Study regionThe Wangmaogou watershed (5.97 km2), a representative catchment in the hilly-gully region of China's Loess Plateau, middle Yellow River Basin—an area characterized by severe historical erosion and decades of intensive soil and water conservation.Study focusThis study quantifies the evolving sediment reduction benefits of check dams under progressive land use change (LUC) using a decoupling-based quantification framework. The WaTEM/SEDEM model and multi-scenario simulations were employed to isolate check dam benefits conditional on the LUC-determined sediment supply regime.New hydrological insights for the regionBetween 1970 and 2017, LUC reduced total watershed erosion by >60%, fundamentally reconfiguring the sediment supply regime. Under this evolving background, decoupling analysis reveals a supply‑driven decline in check dam benefits—from 90.9% under the 1970 high‑supply regime to 26% after 2012—while the sediment delivery ratio remained relatively stable, confirming that this decline reflects a regime shift rather than engineering failure. A double‑logarithmic nested model was developed to characterize the response of check dam benefits to declining erosion modulus. Extreme event analysis (2017 "7·26" rainstorm) further demonstrates that check dams retain irreplaceable "safety net" value, intercepting 1.78 times mean annual retention under transient high‑supply conditions. These findings indicate that on a greening Loess Plateau, check dams have evolved from primary sediment control structures to regime‑dependent safety nets, supporting their strategic functional transformation toward multi‑purpose water resource hubs.

Under global climate change, sand and dust storms (SDS) in Northern China have exhibited new spatiotemporal evolution characteristics. To investigate SDS driving mechanisms, this study integrated multi-source remote sensing and reanalysis data (2005-2024), employing SHapley Additive exPlanations (SHAP), receiver operating characteristic curve analysis method, and the extreme gradient boosting machine learning model. The results indicated that SDS frequency increased significantly after 2015, with a 47.6% rise in annual events (from 4 to 6 events/year), while high-intensity events declined from 23.8% to 14.5%, revealing increasing frequency but decreasing intensity. SDS occurrence is primarily triggered by the synergy between strong wind hours and the concurrent VHI. The lag period of eco-hydrological factors such as vegetation, temperature, and moisture on SDS was approximate 5 months. SHAP analysis revealed VHI is dominant driver in hyper-arid and arid transition zones, while soil moisture and evapotranspiration became the primary controls in semi-arid regions. Critical thresholds with narrow 95% confidence intervals for dust occurrence were identified, including VHI below 0.35, strong wind hours exceeding 12.7 h, NDVI below 0.10, and evapotranspiration below 10.8 mm. When VHI exceeds 0.35, the relative SDS risk is reduced by 88.4%, underscoring its potent protective effect. The dynamic thresholds and high-precision prediction model achieved robust performance with an out-of-sample PR-AUC of 0.843, together with strong predictive accuracy as evidenced by a test AUC of 0.935 and annual-scale R2 greater than 0.7, providing a scientific basis for accurate dust forecasting and risk management.

Over the past 30 years, vegetation restoration on the Loess Plateau, China, has yielded remarkable results. However, the impact of different vegetation restoration stages on slope erosion control and sediment source-sink dynamics during succession remains unclear. Consequently, in-situ scouring experiments were conducted in Loess hilly and gully Ito assess vegetation restoration stages on runoff and sediment and to understand erosion-deposition transitions. Treatments comprised three inflow rates (4, 8, and 16 L/min), four vegetation succession stages (1, 11, 15, and 25 years), and three consecutive scouring periods (0-30, 31-60, and 61-90 min), with 3D laser scanning used for topographic analysis. Results showed that the capacity of vegetation to slow runoff and reduce erosion did not increase linearly with succession duration. The 11-and 25-year succession stages achieved the greatest reductions in runoff and sediment. At year 25, heavily deposited areas (<-10 mm) increased by 480.17 % in size and 33.13 % in depth compared to early succession. The primary erosion evolution path was mild deposition > mild erosion > moderate erosion, with high scouring flow rates accelerating this dynamic process. With natural succession, sediment source-sink transitions on slopes gradually stabilized, and non-converted areas during erosion were 71.62 % (year 1), 61.18 % (year 11), 68.26 % (year 15), and 53.00 % (year 25). Over time, the slopes transitioned from an erosion-dominated state to more stable conditions. This study offers a more systematic evaluation of the dynamic outcomes of the Grain for Green Project, supporting soil conservation and ecological restoration of the Loess Plateau.

