia. The output of this study highlights the positive impact of CMAP, adopted by EU countries, in minimizing GHG emissions. Despite some fluctuations in CO2 emissions, strategies for attaining carbon neutrality in the agricultural sector, across the European Union, should be pursued.

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    Energies
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    Article . 2020
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      Energies
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    Authors: Endre Harsányi; Bashar Bashir; Gafar Almhamad; Omar Hijazi; +6 Authors

    Climate mitigation and adaptation planning (CMAP) has recently been implemented across the EU-28 to reduce GHG emissions (CO2, CH4, N2O). Thus, the aim of this study was to provide an overview of GHG emissions from the agricultural sector in the EU-28 from 1990 to 2019, and cluster the EU-28 countries regarding their total GHG emissions. The results emphasize the positive impact of CMAP through a negative trend of the total GHG emissions (−2653.01 thousand tons/year, p < 0.05). Despite the positive and not significant trend of the total CO2 emissions, both CH4 and N2O exhibited a negative and significant trend. At the country scale, Italy, the United Kingdom, and the Netherlands showed the highest reduction in total GHG emissions, by −282.61thousand tons/year (p < 0.05), −266.40 thousand tons/year (p < 0.05), and −262.91 thousand tons/year (p < 0.05), respectively. The output of the multivariate analysis approach indicates changes in the pattern of GHG emissions between 1990 and 2019, where CO2 emissions decreased in the case of Poland and Czechia. The output of this study highlights the positive impact of CMAP, adopted by EU countries, in minimizing GHG emissions. Despite some fluctuations in CO2 emissions, strategies for attaining carbon neutrality in the agricultural sector, across the European Union, should be pursued.

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    Energies
    Article . 2021 . Peer-reviewed
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    Energies
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    MediaTUM
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    Authors: Ismail, Abd-Elaty; N L, Kushwaha; Mark E, Grismer; Ahmed, Elbeltagi; +1 Authors

    Sustainable management of natural water resources and food security in the face of changing climate conditions is critical to the livelihood of coastal communities. Increasing inundation and saltwater intrusion (SWI) will likely adversely affect agricultural production and the associated beach access for tourism. This study uses an integrated surface-ground water model to introduce a new approach for retardation of SWI that consists of placing aquifer fill materials along the existing shoreline using Coastal Land Reclamation (CLR). The modeling results suggest that the artificial aquifer materials could be designed to decrease SWI by increasing the infiltration area of coastal precipitation, collecting runoffs from the catchment area, and applying treated wastewater or desalinated brackish water-using coastal wave energy to reduce water treatment costs. The SEAWAT model was applied to verify that it correctly addressed Henry's problem and then applied to the Biscayne aquifer, Florida, USA. In this study, to better inform Coastal Aquifer Management (CAM), we developed four modeling scenarios, namely, Physical Surface Barriers (PSB), including the artificial aquifer widths, permeability, and side slopes and recharge. In the base case scenario without artificial aquifer placement, results show that seawater levels would increase aquifer salinity and displace large amounts of presently available fresh groundwater. More specifically, for the Biscayne aquifer, approximately 0.50% of available fresh groundwater will be lost (that is, 41,192 m3) per km of the width of the aquifer considering the increasing seawater level. Furthermore, the results suggest that placing the PSB aquifer with a smaller permeability of <100 m per day at a width of approximately 615 m increases the available fresh groundwater by approximately 45.20 and 43.90% per km of shoreline, respectively. Similarly, decreasing the slope on the aquifer-ocean side and increasing the aquifer recharge will increase freshwater availability by about 43.90 and 44.50% per km of the aquifer. Finally, placing an aquifer fill along the shallow shoreline increases net revenues to the coastal community through increased agricultural production and possibly tourism that offset fill placement and water treatment costs. This study is useful for integrated management of coastal zones by delaying aquifer salinity, protecting fresh groundwater bodies, increasing agricultural lands, supporting surface water supplies by harvesting rainfall and flash flooding, and desalinating saline water using wave energy. Also, the feasibility of freshwater storage and costs for CAM is achieved in this study.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao The Science of The T...arrow_drop_down
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    The Science of The Total Environment
    Article . 2022 . Peer-reviewed
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      The Science of The Total Environment
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    Authors: Ismail, Abd-Elaty; N L, Kushwaha; Mark E, Grismer; Ahmed, Elbeltagi; +1 Authors

    Sustainable management of natural water resources and food security in the face of changing climate conditions is critical to the livelihood of coastal communities. Increasing inundation and saltwater intrusion (SWI) will likely adversely affect agricultural production and the associated beach access for tourism. This study uses an integrated surface-ground water model to introduce a new approach for retardation of SWI that consists of placing aquifer fill materials along the existing shoreline using Coastal Land Reclamation (CLR). The modeling results suggest that the artificial aquifer materials could be designed to decrease SWI by increasing the infiltration area of coastal precipitation, collecting runoffs from the catchment area, and applying treated wastewater or desalinated brackish water-using coastal wave energy to reduce water treatment costs. The SEAWAT model was applied to verify that it correctly addressed Henry's problem and then applied to the Biscayne aquifer, Florida, USA. In this study, to better inform Coastal Aquifer Management (CAM), we developed four modeling scenarios, namely, Physical Surface Barriers (PSB), including the artificial aquifer widths, permeability, and side slopes and recharge. In the base case scenario without artificial aquifer placement, results show that seawater levels would increase aquifer salinity and displace large amounts of presently available fresh groundwater. More specifically, for the Biscayne aquifer, approximately 0.50% of available fresh groundwater will be lost (that is, 41,192 m3) per km of the width of the aquifer considering the increasing seawater level. Furthermore, the results suggest that placing the PSB aquifer with a smaller permeability of <100 m per day at a width of approximately 615 m increases the available fresh groundwater by approximately 45.20 and 43.90% per km of shoreline, respectively. Similarly, decreasing the slope on the aquifer-ocean side and increasing the aquifer recharge will increase freshwater availability by about 43.90 and 44.50% per km of the aquifer. Finally, placing an aquifer fill along the shallow shoreline increases net revenues to the coastal community through increased agricultural production and possibly tourism that offset fill placement and water treatment costs. This study is useful for integrated management of coastal zones by delaying aquifer salinity, protecting fresh groundwater bodies, increasing agricultural lands, supporting surface water supplies by harvesting rainfall and flash flooding, and desalinating saline water using wave energy. Also, the feasibility of freshwater storage and costs for CAM is achieved in this study.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao The Science of The T...arrow_drop_down
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    The Science of The Total Environment
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      The Science of The Total Environment
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    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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    Sustainability
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    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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