Yangtze Research Articles

Determining the evaporation and evolution of surface water in a large catchment using isotopes and multiple models

The evolution and formation mechanisms of chemical components in surface water can reflect changes in the geological background of a basin and the extent of human interference. The Yangtze River basin is the largest water source area in China, yet its main ion sources and formation mechanisms are not fully understood. This study uses a combination of hydrochemistry, stable isotopes (δ18O, δD), the Craig-Gordon model, and the APCS-MLR model to quantitatively assess the water source replenishment and evaporation intensity of surface water in the Yangtze River. The study reveals the primary ion sources and controlling factors of surface water in the Yangtze River. The results show that the hydrochemical type in the upstream is mainly HCO3−-Ca2+ and Na+-K+, while in the midstream and downstream it is primarily HCO3−-Ca2+ and SO42−-Ca2+. The evolution of hydrochemical types is mainly controlled by rock weathering and human inputs. The surface water sources in the Yangtze River are directly replenished by precipitation, with the evaporation ratio in the upstream (0.66) being higher than in the midstream (0.63) and downstream (0.47). The lc-excess in the upstream (−0.32 ‰) is lower than in the midstream (1.21 ‰) and downstream (−0.27 ‰), indicating more intense evaporation in the upstream. The hydrochemical composition of the Yangtze River surface water mainly comes from geological factors (80.5 %), industrial factors (11.1 %), agricultural factors (6.4 %), and unknown factors (2.0 %). This study enhances the understanding of the chemical composition, water source replenishment, ion sources, and evolution mechanisms of the Yangtze River surface water, providing a basis for maintaining water quality and sustainable development in the Yangtze River basin.

Unveiling mid-century conservation priorities: Co-occurrence of biodiversity, climate change exposure, and carbon storage in the Middle and Lower Yangtze River Basin, China

The global challenges of biodiversity loss and climate change necessitate the implementation of integrated conservation strategies. A forward-looking framework is necessary to reconcile climate change adaptation and mitigation efforts with biodiversity goals, supporting effective long-term planning and management of protected areas (PAs) network. This study develops a comprehensive approach to identify priority areas for biodiversity conservation until 2050, integrating assessments of species distributions, climate change exposure and carbon storage under distinct shared socioeconomic pathways. The Middle and Lower Yangtze River Basin (MLYRB) in China serves as a case study. Using an ensemble species distribution modeling (ESDM) method, we predicted the distributions of 435 threatened terrestrial vertebrate species and plants. We then mapped their richness in the MLYRB. Distance-based climate velocity analysis was performed to identify climate change coldspots and hotspots. The patch-generating land use simulation (PLUS) model and InVEST model were coupled to simulate carbon storage changes. Systematic conservation planning tool, Zonation, was used to prioritize species conservation hotspots. By examining the co-occurrence of these hotspots with climate change coldspots/hotspots and areas of high carbon storage, conservation priorities for the MLYRB were revealed. Our findings indicate that 18.27–24.94% of the MLYRB risks over 20% species richness declines by 2050 under various scenarios, while increases over 10% are projected for only 0.81–1.75% of the area. Co-occurrence analysis highlights significant associations, such as a 32.26% overlap between species conservation hotspots and climate change hotspots in SSP1-2.6. Particularly noteworthy is the substantial co-occurrence (57.93–59.50% across scenarios) between areas maximizing species conservation and carbon storage. The identified conservation priority areas, covering 41.95% of the MLYRB (441554km2), hold potential for long-term species conservation, climate resilience, and nature-based climate solutions by 2050. However, only 6.08% of these priorities currently benefit from protection. These results offer valuable guidance for region-specific landscape management and conservation policy aligned with international goals. The presented methodology provides a broader application, serving as a valuable resource for prioritizing conservation efforts in other regions integrating biodiversity, climate change adaptation, and mitigation goals.