The vegetation ecosystem in the Yellow River Basin is highly sensitive to climate change.Analyzing the driving mechanism of climate on vegetation dynamics plays an important role in the ecological management of the Yellow River Basin.Based on the data of the normalized difference vegetation index,total primary productivity,leaf area index,enhanced vegetation index,chlorophyll fluorescence,and vegetation coverage from 2001 to 2020,combined with the IGBP vegetation classification system,the differences and trends of vegetation characteristics of different vegetation types were quantified.By constructing a multi-scale geographically weighted regression model and Geodetector,the spatial heterogeneity and interaction mechanism of climatic factors and soil moisture on vegetation coverage were revealed.The results showed that:① From 2001 to 2020,the vegetation in the central and eastern parts of the Yellow River Basin was significantly improved,whereas that in the northwest showed a trend of degradation,while the interannual variability of the middle reaches of the Loess Plateau was the largest.② The vegetation characteristic index value of forest type was significantly higher than that of other types,and the vegetation coverage was the most sensitive to the differentiation of vegetation types.③ In most areas of the Yellow River Basin,precipitation promoted vegetation growth,temperature inhibited vegetation growth in the north and middle,and saturated vapor pressure difference significantly promoted vegetation coverage in the southeast and northwest.In the humid areas of the south and southeast,the saturated vapor pressure difference showed a promoting effect,and the soil moisture showed an inhibitory effect.In the whole basin,precipitation and temperature,saturated vapor pressure difference,and soil moisture had a strong interaction,which promoted vegetation coverage.The research results provide theoretical support for the ecological zoning management of the Yellow River Basin.

Baseflow represents a pivotal hydrological component that sustains hydrological resilience and ecosystem integrity in arid and semi-arid regions, yet its natural dynamics are increasingly perturbed by the combined effects of climate change and anthropogenic ecological construction. Baseflow dynamics in 12 typical watersheds of China's Loess Plateau over 1960-2020 are systematically investigated, integrating multi-method baseflow separation, a time-varying Budyko model for baseflow attribution, and quantile regression analysis to disentangle the relative impacts of climatic variability and ecological construction on baseflow regimes. Results reveal significant spatiotemporal heterogeneity: 10 watersheds exhibit a marked decline in annual baseflow, while only the Yiluo River Basin shows a significant increase, with the Arnold_Allen, Chapman_Maxwell, and Eckhardt methods identified as optimal for robust baseflow separation (p < 0.05). Attribution analysis demonstrates divergent dominant drivers of baseflow reduction-precipitation in 5 watersheds, attribution model parameter alpha in 3 watersheds, and attribution model parameter w in 4 watersheds-with ecological construction's contribution rising significantly in 9 basins via mediating effect of alpha and w (p < 0.05). Quantile regression further elucidates a critical vegetation threshold effect on daily baseflow dynamics: baseflow increases with rising NDVI values below a watershed-specific threshold ranging from 0.47 to 0.70, but declines precipitously once this threshold is exceeded. In 58.3% of the studied watersheds, vegetation exerts a suppressive effect on baseflow across the majority of flow quantiles. These findings highlight the dualistic role of ecological construction in regulating baseflow in global arid and semi-arid regions, and provide a rigorous scientific foundation for balancing ecological conservation objectives with the sustainable management of water resources in these vulnerable landscapes.

