A changing climate has been posing significant impacts on vegetation growth, especially in the Yellow River Basin (YRB) where agriculture and ecosystems are extremely vulnerable. In this study, data for normalized difference index (NDVI) obtained from moderate-resolution imaging spectroradiometer (MODIS) sensors (precipitation temperature) derived national meteorological stations were employed to examine spatiotemporal differences growth its reaction changes YRB 2000–2019, using several...

Understanding the pixel-scale hydrology and spatiotemporal distribution of regional precipitation requires high precision high-resolution data. Satellite-based products have coarse spatial resolutions (~10 km–75 km), rendering them incapable translating variability induced by dynamic interactions between climatic forcing, ground cover, altitude variations. This study investigates performance a downscaled-calibration procedure to generate fine-scale (1 km × 1 km) gridded estimates from...

The source region of the Yellow River Basin (SRYRB) is not only sensitive to climate change and vulnerable ecological environment but also primary runoff generating (YRB). Its changes drought wetness profoundly impact water resources security, food production in middle downward reaches YRB. In context global warming, based on daily precipitation, maximum minimum temperature 12 national meteorological stations around within SRYRB during 1960–2015, this study obtained standardized...

This study assessed the drought susceptibility in Golestan Province, Northeastern Iran, using land use change modeling and climate projections from CMIP6 framework, under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5) for 2030–2050. The development of current (2022) future maps was based on agrometeorological sample points 14 environmental factors—such as use, precipitation, mean temperature, soil moisture, remote sensing-driven vegetation indices—used inputs into a...

Desertification presents major environmental challenges in Central Asia, driven by climatic and anthropogenic factors. The present study quantifies desertification risk through an integrated approach using Bayesian networks the ESAS model, offering a holistic perspective on dynamics. Four key variables—vegetation cover, precipitation, land-use intensity, soil quality—were incorporated into model to evaluate their influence desertification. A probabilistic was developed gauge with simulations...

The segmentation of cardiac anatomy represents a crucial stage in accurate diagnosis and subsequent treatment planning for patients with congenital heart disease (CHD). However, the current deep learning-based networks are ineffective when applied to 3D medical images CHD because limited availability training datasets inherent complexity exhibited by variability large vessel tissues. To address this challenge, we propose novel hybrid layer-based encoder-decoder framework image segmentation....

Against the backdrop of global warming, heatwaves in China have become more frequent, posing serious risks to public health and socio-economic stability. However, existing identification methods lack precision, driving mechanisms remain unclear. This study applies Excess Heat Factor (EHF) characterize across from 2013 2023, analyzing their spatiotemporal patterns exploring key drivers such as atmospheric circulation soil moisture. Key findings reveal significant regional differences: (1)...

Global warming and rapid socioeconomic development increased the risk of regional global disasters. Particularly in China, annual heatwaves (HWs) caused many fatalities substantial property damage, with an increasing trend. Therefore, it is great scientific value practical importance to analyze spatiotemporal changes HW China for sustainable disaster management. In this study, based on gridded maximum temperature product specific humidity dataset, evaluation algorithm, considering impact...

In the context of global warming, general increase in temperature has led to an heatwave events, as well a dramatic intensification economic losses and social risks. This study employs latest intensity–area–duration (IAD) framework that takes into account temporal continuity spatial dynamics extreme events identify regional extracts key parameters associated changes frequency, intensity, influence area, duration seven geographic subregions China 1979–2018 period. Heatwaves all durations...

Abstract In the context of global warming, frequency, intensity, and duration heatwave events have markedly increased, bearing profound implications for both natural ecosystems human societies. To effectively cope with this challenge, it is imperative to accurately identify comprehensively assess risks posed by heatwaves. This study undertakes a systematic approach robust methodology leveraging diverse array data sources—encompassing remote sensing, statistical analyses. The integrates risk...

Focusing on the Lower Bari Doab Canal (LBDC) command area, characterized by its heavy reliance agriculture, this study addresses critical issue of groundwater table fluctuations in response to diverse pumping scenarios. Herein, we comprehensively evaluated dynamic interplay between crop water requirements and within expansive canvas LBDC, which is facing shortages. Using Penman–Monteith equation, calculated annual average evapotranspiration for major crops—wheat, maize, cotton, rice,...

High accuracy, high spatial resolution precipitation data is important for understanding basin-scale hydrology and the spatiotemporal distributions of regional precipitation. The objective this study was to develop a reliable statistical downscaling algorithm produce quality, products from Tropical Rainfall Monitoring Mission (TRMM) 3B43 over Yarlung Zangbo River Basin using an optimal subset regression (OSR) model combined with multiple topographical factors, Normalized Difference...

A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of deep learning network model (DLNM). To explore influence label image on performance concrete crack segmentation in semantic dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening topological structure respectively, generate images construct sets datasets with different accuracy. Four models (SSNMs), U-Net, High-Resolution Net...

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding their impact on human health socio-economic realms. This study delves into anticipated implications elevated temperatures, specifically under SSP2-4.5 SSP5-8.5 pathways, population GDP exposure heatwaves in China. We also evaluated aggregated impacts climate, population, interactions future across leveraged...

Two new dibenzocyclooctadiene lignans angeloyl-(+)-gomisin K3 (1) and methylisogomisin O (2), together with six known ones, isogomisin O, angeloylisogomisin gomisin angeloygomisin benzoylgomisin epigomisin four 1,4-bis(phenyl)-2,3-dimethylbutane type lignans, pregomisin, meso-dihydroguaiaretic acid, isoanwulignan, sphenanlignan were isolated from the aerial parts of Schisandra propinqua var. propinqua. The structures 1 2 elucidated by spectroscopic methods including extensive 1D- 2D-NMR techniques.

Long-term hydro-climatic datasets and sophisticated change detection methods are essential for estimating trends at regional global scales. Here, we use the ensemble empirical mode decomposition method (EEMD) to investigate runoff oscillations different time scales its response climatic fluctuations in middle of Yarlung Zangbo River Basin (MYZRB) over period 1961–2009. In study region, results revealed that presented an overall nonlinear nonstationary decreasing-increasing alternative trend...