Evolution mechanism of physical morphology of oxbow lake in the middle Yangtze River

Oxbow lakes, formed through river meandering cutoffs, are recognized as key components of river ecosystems, characterized by both fluvial and lacustrine features. The focus of previous research has been placed primarily on post-disconnection changes, leaving gaps in the understanding of their long-term morphological evolution. This gap is addressed through a comparative analysis of gate-controlled and naturally connected oxbow lakes over a 30-year period. In this study, Tian’ezhou Lake (gate-controlled) and Shangchewan Lake (naturally connected), located in the middle Yangtze River, are investigated. Key morphological parameters such as curvature, shoreline development index, and shrinkage rate were measured using Google Earth Engine (GEE). The influence of hydrological and meteorological factors on lake morphology was analyzed through Redundancy Analysis (RDA). Significant morphological changes were observed from 1990 to 2000. During this period, Tian’ezhou’s curvature was found to increase by 0.003/year, while Shangchewan’s curvature decreased by 0.011/year. After the construction of the Three Gorges Dam (TGD), a reduction in the rate of morphological evolution was detected, particularly between 2000 and 2010, when Tian’ezhou’s curvature decreased by 0.071/year and Shangchewan’s increased by 0.04/year. Post-2010, no significant changes in planar morphology were recorded in either lake. It was revealed by RDA that annual precipitation from 1990 to 1999 played a dominant role in influencing the morphological evolution of both lakes. From 2000 to 2020, water level fluctuations and hydrological connectivity emerged as the primary drivers. Gate control at Tian’ezhou Lake mitigated extreme water level fluctuations, contributing to a more stable environment and a slower rate of morphological evolution compared to Shangchewan. The findings underscore the importance of balanced water management strategies, integrating both natural and engineered hydrological interventions. Practical guidance is provided for ecological restoration and river management, with an emphasis on maintaining stable habitats and ensuring ecosystem resilience in response to hydrological changes.

Response of bottom dissolved oxygen reduction to net ecosystem production observed by a wave-driven profiler in the Changjiang River Plume

Coastal hypoxia, exacerbated by the combined influence of eutrophication and global warming, presents a significant environmental challenge. However, the lag correlation between organic matter (OM) export from the upper layers and bottom dissolved oxygen (DOBOT) reduction still lack clear elucidation. This study investigated the coupling between net ecosystem production (NEP, representing the maximum OM export) and DOBOT in the Changjiang River plume (CRP), using a wave-driven profiler system. The high-resolution profiles revealed rhythmic fluctuations in water column NEP, with sediment-water exchange (−74.6%) and NEP (−4.0%) dominating DOBOT reduction. Notably, surface NEP impacts DOBOT with a lag time of 25.65 h, indicating an OM sinking speed of 1.32 mm s−1. NEP at a depth of 3.4 m exerted the most significant influence on DOBOT, explaining a 12% reduction. These findings elucidate the response mechanism of DOBOT reduction to upper OM export and provide insights for hypoxia prediction in coastal and estuarine areas.

Exploration of the Path of Industrial Structure Adjustment Forced by the Rigid Constraint of Water Ecology in the Yangtze River Economic Belt

Considering the two-way influence of water ecology and industrial structure, decompose and quantify the water ecological rigidity constraints into water environment constraints and water resources constraints, construct the evaluation system based on the theoretical framework of PSR, and analyze the spatio-temporal evolution characteristics of water ecological rigidity constraints of the Yangtze River Economic Belt from 2010 to 2021 by using the entropy weighting method, the method of catastrophe progression, and the kernel density estimation. Then, putting forward the types of zoning in the Yangtze River Economic Zone through K-means algorithm analysis to explore the rigid constraints of water ecology to force the path of industrial structure adjustment. The results indicate that: (1) the water ecological rigidity constraints show a decreasing trend, and the decreasing amplitude is upstream > downstream > midstream; (2) the water ecological rigidity constraints generally show the characteristic of “gradually decreasing from east to west”, and the degree of regional differences first decreases, then increases, and then decreases again; (3) it can be divided into six types, and the zoning results gradually change from the concentration in the medium-high type and high-high type to the concentration in the low-low type and medium-low type, and the rigidity constraint of water ecology is obviously improved. In light of the findings, the Yangtze River Economic Belt is divided into five types of development regions and further discusses that the industrial restructuring in different zones has different influencing effects on the regional socio-economic development, which provides suggestions for differentiated paths of water ecological protection and industrial restructuring.