ABSTRACT Aquatic vegetated habitats are disappearing rapidly, and restoration projects are crucial for maintaining their ecological functions. The success of these projects hinges on the ability to retain sediment, necessitating a comprehensive understanding of sediment transport in vegetated areas. Therefore, this study builds a model based on the flow turbulent kinetic energy near the riverbed to predict bedload transport. The turbulent kinetic energy in the model comprises turbulent terms generated by the riverbed and vegetation, which can be further divided into a shear turbulent term induced by the velocity difference and a stem turbulent term induced by the vegetation stem. The experimental data confirmed that turbulent kinetic energy can predict the bedload transport rate more effectively than bed shear stress. The average relative error of the predicted bedload transport based on bed shear stress was within 632%, and the average relative error of the predicted value based on turbulent kinetic energy was within 97%. When the dimensionless submerged vegetation density was less than a threshold, the bedload transport rate increased with increasing vegetation density. These findings yield crucial insights into the interaction mechanisms among vegetation, flow, and sediment and provide a promising direction for predicting sediment transport in the future.

The Jialing River Basin is a major sand-producing area in the upper reaches of the Yangtze River and requires thorough management and ecological restoration efforts. Ecosystem services are important indicators for assessing the effectiveness of ecological restoration work. Taking the Jialing River Basin as the research object, this paper elucidates the spatial and temporal evolution characteristics of various ecosystem services, identifies the main factors affecting these functions, and predicts the spatial distribution characteristics of the basin’s ecosystem service functions under future scenario models. The main conclusions drawn are as follows: From 2000 to 2020, there is a gradual increasing trend in the functions of soil conservation, wind and sand control, water conservation, and habitat quality. The main factors affecting the functions of soil conservation and wind and sand control are slope and landform type, while the main factor affecting the functions of water conservation and habitat quality is land use type. Surface elements mainly affect soil conservation and habitat quality, human activities have the greatest impact on water conservation, and climatic factors mainly affect wind and sand protection. In the future scenario, by 2050, the water source conservation function and soil conservation capacity of the Jialing River Basin will gradually increase, but the habitat quality will continue to deteriorate, and there will be no marked change in the wind and sand control capacity. The study provides a scientific basis for the formulation of corresponding environmental policies and resource management strategies, and helps to promote the sustainable development of regional ecosystem services.

ABSTRACTConducting a comprehensive investigation into the interplay between runoff and sediment discharge in a dynamic environment is essential to uphold aquatic ecosystems and promote sustainable regional development of high quality. Initiated since the 1950s, extensive soil and water conservation projects in the middle reaches of the Loess Plateau, China, have resulted in a substantial reduction in runoff and sediment discharge. This reduction has prompted alterations in the dynamics between runoff and sediment discharge, impacting the frequency of their interactions. Analyzing measured data from the Kuye River Basin (Kuye Basin) in the middle reaches of the Yellow River for the period 1956 to 2019, this study investigates the evolving patterns of runoff and sediment discharge. Utilizing the Copula function, we analyzed the joint probability distribution characteristics of runoff and sediment discharge, aiming to identify the factors influencing their evolution patterns. The findings revealed a substantial downward trend (p < 0.01) in both monthly and annual scales for runoff and sediment discharge in the Kuye Basin. Additionally, two abrupt changes were observed in 1979 and 1996, demonstrating multi‐timescale periodicity. Based on the mutation points, the study period was divided into three phases: P1 (1956–1978), P2 (1979–1995), and P3 (1996–2019). The optimal model for the joint distribution of runoff and sediment discharge is the Clayton Copula in both P1 and P2, while in P3, the optimal model shifts to the Gumbel Copula. Over the transition from P1 to P3, the runoff and sediment discharge in each recurrence period experienced a significant decrease, and the asynchronous probability of abundance encounters for runoff and sediment discharge at different design frequencies increased. Human activities, such as soil and water conservation measures, have influenced the variations in runoff and sediment discharge at different stages. With the passage of time, the effectiveness of current measures has approached saturation, resulting in cumulative values of nearly 28 × 109 m3 for runoff and 4.4 × 109 t for sediment discharge, respectively. These research findings lay the groundwork for a deeper comprehension of the evolving dynamics between runoff and sediment discharge in the basin and contribute to the formulation of effective policies for soil erosion control.

