Weather Events Research Articles

Enhancing runoff predictions in data-sparse regions through hybrid deep learning and hydrologic modeling

Amidst growing concerns over climate-induced extreme weather events, precise flood forecasting becomes imperative, especially in regions like the Chaersen Basin where data scarcity compounds the challenge. Traditional hydrologic models, while reliable, often fall short in areas with insufficient observational data. This study introduces a hybrid modeling approach that combines the deep learning capabilities of the Informer model with the robust hydrological simulation by the WRF-Hydro model to enhance runoff predictions in such data-sparse regions. Trained initially on the diverse and extensive CAMELS dataset in the United States, the Informer model successfully applied its learned insights to predict runoff in the Chaersen Basin, leveraging transfer learning to bridge data gaps. Concurrently, the WRF-Hydro model, when integrated with The Global Forecast System (GFS) data, provided a basis for comparison and further refinement of flood prediction accuracy. The integration of these models resulted in a significant improvement in prediction precision. The synergy between the Informer’s advanced pattern recognition and the physical modeling strength of the WRF-Hydro significantly enhanced the prediction accuracy. The final predictions for the years 2015 and 2016 demonstrated notable increases in the Nash–Sutcliffe Efficiency (NSE) and the Index of Agreement (IOA) metrics, confirming the effectiveness of the hybrid model in capturing complex hydrological dynamics during runoff predictions. Specifically, in 2015, the NSE improved from 0.5 with WRF-Hydro and 0.63 with the Informer model to 0.66 using the hybrid model, while in 2016, the NSE increased from 0.42 to 0.76. Similarly, the IOA in 2015 rose from 0.83 with WRF-Hydro and 0.84 with the Informer model to 0.87 using the hybrid approach, and in 2016, it increased from 0.78 to 0.92. Further investigation into the respective contributions of the WRF-Hydro and the Informer models revealed that the hybrid model achieved the optimal performance when the contribution of the Informer model was maintained between 60%-80%.

The Unequal Impact of Disasters: Assessing the Interplay Between Social Vulnerability, Public Assistance, Flood Insurance, and Migration in the U.S

Extreme weather events, such as hurricanes with intense rainfall and storm surges, are posing increasing challenges to local communities worldwide. These hazards not only result in substantial property damage but also lead to significant population displacement. Federal disaster assistance programs are crucial for providing financial support for disaster response and recovery, but the allocation of these resources often unequal due to the complex interplay of environmental, social, and institutional factors. Relying on datasets collected from diverse sources, this study employs a structural equation model to explore the complex relationships between disaster damage (DD), social vulnerability (SV), public disaster assistance (PDA), the national flood insurance (NFI), and population migration (PM) across counties in the contiguous US. Our findings reveal that communities with lower SV tend to experience higher levels of DD across US counties. SV is negatively associated with PM, PDA, and NFI, both directly and indirectly. Furthermore, PDA is positively linked to PM, whereas DD has a direct negative effect on PM but an indirect positive effect through PDA.

The Palamas Archaeological Project 2023. A preliminary report of the Greek–Swedish collaboration in the municipality of Palamas, region of Karditsa, Thessaly

The 2023 fieldwork in the area of Palamas, Thessaly, was severely hampered by catastrophic weather events affecting the area. In spite of this, the project managed to conduct excavations, surface and architectural surveys, as well as geophysical prospection at a number of sites in the region. The work continues to highlight the chronological breadth of archaeological remains in the area, as well as further details regarding little-known periods of Thessalian history.

Impacts of changing weather patterns on the dynamics of water pollutants in agricultural catchments: Insights from 11-year high temporal resolution data analysis

