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The Upper Meghna Basin (UMB), a critical large transboundary highly responsive catchment shared between Bangladesh and India, is facing escalating hydro-climatic extremes under climate change, impacting millions of livelihoods. This study innovatively assesses the future changes with monthly, seasonal, and annual matrices of near and far future rainfall, temperature, high flows, and low flows including flood frequencies, shifting patterns, and probability of exceedances using the Soil and Water Assessment Tool (SWAT), for the very first time, forced by bias-corrected CMIP6 projections of two unique SSP2-4.5 and SSP3-7.0 pathways unlike any past studies on the UMB. To reduce uncertainty, a performance-ranking ensemble approach was also applied for the first time in the context of UMB. Key findings reveal significant hydrological shifts towards the end of the century. Rainfall is projected to get more intense during the monsoon season, and temperatures are expected to rise during summer. The 100-year return period high flows are projected to increase by 17.5% and 15.3% in the near future (2026-2055) and 28.3% and 29.9% in the far future (2071-2100) through SSP2-4.5 and SSP3-7.0, respectively. Likewise, 100-year return period low flows are expected to decline by 12.8% and 6.5% during the near future (2026-2055), while a 5.3% reduction and a 7.1% increase are projected in the far future (2071-2100) under SSP2-4.5 and SSP3-7.0, respectively. These findings highlight a future risk of both extreme floods and possible seasonal low-flow shortages depending on the climatic conditions. Policymakers should prioritize early warning systems, floodplain zoning, and drought management strategies to buffer communities against future hydrological variability. Furthermore, the diverging outcomes across emission pathways underscore the importance of climate mitigation efforts to limit long-term hydrological disruptions in the UMB.
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http://dx.doi.org/10.1007/s11356-025-36754-0 | DOI Listing |
Sci Rep
July 2025
Guizhou Institute of Crop Germplasm Resources, Guizhou Academy of Agricultural Sciences, Guiyang, 550006, China.
Bletilla striata, an important traditional Chinese medicine resource, holds high medicinal and ornamental value. However, unscientific habitat selection for its cultivation has led to low yields and poor quality as medicinal materials in China. The optimized MaxEnt model is a powerful tool for analyzing the potential impacts of environmental factors on species distribution and predicting habitat changes under climate change.
View Article and Find Full Text PDFEnviron Monit Assess
February 2025
Key Laboratory of Green and High-End Utilization of Salt Lake Resources, Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, Xining, 810008, China.
The desertification in the Qaidam Basin has significantly impacted the ecological environment and human livelihood. Amidst the backdrop of anomalous climate warming, predicting the dynamic changes and future trends of desertification within the basin is imperative. In this study, we employ a variety of spatio-temporal statistical analyses to examine the evolutionary trend and driving forces of desertification from 2000 to 2021, integrating vegetation coverage (FVC) indices with climatic factors.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Key Laboratory of Biohazard Monitoring and Green Prevention and Control for Artificial Grassland, Ministry of Agriculture and Rural Affairs, Grassland Research Institute, Chinese Academy of Agricultural Science, Hohhot 010019, China.
() is a highly invasive weed native to South America and distributed in 17 provinces (municipalities) of China. It has severely negative influences on ecosystems, agriculture, and husbandry. However, few studies have reported on the impact of human activity and climate change on the future distribution and centroid shift of .
View Article and Find Full Text PDFInsects
June 2023
Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou 510260, China.
Tomato leafminer (), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. The study and prediction of the current and future suitable habitats for tomato leafminer in China can provide an important reference for the monitoring, early warning, and prevention and control of the pest.
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