Remote sensed precipitation products (RSPPs) can provide reliable data for drought monitoring. However, using numerous RSPPs can introduce significant uncertainties due to their discrepancies. This study focuses on the Huang-Huai-Hai Plain in China, a key agricultural region sensitive to meteorological drought. Using grid precipitation interpolated by observed data from the China Meteorological Administration (CMA), we evaluated the performance of three long-term series (> 30 years) RSPPs (PERSIANN-CDR, CHIRPS, and MSWEP) in capturing the spatial and temporal characteristics of meteorological drought events. We found that (1) three RSPPs can generally reproduce the pattern of annual precipitation, but they are difficult to accurately capture the trend of CMA. (2) MSWEP performs better than the other two products in identifying drought variation and area proportions at various spatiotemporal scales, with the one-month scale (SPI1) being the optimal timescale for RSPPs to identify meteorological drought. (3) All RSPPs can reproduce the pattern of drought categories and characteristics, with their performance order of MSWEP > CHIRPS > PERSIANN-CDR. This indicates considerable room for improvement in depicting the drought characteristics. Our results can guide the selection of the RSPPs for meteorological drought monitoring and disaster avoidance.

The upper and middle of the Yellow River Basin (UMYRB) are globally recognized as an ecologically fragile region due to severe soil erosion, arid climate, and frequent extreme weather events. Over the past two decades, large-scale ecological restoration measures have led to pronounced changes in ecosystem services (ES). However, there is a lack of systematic analysis addressing the spatiotemporal dynamics and driving mechanisms of multiple ecosystem services under the combined effects of ecological restoration projects and extreme climatic events. To fill this gap, this study employed the InVEST model, geographically weighted regression, and partial least squares structural equation modeling to comprehensively investigate the evolution of various ecosystem services in this basin and their key influencing factors. The results indicate that (1) in regions where vegetation recovery was particularly successful, water yield (WY) increased from 24 mm to 88 mm and soil conservation (SC) capacity was substantially enhanced; carbon storage (CS) rose by approximately 12 % in the humid southern area but remained stable in the arid northern region. (2) Precipitation, slope, vegetation cover, and land-use changes collectively shaped the spatial patterns of ecosystem services, with precipitation exhibiting the strongest explanatory power for WY, and slope together with vegetation recovery exerting notable impacts on SC. (3) In areas of vegetation recovery, multiple ecosystem services showed stronger synergy, whereas habitat quality (HQ) and CS exhibited significant trade-offs in regions experiencing agricultural expansion. (4) Extreme precipitation events markedly amplified the variability of WY, SC, and CS, accounting for 61.5 %, 57.8 %, and 27.4 % of their respective variances, while exerting relatively limited effects on HQ. These findings elucidate the mechanisms by which ecological restoration projects and extreme precipitation events jointly influence multiple ecosystem services, and provide scientific guidance for targeted ecological management and service optimization in UMYRB.

In arid and semi-arid regions, where water scarcity and fragile ecosystems are critical challenges, the sustainable use of wind and solar energy resources is vital for regional water management and ecological resilience. This study, focusing on the Yellow River's Crooked Bend Area, analyzed the spatiotemporal evolution of wind and solar resources (1965-2019) using radiation and wind energy density models. The wind-solar complementarity rate was quantified across multiple scales, and its impact on watershed water yield availability in check dam-controlled areas was assessed constructing conditional probability and linear regression models. Key drivers of wind-solar complementarity rate and factors influencing water yield dynamic risks were identified through geographic detector analysis. The results reveals that the Yellow River's Crooked Bend Area exhibits significant spatiotemporal variation in renewable resources, with mean annual solar radiation of 66,937.65 Wm(-2) and wind energy density of 6,191.59 Wm(-2) (p < 0.05). Wind energy is consistently lower than solar radiation across multiple time scales, and the area experiencing a significant decline in wind energy far exceeds that of solar radiation (p < 0.05). The wind-solar complementarity rate, ranging from 0.08 to 0.24 with a mean of 0.17, shows a declining trend, indicating long-term impacts of climate change. Water yield demonstrates nonlinear sensitivity to wind-solar complementarity rate with a threshold, particularly in low-yield regions such as Yan'an area, Ordos eastern area, and Yulin area. Geographic detector analysis identifies cloud cover (q = 0.71), NDVI (q = 0.59), temperature difference (q = 0.44), relative landscape deviation (q = 0.41), and vapor pressure (q = 0.40) as primary factors driving spatial variability of the wind-solar complementarity rate across the entire region on the mean annual scale, while sliding window analysis highlights the roles of precipitation, potential evapotranspiration, and temperature difference in influencing risk between water yield and wind-solar complementarity rate. Conditional return period analysis shows that possibility of higher water yields is decreasing, while increasing the complementarity reduces return periods and enhances resilience. These findings provide a risk assessment framework for integrating wind and solar energy with water resources, offering scientific support for ecological conservation and sustainable development in the Yellow River bend region.