Widespread and long-term shifts in weather patterns are contributing to further degradation of surface water quality. This challenge caused by the increasing frequency of extreme weather events requires appropriate adaptation of current mitigation strategies. But to confirm the need to redesign such strategies, an understanding of the impacts of increasing weather extremes on pollutant losses in different catchment types is required. With this in view, this study investigated the impact of changing weather patterns on the inter-seasonal and inter-annual dynamics of nutrient losses in six agricultural catchments in Ireland over 11 years. The high temporal resolution data (10-min) from these intensively managed catchments represented different characteristics and management practices. Mann-Kendall Trend Analysis and Generalised Additive Models were used to study nutrient concentration trends, and to investigate the significance of water discharge, precipitation, potential evapotranspiration, soil moisture deficit, air temperature, and soil temperature on the losses of nutrients, respectively. The analysis of historical data revealed changes in the trends of daily average nitrate (NO3-N), phosphorus (P), and suspended sediment (SS) concentrations in association with significant increasing trends in air temperature, soil temperature, and precipitation across the same month over 11 years of monitoring. While discharge was significantly contributing to the concentrations of NO3-N, P, and SS across different catchments, air and soil temperature were significantly correlated to NO3-N losses, and precipitation was the major contributor to regulating P (total P and total reactive P) concentrations. In short, air temperature, soil temperature, soil moisture deficit, and precipitation were the main climatic drivers regulating the nutrient concentrations while the soil chemistry and drainage status were the non-climatically related drivers. The results revealed that the extent of the impact of climatic drivers depends on catchment characteristics. Therefore, expanding the application of this type of study would facilitate better understanding of current and future challenges to water management and provision of climate-resilient mitigation strategies for different catchment typologies.

Country-wide assessment of plastic removal rates on riverbanks and water surfaces.

Plastic pollution in river basins poses a significant environmental challenge, particularly in Japan, located in the northwestern North Pacific, often referred to as a hotspot for plastics. This study quantified the annual recovery of anthropogenic plastic litter from riverbanks and water surfaces, utilizing a nationwide cleanup dataset provided by the Japanese Ministry of Land, Infrastructure, Transport and Tourism. The dataset includes the amount of litter recovered through volunteer and administrative cleanup campaigns from 2016 to 2020 in 109 Japanese river basins. Total plastic recovery ranged from 763 to 1177 tons/year, averaging 938 tons/year. Basin-specific recovery was associated with extreme weather events, such as typhoon approaches and heavy rain, which caused significant flood damage in local regions. The estimated annual plastic recovery was an order of magnitude smaller than the previously estimated annual emission of land-based plastic.

Climate change, climate disasters and oncology care: a descriptive global survey of oncology healthcare professionals.

Climate disasters and climate change have implications for healthcare globally. As the number and intensity of climate disasters increase, it is important to understand the effects on healthcare. We conducted a global survey of oncology healthcare providers to identify awareness, experiences, and educational needs related to climate change. An existing climate and health survey was adapted to oncology. This IRB- approved, 30-item survey measured demographics, climate disaster awareness, effects on cancer care and educational needs. Healthcare professionals employed in oncology settings (practice, research, or academic) were eligible. The survey was disseminated via social media and professional organizations. Descriptive statistics were computed using SPSS. 154 responses from 26 countries were received from nurses (56%), physicians (19%), and other healthcare professionals (25%). Common climate change-related events impacting oncology care were extreme heat (63.8%) and heavy rains (52.2%). Respondents reported their workplace has a disaster plan for climate-related weather events (50.4%) or has taken steps to prepare for a climate-related weather event (48.5%). Respondents were aware that the planet has warmed significantly (98.7%), that healthcare contributes to greenhouse gas emissions (98.6%) and reported wanting to learn more about how climate change affects cancer care (88.3%). Preferred educational modalities include webinars (69%), e-learning (55%), journal articles (48.3%), conferences (46.3%) and podcasts (38.9%). This global survey is the first to identify the awareness, experiences, and educational needs of oncology healthcare professionals related to climate change and climate disasters. Healthcare providers are positioned to take leadership roles related to climate and health.

The impact of long-term organic horticultural systems on energy outputs and carbon storages in relation to extreme rainfall events

Enhancing resilience of agroecosystems of Mediterranean area is a challenge that involves both researchers and different stakeholders and, in this context, increasing crop diversity by redesigning agricultural systems can be considered among the most important tools. Therefore, the response of agroecological practices to climate change effects was tested in a long-term experiment on organic horticultural crops (MITIORG), which is characterized by a soil hydraulic arrangement in ridges, strips and the use (with different management options) of cover crops within cash crops rotations. The main objective of this study was to show how powerful is the sustainability assessment of agroecological practices by converting crops yield and biomass into energy outputs and carbon storages, in diversified horticultural systems. The obtained outputs (expressed in energy and carbon equivalents) were evaluated and analyzed considering the site-specific meteorological data in more than 10 horticultural cropping cycles, from autumn-winter 2014-15 to autumn-winter 2020-21. The Ridge and Strips (RS) system 1 (RS1 - cover crops as living mulch on ridges and break crops in strips, both with no-till termination) showed an enhancement of about 18% of energy output and carbon (C) storages compared to RS2 (ridges and strips with green manured cover) when extreme precipitation events occurred. Moreover, RS3 (ridges and strips without cover crops) recorded a reduction of about 5 and 9% of energy output and C storage, respectively, compared to the mean of RS1 and RS2 in periods with extreme events. Our results highlighted that using more diversified agroecological systems improved their overall average outputs, ensuring greater resilience during extreme weather events, since at least part of crop productions was safeguarded. Therefore, it is important to combine techniques that allow long-term resilience, such as choosing and well managing cover crops (agroecological service crops), according to site and systems specific conditions.