Climate-related risk to maize crops in China from Fall Armyworm, Spodoptera frugiperda

AbstractThe Fall Armyworm, Spodoptera frugiperda, invaded China late in 2018 and was responsible for substantial crop losses, especially to maize. This work focuses on the suitability of climate across China for Fall Armyworm survival and spread. It uses climate metrics derived with guidance from experts to enable assessment of the risks posed by Fall Armyworm on maize production in different regions of China. The locations and time of year when temperature conditions are within a viable range for Fall Armyworm survival (minimum temperature higher than 9.7$$^\circ$$ ∘ C and maximum temperature lower than 39.2$$^\circ$$ ∘ C) are used to estimate the spatial distribution of winter breeding and overwintering zones, which helps understand the regions and timing of Fall Armyworm migration risk into northern maize production regions. In addition, meridional wind conditions across the Yangtze River basin area are assessed, and a metric of migration potential from the winter breeding and overwintering regions in the south towards northern regions with maize production is established. Results show that temperature during the winter months currently limits Fall Armyworm winter breeding populations to the very southern regions of China (and bordering countries to the south). However, due to the consistent timing and direction of the East Asian Summer Monsoon winds, the Fall Armyworm could easily be directed northwards to the Yangtze River basin during summer months with a peak in July. For this reason, pest management actions against the Fall Armyworm on summer maize should be taken.

Light attenuation parameterization in a highly turbid mega estuary and its impact on the coastal planktonic ecosystem

Light is essential for phytoplankton photosynthesis and many other biogeochemical processes in the aquatic system. However, light regimes vary greatly in the estuaries and coasts due to the optical complexity of the Case-2 waters. In this study, observed vertical profiles of photosynthetically active radiation (PAR; 400-700 nm) in a highly turbid mega estuary, the Changjiang (Yangtze River) Estuary, are used to quantify the effects of sedimentary and biogeochemical components on PAR attenuation in the water column and associated ecological impacts. The in-situ data suggest suspended sediment plays the most crucial role in light diffuse attenuation coefficient (Kd) distribution, followed by salinity (i.e., an index for colored dissolved organic matter) and phytoplankton chlorophyll-a. A new parameterization of Kd, based on suspended sediment, chlorophyll-a concentration, and salinity, is fitted using multiple linear regression. The previous and new Kd parameterizations are further applied to a coupled hydrodynamics-sediment-ecosystem model to simulate spring phytoplankton blooms. Comparative model runs reveal that the new Kd parameterization resulted in a better representation of the spring bloom patterns in magnitude, horizontal distribution, and vertical thickness of the high chlorophyll-a band offshore the turbidity maximum zone during the spring bloom. In summary, accurate representations of underwater light fields in the optically complex Case-2 water are critical in understanding biophysical processes that control planktonic ecosystem dynamics in the estuaries and coastal seas.

Shear Instability and Turbulent Mixing by Kuroshio Intrusion Into the Changjiang River Plume

AbstractShear instability is a dominant mechanism for mixing in the stratified oceans and coastal seas. For the first time, we present fine‐scale, direct measurements of shear instabilities in the bottom front generated by the Kuroshio intrusion into the Changjiang (Yangtze) river plume. Shear instabilities were identified using a shipboard echo‐sounder and the resulting turbulent mixing was quantified using a turbulence microstructure profiler. The shear instabilities generate vigorous turbulent mixing with dissipation rate and vertical diffusivity up to O (10−4 m2 s−3) and O (10−1 m2 s−1), respectively, comparable to values associated with shear instabilities observed in river plumes and western boundary currents but several orders of magnitude larger than typical values in the open ocean. The enhanced turbulence may contribute significantly to mixing between the Kuroshio water and coastal water and thereby alter the coastal biogeochemistry cycles.