Globally, severe soil erosion in river basins presents critical challenges for watershed management and environmental sustainability. Traditional sediment load models often fail to accurately capture sediment dynamics in watersheds due to limited understanding of the energy mechanisms driving soil erosion and their relationship with human activities and other influencing factors. To address this gap, a watershed sediment load model based on runoff erosion power was developed and improved, and then validated using long-term daily observation data from 9 typical watersheds in the Yellow and Yangtze River Basins. Results demonstrate that the runoff erosion power is a superior predictor of sediment load, with a R-2 of regression equation between runoff erosion power and sediment load being higher than rainfall erosivity and runoff in 78 % of the typical watersheds at both annual and monthly scales. At both multi-year and annual scales, the binary mixed distribution can effectively fit the nonlinear distribution characteristics of sediment load across different flow grades, with both theoretical and empirical cumulative probabilities achieving an R-2 of over 0.90. A significant increase in reservoirs and vegetation is likely a major factor contributing to changes in sediment load within the catchment (p < 0.05), showing a highly negative correlation with sediment load in all typical watersheds on an annual scale. The inclusion of engineering and vegetation indexes further improves model accuracy, achieving NSE values between the 50th percentile of the simulated sediment loads from the improved model and observed values above 0.76 on both annual and monthly scales across all watersheds, with the maximum value reaching 0.97. Notably, the overall accuracy on the monthly scale is higher than on the annual scale. This study offers quantitative evidence supporting the integration of runoff erosion energy, engineering, and ecological processes in sediment modeling, thereby advancing the scientific understanding of sediment dynamics and promoting sustainable watershed management under changing environmental conditions.

Under the dual pressures of global climate change and anthropogenic activities, identifying key thresholds for ecosystem health is essential for biodiversity conservation, climate change mitigation, and regional sustainable development. Utilizing the vitality-organization-resilience-service model, this study quantifies the spatiotemporal evolution of ecosystem health in the upper and middle reaches of the Yellow River from 2000 to 2020. Extreme precipitation indices, integrated with partial least squares structural equation modeling, were employed to elucidate the mechanisms by which extreme rainfall impacts ecosystem health. The results indicate that:(1) Both ecosystem vitality and ecosystem organization increased, reflecting enhanced ecosystem stability and connectivity, with significant vegetation recovery in forest and grassland regions. (2) Ecosystem health significantly improved in 69.48 % of the regions. The improvement of ecosystem health in the midstream is primarily attributed to the extensive restoration of forest and grassland. Ecological restoration did not substantially change the ecological vulnerability of the northern desert areas, and restoration should be prioritized in the future. (3) As a primary driver of ecosystem health, moderate increases in vegetation coverage can enhance ecosystem health; the threshold values for nighttime light intensity, relative humidity, precipitation, and land use intensity are 0.6, 68.61 %, 789.92 mm, and 2.34, respectively. (4) Extreme precipitation indirectly affects ecosystem health by influencing vegetation, with a combined contribution rate of 26.10 %. The long-term impact of single extreme precipitation events is limited, and cumulative precipitation events have a greater effect on ecosystem stability. This study determines the threshold of environmental and anthropogenic factors on ecosystem health and clarifies the indirect impact of extreme precipitation on ecosystem health through vegetation, thereby providing a scientific basis for the sustainable management of large-scale vulnerable river systems.