Linking patterns of forest dieback to triggering climatic and weather events: an overview on Mediterranean forests

Linking patterns of forest dieback to triggering climatic and weather events: an overview on Mediterranean forests

Diurnal Cycles of Cloud Properties and Precipitation Patterns over the Northeastern Tibetan Plateau During Summer

In the context of rising temperatures and increasing humidity in Northwest China, substantial gaps remain in understanding the mechanisms of land–atmosphere cloud–precipitation coupling across the northeastern Tibetan Plateau (TP), Loess Plateau (LP), and Huangshui Valley (HV). This study addresses these gaps by investigating cloud properties and precipitation patterns utilizing the Fengyun-4 Satellite Quantitative Precipitation Estimation Product (FY4A-QPE) and ERA5 datasets. We specifically focus on Lanzhou, a pivotal city within the LP, and Xining, which epitomizes the HV. Our findings reveal that diurnal variations in precipitation are significantly less pronounced in the eastern regions compared to northeastern TP. This discrepancy is attributed to marked diurnal fluctuations in convective available potential energy (CAPE) and wind shear between 200 and 500 hPa. While both cities share similar wind shear patterns and moisture transport directions, Xining benefits from enhanced snowmelt and effective water retention in surrounding mountains, resulting in higher precipitation levels. Conversely, Lanzhou suffers from moisture deficits, with dry, hot winds exacerbating the situation. Notably, precipitation in Xining is strongly correlated with CAPE, influenced by diurnal variability, and intensified by valley and lake–land breezes, which drive afternoon convection. In contrast, Lanzhou’s precipitation exhibits a weak relationship with CAPE, as even elevated values fail to generate significant cloud formation due to insufficient moisture. The ongoing trends of warming and humidification may lead to improved precipitation patterns, especially in the HV, with potential ecological benefits. However, concentrated rainfall during summer afternoons and midnights raises concerns regarding extreme weather events, highlighting the susceptibility of the HV to geological hazards. This research underscores the need to further explore the uncertainties inherent in precipitation dynamics in these regions.

Artificial Intelligence-Based Precipitation Estimation Method Using Fengyun-4B Satellite Data

This paper proposes a novel precipitation estimation method based on FY-4B meteorological satellite data (FY-4B_AI). This method facilitates the spatiotemporal matching of 125 features derived from the multi-temporal and multi-channel data of the FY-4B satellite with precipitation data at stations. Subsequently, a precipitation model was constructed using the light gradient boosting machine (LGBM) algorithm. A comparative analysis of FY-4B_AI and GPM/IMERG-L products for over 450 million station cases throughout 2023 revealed the following: (1) The results demonstrate that FY-4B_AI is more accurate than GPM/IMERG-L. Six of the eight evaluation indices exhibit superior performance for FY-4B_AI in comparison to GPM/IMERG-L. These indices include the mean absolute error (MAE), root mean square error (RMSE), relative error (RE), correlation coefficient (CC), probability of detection (POD), and critical success index (CSI). As for the MAE, the results are 1.67 (FY-4B_AI) and 1.92 (GPM/IMERG-L), respectively. The RMSEs are 3.68 and 4.07, respectively. The REs are 17.72% and 26.28%, respectively. The CCs are 0.44 and 0.36, respectively. The PODs are 61.84% and 47.31%, respectively. The CSIs are 0.30 and 0.27, respectively. However, with regard to the mean errors (MEs) and false alarm rates (FARs), FY-4B_AI (−0.88 and 62.85%, respectively) displays a slight degree of inferiority in comparison to GPM/IMERG-L (−0.80 and 62.21%, respectively). (2) An evaluation of two strong weather events to represent the spatial distribution of precipitation in different climatic zones revealed that both FY-4B_AI and GPM/IMERG-L are equally capable of accurately representing these phenomena, irrespective of whether the region in question is humid, as is the case in the southeast, or dry, as is the case in the northwest.