Assessment of eco-environment quality using multi-source remote sensing data

ABSTRACT Accurate analysis of regional eco-environment quality (EEQ) changes is essential for urban sustainability. Most of the widely used EEQ indicators ignore the impact of air pollution caused by urbanization and economic growth. This study proposed a remote sensing-based approach using a time-series comprehensive evaluation index (CEI), which was developed by PM2.5 concentration, Land surface temperature (LST), and vegetation coverage (VC) to assess the EEQ in the Demonstration Zone of Green and Integrated Ecological Development of The Yangtze River Delta (demonstration zone) from 2000 to 2020. The EEQ changes of all districts and townships were classified into five levels. The results suggested that from 2000 to 2020, the CEI was significantly decreased (p < 0.01) in the demonstration zone, indicating an overall improvement of the EEQ. Differences in the mean annual CEI values and EEQ changes were found among districts and to wnships. Higher CEI values, which indicated a lower degree of EEQ were found in areas where build-up land comprised a higher percentage of the total area. Townships with degraded EEQ change exhibited a higher percentage of increase in build-up land (32.3%) than others (8.67% to 16.68%) from 2000 to 2020. Moreover, the change of annual CEI at the administrative district scale was found to be strongly correlated with the proportion of the secondary sector in GDP in three districts. The results of our study indicated the importance of land use optimization, air pollution reduction, and vegetation coverage enhancement to improve the regional EEQ in the urban wetland ecosystems with rapid urbanization.

Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods

AbstractFloods are widespread and dangerous natural hazards worldwide. It is essential to grasp the causes of floods to mitigate their severe effects on people and society. The key drivers of flood susceptibility in rapidly urbanizing areas can vary depending on the specific context and require further investigation. This research developed an index system comprising 10 indicators associated with factors and environments that lead to disasters, and used machine learning methods to assess flood susceptibility. The core urban area of the Yangtze River Delta served as a case study. Four scenarios depicting separate and combined effects of climate change and human activity were evaluated using data from various periods, to measure the spatial variability in flood susceptibility. The findings demonstrate that the extreme gradient boosting model outperformed the decision tree, support vector machine, and stacked models in evaluating flood susceptibility. Both climate change and human activity were found to act as catalysts for flooding in the region. Areas with increasing susceptibility were mainly distributed to the northwest and southeast of Taihu Lake. Areas with increased flood susceptibility caused by climate change were significantly larger than those caused by human activity, indicating that climate change was the dominant factor influencing flood susceptibility in the region. By comparing the relationship between the indicators and flood susceptibility, the rising intensity and frequency of extreme precipitation as well as an increase in impervious surface areas were identified as important reasons of heightened flood susceptibility in the Yangtze River Delta region. This study emphasized the significance of formulating adaptive strategies to enhance flood control capabilities to cope with the changing environment.

Optimization of sowing dates for enhanced rice yield: insights from field experiments in the middle and lower reaches of the Yangtze River, China

An efficacious strategy to adapt to climate change involves optimizing the planting season, a technique that has been extensively utilized to enhance the use of solar radiation and temperature resources in rice cultivation. Field experiments were executed in the middle and lower reaches of the Yangtze River, China, employing three distinct rice cultivars and seven disparate sowing periods spanning 2019 to 2021. The objective of assessing the impact of sowing date on apparent radiation use efficiency (RUEA), accumulated temperature use efficiencies (TUE), and overall rice yield. Subsequent to the delay of sowing dates, the duration of the comprehensive growth period initially exhibited a declining trajectory before subsequently escalating, with the reduction predominantly ascribed to a decrease in the number of days preceding heading. Furthermore, there was a tendency for both the mean daily and effective cumulative solar radiation to decline over the course of the growing period. The yield of the three rice varieties demonstrated an initial surge, which was then followed by a subsequent decline in reaction to the delay of sowing dates. A correlation analysis disclosed that solar radiation and effective cumulative temperature (EAT) were the predominant elements impacting grain yield. The outcomes of the path analysis indicate that EAT exerts the most substantial influence on yield, succeeded by cumulative total solar radiation (TSR), while photothermal quotient (PTQ) demonstrates the least impact on yield. There was a significant positive correlation between EAT and cumulative TSR with spikelets per panicle (0.237** and 0.218**), grain filling (0.753** and 0.576**), and grain weight (0.339** and 0.359**), respectively. The findings of this study indicate that an increase in yield is facilitated when the EAT after heading exceeds 594.9 ℃, the EAT surpasses 2016.7 ℃, the cumulative TSR before heading is above 1548.7 MJ m− 2, the cumulative TSR after heading is over 603.0 MJ m− 2, and the cumulative total radiation throughout the entire growth period is more than 2151.8 MJ m− 2. Furthermore, the most optimal sowing date, as identified by this study, is June 6. This study provides key insights into boosting rice productivity in the middle and lower reaches of the Yangtze River, China by analyzing the impact of temperature and solar radiation on yield and identifying optimal growth conditions.Clinical trial number Not applicable.