As climate change accelerates, understanding the mechanisms of ecosystem phenology in vulnerable regions is crucial for terrestrial environments. This research systematically used remote sensing data to study the dynamic changes in vegetation phenology in the upper and middle Yellow River Basin (UMYRB), examined the effects of environmental shifts on vegetation phenology, and quantified the contributions of different driving factors. The key findings are as follows: (1) As elevation and latitude increase, the start of the growing season (SOGS) is generally delayed, particularly in the northwest and northeast, where it typically occurs between days 140 and 180. The end of the growing season (EOGS) shifts later from west to east, with 86.66 % of the area experiencing EOGS between days 260 and 300. From 1981 to 2016, approximately 61.35 % of the area exhibited a trend of advancing SOGS (-0.09 days/year), while 60.10 % of the area showed a delay in EOGS (0.08 days/year). (2) Both SOGS and EOGS exhibit significant spatial variability influenced by climatic factors, with the primary preseason impact period ranging from 1 to 4 months. SOGS is typically negatively correlated with precipitation and temperature, whereas EOGS often shows a positive correlation with precipitation and temperature. Temperature and solar radiation are the primary climatic drivers influencing vegetation phenology in the study region. Temperature accounts for 53.57 % of SOGS and 50.73 % of EOGS, advancing them by 0.18 and 0.22 days, respectively. Solar radiation also significantly influences SOGS and EOGS, advancing them by 0.14 and 0.13 days, respectively. While the impact of diurnal temperature range (DTR) and precipitation is less pronounced, DTR is notably important in high-altitude regions. (3) Vegetation phenology varies significantly across various vegetation types. Forests usually experience an earlier SOGS and a later EOGS, while shrubs in high-altitude areas tend to have a delayed SOGS due to a greater diurnal temperature range. The growing season of grasslands and wetlands is more significantly affected by precipitation and temperature, particularly in the eastern and northern regions. Solar radiation significantly impacts the entire growing season in croplands and grasslands in the central and southern regions. Uncertainty in vegetation phenology was assessed through Bootstrap analysis, and the spatial adaptability of climate driving factors was optimized using the ridge regression model. The results indicate that despite certain sources of uncertainty, the analysis demonstrates high accuracy and stability, providing a reliable scientific basis for ecological management and restoration.

Soil erosion is undeniably a significant cause of a variety of problems in the Upper Yangtze River (UYR), including floods, land degradation, and sedimentation in rivers. Recognizing alterations in soil erosion and its influencing variables in this area recently is a crucial scientific challenge requiring prompt solutions in regional soil erosion control. This study examines soil erosion and its influencing factors in the Jialing River Basin (JRB) from 1990 to 2018 using RUSLE and geographical detector. It focuses on the relationship between land use, landscape patterns, and soil erosion in this typical basin in the UYR. The results indicated that: (1) The average soil erosion modulus of the JRB decreased during 1990-2018, with predominant slight (< 500 t·km−2·a−1) and light (< 2,500 t·km−2·a−1) erosion intensity. Moderate and higher grades of erosion mainly occurred in the middle and lower JRB. (2) Cultivated land, forest land, and grassland accounted for over 97% of the JRB’s land use from 1990-2018, with cultivated land dominating the middle and lower areas. Over the years, there was an increase in forest land and construction areas, while cultivated land decreased. The landscape pattern was characterized by diversity, fragmentation, and decentralization. (3) The soil erosion control area (SECA), primarily situated in the middle and lower JRB, was predominantly cultivated land. Between 1990 and 2018, the SECA area underwent significant changes, with the most notable changes occurring in the lower Fujiang River Basin (FRB) and the western and middle parts of the Qujiang River Basin (QRB). The area experienced more fluctuations on the left bank of the JRB and the right bank of the JRB, specifically in the QRB and FRB. The research can serve as a reference for future decision-making on land use planning and soil erosion management in the UYR.