“When you have stress because you don’t have food”: Climate, food security, and mental health during pregnancy among Bakiga and Indigenous Batwa women in rural Uganda

Climate change exerts wide-ranging and significant effects on global mental health via multifactorial pathways, including food insecurity. Indigenous Peoples and pregnant women inequitably experience the harms associated with climate change and food insecurity. This study explores food security and maternal mental health during pregnancy among rural Ugandan Bakiga and Indigenous Batwa women in the context of climate change. Using a community-based research approach, we conducted a series of focus group discussions about climate, food security, and health during pregnancy in four Indigenous Batwa communities and four Bakiga communities in rural Kanungu District, Uganda, as well as longitudinal follow up interviews later in the year. Data were evaluated using a qualitative thematic analysis. Women consistently identified mental health as an important factor affecting maternal-fetal wellbeing during pregnancy. Many women identified that weather and climate extremes, such as prolonged droughts and unpredictable weather events, have made it more difficult for them to obtain sufficient food for themselves and their families during pregnancy, resulting in significant mental distress. More extreme weather conditions have made physical labour difficult or impossible during pregnancy, and resultant hunger further decreased ability to obtain food—a vicious cycle. Women described how anxiety was compounded by worry about future famine, as they anticipated further decreases in crop yields and rising food prices in a changing climate. Indigenous Batwa women experienced additional distress around their lack of access to Indigenous lands and its nutritious food sources. Overall, mothers in rural Uganda described food insecurity and climate extremes as major sources of stress during pregnancy, and they anticipate challenges will worsen. Interventions to enhance adaptive capacity to climate change are needed and should have a focus on the intricate connections with food insecurity and mental health as drivers of overall maternal health.

Stability Assessment of Weirs Reinforced with Sheet Piles

Extreme weather events induced by climate change are increasing across the world. In particular, floods resulting from unpredictable heavy rains cause significant damage to property and human life. In Korea, river and underwater structure management is performed continuously in accordance with strict regulations. However, to prepare for unprecedented downpours, the structures of river reservoirs must be reinforced and their stability must be evaluated. This study focuses on the stability evaluation of piping, which represents the main cause of weir collapse. To this end, sheet piles are applied to weirs to evaluate the effects of changes in their length and location on their seepage discharge, seepage velocity, and maximum hydraulic gradient. Additionally, piping stability evaluation of weirs is conducted using sheet piles by evaluating the critical velocity. The results derived in this study are expected to be highly beneficial for reinforcing weirs currently in operation as well as for the design, construction, and operation of future underwater structures.

Urban Planning Strategies for Coastal Cities in China in Response to Climate Change

Global climate change has increasingly posed a serious threat to coastal cities, rendering them particularly vulnerable to the adverse effects of rising sea levels, more frequent and intense extreme weather events, and the shifting patterns of climate. Traditional urban planning methods, which had been the cornerstone of city development, were found to be inadequate in addressing these escalating challenges. The previous studies often failed to account for the critical importance of integrating climate factors into the planning process, leading to vulnerabilities in urban infrastructure and design. This study meticulously examined the limitations of these conventional urban planning approaches and explored the potential for adapting urban planning strategies in Chinas coastal cities to better respond to the looming threat of climate change. By conducting a thorough analysis of the impacts of high temperatures, floods, and other climate-related events, the study proposed a comprehensive series of response measures tailored to the specific conditions of the time. These measures included the integration of green policies into urban planning to enhance environmental sustainability, the strategic selection of building materials aimed at mitigating urban heat, and the enhancement of water resource management systems to alleviate the urban heat island effect. Moreover, the study closely investigated existing climate response measures through detailed case studies in Xiamen and Dalian, two prominent coastal cities in China. The primary objective was to significantly enhance the resilience of these cities, effectively reduce the risks associated with climate change, and promote a path towards sustainable development. Ultimately, the goal was to create more livable, safer, and sustainable urban environments that would be better equipped to face the challenges posed by an unpredictable climate future.