Spatial-Temporal Evolution Analysis of Regional MWPIIs and the Development Path under the Integrated Strategy in the Yangtze River Delta, China

Spatial-Temporal Evolution Analysis of Regional MWPIIs and the Development Path under the Integrated Strategy in the Yangtze River Delta, China

Investigation of the impact of diverse climate conditions on the cultivation suitability of Cinnamomum cassia using the MaxEnt model, HPLC and chemometric methods in China

Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China, with an area of 706,129.08 km2. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River, particularly in the 2090s SSP585 scenario, the total area of newly extended suitable habitat reaches 312,963.53 km2. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde (0.85%) is significantly higher in the high suitability habitat compared to the medium-low suitability habitat (0.30%). Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats.

The impact of green behavior on spatial heterogeneity of city green development-the case of Yangtze River Delta city cluster

The impact of green behavior on spatial heterogeneity of city green development-the case of Yangtze River Delta city cluster

A Satellite-Based Indicator for Diagnosing Particulate Nitrate Sensitivity to Precursor Emissions: Application to East Asia, Europe, and North America.

Particulate nitrate is a major component of fine particulate matter (PM2.5) and a key target for improving air quality. Its formation is varyingly sensitive to emissions of nitrogen oxides (NOx ≡ NO + NO2), ammonia (NH3), and volatile organic compounds (VOCs). Diagnosing the dominant sensitivity is critical for effective pollution control. Here, we show that satellite observations of the NO2 column and the NH3/NO2 column ratio can effectively diagnose the dominant sensitivity regimes in polluted regions of East Asia, Europe, and North America, in different seasons, though with reduced performance in the summer. We demarcate the different sensitivity regimes using the GEOS-Chem chemical transport model and apply the method to satellite observations from the OMI (NO2) and IASI (NH3) in 2017. We find that the dominant sensitivity regimes vary across regions and remain largely consistent across seasons. Sensitivity to NH3 emissions dominates in the northern North China Plain (NCP), the Yangtze River Delta, South Korea, most of Europe, Los Angeles, and the eastern United States. Sensitivity to NOx emissions dominates in central China, the Po Valley in Italy, the central United States, and the Central Valley in California. Sensitivity to VOCs emissions dominates only in the southern NCP in the winter. These results agree well with those of previous local studies. Our satellite-based indicator provides a simple tool for air quality managers to choose emission control strategies for decreasing PM2.5 nitrate pollution.

Enhancing streamflow prediction in the Wujiang River basin: a two-stage decomposition approach with deep learning integration

ABSTRACT Global climate change and human activities have profoundly impacted the geological and hydrological processes in watersheds, increasing the challenges in streamflow prediction. In this study, we propose a streamflow prediction model based on deep learning and dual-mode decomposition specifically tailored for the Wujiang River basin, a significant tributary on the southern bank of the upper Yangtze River. This model effectively addresses the prediction error issue caused by high-frequency components through dual-mode decomposition of time-series data. The results demonstrate that employing the coupled complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)–variational mode decomposition (VMD)–temporal convolutional network (TCN)–long short-term memory network (LSTM) model reduces prediction errors by at least 35% compared to single decomposition models. Furthermore, compared to individual TCN or LSTM models, the TCN–LSTM coupled model exhibits greater stability and higher prediction accuracy during training, with reductions in mean absolute error and root mean square error by 43.13 and 24.57%, respectively. This model holds promising prospects for application and can provide crucial insights for water resource management.