The accurate estimation of sediment flux in naturally confluent rivers remains challenging. In this study, we developed a momentum-sediment model (MSM) that considers the complex structure of confluent rivers to estimate sediment flux. Trend analyses of annual runoff and sediment flux from 1956 to 2022 were conducted at four hydrological stations in the upper reaches of the Yangtze River Basin: Pingshan, Zhutuo, Cuntan, and Yichang. Runoff change was insignificant, whereas the sediment flux decreased significantly at all four stations. The entire time series was divided into five periods: a reference period (P1: 1956-1984) and four changing periods (P2: 1985-1993; P3: 1994-2002; P4: 2003-2012; and P5: 2013-2022). The hydrological time series of the reference period served as the calibration period for constructing the momentum-sediment models for Zhutuo, Cuntan, and Yichang stations. The MSM expressions were validated in the four changing periods. The momentum-sediment models for period P1 at Zhutuo and Cuntan stations could be directly applied in periods P2-P5. The MSM for the Yichang station was improved by incorporating the trapping efficiency of the Three Gorges Reservoir. The simulation results of the MSM for sediment flux outperformed the sediment rating curves and linear relationship, particularly for maximum measured values. The applicability of the MSM was validated in the Jialing River, which is characterized by a small basin area, and the Yellow River, which is known for its scarce water and rich sediments. This confirmed that the MSM was insensitive to watershed scale and hydrological conditions.

Recent years have witnessed a significant rise in heat stress, including human-perceived temperature (HPT), which has led to increased incidents of heat stroke and even fatalities, raising considerable concern about the risk to human settlement environments. However, the spatiotemporal pattern of HPT and the potential drivers related to climate and urbanisation remain unclear. This study focuses on the Yangtze River Delta region of China, a typical heat stress-sensitive area, to examine the spatiotemporal dynamics of HPT using six commonly used indices: indoor apparent temperature (AT(in)), outdoor shaded apparent temperature (AT(out)), discomfort index (DI), effective temperature (ET), heat index (HI) and wet-bulb temperature (WBT). Our analysis indicates a significant upward trend (p < 0.05) during the summer months from 1990 to 2019. AT(out) and WBT represent the most and least warming indices, respectively. Trends in HPT indices show significant regional variations. Over half of the cities analysed (56%) demonstrate positive urban-rural temperature differentials across all indices, with the most pronounced warming occurring in humid regions. The increase in anthropogenic heat emissions primarily drives HPT in the relatively arid regions in the northern and eastern areas. In contrast, decreasing vegetation cover contributes to changes in the southwestern, more humid area. Our findings can provide theoretical support for improving urban thermal environment management and developing mitigation strategies for human health.

Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally.

[Objective]With the intensified influence of climate change and human activities,the climate and underlying surface conditions of the basins have changed.Accurately simulating the process of soil moisture change and analyzing its influencing factors are of great significance for regional water resource management and vegetation construction.[Methods]The Weihe River Basin in the Loess Plateau was taken as the research object.Based on the ABCD hydrological model,the EFAST method was used to analyze the parameter sensitivity of the model,and the constant parameter and time-varying parameter models were constructed.The runoff depth and soil water storage simulation accuracy of different parameter models were compared.The effects of climate change and vegetation restoration on soil water storage changes in the Weihe River Basin were discussed,and the dominant factors of soil water storage changes were clarified.[Results]The proportional parameter of soil water layer recharge groundwater c was the most sensitive,followed by the groundwater storage coefficient d,the upper limit parameter b of the sum of actual evapotranspiration and soil water storage,and the tendency parameter a of runoff that before the soil is completely saturated was the least sensitive.Compared with the ABCD constant parameter model,the time-varying parameter model increased the values of NSE,KGE,and R2 of the runoff depth simulation results by 19％,10％,and 19％,respectively,and the NSE,KGE,and R2 of the verification period increased by 7％,7％,and 9％,respectively.The time-varying parameter model significantly improved the runoff depth simulation results.The srtongest correlation between soil water storage in the Weihe river basin and ERA 5-Land 0-100 cm soil layer based on time-varying parameter model simulation,and the change process of the two agreed well.The degree of different influencing factors on the change of soil water storage in the Weihe River Basin from strong to weak was potential evapotranspiration＞precipitation＞NDVI.[Conclusion]The research results provide a scientific basis for water resources planning and management and vegetation construction in this area and they also provide references for soil water storage research in other similar areas.