The Basque Impact Weather Catalogue

Abstract. This paper introduces the Basque Country impact weather catalogue, a versatile tool designed, developed, and maintained by the Basque Meteorology Agency (Euskalmet), with the primary objective of systematically recording detailed information regarding adverse weather events that generate some degree of impact in the Basque Autonomous Community (BAC). The catalogue serves as a repository where information is gathered for the comprehensive characterisation and evaluation of extreme weather events, focusing on both environmental conditions and their associated impacts. For this purpose, three key aspects are included: context, hazard and risk and impact. In the context section, we include information about the date, duration, spatial extent, measurement statistics data, synoptic/mesoscale aspects, and other metadata. The hazard and risk section includes information about hazard and risk typology according to Euskalmet severe weather criteria and warnings procedure. Regarding the impact, a range of metrics and indicators are defined to characterise critical aspects, encompassing the severity of impact including economic damages, human fatalities, and disruptions to normal life. The creation of the Catalogue involves utilising various data sources and repositories, not only from Euskalmet but also, particularly in terms of impact, from emergency interventions, newspapers, local media websites, social media, and data from the Spanish Insurance Consortium. While the volume of available material from each event description may vary from case to case, a standardised information structure and minimum content are imperative for all registered events. This ensures that qualitative analyses based on extensive reports, and quantitative analyses based on recorded or estimated metrics and indicators, are possible for events included. This paper outlines into the design and structuring of the catalogue, and the fundamental steps undertaken during its implementation.

EFFECTS AND CONSEQUENCES OF CLIMATE CHANGE ON THE NATURAL CONDITIONS OF MIRZACHOL DISTRICT

This article examines the effects and consequences of climate change on the natural conditions of Mirzachol district. Through an in-depth analysis of climate data, ecological studies and socio-economic impacts, the study highlights significant changes in temperature, precipitation and extreme weather events in recent decades. These changes have led to changes in local ecosystems, agricultural productivity, and water resources, challenging the county’s predominantly agricultural economy. The paper also discusses existing adaptation strategies and mitigation efforts and recommends additional measures to increase resilience to future climate change.

Sanitary sewer overflows, household sewage backups, and antibiotic-resistant bacteria: the new frontier of environmental health risks and disasters

Abstract Untreated sewage discharges leading to environmental contamination are increasingly common in communities across the globe. The cause of these discharges range from sewer lines in disrepair, blockages, and in the era of more extreme wet weather events, the infiltration of stormwater into the system during heavy downpours. Regardless of the driver of these events, the aftermath results in raw sewage spilling into local waterways, city streets, and commercial and residential structures. Historical research in public health has thoroughly documented the connection between exposure to untreated sewage and waterborne disease. Recent research has detected antibiotic-resistant bacteria at wastewater treatment facilities at a time when deaths by antibiotic-resistant infections are on the rise. However, no research has explored the exposure pathways of antibiotic resistant bacteria during sanitary sewer overflows and household-level sewage backups. In this commentary, we aim to introduce this new frontier of environmental health risks and disasters. To do this we describe the history of modern sanitation and sewer infrastructure with a particular focus on wastewater infrastructure in the U.S. We also explore emerging risks and current methods for identifying antibiotic-resistant bacteria in the environment. We end with future directions for interdisciplinary scholarship at the nexus of urban planning, engineering, and public health by introducing the Water Emergency Team (WET) Project. WET is a community-based multi-method effort to identify environmental risks in the aftermath of household backups through 1) residential surveys, 2) indoor visual inspections, 3) environmental sampling, and 4) laboratory processing and reporting. Our hope is that by introducing this comprehensive approach to environmental risks analysis, other scholars will join us in this effort and ultimately towards addressing this grand challenge of our time.

Dampak Perubahan Iklim terhadap Keanekaragaman Hayati: Literature Review

Climate change is one of the biggest challenges faced by ecosystems and biodiversity worldwide. This research examines climate change's impact on biodiversity through a comprehensive literature review. By collecting and analyzing various previous studies, this research identifies patterns of change in flora and fauna species in response to changing climate variables, such as temperature, rainfall, and the frequency of extreme weather events. Literature results show that many species experience changes in distribution, behavior and reproductive timing, which have the potential to disrupt ecosystem interactions and damage ecological balance. This research also discusses the impact of climate change on natural habitats and the conservation efforts needed to protect biodiversity. These findings highlight the urgency of taking effective mitigation and adaptation measures to maintain biodiversity amidst the increasing challenges of climate change.