The evolution of spatial and temporal distribution of rainfall erosivity in Henan Province, central China

With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China.

Understanding floods and droughts in the Yangtze River Basin: a historical perspective (1470–2022)

ABSTRACT The Yangtze River basin plays a crucial role in China’s economy, and the impacts of drought and flood in the basin are becoming more uncertain due to climate change. Thus, a study was conducted to analyse the flood–drought rating sequence for the Yangtze River basin in 1470–2022. The frequency of flood and drought occurrences during the flood season followed a normal distribution. Extreme drought and flood accounted for 2–4% of occurrences. Partial and extreme floods increased notably in the 19th and 20th centuries, while droughts became more frequent after the 20th century. Furthermore, the Three Gorges Reservoir area’s storage capacity did not significantly impact flood season precipitation in the upper reaches of the Yangtze River and the reservoir area. This comprehensive study serves to uncover evolutionary patterns and trends of drought and flood, providing valuable insights for effectively managing water resources in the basin.

Water-surface photovoltaic systems have affected water physical and chemical properties and biodiversity

The implementation of water-surface photovoltaic systems as a source of renewable power has expanded rapidly worldwide in recent decades. Water-surface photovoltaic avoids negative impacts on terrestrial ecosystems, while the impacts on aquatic physical and chemical properties and biodiversity are unclear. To understand the ecological and environmental impacts of water-surface photovoltaic systems, here we conducted a field survey on water physical and chemical properties, plankton and bird communities of 26 water-surface photovoltaic systems in the Yangtze River basin in China during the winter and summer of 2022. We found that water-surface photovoltaic systems decreased water temperature, dissolved oxygen saturation and uncovered area of the water surface, which caused a reduction in plankton species and individual density, altering the community composition. Water-surface photovoltaic systems also caused an overall decrease in bird diversity and changed bird community compositions. These findings suggested that water-surface photovoltaic systems have impacts on the water environment and ecology. Since water-surface photovoltaic systems will continue to expand in the future, our results emphasize that rational planning is critical for the sustainable development of water-surface photovoltaic systems and the protection of the aquatic environment and biodiversity.

Evaluating functional ability in older adults’ object retrieval behavior from kitchen furniture using OpenPose and REBA

The purpose of this study is to evaluate, through analysis, the ability of older persons to retrieve items from kitchen cabinets. To achieve this goal, data were collected from 128 valid questionnaires and supplemented with field research and user interviews. The study revealed that the elderly’s behavior in retrieving items from kitchen spaces is characterized by both high frequency and difficulty. For this experiment, a total of 42 participants, comprising 21 males and 21 females from the self-care elderly population in the Yangtze River Delta region, were recruited. Two different experimental settings were arranged: one with kitchen utensils arranged in a straight line and another with a purpose-made chest of drawers with varying heights. Video recordings using the Logitech C930C were utilized to capture the gestures and behaviors of the elderly while retrieving objects from the kitchen cupboards (cabinets). By employing a combination of the OpenPose model and the Rapid Entire Body Assessment (REBA) method, which involves calculating human posture angles, REBA scores, and determining the risk level of Work-Related Musculoskeletal Disorders (WMSDs), a risk assessment framework for manual operations associated with WMSDs was developed. Using the angle data acquired from the user operation experiment as parameters, a gradient model of the elderly user’s operational capability was established. The findings indicated a significant impact of neck, trunk, and knee movements on the subjects (P < 0.001). The participants were able to distinguish between different levels of exertion, categorizing movements as ‘easy’, ‘moderate,’ or ‘strenuous.’ These results form the basis for a comfort gradient model for leaning over and retrieving items. Given the prevalent conditions of bone and joint degeneration and osteoporosis among the elderly population, it is evident that they face challenges when accessing items in the kitchen. Therefore, investigating the elderly’s execution abilities during the retrieval process becomes crucial. Understanding how different cabinet heights impact the joint angles of the elderly can be instrumental in optimizing cabinet designs for elderly users, thereby reducing their physical exertion in the kitchen and enhancing their comfort levels. This research holds significant value in improving the quality of life for the elderly population at home and fostering the advancement of elderly-friendly design principles.