An Impact-Based Flood Forecasting System for Citizen Empowerment

This work addresses the critical issue of flooding, a significant natural hazard, consistently ranked highest in the 2023 World Risk Index. The annual onslaught of tropical cyclones and the associated abnormal rainfall threaten lives, and destroy crops and property, thereby causing great economic damage, demanding urgent and science-based decision-making. We introduce an impact-based flood forecasting system as a proactive anticipatory action (i.e., AA) measure, linking climate services and disaster risk management to mitigate extreme weather impacts. Developed by the University of the Philippines Resilience Institute, the National Operational Assessment of Hazards (NOAH) Center, and Gerry Bagtasa of the Institute of Environmental Science and Meteorology, this system advances disaster resilience efforts, leveraging science-based forecasts to prioritize vulnerable barangays (villages). Unlike traditional early warning systems, the proposed automated system predicts flooding one day in advance and assesses exposure levels based on population distribution. By utilizing global weather forecast models locally calibrated for Philippine conditions and 100-year rain return flood hazard maps for the Philippines, the system forecasts river inundated areas, enabling local government units (LGUs) and humanitarian organizations to prioritize preparations for communities and allocate resources during flooding events effectively. This system enhances the efficiency of disaster response planning, fostering a proactive and impactful strategy to address the recurring threat of flooding in the country. The system also underscores the role of open data in disaster resilience, exemplified by NOAH’s system to disseminating big data, which aligns with open governance principles. By encouraging transparency and stakeholder collaboration, data exchange is promoted, providing actionable information that fosters collaboration between the LGUs, humanitarian organizations, and other stakeholders. Cognizant of the importance of community engagement in disaster resilience, the newly developed impact-based flood forecasting system encourages community involvement by providing easily accessible information, which can be used to validate the forecasts based on local knowledge and experience. This research contributes to the urgent call for anticipatory action in the face of escalating extreme weather events globally.

Nuclear Energy's Role in Sustainability and Environmental Protection in India

The world today stands at a critical juncture, grappling with the profound and far-reaching impacts of climate change. The increasing frequency of extreme weather events, rising sea levels, and deteriorating ecosystems only serve to underscore the urgency of transitioning to a low-carbon economy. Governments across the globe are intensifying their climate policies, striving to meet the ambitious goals set forth in international agreements such as the Paris Agreement. Central to these efforts is the systematic decarbonization of national energy mixes [1], where nations are increasingly turning to green and clean technologies to power their economies and ensure sustainable electrification. In this global race to mitigate climate change, renewable energy sources like wind, solar, and hydropower are often highlighted as the vanguards of a sustainable future [2]. However, the challenge lies not only in generating sufficient clean energy but also in ensuring a reliable and continuous supply that can meet the growing demands of an energy-hungry world.

The critical need for child and youth perceptions of active living in India: capturing context complexity in rural and urban regions

Background The physical inactivity pandemic not only has a negative impact on the physical and mental health of children and youth, but it is also a key contributor to the non-communicable disease (NCD) burden, particularly among low- and middle-income countries. The widespread effects of climate change, ranging from extreme weather events to worsening air quality, are exacerbating the physical inactivity pandemic, highlighting the need to undertake holistic interventions to address environmental barriers while promoting physical activity. Despite the potential benefits of active school transportation (AST) on physical activity and the environment, no study has examined the intersection between perceptions of AST, environmental perceptions, and moderate-to-vigorous physical activity (MVPA) among children and youth in India from a child and youth perspective. Methods As a part of this cross-sectional, observational study, digital survey links were administered to 1,042 children and youth aged 5 to 17 (50.3% boys; 49.7% girls). Participants were recruited from 41 schools across 28 rural and urban regions in India. Children and youth provided information on various sociodemographic factors, perceptions of crime and air pollution, and peer support factors. MVPA data were collected using an adapted version of the IPAQ short-form questionnaire. The overall sample was stratified by age, gender, and location, resulting in a total of seven multiple linear regression models to assess the association between AST and MVPA. Results Children and youth who engaged in AST were associated with higher MVPA than those who did not engage in AST (β = 18.020, 95% CI [5.890 to 30.149], p = 0.004), after adjusting for age, gender, and location. In contrast, perceptions of high crime in the neighbourhood (β = − 21.921, CI [−36.195 to −7.647], p = 0.003) and perceptions of air pollution (β = − 12.472, CI [−23.797 to −1.147], p = 0.031) were associated with lower MVPA. Moreover, having active friends was associated with higher MVPA (β = 32.391, CI [9.264 to 55.518], p = 0.006) than not having active friends. AST was significantly associated with higher MVPA in the boys, rural, and aged 13 to 17 models; however, this association was not statistically significant in the girls, urban, and aged 5 to 12 models. Conclusions These findings highlight that promoting AST can potentially promote MVPA and contribute to mitigating the NCD burden among children and youth in India. Future policies and interventions should prioritize initiatives that promote AST, considering diverse sociodemographic factors, and addressing environmental challenges such as perceptions of crime and air pollution.